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• SQL Sentry First Impressions

  - by AjarnMark

  After struggling to defend my SQL Servers from a political attack recently, I realized that I needed better tools to back me up, and SQL Sentry is the leading candidate. A couple of weeks ago, seemingly from out of nowhere, complaints from the business users started coming in that one of the core internal applications was running dramatically slower than normal, and fingers were being pointed at the SQL Server.  Unfortunately, we don’t have a production DBA whose entire job is to monitor and maintain our SQL Servers.  The responsibility falls to me to do the best I can, investing only a small portion of my time, because there are so many other responsibilities to take care of, and our industry is still deep in recession.  I inherited these SQL Servers and have made significant improvements in process and procedure, but I had not yet made the time to take real baseline measurements or keep a really close eye on the performance.  Like many DBAs, I wrote several of my own tools and used the “built-in tools” like Profiler, PerfMon, and sp_who2 (did I mention most of our instances are SQL Server 2000?).  These have all served me well for in-the-moment troubleshooting and maintenance, but they really fell down on the job when I was called upon to “prove” that SQL Server performance was acceptable and more importantly had not degraded recently (i.e. historical comparisons).  I really didn’t have anything from a historical comparison perspective, but I was able to show that current performance was acceptable, and deflect attention back onto other components (which in fact turned out to be the real culprit). That experience dramatically illustrated the need for better monitoring tools.  Coincidentally, I had been talking recently to my boss about the mini nightmare of monitoring several critical and interdependent overnight jobs that operate on separate instances of SQL Server.  Among other tools, I had been using Idera’s SQL Job Manager which is a free tool and did a nice job of showing me job schedules and histories in a nice calendar view.  This worked fairly well, and for the money (did I mention it was free?) it couldn’t be beat.  But it is based on the stored job history in MSDB, and there were other performance problems that we ran into when we started changing the settings for how much job history to retain, in order to be able to look back a month or more in the calendar view.  Another coincidence (if you believe in such things) was that when we had some of those performance challenges, I posted a couple of questions to the #sqlhelp hashtag on Twitter and Greg Gonzalez (@SQLSensei) suggested I check out SQL Sentry’s Event Manager.  At the time, I just thought he worked there, but later found out that he founded the company.  When I took a quick look at the features & benefits, the one that really jumped out at me is Chaining and Queueing which sounded like it would really help with our “interdependent jobs on different servers” issue. I know that is a lot of background story and coincidences, but hopefully you have stuck with me so far, and now we have arrived at the point where last week I downloaded and installed the 30-day trial of the SQL Sentry Power Suite, which is Event Manager plus Performance Advisor.  And I must say that I really like what I see so far.  Here are a few highlights: Great Support.  I had two issues getting the trial setup and monitoring a handful of our servers.  One of which was entirely my fault (missed a security setting in SQL 2008) and the other was mostly my fault (late change to some config settings that were apparently cached and did not get refreshed properly).  In both cases, the support staff at SQL Sentry were very responsive and rather quickly figured out what the cause and fix was for each of them.  This left me with a great impression of the company.  Kudos to them! Chaining and Queueing.  While I have not yet activated this feature, I am very excited about the possibilities.  We have jobs on three different instances of SQL Server that have to be run in a certain order, and each has to finish before the next can successfully begin, and I believe this feature will ensure just that.  It has been a real pain in the backside when one of those jobs runs just a little too long and does not finish before the job on another instance starts, thus triggering a chain reaction of either outright job failures, or worse, successful completion of completely invalid processing. Calendar View.  I really, really like the Event Manager calendar view where I can see all jobs and events across all instances and identify potential resource contention as well as windows of opportunity for maintenance activity.  Very well done, and based on Event Manager’s own database of accumulated historical information rather than querying the source instances every time. Performance Advisor Dashboard History View.  This view let’s me quickly select a date and time range and it displays graphs of key SQL Server and Windows metrics.  This is exactly the thing I needed to answer the “has performance changed recently” question at the beginning of this post. Reporting Services Subscription Jobs with Report Name.  This was a big and VERY pleasant surprise.  If you have ever looked at the list of SQL Server jobs that SQL Server Reporting Services creates when you make a Subscription, you will notice that they all have some sort of GUID as the name of the job.  This is really ugly, and really annoying because when you are just looking at the SQL Agent and Job Activity Monitor, if you see that Job X failed, you really do not have any indication in the name or the properties of the Job itself, as to what Report that was for.  But with SQL Sentry Event Manager you do.  The Jobs list in the Navigator pane in SQL Sentry, amazingly, displays the name of the Report that the Subscription Job is for.  And when you open it to see more details, it shows you the full Reporting Services path to that Report, so you can immediately track it down in the Report Manager in case you want to identify/notify the owner or edit the Subscription information.  I did not expect this at all, but I sure do like it.  HOORAY! That is just my first impressions from using the tools for a few days.  And I haven’t even gotten into how it showed me where I was completely mistaken about one aspect of my SQL Server disk configurations.  I’ll share that lesson in another blog entry.  But I have to say it again, the combination of Event Manager and Performance Advisor working together have really made me a fan.

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• Unlocking Productivity

  - by Michael Snow

  Unlocking Productivity in Life Sciences with Consolidated Content Management by Joe Golemba, Vice President, Product Management, Oracle WebCenter As life sciences organizations look to become more operationally efficient, the ability to effectively leverage information is a competitive advantage. Whether data mining at the drug discovery phase or prepping the sales team before a product launch, content management can play a key role in developing, organizing, and disseminating vital information. The goal of content management is relatively straightforward: put the information that people need where they can find it. A number of issues can complicate this; information sits in many different systems, each of those systems has its own security, and the information in those systems exists in many different formats. Identifying and extracting pertinent information from mountains of farflung data is no simple job, but the alternative—wasted effort or even regulatory compliance issues—is worse. An integrated information architecture can enable health sciences organizations to make better decisions, accelerate clinical operations, and be more competitive. Unstructured data matters Often when we think of drug development data, we think of structured data that fits neatly into one or more research databases. But structured data is often directly supported by unstructured data such as experimental protocols, reaction conditions, lot numbers, run times, analyses, and research notes. As life sciences companies seek integrated views of data, they are typically finding diverse islands of data that seemingly have no relationship to other data in the organization. Information like sales reports or call center reports can be locked into siloed systems, and unavailable to the discovery process. Additionally, in the increasingly networked clinical environment, Web pages, instant messages, videos, scientific imaging, sales and marketing data, collaborative workspaces, and predictive modeling data are likely to be present within an organization, and each source potentially possesses information that can help to better inform specific efforts. Historically, content management solutions that had 21CFR Part 11 capabilities—electronic records and signatures—were focused mainly on content-enabling manufacturing-related processes. Today, life sciences companies have many standalone repositories, requiring different skills, service level agreements, and vendor support costs to manage them. With the amount of content doubling every three to six months, companies have recognized the need to manage unstructured content from the beginning, in order to increase employee productivity and operational efficiency. Using scalable and secure enterprise content management (ECM) solutions, organizations can better manage their unstructured content. These solutions can also be integrated with enterprise resource planning (ERP) systems or research systems, making content available immediately, in the context of the application and within the flow of the employee’s typical business activity. Administrative safeguards—such as content de-duplication—can also be applied within ECM systems, so documents are never recreated, eliminating redundant efforts, ensuring one source of truth, and maintaining content standards in the organization. Putting it in context Consolidating structured and unstructured information in a single system can greatly simplify access to relevant information when it is needed through contextual search. Using contextual filters, results can include therapeutic area, position in the value chain, semantic commonalities, technology-specific factors, specific researchers involved, or potential business impact. The use of taxonomies is essential to organizing information and enabling contextual searches. Taxonomy solutions are composed of a hierarchical tree that defines the relationship between different life science terms. When overlaid with additional indexing related to research and/or business processes, it becomes possible to effectively narrow down the amount of data that is returned during searches, as well as prioritize results based on specific criteria and/or prior search history. Thus, search results are more accurate and relevant to an employee’s day-to-day work. For example, a search for the word "tissue" by a lab researcher would return significantly different results than a search for the same word performed by someone in procurement. Of course, diverse data repositories, combined with the immense amounts of data present in an organization, necessitate that the data elements be regularly indexed and cached beforehand to enable reasonable search response times. In its simplest form, indexing of a single, consolidated data warehouse can be expected to be a relatively straightforward effort. However, organizations require the ability to index multiple data repositories, enabling a single search to reference multiple data sources and provide an integrated results listing. Security and compliance Beyond yielding efficiencies and supporting new insight, an enterprise search environment can support important security considerations as well as compliance initiatives. For example, the systems enable organizations to retain the relevance and the security of the indexed systems, so users can only see the results to which they are granted access. This is especially important as life sciences companies are working in an increasingly networked environment and need to provide secure, role-based access to information across multiple partners. Although not officially required by the 21 CFR Part 11 regulation, the U.S. Food and Drug Administraiton has begun to extend the type of content considered when performing relevant audits and discoveries. Having an ECM infrastructure that provides centralized management of all content enterprise-wide—with the ability to consistently apply records and retention policies along with the appropriate controls, validations, audit trails, and electronic signatures—is becoming increasingly critical for life sciences companies. Making the move Creating an enterprise-wide ECM environment requires moving large amounts of content into a single enterprise repository, a daunting and risk-laden initiative. The first key is to focus on data taxonomy, allowing content to be mapped across systems. The second is to take advantage new tools which can dramatically speed and reduce the cost of the data migration process through automation. Additional content need not be frozen while it is migrated, enabling productivity throughout the process. The ability to effectively leverage information into success has been gaining importance in the life sciences industry for years. The rapid adoption of enterprise content management, both in operational processes as well as in scientific management, are clear indicators that the companies are looking to use all available data to be better informed, improve decision making, minimize risk, and increase time to market, to maintain profitability and be more competitive. As more and more varieties and sources of information are brought under the strategic management umbrella, the ability to divine knowledge from the vast pool of information is increasingly difficult. Simple search engines and basic content management are increasingly unable to effectively extract the right information from the mountains of data available. By bringing these tools into context and integrating them with business processes and applications, we can effectively focus on the right decisions that make our organizations more profitable. More Information Oracle will be exhibiting at DIA 2012 in Philadelphia on June 25-27. Stop by our booth Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} (#2825) to learn more about the advantages of a centralized ECM strategy and see the Oracle WebCenter Content solution, our 21 CFR Part 11 compliant content management platform.

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• The Faces in the Crowdsourcing

  - by Applications User Experience

  By Jeff Sauro, Principal Usability Engineer, Oracle Imagine having access to a global workforce of hundreds of thousands of people who can perform tasks or provide feedback on a design quickly and almost immediately. Distributing simple tasks not easily done by computers to the masses is called "crowdsourcing" and until recently was an interesting concept, but due to practical constraints wasn't used often. Enter Amazon.com. For five years, Amazon has hosted a service called Mechanical Turk, which provides an easy interface to the crowds. The service has almost half a million registered, global users performing a quarter of a million human intelligence tasks (HITs). HITs are submitted by individuals and companies in the U.S. and pay from $.01 for simple tasks (such as determining if a picture is offensive) to several dollars (for tasks like transcribing audio). What do we know about the people who toil away in this digital crowd? Can we rely on the work done in this anonymous marketplace? A rendering of the actual Mechanical Turk (from Wikipedia) Knowing who is behind Amazon's Mechanical Turk is fitting, considering the history of the actual Mechanical Turk. In the late 1800's, a mechanical chess-playing machine awed crowds as it beat master chess players in what was thought to be a mechanical miracle. It turned out that the creator, Wolfgang von Kempelen, had a small person (also a chess master) hiding inside the machine operating the arms to provide the illusion of automation. The field of human computer interaction (HCI) is quite familiar with gathering user input and incorporating it into all stages of the design process. It makes sense then that Mechanical Turk was a popular discussion topic at the recent Computer Human Interaction usability conference sponsored by the Association for Computing Machinery in Atlanta. It is already being used as a source for input on Web sites (for example, Feedbackarmy.com) and behavioral research studies. Two papers shed some light on the faces in this crowd. One paper tells us about the shifting demographics from mostly stay-at-home moms to young men in India. The second paper discusses the reliability and quality of work from the workers. Just who exactly would spend time doing tasks for pennies? In "Who are the crowdworkers?" University of California researchers Ross, Silberman, Zaldivar and Tomlinson conducted a survey of Mechanical Turk worker demographics and compared it to a similar survey done two years before. The initial survey reported workers consisting largely of young, well-educated women living in the U.S. with annual household incomes above $40,000. The more recent survey reveals a shift in demographics largely driven by an influx of workers from India. Indian workers went from 5% to over 30% of the crowd, and this block is largely male (two-thirds) with a higher average education than U.S. workers, and 64% report an annual income of less than $10,000 (keeping in mind $1 has a lot more purchasing power in India). This shifting demographic certainly has implications as language and culture can play critical roles in the outcome of HITs. Of course, the demographic data came from paying Turkers $.10 to fill out a survey, so there is some question about both a self-selection bias (characteristics which cause Turks to take this survey may be unrepresentative of the larger population), not to mention whether we can really trust the data we get from the crowd. Crowds can perform tasks or provide feedback on a design quickly and almost immediately for usability testing. (Photo attributed to victoriapeckham Flikr While having immediate access to a global workforce is nice, one major problem with Mechanical Turk is the incentive structure. Individuals and companies that deploy HITs want quality responses for a low price. Workers, on the other hand, want to complete the task and get paid as quickly as possible, so that they can get on to the next task. Since many HITs on Mechanical Turk are surveys, how valid and reliable are these results? How do we know whether workers are just rushing through the multiple-choice responses haphazardly answering? In "Are your participants gaming the system?" researchers at Carnegie Mellon (Downs, Holbrook, Sheng and Cranor) set up an experiment to find out what percentage of their workers were just in it for the money. The authors set up a 30-minute HIT (one of the more lengthy ones for Mechanical Turk) and offered a very high $4 to those who qualified and $.20 to those who did not. As part of the HIT, workers were asked to read an email and respond to two questions that determined whether workers were likely rushing through the HIT and not answering conscientiously. One question was simple and took little effort, while the second question required a bit more work to find the answer. Workers were led to believe other factors than these two questions were the qualifying aspect of the HIT. Of the 2000 participants, roughly 1200 (or 61%) answered both questions correctly. Eighty-eight percent answered the easy question correctly, and 64% answered the difficult question correctly. In other words, about 12% of the crowd were gaming the system, not paying enough attention to the question or making careless errors. Up to about 40% won't put in more than a modest effort to get paid for a HIT. Young men and those that considered themselves in the financial industry tended to be the most likely to try to game the system. There wasn't a breakdown by country, but given the demographic information from the first article, we could infer that many of these young men come from India, which makes language and other cultural differences a factor. These articles raise questions about the role of crowdsourcing as a means for getting quick user input at low cost. While compensating users for their time is nothing new, the incentive structure and anonymity of Mechanical Turk raises some interesting questions. How complex of a task can we ask of the crowd, and how much should these workers be paid? Can we rely on the information we get from these professional users, and if so, how can we best incorporate it into designing more usable products? Traditional usability testing will still play a central role in enterprise software. Crowdsourcing doesn't replace testing; instead, it makes certain parts of gathering user feedback easier. One can turn to the crowd for simple tasks that don't require specialized skills and get a lot of data fast. As more studies are conducted on Mechanical Turk, I suspect we will see crowdsourcing playing an increasing role in human computer interaction and enterprise computing. References: Downs, J. S., Holbrook, M. B., Sheng, S., and Cranor, L. F. 2010. Are your participants gaming the system?: screening mechanical turk workers. In Proceedings of the 28th international Conference on Human Factors in Computing Systems (Atlanta, Georgia, USA, April 10 - 15, 2010). CHI '10. ACM, New York, NY, 2399-2402. Link: http://doi.acm.org/10.1145/1753326.1753688 Ross, J., Irani, L., Silberman, M. S., Zaldivar, A., and Tomlinson, B. 2010. Who are the crowdworkers?: shifting demographics in mechanical turk. In Proceedings of the 28th of the international Conference Extended Abstracts on Human Factors in Computing Systems (Atlanta, Georgia, USA, April 10 - 15, 2010). CHI EA '10. ACM, New York, NY, 2863-2872. Link: http://doi.acm.org/10.1145/1753846.1753873

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• Source-control 'wet-work'?

  - by Phil Factor

  When a design or creative work is flawed beyond remedy, it is often best to destroy it and start again. The other day, I lost the code to a long and intricate SQL batch I was working on. I’d thought it was impossible, but it happened. With all the technology around that is designed to prevent this occurring, this sort of accident has become a rare event.  If it weren’t for a deranged laptop, and my distraction, the code wouldn’t have been lost this time.  As always, I sighed, had a soothing cup of tea, and typed it all in again.  The new code I hastily tapped in  was much better: I’d held in my head the essence of how the code should work rather than the details: I now knew for certain  the start point, the end, and how it should be achieved. Instantly the detritus of half-baked thoughts fell away and I was able to write logical code that performed better.  Because I could work so quickly, I was able to hold the details of all the columns and variables in my head, and the dynamics of the flow of data. It was, in fact, easier and quicker to start from scratch rather than tidy up and refactor the existing code with its inevitable fumbling and half-baked ideas. What a shame that technology is now so good that developers rarely experience the cleansing shock of losing one’s code and having to rewrite it from scratch.  If you’ve never accidentally lost  your code, then it is worth doing it deliberately once for the experience. Creative people have, until Technology mistakenly prevented it, torn up their drafts or sketches, threw them in the bin, and started again from scratch.  Leonardo’s obsessive reworking of the Mona Lisa was renowned because it was so unusual:  Most artists have been utterly ruthless in destroying work that didn’t quite make it. Authors are particularly keen on writing afresh, and the results are generally positive. Lawrence of Arabia actually lost the entire 250,000 word manuscript of ‘The Seven Pillars of Wisdom’ by accidentally leaving it on a train at Reading station, before rewriting a much better version.  Now, any writer or artist is seduced by technology into altering or refining their work rather than casting it dramatically in the bin or setting a light to it on a bonfire, and rewriting it from the blank page.  It is easy to pick away at a flawed work, but the real creative process is far more brutal. Once, many years ago whilst running a software house that supplied commercial software to local businesses, I’d been supervising an accounting system for a farming cooperative. No packaged system met their needs, and it was all hand-cut code.  For us, it represented a breakthrough as it was for a government organisation, and success would guarantee more contracts. As you’ve probably guessed, the code got mangled in a disk crash just a week before the deadline for delivery, and the many backups all proved to be entirely corrupted by a faulty tape drive.  There were some fragments left on individual machines, but they were all of different versions.  The developers were in despair.  Strangely, I managed to re-write the bulk of a three-month project in a manic and caffeine-soaked weekend.  Sure, that elegant universally-applicable input-form routine was‘nt quite so elegant, but it didn’t really need to be as we knew what forms it needed to support.  Yes, the code lacked architectural elegance and reusability. By dawn on Monday, the application passed its integration tests. The developers rose to the occasion after I’d collapsed, and tidied up what I’d done, though they were reproachful that some of the style and elegance had gone out of the application. By the delivery date, we were able to install it. It was a smaller, faster application than the beta they’d seen and the user-interface had a new, rather Spartan, appearance that we swore was done to conform to the latest in user-interface guidelines. (we switched to Helvetica font to look more ‘Bauhaus’ ). The client was so delighted that he forgave the new bugs that had crept in. I still have the disk that crashed, up in the attic. In IT, we have had mixed experiences from complete re-writes. Lotus 123 never really recovered from a complete rewrite from assembler into C, Borland made the mistake with Arago and Quattro Pro  and Netscape’s complete rewrite of their Navigator 4 browser was a white-knuckle ride. In all cases, the decision to rewrite was a result of extreme circumstances where no other course of action seemed possible.   The rewrite didn’t come out of the blue. I prefer to remember the rewrite of Minix by young Linus Torvalds, or the rewrite of Bitkeeper by a slightly older Linus.  The rewrite of CP/M didn’t do too badly either, did it? Come to think of it, the guy who decided to rewrite the windowing system of the Xerox Star never regretted the decision. I’ll agree that one should often resist calls for a rewrite. One of the worst habits of the more inexperienced programmer is to denigrate whatever code he or she inherits, and then call loudly for a complete rewrite. They are buoyed up by the mistaken belief that they can do better. This, however, is a different psychological phenomenon, more related to the idea of some motorcyclists that they are operating on infinite lives, or the occasional squaddies that if they charge the machine-guns determinedly enough all will be well. Grim experience brings out the humility in any experienced programmer.  I’m referring to quite different circumstances here. Where a team knows the requirements perfectly, are of one mind on methodology and coding standards, and they already have a solution, then what is wrong with considering  a complete rewrite? Rewrites are so painful in the early stages, until that point where one realises the payoff, that even I quail at the thought. One needs a natural disaster to push one over the edge. The trouble is that source-control systems, and disaster recovery systems, are just too good nowadays.   If I were to lose this draft of this very blog post, I know I’d rewrite it much better. However, if you read this, you’ll know I didn’t have the nerve to delete it and start again.  There was a time that one prayed that unreliable hardware would deliver you from an unmaintainable mess of a codebase, but now technology has made us almost entirely immune to such a merciful act of God. An old friend of mine with long experience in the software industry has long had the idea of the ‘source-control wet-work’,  where one hires a malicious hacker in some wild eastern country to hack into one’s own  source control system to destroy all trace of the source to an application. Alas, backup systems are just too good to make this any more than a pipedream. Somehow, it would be difficult to promote the idea. As an alternative, could one construct a source control system that, on doing all the code-quality metrics, would systematically destroy all trace of source code that failed the quality test? Alas, I can’t see many managers buying into the idea. In reading the full story of the near-loss of Toy Story 2, it set me thinking. It turned out that the lucky restoration of the code wasn’t the happy ending one first imagined it to be, because they eventually came to the conclusion that the plot was fundamentally flawed and it all had to be rewritten anyway.  Was this an early  case of the ‘source-control wet-job’?’ It is very hard nowadays to do a rapid U-turn in a development project because we are far too prone to cling to our existing source-code.

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• Augmenting your Social Efforts via Data as a Service (DaaS)

  - by Mike Stiles

  The following is the 3rd in a series of posts on the value of leveraging social data across your enterprise by Oracle VP Product Development Don Springer and Oracle Cloud Data and Insight Service Sr. Director Product Management Niraj Deo. In this post, we will discuss the approach and value of integrating additional “public” data via a cloud-based Data-as-as-Service platform (or DaaS) to augment your Socially Enabled Big Data Analytics and CX Management. Let’s assume you have a functional Social-CRM platform in place. You are now successfully and continuously listening and learning from your customers and key constituents in Social Media, you are identifying relevant posts and following up with direct engagement where warranted (both 1:1, 1:community, 1:all), and you are starting to integrate signals for communication into your appropriate Customer Experience (CX) Management systems as well as insights for analysis in your business intelligence application. What is the next step? Augmenting Social Data with other Public Data for More Advanced Analytics When we say advanced analytics, we are talking about understanding causality and correlation from a wide variety, volume and velocity of data to Key Performance Indicators (KPI) to achieve and optimize business value. And in some cases, to predict future performance to make appropriate course corrections and change the outcome to your advantage while you can. The data to acquire, process and analyze this is very nuanced: It can vary across structured, semi-structured, and unstructured data It can span across content, profile, and communities of profiles data It is increasingly public, curated and user generated The key is not just getting the data, but making it value-added data and using it to help discover the insights to connect to and improve your KPIs. As we spend time working with our larger customers on advanced analytics, we have seen a need arise for more business applications to have the ability to ingest and use “quality” curated, social, transactional reference data and corresponding insights. The challenge for the enterprise has been getting this data inline into an easily accessible system and providing the contextual integration of the underlying data enriched with insights to be exported into the enterprise’s business applications. The following diagram shows the requirements for this next generation data and insights service or (DaaS): Some quick points on these requirements: Public Data, which in this context is about Common Business Entities, such as - Customers, Suppliers, Partners, Competitors (all are organizations) Contacts, Consumers, Employees (all are people) Products, Brands This data can be broadly categorized incrementally as - Base Utility data (address, industry classification) Public Master Reference data (trade style, hierarchy) Social/Web data (News, Feeds, Graph) Transactional Data generated by enterprise process, workflows etc. This Data has traits of high-volume, variety, velocity etc., and the technology needed to efficiently integrate this data for your needs includes - Change management of Public Reference Data across all categories Applied Big Data to extract statics as well as real-time insights Knowledge Diagnostics and Data Mining As you consider how to deploy this solution, many of our customers will be using an online “cloud” service that provides quality data and insights uniformly to all their necessary applications. In addition, they are requesting a service that is: Agile and Easy to Use: Applications integrated with the service can obtain data on-demand, quickly and simply Cost-effective: Pre-integrated into applications so customers don’t have to Has High Data Quality: Single point access to reference data for data quality and linkages to transactional, curated and social data Supports Data Governance: Becomes more manageable and cost-effective since control of data privacy and compliance can be enforced in a centralized place Data-as-a-Service (DaaS) Just as the cloud has transformed and now offers a better path for how an enterprise manages its IT from their infrastructure, platform, and software (IaaS, PaaS, and SaaS), the next step is data (DaaS). Over the last 3 years, we have seen the market begin to offer a cloud-based data service and gain initial traction. On one side of the DaaS continuum, we see an “appliance” type of service that provides a single, reliable source of accurate business data plus social information about accounts, leads, contacts, etc. On the other side of the continuum we see more of an online market “exchange” approach where ISVs and Data Publishers can publish and sell premium datasets within the exchange, with the exchange providing a rich set of web interfaces to improve the ease of data integration. Why the difference? It depends on the provider’s philosophy on how fast the rate of commoditization of certain data types will occur. How do you decide the best approach? Our perspective, as shown in the diagram below, is that the enterprise should develop an elastic schema to support multi-domain applicability. This allows the enterprise to take the most flexible approach to harness the speed and breadth of public data to achieve value. The key tenet of the proposed approach is that an enterprise carefully federates common utility, master reference data end points, mobility considerations and content processing, so that they are pervasively available. One way you may already be familiar with this approach is in how you do Address Verification treatments for accounts, contacts etc. If you design and revise this service in such a way that it is also easily available to social analytic needs, you could extend this to launch geo-location based social use cases (marketing, sales etc.). Our fundamental belief is that value-added data achieved through enrichment with specialized algorithms, as well as applying business “know-how” to weight-factor KPIs based on innovative combinations across an ever-increasing variety, volume and velocity of data, will be where real value is achieved. Essentially, Data-as-a-Service becomes a single entry point for the ever-increasing richness and volume of public data, with enrichment and combined capabilities to extract and integrate the right data from the right sources with the right factoring at the right time for faster decision-making and action within your core business applications. As more data becomes available (and in many cases commoditized), this value-added data processing approach will provide you with ongoing competitive advantage. Let’s look at a quick example of creating a master reference relationship that could be used as an input for a variety of your already existing business applications. In phase 1, a simple master relationship is achieved between a company (e.g. General Motors) and a variety of car brands’ social insights. The reference data allows for easy sort, export and integration into a set of CRM use cases for analytics, sales and marketing CRM. In phase 2, as you create more data relationships (e.g. competitors, contacts, other brands) to have broader and deeper references (social profiles, social meta-data) for more use cases across CRM, HCM, SRM, etc. This is just the tip of the iceberg, as the amount of master reference relationships is constrained only by your imagination and the availability of quality curated data you have to work with. DaaS is just now emerging onto the marketplace as the next step in cloud transformation. For some of you, this may be the first you have heard about it. Let us know if you have questions, or perspectives. In the meantime, we will continue to share insights as we can.Photo: Erik Araujo, stock.xchng

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• The Madness of March

  - by Kristin Rose

  Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} From “Linsanity” to “LOB City”, there is no doubt that basketball dominates the month of March. As many are aware, March Madness is well underway and continues to be a time when college basketball teams get together to bring their A-game to the court. Here at Oracle we also like to bring our A-game, and that includes some new players and talent from our newly acquired companies. Each new acquisition expands Oracle’s solution portfolio, fills customer requirements, and ultimately brings greater opportunities for partners. OPN follows a consistent approach to delivering key information about these acquisitions to you in a timely manner. We do this so partners can get educated, get trained and gain access to demand gen and sales tools. Through this slam dunk of a process we provide (using Pillar Data Systems as an example): A welcome page where partners can download information and learn how to sell and maximize sales returns. A Discovery section where partners can listen to key Oracle Executives speak about the many benefits this new solution brings, as well review a FAQ sheet. A Prepare section where partners can learn about the product strategies and the different OPN Knowledge Zones that have become available. A Sell and Deliver section that partners can leverage when discussing product positioning and functionality, as well as gain access to relevant deliverables. Just as any competitive team strives to be #1, Oracle also wants to stay best-in-class which is why we have recently joined forces with some ‘baller’ companies such as RightNow, Endeca and Pillar Axiom to secure our place in the industry bracket. By running our 3-2 Oracle play and bringing in our newly acquired products, we are able to deliver a solid, expanded solution to our partners. These and many other MVP companies have helped Oracle broaden its offerings and score big. Watch the half time show below to find out what Judson thinks about Oracle’s current offerings: Mergers and acquisitions are a strategic part of how we currently go to market. If you haven’t done so already, dribble down or post up and visit the Acquisition Catalog to learn more about Oracle’s acquired products and the unique benefits they can bring to your own court. Or click here to learn about the ways of monetizing opportunities through Oracle acquisitions. Until Next Time, It’s Game Time, The OPN Communications Team Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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• Need personal advice on how to get out of a company..

  - by SOfan

  Hi, I am an SO user since past 6 months and this is the first time I am turning to SO for personal help. I have asked technical questions before with my real ID. I am stuck inside a service based IT company for the past one year and haven't been able to decide if to leave it, when to leave it and how to leave it. I had taken 2 weeks LWP on medical reason roughly at end of 1 year and then soon after reporting, I applied for 2 months more LWP (on medical/personal ground) with the intention of working on my health,take up a hobby class to ward off depression,pessimism, to have some fun in life, and to look for a job which I really would be excited about - that interests me and which matches with my strength. My leave starts from this Monday. So in any case, I had hard set in mind that I will leave the company after I join them back hopefully with some job offer already in hand (after figuring out what I want do). Neither I can stand the past project,past colleagues,company, HR, pathetically low salary. But if I really listen to my heart, I don't want to have to go back to that office after my sabbatical and again have to see those people. I will have to resign it after my sabbatical ends. Then HR people perhaps wont like it, may even accuse me on face or behind back that primary purpose of my leave must have been to hunt for a better job and I lied about medical and person reasons. Also, if they get nasty and force me to serve 2 months notice period. There is no way I see myself after sabbatical resuming in old project or starting new work. It will be a pain. Since they have already approved 2 months leave and stuff, ideally if they want, they should be just able to relieve me right on the next day after I join back. But, I don't know if they want to get nasty, will they mention about my 2 months sabbatical leave in my experience letter or more scary, the term medical/personal reason. I have hard earned my experience here, have worked against my will, mostly it has been painful and slogged like anything, because I realize the importance of work experience in IT industry. I don't have greed to have those 2 months included extra in my experience letter, but I don't want to mess up with my experience letter in a way which makes my next employer ask question, get suspicious, or be wary if I have any medical reason going on. Being an emotional,moody person or somebody who can't be in an environment, once my mind and heart starts hating it. I think it perhaps is best, if I resign on Monday itself telling them (in polite manner) something that look I took sabbatical for some reason but I don't want to resume working in the company after my sabbatical ends. So please accept my resignation. Now tell me what you want to do about my leave request, my notice period and when you are willing to relieve me. What should I write and how? Some background: I am working in an IT company in India.I am overqualified in the company. It is grossly underpaying me. My education qualifications far exceed anyone's in the whole company being a CS undergrad as well as a CS grad. I joined this company after finishing the grad. I had self-doubts about my skills and interest as a programmer. I like doing research oriented work, though didn't have any particular success during grad. My life here has been very hectic. The project containing many many sub-projects has kept me on my toes and I have never really liked the work. I have been playing against my strength. Also the company strict internet usage policy (you can't read gmails, can't browse any non-work related sites not even news). When working for a client, from the machine we can't even check company related emails.For this one has to go to kiosk like 5 machines in a small room etc. Most of the times those machines are not available, so it was not unusual to keep making rounds to these kiosk machines to check company emails, browse company related emails etc.So it was not so easy to keep in touch with company related basic affairs for a not particular careful person. Things like this which are new to me, make me feel restricted. I am an undecisive person with a sense of failure, self-doubt, not meeting up unrealistic expectation. Somewhere at back of mind, I envy my classmates who make a smooth transition from company to company without causing any gap in their resume. I on other hand have gaps in resume. I get tired after working in a place for sometime. problem with colleagues in general. I am not particular great with people, have few friends, not known for a fun nature, rather serious, scholar. I am not a typical conventional female. I think females are usually more disciplined. But I am not so. I reach office late (though after informing manager). I don't want to blame them entirely, because from my past, it is not unusual for me to get undecisive on things. Also I had doubts about my ability as researched and to succeed there. of building a relationship in a group, to have something to talk about, newspaper. I get cut-off from people. peer pressure. I make blunders in coding, lose patience. Consciously or unconsciously I feel contempt for people here, work here, environment here. I have doubts that either I go to a place which does innovation, does research oriented work, product biggies, have great motivated people, have competent people passionate about products they are building. But then I also doubt my ability to survive there. I have identified that an idea job for me would be 4 days a week, a high salary job. When among people in company/team, I can't think much. I need some time at home to read good authentic books written in good style on what work I am doing.So that I am comfortable with my understanding of work. I get into pressure easily under deadline and need 5th day to cool myself off. I took for 2 weeks leave, because each day was hell for me. May be the depression phase of bipolar is on and also partially it could be that being a work centered person, who derives happiness,self-esteem from work, haven't been enjoying work and have been working for the sole person of proving stability, and ability to stick, against all odds, and facing what challenges I see, bonding with people, identifying opportunities to learn in given task etc.have been averaging one day LWP in 1 week or 10 days. or may be because of my nature,ADD,not being able to switch context,out of touch with news, don't have a circle of friends with who I enjoy. less knowledge in general to talk about, just some technical stuff.anyway, so due to emotional reason, some practical reason etc, I wanted to be very sure before leaving. So my leave starts from Monday and I should feel happy about it. I have taken the leave to for a few purposes - to take care of my health by regular yoga/exercise (with project on, I just can't do anything regular), reassess myself to see what I want to try next which work I might like, look for next job, take up a hobby which I like say singing. I am not clear on my career,job aspiration. I have tried my hands on research. During this year appraisal yesterday, I even had some conflict with my last manager. In meeting with me one on one, he would say all nice things about me, but in feedback to new manager, he hasn't given any excellent feedback. It is all only good. I am angry at this old Manager. Also new manager also scolded me as I didn't agree to his appraisal and waited to hear myself from old Manager. He kind of scolded me for wasting his time. Am I being unethical somewhere? I am always very conscious of if I am cheating anywhere. What advice I am seeking? How to resign and what to write in resignation letter

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• Five Key Strategies in Master Data Management

  - by david.butler(at)oracle.com

  Here is a very interesting Profit Magazine article on MDM: A recent customer survey reveals the deleterious effects of data fragmentation. by Trevor Naidoo, December 2010   Across industries and geographies, IT organizations have grown in complexity, whether due to mergers and acquisitions, or decentralized systems supporting functional or departmental requirements. With systems architected over time to support unique, one-off process needs, they are becoming costly to maintain, and the Internet has only further added to the complexity. Data fragmentation has become a key inhibitor in delivering flexible, user-friendly systems. The Oracle Insight team conducted a survey assessing customers' master data management (MDM) capabilities over the past two years to get a sense of where they are in terms of their capabilities. The responses, by 27 respondents from six different industries, reveal five key areas in which customers need to improve their data management in order to get better financial results. 1. Less than 15 percent of organizations surveyed understand the sources and quality of their master data, and have a roadmap to address missing data domains. Examples of the types of master data domains referred to are customer, supplier, product, financial and site. Many organizations have multiple sources of master data with varying degrees of data quality in each source -- customer data stored in the customer relationship management system is inconsistent with customer data stored in the order management system. Imagine not knowing how many places you stored your customer information, and whether a customer's address was the most up to date in each source. In fact, more than 55 percent of the respondents in the survey manage their data quality on an ad-hoc basis. It is important for organizations to document their inventory of data sources and then profile these data sources to ensure that there is a consistent definition of key data entities throughout the organization. Some questions to ask are: How do we define a customer? What is a product? How do we define a site? The goal is to strive for one common repository for master data that acts as a cross reference for all other sources and ensures consistent, high-quality master data throughout the organization. 2. Only 18 percent of respondents have an enterprise data management strategy to ensure that data is treated as an asset to the organization. Most respondents handle data at the department or functional level and do not have an enterprise view of their master data. The sales department may track all their interactions with customers as they move through the sales cycle, the service department is tracking their interactions with the same customers independently, and the finance department also has a different perspective on the same customer. The salesperson may not be aware that the customer she is trying to sell to is experiencing issues with existing products purchased, or that the customer is behind on previous invoices. The lack of a data strategy makes it difficult for business users to turn data into information via reports. Without the key building blocks in place, it is difficult to create key linkages between customer, product, site, supplier and financial data. These linkages make it possible to understand patterns. A well-defined data management strategy is aligned to the business strategy and helps create the governance needed to ensure that data stewardship is in place and data integrity is intact. 3. Almost 60 percent of respondents have no strategy to integrate data across operational applications. Many respondents have several disparate sources of data with no strategy to keep them in sync with each other. Even though there is no clear strategy to integrate the data (see #2 above), the data needs to be synced and cross-referenced to keep the business processes running. About 55 percent of respondents said they perform this integration on an ad hoc basis, and in many cases, it is done manually with the help of Microsoft Excel spreadsheets. For example, a salesperson needs a report on global sales for a specific product, but the product has different product numbers in different countries. Typically, an analyst will pull all the data into Excel, manually create a cross reference for that product, and then aggregate the sales. The exact same procedure has to be followed if the same report is needed the following month. A well-defined consolidation strategy will ensure that a central cross-reference is maintained with updates in any one application being propagated to all the other systems, so that data is synchronized and up to date. This can be done in real time or in batch mode using integration technology. 4. Approximately 50 percent of respondents spend manual efforts cleansing and normalizing data. Information stored in various systems usually follows different standards and formats, making it difficult to match the data. A customer's address can be stored in different ways using a variety of abbreviations -- for example, "av" or "ave" for avenue. Similarly, a product's attributes can be stored in a number of different ways; for example, a size attribute can be stored in inches and can also be entered as "'' ". These types of variations make it difficult to match up data from different sources. Today, most customers rely on manual, heroic efforts to match, cleanse, and de-duplicate data -- clearly not a scalable, sustainable model. To solve this challenge, organizations need the ability to standardize data for customers, products, sites, suppliers and financial accounts; however, less than 10 percent of respondents have technology in place to automatically resolve duplicates. It is no wonder, therefore, that we get communications about products we don't own, at addresses we don't reside, and using channels (like direct mail) we don't like. An all-too-common example of a potential challenge follows: Customers end up receiving duplicate communications, which not only impacts customer satisfaction, but also incurs additional mailing costs. Cleansing, normalizing, and standardizing data will help address most of these issues. 5. Only 10 percent of respondents have the ability to share data that was mastered in a master data hub. Close to 60 percent of respondents have efforts in place that profile, standardize and cleanse data manually, and the output of these efforts are stored in spreadsheets in various parts of the organization. This valuable information is not easily shared with the rest of the organization and, more importantly, this enriched information cannot be sent back to the source systems so that the data is fixed at the source. A key benefit of a master data management strategy is not only to clean the data, but to also share the data back to the source systems as well as other systems that need the information. Aside from the source systems, another key beneficiary of this data is the business intelligence system. Having clean master data as input to business intelligence systems provides more accurate and enhanced reporting.  Characteristics of Stellar MDM When deciding on the right master data management technology, organizations should look for solutions that have four main characteristics: enterprise-grade MDM performance complete technology that can be rapidly deployed and addresses multiple business issues end-to-end MDM process management with data quality monitoring and assurance pre-built MDM business relevant applications with data stores and workflows These master data management capabilities will aid in moving closer to a best-practice maturity level, delivering tremendous efficiencies and savings as well as revenue growth opportunities as a result of better understanding your customers.  Trevor Naidoo is a senior director in Industry Strategy and Insight at Oracle. 

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• Projected Results

  - by Sylvie MacKenzie, PMP

  Excerpt from PROFIT - ORACLE - by Monica Mehta Yasser Mahmud has seen a revolution in project management over the past decade. During that time, the former Primavera product strategist (who joined Oracle when his company was acquired in 2008) has not only observed a transformation in the way IT systems support corporate projects but the role project portfolio management (PPM) plays in the enterprise. “15 years ago project management was the domain of project management office (PMO),” Mahmud recalls of earlier days. “But over the course of the past decade, we've seen it transform into a mission critical enterprise discipline, that has made Primavera indispensable in the board room. Now, as a senior manager, a board member, or a C-level executive you have direct and complete visibility into what’s kind of going on in the organization—at a level of detail that you're going to consume that information.” Now serving as Oracle’s vice president of product strategy and industry marketing, Mahmud shares his thoughts on how Oracle’s Primavera solutions have evolved and how best-in-class project portfolio management systems can help businesses stay competitive. Profit: What do you feel are the market dynamics that are changing project management today? Mahmud: First, the data explosion. We're generating data at twice the rate at which we can actually store it. The same concept applies for project-intensive organizations. A lot of data is gathered, but what are we really doing with it? Are we turning data into insight? Are we using that insight and turning it into foresight with analytics tools? This is a key driver that will separate the very good companies—the very competitive companies—from those that are not as competitive. Another trend is centered on the explosion of mobile computing. By the year 2013, an estimated 35 percent of the world’s workforce is going to be mobile. That’s one billion people. So the question is not if you're going to go mobile, it’s how fast you are going to go mobile. What kind of impact does that have on how the workforce participates in projects? What worked ten to fifteen years ago is not going to work today. It requires a real rethink around the interfaces and how data is actually presented. Profit: What is the role of project management in this new landscape? Mahmud: We recently conducted a PPM study with the Economist Intelligence Unit centered to determine how important project management is considered within organizations. Our target was primarily CFOs, CIOs, and senior managers and we discovered that while 95 percent of participants believed it critical to their business, only six percent were confident that projects were delivered on time and on budget. That’s a huge gap. Most organizations are looking for efficiency, especially in these volatile financial times. But senior management can’t keep track of every project in a large organization. As a result, executives are attempting to inventory the work being conducted under their watch. What is often needed is a very high-level assessment conducted at the board level to say, “Here are the 50 initiatives that we have underway. How do they line up with our strategic drivers?” This line of questioning can provide early warning that work and strategy are out of alignment; finding the gap between what the business needs to do and the actual performance scorecard. That’s low-hanging fruit for any executive looking to increase efficiency and save money. But it can only be obtained through proper assessment of existing projects—and you need a project system of record to get that done. Over the next decade or so, project management is going to transform into holistic work management. Business leaders will want make sure key projects align with corporate strategy, but also the ability to drill down into daily activity and smaller projects to make sure they line up as well. Keeping employees from working on tasks—even for a few hours—that don’t line up with corporate goals will, in many ways, become a competitive differentiator. Profit: How do all of these market challenges and shifting trends impact Oracle’s Primavera solutions and meeting customers’ needs? Mahmud: For Primavera, it’s a transformation from being a project management application to a PPM system in the enterprise. Also making that system a mission-critical application by connecting to other key applications within the ecosystem, such as the enterprise resource planning (ERP), supply chain, and CRM systems. Analytics have also become a huge component. Business analytics have made Oracle’s Primavera applications pertinent in the boardroom. Now, as a senior manager, a board member, a CXO, CIO, or CEO, you have direct visibility into what’s going on in the organization at a level that you're able to consume that information. In addition, all of this information pairs up really well with your financials and other data. Certainly, when you're an Oracle shop, you have that visibility that you didn’t have before from a project execution perspective. Profit: What new strategies and tools are being implemented to create a more efficient workplace for users? Mahmud: We believe very strongly that just because you call something an enterprise project portfolio management system doesn’t make it so—you have to get people to want to participate in the system. This can’t be mandated down from the top. It simply doesn’t work that way. A truly adoptable solution is one that makes it super easy for all types users to participate, by providing them interfaces where they live. Keeping that in mind, a major area of development has been alternative user interfaces. This is increasingly resulting in the creation of lighter weight, targeted interfaces such as iOS applications, and smartphones interfaces such as for iPhone and Android platform. Profit: How does this translate into the development of Oracle’s Primavera solutions? Mahmud: Let me give you a few examples. We recently announced the launch of our Primavera P6 Team Member application, which is a native iOS application for the iPhone. This interface makes it easier for team members to do their jobs quickly and effectively. Similarly, we introduced the Primavera analytics application, which can be consumed via mobile devices, and when married with Oracle Spatial capabilities, users can get a geographical view of what’s going on and which projects are occurring in various locations around the world. Lastly, we introduced advanced email integration that allows project team members to status work via E-mail. This functionality leverages the fact that users are in E-mail system throughout the day and allows them to status their work without the need to launch the Primavera application. It comes back to a mantra: provide as many alternative user interfaces as possible, so you can give people the ability to work, to participate, to raise issues, to create projects, in the places where they live. Do it in such a way that it’s non-intrusive, do it in such a way that it’s easy and intuitive and they can get it done in a short amount of time. If you do that, workers can get back to doing what they're actually getting paid for.

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• Using R to Analyze G1GC Log Files

  - by user12620111

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  Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

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• A Bite With No Teeth&ndash;Demystifying Non-Compete Clauses

  - by D'Arcy Lussier

  *DISCLAIMER: I am not a lawyer and this post in no way should be considered legal advice. I’m also in Canada, so references made are to Canadian court cases. I received a signed letter the other day, a reminder from my previous employer about some clauses associated with my employment and entry into an employee stock purchase program. So since this is in effect for the next 12 months, I guess I’m not starting that new job tomorrow. I’m kidding of course. How outrageous, how presumptuous, pompous, and arrogant that a company – any company – would actually place these conditions upon an employee. And yet, this is not uncommon. Especially in the IT industry, we see time and again similar wording in our employment agreements. But…are these legal? Is there any teeth behind the threat of the bite? Luckily, the answer seems to be ‘No’. I want to highlight two cases that support this. The first is Lyons v. Multari. In a nutshell, Dentist hires younger Dentist to be an associate. In their short, handwritten agreement, a non-compete clause was written stating “Protective Covenant. 3 yrs. – 5mi” (meaning you can’t set up shop within 5 miles for 3 years). Well, the young dentist left and did start an oral surgery office within 5 miles and within 3 years. Off to court they go! The initial judge sided with the older dentist, but on appeal it was overturned. Feel free to read the transcript of the decision here, but let me highlight one portion from section [19]: The general rule in most common law jurisdictions is that non-competition clauses in employment contracts are void. The sections following [19] explain further, and discuss Elsley v. J.G. Collins Insurance Agency Ltd. and its impact on Canadian law in this regard. The second case is Winnipeg Livestock Sales Ltd. v. Plewman. Desmond Plewman is an auctioneer, and worked at Winnipeg Livestock Sales. Part of his employment agreement was that he could not work for a competitor for 18 months if he left the company. Well, he left, and took up an important role in a competing company. The case went to court and as with Lyons v. Multari, the initial judge found in favour of the plaintiffs. Also as in the first case, that was overturned on appeal. Again, read through the transcript of the decision, but consider section [28]: In other words, even though Plewman has a great deal of skill as an auctioneer, Winnipeg Livestock has no proprietary interest in his professional skill and experience, even if they were acquired during his time working for Winnipeg Livestock.  Thus, Winnipeg Livestock has the burden of establishing that it has a legitimate proprietary interest requiring protection.  On this key question there is little evidence before the Court.  The record discloses that part of Plewman’s job was to “mingle with the … crowd” and to telephone customers and prospective customers about future prospects for the sale of livestock.  It may seem reasonable to assume that Winnipeg Livestock has a legitimate proprietary interest in its customer connections; but there is no evidence to indicate that there is any significant degree of “customer loyalty” in the business, as opposed to customers making choices based on other considerations such as cost, availability and the like. So are there any incidents where a non-compete can actually be valid? Yes, and these are considered “exceptional” cases, meaning that the situation meets certain circumstances. Michael Carabash has a great blog series discussing the above mentioned cases as well as the difference between a non-compete and non-solicit agreement. He talks about the exceptional criteria: In summary, the authorities reveal that the following circumstances will generally be relevant in determining whether a case is an “exceptional” one so that a general non-competition clause will be found to be reasonable: - The length of service with the employer. - The amount of personal service to clients. - Whether the employee dealt with clients exclusively, or on a sustained or     recurring basis. - Whether the knowledge about the client which the employee gained was of a   confidential nature, or involved an intimate knowledge of the client’s   particular needs, preferences or idiosyncrasies. - Whether the nature of the employee’s work meant that the employee had   influence over clients in the sense that the clients relied upon the employee’s   advice, or trusted the employee. - If competition by the employee has already occurred, whether there is   evidence that clients have switched their custom to him, especially without   direct solicitation. - The nature of the business with respect to whether personal knowledge of   the clients’ confidential matters is required. - The nature of the business with respect to the strength of customer loyalty,   how clients are “won” and kept, and whether the clientele is a recurring one. - The community involved and whether there were clientele yet to be exploited   by anyone. I close this blog post with a final quote, one from Zvulony & Co’s blog post on this subject. Again, all of this is not official legal advice, but I think we can see what all these sources are pointing towards. To answer my earlier question, there’s no teeth behind the threat of the bite. In light of this list, and the decisions in Lyons and Orlan, it is reasonably certain that in most employment situations a non-competition clause will be ineffective in protecting an employer from a departing employee who wishes to compete in the same business. The Courts have been relatively consistent in their position that if a non-solicitation clause can protect an employer’s interests, then a non-competition clause is probably unreasonable. Employers (or their solicitors) should avoid the inclination to draft restrictive covenants in broad, catch-all language. Or in other words, when drafting a restrictive covenant – take only what you need! D

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• Let your Signature Experience drive IT-decision making

  - by Tania Le Voi

  Today’s CIO job description:  ‘’Align IT infrastructure and solutions with business goals and objectives ; AND while doing so reduce costs; BUT ALSO, be innovative, ensure the architectures are adaptable and agile as we need to act today on the changes that we may request tomorrow.”   Sound like an unachievable request? The fact is, reality dictates that CIO’s are put under this type of pressure to deliver more with less. In a past career phase I spent a few years as an IT Relationship Manager for a large Insurance company. This is a role that we see all too infrequently in many of our customers, and it’s a shame.  The purpose of this role was to build a bridge, a relationship between IT and the business. Key to achieving that goal was to ensure the same language was being spoken and more importantly that objectives were commonly understood - hence service and projects were delivered to time, to budget and actually solved the business problems. In reality IT and the business are already married, but the relationship is most often defined as ‘supplier’ of IT rather than a ‘trusted partner’. To deliver business value they need to understand how to work together effectively to attain this next level of partnership. The Business cannot compete if they do not get a new product to market ahead of the competition, or for example act in a timely manner to address a new industry problem such as a legislative change. An even better example is when the Application or Service fails and the Business takes a hit by bad publicity, being trending topics on social media and losing direct revenue from online channels. For this reason alone Business and IT need the alignment of their priorities and deliverables now more than ever! Take a look at Forrester’s recent study that found ‘many IT respondents considering themselves to be trusted partners of the business but their efforts are impaired by the inadequacy of tools and organizations’.  IT Meet the Business; Business Meet IT So what is going on? We talk about aligning the business with IT but the reality is it’s difficult to do. Like any relationship each side has different goals and needs and language can be a barrier; business vs. technology jargon! What if we could translate the needs of both sides into actionable information, backed by data both sides understand, presented in a meaningful way?  Well now we can with the Business-Driven Application Management capabilities in Oracle Enterprise Manager 12cR2! Enterprise Manager’s Business-Driven Application Management capabilities provide the information that IT needs to understand the impact of its decisions on business criteria.  No longer does IT need to be focused solely on speeds and feeds, performance and throughput – now IT can understand IT’s impact on business KPIs like inventory turns, order-to-cash cycle, pipeline-to-forecast, and similar.  Similarly, now the line of business can understand which IT services are most critical for the KPIs they care about. There are a good deal of resources on Oracle Technology Network that describe the functionality of these products, so I won’t’ rehash them here.  What I want to talk about is what you do with these products. What’s next after we meet? Where do you start? Step 1:  Identify the Signature Experience. This is THE business process (or set of processes) that is core to the business, the one that drives the economic engine, the process that a customer recognises the company brand for, reputation, the customer experience, the process that a CEO would state as his number one priority. The crème de la crème of your business! Once you have nailed this it gets easy as Enterprise Manager 12c makes it easy. Step 2:  Map the Signature Experience to underlying IT.  Taking the signature experience, map out the touch points of the components that play a part in ensuring this business transaction is successful end to end, think of it like mapping out a critical path; the applications, middleware, databases and hardware. Use the wealth of Enterprise Manager features such as Systems, Services, Business Application Targets and Business Transaction Management (BTM) to assist you. Adding Real User Experience Insight (RUEI) into the mix will make the end to end customer satisfaction story transparent. Work with the business and define meaningful key performance indicators (KPI’s) and thresholds to enable you to report and action upon. Step 3:  Observe the data over time.  You now have meaningful insight into every step enabling your signature experience and you understand the implication of that experience on your underlying IT.  Watch if for a few months, see what happens and reconvene with your business stakeholders and set clear and measurable targets which can re-define service levels.  Step 4:  Change the information about which you and the business communicate.  It’s amazing what happens when you and the business speak the same language.  You’ll be able to make more informed business and IT decisions. From here IT can identify where/how budget is spent whether on the level of support, performance, capacity, HA, DR, certification etc. IT SLA’s no longer need be focused on metrics such as %availability but structured around business process requirements. The power of this way of thinking doesn’t end here. IT staff get to see and understand how their own role contributes to the business making them accountable for the business service. Take a step further and appraise your staff on the business competencies that are linked to the service availability. For the business, the language barrier is removed by producing targeted reports on the signature experience core to the business and therefore key to the CEO. Chargeback or show back becomes easier to justify as the ‘cost of day per outage’ can be more easily calculated; the business will be able to translate the cost to the business to the cost/value of the underlying IT that supports it. Used this way, Oracle Enterprise Manager 12c is a key enabler to a harmonious relationship between the end customer the business and IT to deliver ultimate service and satisfaction. Just engage with the business upfront, make the signature experience visible and let Enterprise Manager 12c do the rest. In the next blog entry we will cover some of the Enterprise Manager features mentioned to enable you to implement this new way of working.  

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• 5 Lessons learnt in localization / multi language support in WPF

  - by MarkPearl

  For the last few months I have been secretly working away at the second version of an application that we initially released a few years ago. It’s called MaxCut and it is a free panel/cut optimizer for the woodwork, glass and metal industry. One of the motivations for writing MaxCut was to get an end to end experience in developing an application for general consumption. From the early days of v1 of MaxCut I would get the odd email thanking me for the software and then listing a few suggestions on how to improve it. Two of the most dominant suggestions that we received were… Support for imperial measurements (the original program only supported the metric system) Multi language support (we had someone who volunteered to translate the program into Japanese for us). I am not going to dive into the Imperial to Metric support in todays blog post, but I would like to cover a few brief lessons we learned in adding support for multi-language functionality in the software. I have sectioned them below under different lessons. Lesson 1 – Build multi-language support in from the start So the first lesson I learnt was if you know you are going to do multi language support – build it in from the very beginning! One of the power points of WPF/Silverlight is data binding in XAML and so while it wasn’t to painful to retro fit multi language support into the programing, it was still time consuming and a bit tedious to go through mounds and mounds of views and would have been a minor job to have implemented this while the form was being designed. Lesson 2 – Accommodate for varying word lengths using Grids The next lesson was a little harder to learn and was learnt a bit further down the road in the development cycle. We developed everything in English, assuming that other languages would have similar character length words for equivalent meanings… don’t!. A word that is short in your language may be of varying character lengths in other languages. Some language like Dutch and German allow for concatenation of nouns which has the potential to create really long words. We picked up a few places where our views had been structured incorrectly so that if a word was to long it would get clipped off or cut out. To get around this we began using the WPF grid extensively with column widths that would automatically expand if they needed to. Generally speaking the grid replacement got round this hurdle, and if in future you have a choice between a stack panel or a grid – think twice before going for the easier option… often the grid will be a bit more work to setup, but will be more flexible. Lesson 3 – Separate the separators Our initial run through moving the words to a resource dictionary led us to make what I thought was one potential mistake. If we had a label like the following… “length : “ In the resource dictionary we put it as a single entry. This is fine until you start using a word more than once. For instance in our scenario we used the word “length’ frequently. with different variations of the word with grammar and separators included in the resource we ended up having what I would consider a bloated dictionary. When we removed the separators from the words and put them as their own resources we saw a dramatic reduction in dictionary size… so something that looked like this… “length : “ “length. “ “length?” Was reduced to… “length” “:” “?” “.” While this may not seem like a reduction at first glance, consider that the separators “:?.” are used everywhere and suddenly you see a real reduction in bloat. Lesson 4 – Centralize the Language Dictionary This lesson was learnt at the very end of the project after we had already had a release candidate out in the wild. Because our translations would be done on a volunteer basis and remotely, we wanted it to be really simple for someone to translate our program into another language. As a common design practice we had tiered the application so that we had a business logic layer, a ui layer, etc. The problem was in several of these layers we had resource files specific for that layer. What this resulted in was us having multiple resource files that we would need to send to our translators. To add to our problems, some of the wordings were duplicated in different resource files, which would result in additional frustration from our translators as they felt they were duplicating work. Eventually the workaround was to make a separate project in VS2010 with just the language translations. We then exposed the dictionary as public within this project and made it as a reference to the other projects within the solution. This solved out problem as now we had a central dictionary and could remove any duplication's. Lesson 5 – Make a dummy translation file to test that you haven’t missed anything The final lesson learnt about multi language support in WPF was when checking if you had forgotten to translate anything in the inline code, make a test resource file with dummy data. Ideally you want the data for each word to be identical. In our instance we made one which had all the resource key values pointing to a value of test. This allowed us point the language file to our test resource file and very quickly browse through the program and see if we had missed any linking. The alternative to this approach is to have two language files and swap between the two while running the program to make sure that you haven’t missed anything, but the downside of dual language file approach is that it is much a lot harder spotting a mistake if everything is different – almost like playing Where’s Wally / Waldo. It is much easier spotting variance in uniformity – meaning when you put the “test’ keyword for everything, anything that didn’t say “test” stuck out like a sore thumb. So these are my top five lessons learnt on implementing multi language support in WPF. Feel free to make any suggestions in the comments section if you feel maybe something is more important than one of these or if I got it wrong!

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• Delight and Excite

  - by Applications User Experience

  Mick McGee, CEO & President, EchoUser Editor’s Note: EchoUser is a User Experience design firm in San Francisco and a member of the Oracle Usability Advisory Board. Mick and his staff regularly consult on Oracle Applications UX projects. Being part of a user experience design firm, we have the luxury of working with a lot of great people across many great companies. We get to help people solve their problems.  At least we used to. The basic design challenge is still the same; however, the goal is not necessarily to solve “problems” anymore; it is, “I want our products to delight and excite!” The question for us as UX professionals is how to design to those goals, and then how to assess them from a usability perspective. I’m not sure where I first heard “delight and excite” (A book? blog post? Facebook  status? Steve Jobs quote?), but now I hear these listed as user experience goals all the time. In particular, somewhat paradoxically, I routinely hear them in enterprise software conversations. And when asking these same enterprise companies what will make the project successful, we very often hear, “Make it like Apple.” In past days, it was “make it like Yahoo (or Amazon or Google“) but now Apple is the common benchmark. Steve Jobs and Apple were not secrets, but with Jobs’ passing and Apple becoming the world’s most valuable company in the last year, the impact of great design and experience is suddenly very widespread. In particular, users’ expectations have gone way up. Being an enterprise company is no shield to the general expectations that users now have, for all products. Designing a “Minimum Viable Product” The user experience challenge has historically been, to echo the words of Eric Ries (author of Lean Startup) , to create a “minimum viable product”: the proverbial, “make it good enough”. But, in our profession, the “minimum viable” part of that phrase has oftentimes, unfortunately, referred to the design and user experience. Technology typically dominated the focus of the biggest, most successful companies. Few have had the laser focus of Apple to also create and sell design and user experience alongside great technology. But now that Apple is the most valuable company in the world, copying their success is a common undertaking. Great design is now a premium offering that everyone wants, from the one-person startup to the largest companies, consumer and enterprise. This emerging business paradigm will have significant impact across the user experience design process and profession. One area that particularly interests me is, how are we going to evaluate these new emerging “delight and excite” experiences, which are further customized to each particular domain? How to Measure “Delight and Excite” Traditional usability measures of task completion rate, assists, time, and errors are still extremely useful in many situations; however, they are too blunt to offer much insight into emerging experiences “Satisfaction” is usually assessed in user testing, in roughly equivalent importance to the above objective metrics. Various surveys and scales have provided ways to measure satisfying UX, with whatever questions they include. However, to meet the demands of new business goals and keep users at the center of design and development processes, we have to explore new methods to better capture custom-experience goals and emotion-driven user responses. We have had success assessing custom experiences, including “delight and excite”, by employing a variety of user testing methods that tend to combine formative and summative techniques (formative being focused more on identifying usability issues and ways to improve design, and summative focused more on metrics). Our most successful tool has been one we’ve been using for a long time, Magnitude Estimation Technique (MET). But it’s not necessarily about MET as a measure, rather how it is created. Caption: For one client, EchoUser did two rounds of testing.  Each test was a mix of performing representative tasks and gathering qualitative impressions. Each user participated in an in-person moderated 1-on-1 session for 1 hour, using a testing set-up where they held the phone. The primary goal was to identify usability issues and recommend design improvements. MET is based on a definition of the desired experience, which users will then use to rate items of interest (usually tasks in a usability test). In other words, a custom experience definition needs to be created. This can then be used to measure satisfaction in accomplishing tasks; “delight and excite”; or anything else from strategic goals, user demands, or elsewhere. For reference, our standard MET definition in usability testing is: “User experience is your perception of how easy to use, well designed and productive an interface is to complete tasks.” Articulating the User Experience We’ve helped construct experience definitions for several clients to better match their business goals. One example is a modification of the above that was needed for a company that makes medical-related products: “User experience is your perception of how easy to use, well-designed, productive and safe an interface is for conducting tasks. ‘Safe’ is how free an environment (including devices, software, facilities, people, etc.) is from danger, risk, and injury.” Another example is from a company that is pushing hard to incorporate “delight” into their enterprise business line: “User experience is your perception of a product’s ease of use and learning, satisfaction and delight in design, and ability to accomplish objectives.” I find the last one particularly compelling in that there is little that identifies the experience as being for a highly technical enterprise application. That definition could easily be applied to any number of consumer products. We have gone further than the above, including “sexy” and “cool” where decision-makers insisted they were part of the desired experience. We also applied it to completely different experiences where the “interface” was, for example, riding public transit, the “tasks” were train rides, and we followed the participants through the train-riding journey and rated various aspects accordingly: “A good public transportation experience is a cost-effective way of reliably, conveniently, and safely getting me to my intended destination on time.” To construct these definitions, we’ve employed both bottom-up and top-down approaches, depending on circumstances. For bottom-up, user inputs help dictate the terms that best fit the desired experience (usually by way of cluster and factor analysis). Top-down depends on strategic, visionary goals expressed by upper management that we then attempt to integrate into product development (e.g., “delight and excite”). We like a combination of both approaches to push the innovation envelope, but still be mindful of current user concerns. Hopefully the idea of crafting your own custom experience, and a way to measure it, can provide you with some ideas how you can adapt your user experience needs to whatever company you are in. Whether product-development or service-oriented, nearly every company is ultimately providing a user experience. The Bottom Line Creating great experiences may have been popularized by Steve Jobs and Apple, but I’ll be honest, it’s a good feeling to be moving from “good enough” to “delight and excite,” despite the challenge that entails. In fact, it’s because of that challenge that we will expand what we do as UX professionals to help deliver and assess those experiences. I’m excited to see how we, Oracle, and the rest of the industry will live up to that challenge.

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• At times, you need to hire a professional.

  - by Phil Factor

  After months of increasingly demanding toil, the development team I belonged to was told that the project was to be canned and the whole team would be fired.  I’d been brought into the team as an expert in the data implications of a business re-engineering of a major financial institution. Nowadays, you’d call me a data architect, I suppose.  I’d spent a happy year being paid consultancy fees solving a succession of interesting problems until the point when the company lost is nerve, and closed the entire initiative. The IT industry was in one of its characteristic mood-swings downwards.  After the announcement, we met in the canteen. A few developers had scented the smell of death around the project already hand had been applying unsuccessfully for jobs. There was a sense of doom in the mass of dishevelled and bleary-eyed developers. After giving vent to anger and despair, talk turned to getting new employment. It was then that I perked up. I’m not an obvious choice to give advice on getting, or passing,  IT interviews. I reckon I’ve failed most of the job interviews I’ve ever attended. I once even failed an interview for a job I’d already been doing perfectly well for a year. The jobs I’ve got have mostly been from personal recommendation. Paradoxically though, from years as a manager trying to recruit good staff, I know a lot about what IT managers are looking for.  I gave an impassioned speech outlining the important factors in getting to an interview.  The most important thing, certainly in my time at work is the quality of the résumé or CV. I can’t even guess the huge number of CVs (résumés) I’ve read through, scanning for candidates worth interviewing.  Many IT Developers find it impossible to describe their  career succinctly on two sides of paper.  They leave chunks of their life out (were they in prison?), get immersed in detail, put in irrelevancies, describe what was going on at work rather than what they themselves did, exaggerate their importance, criticize their previous employers, aren’t  aware of the important aspects of a role to a potential employer, suffer from shyness and modesty,  and lack any sort of organized perspective of their work. There are many ways of failing to write a decent CV. Many developers suffer from the delusion that their worth can be recognized purely from the code that they write, and shy away from anything that seems like self-aggrandizement. No.  A resume must make a good impression, which means presenting the facts about yourself in a clear and positive way. You can’t do it yourself. Why not have your resume professionally written? A good professional CV Writer will know the qualities being looked for in a CV and interrogate you to winkle them out. Their job is to make order and sense out of a confused career, to summarize in one page a mass of detail that presents to any recruiter the information that’s wanted. To stand back and describe an accurate summary of your skills, and work-experiences dispassionately, without rancor, pity or modesty. You are no more capable of producing an objective documentation of your career than you are of taking your own appendix out.  My next recommendation was more controversial. This is to have a professional image overhaul, or makeover, followed by a professionally-taken photo portrait. I discovered this by accident. It is normal for IT professionals to face impossible deadlines and long working hours by looking more and more like something that had recently blocked a sink. Whilst working in IT, and in a state of personal dishevelment, I’d been offered the role in a high-powered amateur production of an old ex- Broadway show, purely for my singing voice. I was supposed to be the presentable star. When the production team saw me, the air was thick with tension and despair. I was dragged kicking and protesting through a succession of desperate grooming, scrubbing, dressing, dieting. I emerged feeling like “That jewelled mass of millinery, That oiled and curled Assyrian bull, Smelling of musk and of insolence.” (Tennyson Maud; A Monodrama (1855) Section v1 stanza 6) I was then photographed by a professional stage photographer.  When the photographs were delivered, I was amazed. It wasn’t me, but it looked somehow respectable, confident, trustworthy.   A while later, when the show had ended, I took the photos, and used them for work. They went with the CV to job applications. It did the trick better than I could ever imagine.  My views went down big with the developers. Old rivalries were put immediately to one side. We voted, with a show of hands, to devote our energies for the entire notice period to getting employable. We had a team sourcing the CV Writer,  a team organising the make-overs and photographer, and a third team arranging  mock interviews. A fourth team determined the best websites and agencies for recruitment, with the help of friends in the trade.  Because there were around thirty developers, we were in a good negotiating position.  Of the three CV Writers we found who lived locally, one proved exceptional. She was an ex-journalist with an eye to detail, and years of experience in manipulating language. We tried her skills out on a developer who seemed a hopeless case, and he was called to interview within a week.  I was surprised, too, how many companies were experts at image makeovers. Within the month, we all looked like those weird slick  people in the ‘Office-tagged’ stock photographs who stare keenly and interestedly at PowerPoint slides in sleek chromium-plated high-rise offices. The portraits we used still adorn the entries of many of my ex-colleagues in LinkedIn. After a months’ worth of mock interviews, and technical Q&A, our stutters, hesitations, evasions and periphrastic circumlocutions were all gone.  There is little more to relate. With the résumés or CVs, mugshots, and schooling in how to pass interviews, we’d all got new and better-paid jobs well  before our month’s notice was ended. Whilst normally, an IT team under the axe is a sad and depressed place to belong to, this wonderful group of people had proved the power of organized group action in turning the experience to advantage. It left us feeling slightly guilty that we were somehow cheating, but I guess we were merely leveling the playing-field.

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• 'pip install carbon' looks like it works, but pip disagrees afterward

  - by fennec

  I'm trying to use pip to install the package carbon, a package related to statistics collection. When I run pip install carbon, it looks like everything works. However, pip is unconvinced that the package is actually installed. (This ultimately causes trouble because I'm using Puppet, and have a rule to install carbon using pip, and when puppet asks pip "is this package installed?" it says "no" and it reinstalls it again.) How do I figure out what's preventing pip from recognizing the success of this installation? Here is the output of the regular install: root@statsd:/opt/graphite# pip install carbon Downloading/unpacking carbon Downloading carbon-0.9.9.tar.gz Running setup.py egg_info for package carbon package init file 'lib/twisted/plugins/__init__.py' not found (or not a regular file) Requirement already satisfied (use --upgrade to upgrade): twisted in /usr/local/lib/python2.7/dist-packages (from carbon) Requirement already satisfied (use --upgrade to upgrade): txamqp in /usr/local/lib/python2.7/dist-packages (from carbon) Requirement already satisfied (use --upgrade to upgrade): zope.interface in /usr/local/lib/python2.7/dist-packages (from twisted->carbon) Requirement already satisfied (use --upgrade to upgrade): distribute in /usr/local/lib/python2.7/dist-packages (from zope.interface->twisted->carbon) Installing collected packages: carbon Running setup.py install for carbon package init file 'lib/twisted/plugins/__init__.py' not found (or not a regular file) changing mode of build/scripts-2.7/validate-storage-schemas.py from 664 to 775 changing mode of build/scripts-2.7/carbon-aggregator.py from 664 to 775 changing mode of build/scripts-2.7/carbon-cache.py from 664 to 775 changing mode of build/scripts-2.7/carbon-relay.py from 664 to 775 changing mode of build/scripts-2.7/carbon-client.py from 664 to 775 changing mode of /opt/graphite/bin/validate-storage-schemas.py to 775 changing mode of /opt/graphite/bin/carbon-aggregator.py to 775 changing mode of /opt/graphite/bin/carbon-cache.py to 775 changing mode of /opt/graphite/bin/carbon-relay.py to 775 changing mode of /opt/graphite/bin/carbon-client.py to 775 Successfully installed carbon Cleaning up... root@statsd:/opt/graphite# pip freeze | grep carbon root@statsd: Here is the verbose version of the install: root@statsd:/opt/graphite# pip install carbon -v Downloading/unpacking carbon Using version 0.9.9 (newest of versions: 0.9.9, 0.9.9, 0.9.8, 0.9.7, 0.9.6, 0.9.5) Downloading carbon-0.9.9.tar.gz Running setup.py egg_info for package carbon running egg_info creating pip-egg-info/carbon.egg-info writing requirements to pip-egg-info/carbon.egg-info/requires.txt writing pip-egg-info/carbon.egg-info/PKG-INFO writing top-level names to pip-egg-info/carbon.egg-info/top_level.txt writing dependency_links to pip-egg-info/carbon.egg-info/dependency_links.txt writing manifest file 'pip-egg-info/carbon.egg-info/SOURCES.txt' warning: manifest_maker: standard file '-c' not found package init file 'lib/twisted/plugins/__init__.py' not found (or not a regular file) reading manifest file 'pip-egg-info/carbon.egg-info/SOURCES.txt' writing manifest file 'pip-egg-info/carbon.egg-info/SOURCES.txt' Requirement already satisfied (use --upgrade to upgrade): twisted in /usr/local/lib/python2.7/dist-packages (from carbon) Requirement already satisfied (use --upgrade to upgrade): txamqp in /usr/local/lib/python2.7/dist-packages (from carbon) Requirement already satisfied (use --upgrade to upgrade): zope.interface in /usr/local/lib/python2.7/dist-packages (from twisted->carbon) Requirement already satisfied (use --upgrade to upgrade): distribute in /usr/local/lib/python2.7/dist-packages (from zope.interface->twisted->carbon) Installing collected packages: carbon Running setup.py install for carbon running install running build running build_py creating build creating build/lib.linux-i686-2.7 creating build/lib.linux-i686-2.7/carbon copying lib/carbon/amqp_publisher.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/manhole.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/instrumentation.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/cache.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/management.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/relayrules.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/events.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/protocols.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/conf.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/rewrite.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/hashing.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/writer.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/client.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/util.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/service.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/amqp_listener.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/routers.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/storage.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/log.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/__init__.py -> build/lib.linux-i686-2.7/carbon copying lib/carbon/state.py -> build/lib.linux-i686-2.7/carbon creating build/lib.linux-i686-2.7/carbon/aggregator copying lib/carbon/aggregator/receiver.py -> build/lib.linux-i686-2.7/carbon/aggregator copying lib/carbon/aggregator/rules.py -> build/lib.linux-i686-2.7/carbon/aggregator copying lib/carbon/aggregator/buffers.py -> build/lib.linux-i686-2.7/carbon/aggregator copying lib/carbon/aggregator/__init__.py -> build/lib.linux-i686-2.7/carbon/aggregator package init file 'lib/twisted/plugins/__init__.py' not found (or not a regular file) creating build/lib.linux-i686-2.7/twisted creating build/lib.linux-i686-2.7/twisted/plugins copying lib/twisted/plugins/carbon_relay_plugin.py -> build/lib.linux-i686-2.7/twisted/plugins copying lib/twisted/plugins/carbon_aggregator_plugin.py -> build/lib.linux-i686-2.7/twisted/plugins copying lib/twisted/plugins/carbon_cache_plugin.py -> build/lib.linux-i686-2.7/twisted/plugins copying lib/carbon/amqp0-8.xml -> build/lib.linux-i686-2.7/carbon running build_scripts creating build/scripts-2.7 copying and adjusting bin/validate-storage-schemas.py -> build/scripts-2.7 copying and adjusting bin/carbon-aggregator.py -> build/scripts-2.7 copying and adjusting bin/carbon-cache.py -> build/scripts-2.7 copying and adjusting bin/carbon-relay.py -> build/scripts-2.7 copying and adjusting bin/carbon-client.py -> build/scripts-2.7 changing mode of build/scripts-2.7/validate-storage-schemas.py from 664 to 775 changing mode of build/scripts-2.7/carbon-aggregator.py from 664 to 775 changing mode of build/scripts-2.7/carbon-cache.py from 664 to 775 changing mode of build/scripts-2.7/carbon-relay.py from 664 to 775 changing mode of build/scripts-2.7/carbon-client.py from 664 to 775 running install_lib copying build/lib.linux-i686-2.7/carbon/amqp_publisher.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/manhole.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/amqp0-8.xml -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/instrumentation.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/cache.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/management.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/relayrules.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/events.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/protocols.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/conf.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/rewrite.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/hashing.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/writer.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/client.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/util.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/aggregator/receiver.py -> /opt/graphite/lib/carbon/aggregator copying build/lib.linux-i686-2.7/carbon/aggregator/rules.py -> /opt/graphite/lib/carbon/aggregator copying build/lib.linux-i686-2.7/carbon/aggregator/buffers.py -> /opt/graphite/lib/carbon/aggregator copying build/lib.linux-i686-2.7/carbon/aggregator/__init__.py -> /opt/graphite/lib/carbon/aggregator copying build/lib.linux-i686-2.7/carbon/service.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/amqp_listener.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/routers.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/storage.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/log.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/__init__.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/carbon/state.py -> /opt/graphite/lib/carbon copying build/lib.linux-i686-2.7/twisted/plugins/carbon_relay_plugin.py -> /opt/graphite/lib/twisted/plugins copying build/lib.linux-i686-2.7/twisted/plugins/carbon_aggregator_plugin.py -> /opt/graphite/lib/twisted/plugins copying build/lib.linux-i686-2.7/twisted/plugins/carbon_cache_plugin.py -> /opt/graphite/lib/twisted/plugins byte-compiling /opt/graphite/lib/carbon/amqp_publisher.py to amqp_publisher.pyc byte-compiling /opt/graphite/lib/carbon/manhole.py to manhole.pyc byte-compiling /opt/graphite/lib/carbon/instrumentation.py to instrumentation.pyc byte-compiling /opt/graphite/lib/carbon/cache.py to cache.pyc byte-compiling /opt/graphite/lib/carbon/management.py to management.pyc byte-compiling /opt/graphite/lib/carbon/relayrules.py to relayrules.pyc byte-compiling /opt/graphite/lib/carbon/events.py to events.pyc byte-compiling /opt/graphite/lib/carbon/protocols.py to protocols.pyc byte-compiling /opt/graphite/lib/carbon/conf.py to conf.pyc byte-compiling /opt/graphite/lib/carbon/rewrite.py to rewrite.pyc byte-compiling /opt/graphite/lib/carbon/hashing.py to hashing.pyc byte-compiling /opt/graphite/lib/carbon/writer.py to writer.pyc byte-compiling /opt/graphite/lib/carbon/client.py to client.pyc byte-compiling /opt/graphite/lib/carbon/util.py to util.pyc byte-compiling /opt/graphite/lib/carbon/aggregator/receiver.py to receiver.pyc byte-compiling /opt/graphite/lib/carbon/aggregator/rules.py to rules.pyc byte-compiling /opt/graphite/lib/carbon/aggregator/buffers.py to buffers.pyc byte-compiling /opt/graphite/lib/carbon/aggregator/__init__.py to __init__.pyc byte-compiling /opt/graphite/lib/carbon/service.py to service.pyc byte-compiling /opt/graphite/lib/carbon/amqp_listener.py to amqp_listener.pyc byte-compiling /opt/graphite/lib/carbon/routers.py to routers.pyc byte-compiling /opt/graphite/lib/carbon/storage.py to storage.pyc byte-compiling /opt/graphite/lib/carbon/log.py to log.pyc byte-compiling /opt/graphite/lib/carbon/__init__.py to __init__.pyc byte-compiling /opt/graphite/lib/carbon/state.py to state.pyc byte-compiling /opt/graphite/lib/twisted/plugins/carbon_relay_plugin.py to carbon_relay_plugin.pyc byte-compiling /opt/graphite/lib/twisted/plugins/carbon_aggregator_plugin.py to carbon_aggregator_plugin.pyc byte-compiling /opt/graphite/lib/twisted/plugins/carbon_cache_plugin.py to carbon_cache_plugin.pyc running install_data copying conf/storage-schemas.conf.example -> /opt/graphite/conf copying conf/rewrite-rules.conf.example -> /opt/graphite/conf copying conf/relay-rules.conf.example -> /opt/graphite/conf copying conf/carbon.amqp.conf.example -> /opt/graphite/conf copying conf/aggregation-rules.conf.example -> /opt/graphite/conf copying conf/carbon.conf.example -> /opt/graphite/conf running install_egg_info running egg_info creating lib/carbon.egg-info writing requirements to lib/carbon.egg-info/requires.txt writing lib/carbon.egg-info/PKG-INFO writing top-level names to lib/carbon.egg-info/top_level.txt writing dependency_links to lib/carbon.egg-info/dependency_links.txt writing manifest file 'lib/carbon.egg-info/SOURCES.txt' warning: manifest_maker: standard file '-c' not found reading manifest file 'lib/carbon.egg-info/SOURCES.txt' writing manifest file 'lib/carbon.egg-info/SOURCES.txt' removing '/opt/graphite/lib/carbon-0.9.9-py2.7.egg-info' (and everything under it) Copying lib/carbon.egg-info to /opt/graphite/lib/carbon-0.9.9-py2.7.egg-info running install_scripts copying build/scripts-2.7/validate-storage-schemas.py -> /opt/graphite/bin copying build/scripts-2.7/carbon-aggregator.py -> /opt/graphite/bin copying build/scripts-2.7/carbon-cache.py -> /opt/graphite/bin copying build/scripts-2.7/carbon-relay.py -> /opt/graphite/bin copying build/scripts-2.7/carbon-client.py -> /opt/graphite/bin changing mode of /opt/graphite/bin/validate-storage-schemas.py to 775 changing mode of /opt/graphite/bin/carbon-aggregator.py to 775 changing mode of /opt/graphite/bin/carbon-cache.py to 775 changing mode of /opt/graphite/bin/carbon-relay.py to 775 changing mode of /opt/graphite/bin/carbon-client.py to 775 writing list of installed files to '/tmp/pip-9LuJTF-record/install-record.txt' Successfully installed carbon Cleaning up... Removing temporary dir /opt/graphite/build... root@statsd:/opt/graphite# For reference, this is pip 1.0 from /usr/lib/python2.7/dist-packages (python 2.7)

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• Squid + Dans Guardian (simple configuration)

  - by The Digital Ninja

  I just built a new proxy server and compiled the latest versions of squid and dansguardian. We use basic authentication to select what users are allowed outside of our network. It seems squid is working just fine and accepts my username and password and lets me out. But if i connect to dans guardian, it prompts for username and password and then displays a message saying my username is not allowed to access the internet. Its pulling my username for the error message so i know it knows who i am. The part i get confused on is i thought that part was handled all by squid, and squid is working flawlessly. Can someone please double check my config files and tell me if i'm missing something or there is some new option i must set to get this to work. dansguardian.conf # Web Access Denied Reporting (does not affect logging) # # -1 = log, but do not block - Stealth mode # 0 = just say 'Access Denied' # 1 = report why but not what denied phrase # 2 = report fully # 3 = use HTML template file (accessdeniedaddress ignored) - recommended # reportinglevel = 3 # Language dir where languages are stored for internationalisation. # The HTML template within this dir is only used when reportinglevel # is set to 3. When used, DansGuardian will display the HTML file instead of # using the perl cgi script. This option is faster, cleaner # and easier to customise the access denied page. # The language file is used no matter what setting however. # languagedir = '/etc/dansguardian/languages' # language to use from languagedir. language = 'ukenglish' # Logging Settings # # 0 = none 1 = just denied 2 = all text based 3 = all requests loglevel = 3 # Log Exception Hits # Log if an exception (user, ip, URL, phrase) is matched and so # the page gets let through. Can be useful for diagnosing # why a site gets through the filter. on | off logexceptionhits = on # Log File Format # 1 = DansGuardian format 2 = CSV-style format # 3 = Squid Log File Format 4 = Tab delimited logfileformat = 1 # Log file location # # Defines the log directory and filename. #loglocation = '/var/log/dansguardian/access.log' # Network Settings # # the IP that DansGuardian listens on. If left blank DansGuardian will # listen on all IPs. That would include all NICs, loopback, modem, etc. # Normally you would have your firewall protecting this, but if you want # you can limit it to only 1 IP. Yes only one. filterip = # the port that DansGuardian listens to. filterport = 8080 # the ip of the proxy (default is the loopback - i.e. this server) proxyip = 127.0.0.1 # the port DansGuardian connects to proxy on proxyport = 3128 # accessdeniedaddress is the address of your web server to which the cgi # dansguardian reporting script was copied # Do NOT change from the default if you are not using the cgi. # accessdeniedaddress = 'http://YOURSERVER.YOURDOMAIN/cgi-bin/dansguardian.pl' # Non standard delimiter (only used with accessdeniedaddress) # Default is enabled but to go back to the original standard mode dissable it. nonstandarddelimiter = on # Banned image replacement # Images that are banned due to domain/url/etc reasons including those # in the adverts blacklists can be replaced by an image. This will, # for example, hide images from advert sites and remove broken image # icons from banned domains. # 0 = off # 1 = on (default) usecustombannedimage = 1 custombannedimagefile = '/etc/dansguardian/transparent1x1.gif' # Filter groups options # filtergroups sets the number of filter groups. A filter group is a set of content # filtering options you can apply to a group of users. The value must be 1 or more. # DansGuardian will automatically look for dansguardianfN.conf where N is the filter # group. To assign users to groups use the filtergroupslist option. All users default # to filter group 1. You must have some sort of authentication to be able to map users # to a group. The more filter groups the more copies of the lists will be in RAM so # use as few as possible. filtergroups = 1 filtergroupslist = '/etc/dansguardian/filtergroupslist' # Authentication files location bannediplist = '/etc/dansguardian/bannediplist' exceptioniplist = '/etc/dansguardian/exceptioniplist' banneduserlist = '/etc/dansguardian/banneduserlist' exceptionuserlist = '/etc/dansguardian/exceptionuserlist' # Show weighted phrases found # If enabled then the phrases found that made up the total which excedes # the naughtyness limit will be logged and, if the reporting level is # high enough, reported. on | off showweightedfound = on # Weighted phrase mode # There are 3 possible modes of operation: # 0 = off = do not use the weighted phrase feature. # 1 = on, normal = normal weighted phrase operation. # 2 = on, singular = each weighted phrase found only counts once on a page. # weightedphrasemode = 2 # Positive result caching for text URLs # Caches good pages so they don't need to be scanned again # 0 = off (recommended for ISPs with users with disimilar browsing) # 1000 = recommended for most users # 5000 = suggested max upper limit urlcachenumber = # # Age before they are stale and should be ignored in seconds # 0 = never # 900 = recommended = 15 mins urlcacheage = # Smart and Raw phrase content filtering options # Smart is where the multiple spaces and HTML are removed before phrase filtering # Raw is where the raw HTML including meta tags are phrase filtered # CPU usage can be effectively halved by using setting 0 or 1 # 0 = raw only # 1 = smart only # 2 = both (default) phrasefiltermode = 2 # Lower casing options # When a document is scanned the uppercase letters are converted to lower case # in order to compare them with the phrases. However this can break Big5 and # other 16-bit texts. If needed preserve the case. As of version 2.7.0 accented # characters are supported. # 0 = force lower case (default) # 1 = do not change case preservecase = 0 # Hex decoding options # When a document is scanned it can optionally convert %XX to chars. # If you find documents are getting past the phrase filtering due to encoding # then enable. However this can break Big5 and other 16-bit texts. # 0 = disabled (default) # 1 = enabled hexdecodecontent = 0 # Force Quick Search rather than DFA search algorithm # The current DFA implementation is not totally 16-bit character compatible # but is used by default as it handles large phrase lists much faster. # If you wish to use a large number of 16-bit character phrases then # enable this option. # 0 = off (default) # 1 = on (Big5 compatible) forcequicksearch = 0 # Reverse lookups for banned site and URLs. # If set to on, DansGuardian will look up the forward DNS for an IP URL # address and search for both in the banned site and URL lists. This would # prevent a user from simply entering the IP for a banned address. # It will reduce searching speed somewhat so unless you have a local caching # DNS server, leave it off and use the Blanket IP Block option in the # bannedsitelist file instead. reverseaddresslookups = off # Reverse lookups for banned and exception IP lists. # If set to on, DansGuardian will look up the forward DNS for the IP # of the connecting computer. This means you can put in hostnames in # the exceptioniplist and bannediplist. # It will reduce searching speed somewhat so unless you have a local DNS server, # leave it off. reverseclientiplookups = off # Build bannedsitelist and bannedurllist cache files. # This will compare the date stamp of the list file with the date stamp of # the cache file and will recreate as needed. # If a bsl or bul .processed file exists, then that will be used instead. # It will increase process start speed by 300%. On slow computers this will # be significant. Fast computers do not need this option. on | off createlistcachefiles = on # POST protection (web upload and forms) # does not block forms without any file upload, i.e. this is just for # blocking or limiting uploads # measured in kibibytes after MIME encoding and header bumph # use 0 for a complete block # use higher (e.g. 512 = 512Kbytes) for limiting # use -1 for no blocking #maxuploadsize = 512 #maxuploadsize = 0 maxuploadsize = -1 # Max content filter page size # Sometimes web servers label binary files as text which can be very # large which causes a huge drain on memory and cpu resources. # To counter this, you can limit the size of the document to be # filtered and get it to just pass it straight through. # This setting also applies to content regular expression modification. # The size is in Kibibytes - eg 2048 = 2Mb # use 0 for no limit maxcontentfiltersize = # Username identification methods (used in logging) # You can have as many methods as you want and not just one. The first one # will be used then if no username is found, the next will be used. # * proxyauth is for when basic proxy authentication is used (no good for # transparent proxying). # * ntlm is for when the proxy supports the MS NTLM authentication # protocol. (Only works with IE5.5 sp1 and later). **NOT IMPLEMENTED** # * ident is for when the others don't work. It will contact the computer # that the connection came from and try to connect to an identd server # and query it for the user owner of the connection. usernameidmethodproxyauth = on usernameidmethodntlm = off # **NOT IMPLEMENTED** usernameidmethodident = off # Preemptive banning - this means that if you have proxy auth enabled and a user accesses # a site banned by URL for example they will be denied straight away without a request # for their user and pass. This has the effect of requiring the user to visit a clean # site first before it knows who they are and thus maybe an admin user. # This is how DansGuardian has always worked but in some situations it is less than # ideal. So you can optionally disable it. Default is on. # As a side effect disabling this makes AD image replacement work better as the mime # type is know. preemptivebanning = on # Misc settings # if on it adds an X-Forwarded-For: <clientip> to the HTTP request # header. This may help solve some problem sites that need to know the # source ip. on | off forwardedfor = on # if on it uses the X-Forwarded-For: <clientip> to determine the client # IP. This is for when you have squid between the clients and DansGuardian. # Warning - headers are easily spoofed. on | off usexforwardedfor = off # if on it logs some debug info regarding fork()ing and accept()ing which # can usually be ignored. These are logged by syslog. It is safe to leave # it on or off logconnectionhandlingerrors = on # Fork pool options # sets the maximum number of processes to sporn to handle the incomming # connections. Max value usually 250 depending on OS. # On large sites you might want to try 180. maxchildren = 180 # sets the minimum number of processes to sporn to handle the incomming connections. # On large sites you might want to try 32. minchildren = 32 # sets the minimum number of processes to be kept ready to handle connections. # On large sites you might want to try 8. minsparechildren = 8 # sets the minimum number of processes to sporn when it runs out # On large sites you might want to try 10. preforkchildren = 10 # sets the maximum number of processes to have doing nothing. # When this many are spare it will cull some of them. # On large sites you might want to try 64. maxsparechildren = 64 # sets the maximum age of a child process before it croaks it. # This is the number of connections they handle before exiting. # On large sites you might want to try 10000. maxagechildren = 5000 # Process options # (Change these only if you really know what you are doing). # These options allow you to run multiple instances of DansGuardian on a single machine. # Remember to edit the log file path above also if that is your intention. # IPC filename # # Defines IPC server directory and filename used to communicate with the log process. ipcfilename = '/tmp/.dguardianipc' # URL list IPC filename # # Defines URL list IPC server directory and filename used to communicate with the URL # cache process. urlipcfilename = '/tmp/.dguardianurlipc' # PID filename # # Defines process id directory and filename. #pidfilename = '/var/run/dansguardian.pid' # Disable daemoning # If enabled the process will not fork into the background. # It is not usually advantageous to do this. # on|off ( defaults to off ) nodaemon = off # Disable logging process # on|off ( defaults to off ) nologger = off # Daemon runas user and group # This is the user that DansGuardian runs as. Normally the user/group nobody. # Uncomment to use. Defaults to the user set at compile time. # daemonuser = 'nobody' # daemongroup = 'nobody' # Soft restart # When on this disables the forced killing off all processes in the process group. # This is not to be confused with the -g run time option - they are not related. # on|off ( defaults to off ) softrestart = off maxcontentramcachescansize = 2000 maxcontentfilecachescansize = 20000 downloadmanager = '/etc/dansguardian/downloadmanagers/default.conf' authplugin = '/etc/dansguardian/authplugins/proxy-basic.conf' Squid.conf http_port 3128 hierarchy_stoplist cgi-bin ? acl QUERY urlpath_regex cgi-bin \? cache deny QUERY acl apache rep_header Server ^Apache #broken_vary_encoding allow apache access_log /squid/var/logs/access.log squid hosts_file /etc/hosts auth_param basic program /squid/libexec/ncsa_auth /squid/etc/userbasic.auth auth_param basic children 5 auth_param basic realm proxy auth_param basic credentialsttl 2 hours auth_param basic casesensitive off refresh_pattern ^ftp: 1440 20% 10080 refresh_pattern ^gopher: 1440 0% 1440 refresh_pattern . 0 20% 4320 acl NoAuthNec src <HIDDEN FOR SECURITY> acl BrkRm src <HIDDEN FOR SECURITY> acl Dials src <HIDDEN FOR SECURITY> acl Comps src <HIDDEN FOR SECURITY> acl whsws dstdom_regex -i .opensuse.org .novell.com .suse.com mirror.mcs.an1.gov mirrors.kernerl.org www.suse.de suse.mirrors.tds.net mirrros.usc.edu ftp.ale.org suse.cs.utah.edu mirrors.usc.edu mirror.usc.an1.gov linux.nssl.noaa.gov noaa.gov .kernel.org ftp.ale.org ftp.gwdg.de .medibuntu.org mirrors.xmission.com .canonical.com .ubuntu. acl opensites dstdom_regex -i .mbsbooks.com .bowker.com .usps.com .usps.gov .ups.com .fedex.com go.microsoft.com .microsoft.com .apple.com toolbar.msn.com .contacts.msn.com update.services.openoffice.org fms2.pointroll.speedera.net services.wmdrm.windowsmedia.com windowsupdate.com .adobe.com .symantec.com .vitalbook.com vxn1.datawire.net vxn.datawire.net download.lavasoft.de .download.lavasoft.com .lavasoft.com updates.ls-servers.com .canadapost. .myyellow.com minirick symantecliveupdate.com wm.overdrive.com www.overdrive.com productactivation.one.microsoft.com www.update.microsoft.com testdrive.whoson.com www.columbia.k12.mo.us banners.wunderground.com .kofax.com .gotomeeting.com tools.google.com .dl.google.com .cache.googlevideo.com .gpdl.google.com .clients.google.com cache.pack.google.com kh.google.com maps.google.com auth.keyhole.com .contacts.msn.com .hrblock.com .taxcut.com .merchantadvantage.com .jtv.com .malwarebytes.org www.google-analytics.com dcs.support.xerox.com .dhl.com .webtrendslive.com javadl-esd.sun.com javadl-alt.sun.com .excelsior.edu .dhlglobalmail.com .nessus.org .foxitsoftware.com foxit.vo.llnwd.net installshield.com .mindjet.com .mediascouter.com media.us.elsevierhealth.com .xplana.com .govtrack.us sa.tulsacc.edu .omniture.com fpdownload.macromedia.com webservices.amazon.com acl password proxy_auth REQUIRED acl all src all acl manager proto cache_object acl localhost src 127.0.0.1/255.255.255.255 acl to_localhost dst 127.0.0.0/8 acl SSL_ports port 443 563 631 2001 2005 8731 9001 9080 10000 acl Safe_ports port 80 # http acl Safe_ports port 21 # ftp acl Safe_ports port # https, snews 443 563 acl Safe_ports port 70 # gopher acl Safe_ports port 210 # wais acl Safe_ports port # unregistered ports 1936-65535 acl Safe_ports port 280 # http-mgmt acl Safe_ports port 488 # gss-http acl Safe_ports port 10000 acl Safe_ports port 631 acl Safe_ports port 901 # SWAT acl purge method PURGE acl CONNECT method CONNECT acl UTubeUsers proxy_auth "/squid/etc/utubeusers.list" acl RestrictUTube dstdom_regex -i youtube.com acl RestrictFacebook dstdom_regex -i facebook.com acl FacebookUsers proxy_auth "/squid/etc/facebookusers.list" acl BuemerKEC src 10.10.128.0/24 acl MBSsortnet src 10.10.128.0/26 acl MSNExplorer browser -i MSN acl Printers src <HIDDEN FOR SECURITY> acl SpecialFolks src <HIDDEN FOR SECURITY> # streaming download acl fails rep_mime_type ^.*mms.* acl fails rep_mime_type ^.*ms-hdr.* acl fails rep_mime_type ^.*x-fcs.* acl fails rep_mime_type ^.*x-ms-asf.* acl fails2 urlpath_regex dvrplayer mediastream mms:// acl fails2 urlpath_regex \.asf$ \.afx$ \.flv$ \.swf$ acl deny_rep_mime_flashvideo rep_mime_type -i video/flv acl deny_rep_mime_shockwave rep_mime_type -i ^application/x-shockwave-flash$ acl x-type req_mime_type -i ^application/octet-stream$ acl x-type req_mime_type -i application/octet-stream acl x-type req_mime_type -i ^application/x-mplayer2$ acl x-type req_mime_type -i application/x-mplayer2 acl x-type req_mime_type -i ^application/x-oleobject$ acl x-type req_mime_type -i application/x-oleobject acl x-type req_mime_type -i application/x-pncmd acl x-type req_mime_type -i ^video/x-ms-asf$ acl x-type2 rep_mime_type -i ^application/octet-stream$ acl x-type2 rep_mime_type -i application/octet-stream acl x-type2 rep_mime_type -i ^application/x-mplayer2$ acl x-type2 rep_mime_type -i application/x-mplayer2 acl x-type2 rep_mime_type -i ^application/x-oleobject$ acl x-type2 rep_mime_type -i application/x-oleobject acl x-type2 rep_mime_type -i application/x-pncmd acl x-type2 rep_mime_type -i ^video/x-ms-asf$ acl RestrictHulu dstdom_regex -i hulu.com acl broken dstdomain cms.montgomerycollege.edu events.columbiamochamber.com members.columbiamochamber.com public.genexusserver.com acl RestrictVimeo dstdom_regex -i vimeo.com acl http_port port 80 #http_reply_access deny deny_rep_mime_flashvideo #http_reply_access deny deny_rep_mime_shockwave #streaming files #http_access deny fails #http_reply_access deny fails #http_access deny fails2 #http_reply_access deny fails2 #http_access deny x-type #http_reply_access deny x-type #http_access deny x-type2 #http_reply_access deny x-type2 follow_x_forwarded_for allow localhost acl_uses_indirect_client on log_uses_indirect_client on http_access allow manager localhost http_access deny manager http_access allow purge localhost http_access deny purge http_access allow SpecialFolks http_access deny CONNECT !SSL_ports http_access allow whsws http_access allow opensites http_access deny BuemerKEC !MBSsortnet http_access deny BrkRm RestrictUTube RestrictFacebook RestrictVimeo http_access allow RestrictUTube UTubeUsers http_access deny RestrictUTube http_access allow RestrictFacebook FacebookUsers http_access deny RestrictFacebook http_access deny RestrictHulu http_access allow NoAuthNec http_access allow BrkRm http_access allow FacebookUsers RestrictVimeo http_access deny RestrictVimeo http_access allow Comps http_access allow Dials http_access allow Printers http_access allow password http_access deny !Safe_ports http_access deny SSL_ports !CONNECT http_access allow http_port http_access deny all http_reply_access allow all icp_access allow all access_log /squid/var/logs/access.log squid visible_hostname proxy.site.com forwarded_for off coredump_dir /squid/cache/ #header_access Accept-Encoding deny broken #acl snmppublic snmp_community mysecretcommunity #snmp_port 3401 #snmp_access allow snmppublic all cache_mem 3 GB #acl snmppublic snmp_community mbssquid #snmp_port 3401 #snmp_access allow snmppublic all

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• Lots of first chance Microsoft.CSharp.RuntimeBinderExceptions thrown when dealing with dynamics

  - by Orion Edwards

  I've got a standard 'dynamic dictionary' type class in C# - class Bucket : DynamicObject { readonly Dictionary<string, object> m_dict = new Dictionary<string, object>(); public override bool TrySetMember(SetMemberBinder binder, object value) { m_dict[binder.Name] = value; return true; } public override bool TryGetMember(GetMemberBinder binder, out object result) { return m_dict.TryGetValue(binder.Name, out result); } } Now I call it, as follows: static void Main(string[] args) { dynamic d = new Bucket(); d.Name = "Orion"; // 2 RuntimeBinderExceptions Console.WriteLine(d.Name); // 2 RuntimeBinderExceptions } The app does what you'd expect it to, but the debug output looks like this: A first chance exception of type 'Microsoft.CSharp.RuntimeBinder.RuntimeBinderException' occurred in Microsoft.CSharp.dll A first chance exception of type 'Microsoft.CSharp.RuntimeBinder.RuntimeBinderException' occurred in Microsoft.CSharp.dll 'ScratchConsoleApplication.vshost.exe' (Managed (v4.0.30319)): Loaded 'Anonymously Hosted DynamicMethods Assembly' A first chance exception of type 'Microsoft.CSharp.RuntimeBinder.RuntimeBinderException' occurred in Microsoft.CSharp.dll A first chance exception of type 'Microsoft.CSharp.RuntimeBinder.RuntimeBinderException' occurred in Microsoft.CSharp.dll Any attempt to access a dynamic member seems to output a RuntimeBinderException to the debug logs. While I'm aware that first-chance exceptions are not a problem in and of themselves, this does cause some problems for me: I often have the debugger set to "break on exceptions", as I'm writing WPF apps, and otherwise all exceptions end up getting converted to a DispatcherUnhandledException, and all the actual information you want is lost. WPF sucks like that. As soon as I hit any code that's using dynamic, the debug output log becomes fairly useless. All the useful trace lines that I care about get hidden amongst all the useless RuntimeBinderExceptions Is there any way I can turn this off, or is the RuntimeBinder unfortunately just built like that? Thanks, Orion

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• sp_send_dbmail attach files stored as varbinary in database

  - by Mindstorm Interactive

  I have a two part question relating to sending query results as attachments using sp_send_dbmail. Problem 1: Only basic .txt files will open. Any other format like .pdf or .jpg are corrupted. Problem 2: When attempting to send multiple attachments, I receive one file with all file names glued together. I'm running SQL Server 2005 and I have a table storing uploaded documents: CREATE TABLE [dbo].[EmailAttachment]( [EmailAttachmentID] [int] IDENTITY(1,1) NOT NULL, [MassEmailID] [int] NULL, -- foreign key [FileData] [varbinary](max) NOT NULL, [FileName] [varchar](100) NOT NULL, [MimeType] [varchar](100) NOT NULL I also have a MassEmail table with standard email stuff. Here is the SQL Send Mail script. For brevity, I've excluded declare statements. while ( (select count(MassEmailID) from MassEmail where status = 20 )>0) begin select @MassEmailID = Min(MassEmailID) from MassEmail where status = 20 select @Subject = [Subject] from MassEmail where MassEmailID = @MassEmailID select @Body = Body from MassEmail where MassEmailID = @MassEmailID set @query = 'set nocount on; select cast(FileData as varchar(max)) from Mydatabase.dbo.EmailAttachment where MassEmailID = '+ CAST(@MassEmailID as varchar(100)) select @filename = '' select @filename = COALESCE(@filename+ ',', '') +FileName from EmailAttachment where MassEmailID = @MassEmailID exec msdb.dbo.sp_send_dbmail @profile_name = 'MASS_EMAIL', @recipients = '[email protected]', @subject = @Subject, @body =@Body, @body_format ='HTML', @query = @query, @query_attachment_filename = @filename, @attach_query_result_as_file = 1, @query_result_separator = '; ', @query_no_truncate = 1, @query_result_header = 0; update MassEmailset status= 30,SendDate = GetDate() where MassEmailID = @MassEmailID end I am able to successfully read files from the database so I know the binary data is not corrupted. .txt files only read when I cast FilaData to varchar. But clearly original headers are lost. It's also worth noting that attachment file sizes are different than the original files. That is most likely due to improper encoding as well. So I'm hoping there's a way to create file headers using the stored mimetype, or some way to include file headers in the binary data? I'm also not confident in the values of the last few parameters, and I know coalesce is not quite right, because it prepends the first file name with a comma. But good documentation is nearly impossible to find. Please help!

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• Using ReportViewer 9 control in VS 2010

  - by Fermin

  Hi, I am writing an ASP.NET app that uses a SQL Server 2005 with SSRS setup. I want to use the ReportViewer control but I get an error when using ReportViewer 10 because it needs SSRS 2008. How can I use ReportViewer 9 within my application. I've added a reference to the Microsoft.ReportViewer.WebForms.dll version 9 and removed the reference to version 10. My markup is as follows: <%@ Register Assembly="Microsoft.ReportViewer.WebForms, Version=9.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a" Namespace="Microsoft.Reporting.WebForms" TagPrefix="rsweb" %> <!-- standard markup --> <rsweb:ReportViewer ID="ReportViewer1" runat="server"></rsweb:ReportViewer> but when I try to run this I get the following error: CS0433: The type 'Microsoft.Reporting.WebForms.ReportViewer' exists in both 'c:\WINDOWS\assembly\GAC_MSIL\Microsoft.ReportViewer.WebForms\10.0.0.0__b03f5f7f11d50a3a\Microsoft.ReportViewer.WebForms.dll' and 'c:\WINDOWS\assembly\GAC_MSIL\Microsoft.ReportViewer.WebForms\9.0.0.0__b03f5f7f11d50a3a\Microsoft.ReportViewer.WebForms.dll' What have I missed!? Update: When trying to use the ReportViewer 10 I get the following error: "Remote report processing requires Microsoft SQL Server 2008 Reporting Services or later."

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• Problem displaying custom error page in ASP.NET MVC 2

  - by robert_d

  This is customErrors section from my web.config file <customErrors mode="On"> <error statusCode="500" redirect="HTTP500.aspx" /> </customErrors> HTTP500.aspx is the same as standard /Views/Shared/Error.aspx page. When I get HTTP 500 error I see this page: Server Error in '/' Application. Runtime Error Description: An application error occurred on the server. The current custom error settings for this application prevent the details of the application error from being viewed. Details: To enable the details of this specific error message to be viewable on the local server machine, please create a tag within a "web.config" configuration file located in the root directory of the current web application. This tag should then have its "mode" attribute set to "RemoteOnly". To enable the details to be viewable on remote machines, please set "mode" to "Off". Notes: The current error page you are seeing can be replaced by a custom error page by modifying the "defaultRedirect" attribute of the application's configuration tag to point to a custom error page URL. But when I change the above customErrors section like this: <customErrors mode="On"> <error statusCode="500" redirect="HTTP500.htm" /> </customErrors> then HTTP500.htm page is displayed when HTTP 500 error occurs. Why HTTP500.aspx page isn't displayed?

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• Brother bPAC SDK - Examples only print after Form is shown

  - by Scoregraphic

  Hi there We have a small Brother Barcode printer which we like to control from a WCF Service. Brother has an API called bPAC SDK version 3 which allows to print those labels. But the problem arises, as soon as we want to print from code only without showing a windows with a button on it. As an addition, this happens only if you want to print a QR-code as barcode. Standard EAN-codes seems to work. Below is a small piece of code which outputs the stuff to a bitmap instead of the printer (debugging reasons). DocumentClass doc = new DocumentClass(); if (doc.Open(templatePath)) { doc.GetObject("barcode1").Text = txtCompany.Text; doc.GetObject("barcode2").Text = txtName.Text; doc.Export(ExportType.bexBmp, testImagePath, 300); doc.Close(); } If this is called by a button click, it perfectly works. If this is called in Form.Show-event, it perfectly works. If this is called in Form.Load-event, it does NOT work. If this is called in a Form constructor, it does NOT work. If this is called somewhere else (without forms), it does NOT work. DocumentClass and related classes are COM-objects, so I guess the form setup/show process seems to do something which is not done without opening forms. I tried calling CoInitialize with a p/invoke, but it hadn't changed anything. Is there anyone out there willing and able to help me? Are there any alternatives which (also) MUST be able to print directly on our Brother printer? Thanks lot.

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• Configuring WCF 4 with routing (global.asax) for both http & https endpoints

  - by jammer59

  I'm still a newbie with wcf and not too well informed in .net in general. I have a WCF 4 web service that uses the global.asax routing approach and very simplified web.config using the standard endpoint method. This wcf service runs as an application with the default web site on iis 7.5 at present. I need it support both http and https interfaces, if possible. If that's too complex then only https. How is that best handled maintaining the current approach? The contents of the global.asax.cs and web.config files are pretty basic: public class Global : HttpApplication { void Application_Start(object sender, EventArgs e) { RegisterRoutes(); } private void RegisterRoutes() { // Edit the base address of Service1 by replacing the "ippay" string below RouteTable.Routes.Add(new ServiceRoute("myservice", new WebServiceHostFactory(), typeof(myservice))); } } <system.serviceModel> <serviceHostingEnvironment aspNetCompatibilityEnabled="true"/> <standardEndpoints> <webHttpEndpoint> <standardEndpoint name="" helpEnabled="true" contentTypeMapper="myservice.Util.RawMapper,myservice"> </standardEndpoint> </webHttpEndpoint> </standardEndpoints>

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• ASP.NET MVC returning ContentResult using Ajax form - how to preserve whitespace?

  - by Ben

  In my application users can enter commands that are executed on the server. The results are added to a session object. I then stuff the session object into ViewData and add it to a textarea. When done with a standard HTML form whitespace is preserved. However, when I swap this out for an ajax form (Ajax.BeginForm) and return the result as ContentResult, the whitespace is removed. Controller Action: [HttpPost] public ActionResult Execute(string submitButton, string command) { if (submitButton == "Clear") { this.CurrentConsole = string.Empty; } if (submitButton == "Execute" && !string.IsNullOrEmpty(command)) { var script = new PSScript() { Name = "Ad hoc script", CommandText = command }; this.CurrentConsole += _scriptService.ExecuteScript(script); } if (Request.IsAjaxRequest()) { return Content(this.CurrentConsole, "text/plain"); } return RedirectToAction("Index"); } View: <fieldset> <legend>Shell</legend> <%=Html.TextArea("console", ViewData["console"].ToString(), new {@class = "console", @readonly = "readonly"})%> <% using (Ajax.BeginForm("Execute", new AjaxOptions { UpdateTargetId = "console", OnBegin = "console_begin", OnComplete = "console_complete"})) { %> <input type="text" id="command" name="command" class="commandtext" /> <input type="submit" value="Execute" class="runbutton" name="submitButton" /> <input type="submit" value="Clear" class="runbutton" name="submitButton" /> <%} %> </fieldset> How can I ensure that whitespace is preserved? When I inspect the response in FireBug it looks like the whitespace is transmitted, so can only assume it has something to do with the way in which the javascript handles the response data.

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• Ninject.Web, OnePerRequestModule, and IIS7 Integrated Pipeline

  - by Ted

  Using Ninject.Web with ASP.NET WebForms project. Works without issues using classic pipeline, but when it's under integrated pipeline, a null reference exception occurs on every request (which I've narrowed down to the use of the OnePerRequestModule): [NullReferenceException: Object reference not set to an instance of an object.] System.Web.PipelineStepManager.ResumeSteps(Exception error) +1216 System.Web.HttpApplication.BeginProcessRequestNotification(HttpContext context, AsyncCallback cb) +113 System.Web.HttpRuntime.ProcessRequestNotificationPrivate(IIS7WorkerRequest wr, HttpContext context) +616 The above always occurs unless I remove the OnePerRequestModule initializization. occurs consistently on a very basic test app I put together. On a standard app where I actually want to implement it, I can solve the issue by initializing the OnePerRequestModule like so: protected override IKernel CreateKernel() { // This will always blow up. //var module = new OnePerRequestModule(); //module.Init(this); IKernel kernel = new StandardKernel(new MyModule()); // This works on larger app, but on basic app, it makes no difference under integrated pipeline as the above exception is always thrown. var module = new OnePerRequestModule(); module.Init(this); return kernel; } Before I start spelunking further, is anybody out there using Ninject.Web extension successfully under the integrated pipeline in IIS7 AND using the OnePerRequestModule? There are certain restrictions for modules under the integrated pipeline that weren't there in previous IIS versions/classic pipeline. Quickly thrown together sample project at http://www.filedropper.com/test_59 And in case it's not obvious with Ninject.Web: it's an ASP.NET WebForms project.

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