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  • Industry perspectives on managing content

    - by aahluwalia
    Earlier this week I was noodling over a topic for my first blog post. My intention for this blog is to bring a practitioner's perspective on ECM to the community; to share and collaborate on best practices and approaches that address today's business problems. Reviewing my past 14 years of experience with web technologies, I wondered what topic would serve as a good "conversation starter". During this time, I received a call from a friend who was seeking insights on how content management applies to specific industries. She approached me because she vaguely remembered that I had worked in the Health Insurance industry in the recent past. She wanted me to tell her about the specific business needs of this industry. She was in for quite a surprise as she found out that I had spent the better part of a decade managing content within the Health Insurance industry and I discovered a great topic for my first blog post! I offer some insights from Health Insurance and invite my fellow practitioners to share their insights from other industries. What does content management mean to these industries? What can solution providers be aware of when offering solutions to these industries? The United States health care system relies heavily on private health insurance, which is the primary source of coverage for approximately 58% Americans. In the late 19th century, "accident insurance" began to be available, which operated much like modern disability insurance. In the late 20th century, traditional disability insurance evolved into modern health insurance programs. The first thing a solution provider must be aware of about the Health Insurance industry is that it tends to be transaction intensive. They are the ones who manage and administer our health plans and process our claims when we visit our health care providers. It helps to keep in mind that they are in the business of delivering health insurance and not technology. You may find the mindset conservative in comparison to the IT industry, however, the Health Insurance industry has benefited and will continue to benefit from the efficiency that technology brings to traditionally paper-driven processes. We are all aware of the impact that Healthcare reform bill has had a significant impact on the Health Insurance industry. They are under a great deal of pressure to explore ways to reduce their administrative costs and increase operational efficiency. Overall, administrative costs of health insurance include the insurer's cost to administer the health plan, the costs borne by employers, health-care providers, governments and individual consumers. Inefficiencies plague health insurance, owing largely to the absence of standardized processes across the industry. To achieve this, industry leaders have come together to establish standards and invest in initiatives to help their healthcare provider partners transition to the next generation of healthcare technology. The move to online services and paperless explanation of benefits are some manifestations of technological advancements in health insurance. Several companies have adopted Toyota's LEAN methodology or Six Sigma principles to improve quality, reduce waste and excessive costs, thereby increasing the value of their plan offerings. A growing number of health insurance companies have transformed their business systems in the past decade alone and adopted some form of content management to reduce the costs involved in administering health plans. The key strategy has been to convert paper documents and forms into electronic formats, automate the content development process and securely distribute content to various audiences via diverse marketing channels, including web and mobile. Enterprise content management solutions can enable document capture of claim forms, manage digital assets, integrate with Enterprise Resource Planning (ERP) and Human Capital Management (HCM) solutions, build Business Process Management (BPM) processes, define retention and disposition instructions to comply with state and federal regulations and allow eBusiness and Marketing departments to develop and deliver web content to multiple websites, mobile devices and portals. Content can be shared securely within and outside the organization using Information Rights Management.  At the end of the day, solution providers who can translate strategic goals into solutions that maximize process automation, increase ease of use and minimize IT overhead are likely to be successful in today's health insurance environment.

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  • Why Ultra-Low Power Computing Will Change Everything

    - by Tori Wieldt
    The ARM TechCon keynote "Why Ultra-Low Power Computing Will Change Everything" was anything but low-powered. The speaker, Dr. Johnathan Koomey, knows his subject: he is a Consulting Professor at Stanford University, worked for more than two decades at Lawrence Berkeley National Laboratory, and has been a visiting professor at Stanford University, Yale University, and UC Berkeley's Energy and Resources Group. His current focus is creating a standard (computations per kilowatt hour) and measuring computer energy consumption over time. The trends are impressive: energy consumption has halved every 1.5 years for the last 60 years. Battery life has made roughly a 10x improvement each decade since 1960. It's these improvements that have made laptops and cell phones possible. What does the future hold? Dr. Koomey said that in the past, the race by chip manufacturers was to create the fastest computer, but the priorities have now changed. New computers are tiny, smart, connected and cheap. "You can't underestimate the importance of a shift in industry focus from raw performance to power efficiency for mobile devices," he said. There is also a confluence of trends in computing, communications, sensors, and controls. The challenge is how to reduce the power requirements for these tiny devices. Alternate sources of power that are being explored are light, heat, motion, and even blood sugar. The University of Michigan has produced a miniature sensor that harnesses solar energy and could last for years without needing to be replaced. Also, the University of Washington has created a sensor that scavenges power from existing radio and TV signals.Specific devices designed for a purpose are much more efficient than general purpose computers. With all these sensors, instead of big data, developers should focus on nano-data, personalized information that will adjust the lights in a room, a machine, a variable sign, etc.Dr. Koomey showed some examples:The Proteus Digital Health Feedback System, an ingestible sensor that transmits when a patient has taken their medicine and is powered by their stomach juices. (Gives "powered by you" a whole new meaning!) Streetline Parking Systems, that provide real-time data about available parking spaces. The information can be sent to your phone or update parking signs around the city to point to areas with available spaces. Less driving around looking for parking spaces!The BigBelly trash system that uses solar power, compacts trash, and sends a text message when it is full. This dramatically reduces the number of times a truck has to come to pick up trash, freeing up resources and slashing fuel costs. This is a classic example of the efficiency of moving "bits not atoms." But researchers are approaching the physical limits of sensors, Dr. Kommey explained. With the current rate of technology improvement, they'll reach the three-atom transistor by 2041. Once they hit that wall, it will force a revolution they way we do computing. But wait, researchers at Purdue University and the University of New South Wales are both working on a reliable one-atom transistors! Other researchers are working on "approximate computing" that will reduce computing requirements drastically. So it's unclear where the wall actually is. In the meantime, as Dr. Koomey promised, ultra-low power computing will change everything.

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  • WebCenter Innovation Award Winners

    - by Michael Snow
    Of course, here on our WebCenter blog – we’d like to highlight and brag about our great WebCenter winners. The 2012 WebCenter Innovation Award Winners University of Louisville Location: Louisville, KY, USA Industry: Higher Education Fusion Middleware Products: WebCenter Portal, WebCenter Content, JDeveloper, WebLogic, Oracle BI, Oracle IdM University of Louisville is a state supported research university Statewide Informatics Network to improve public health The University of Louisville has implemented WebCenter as part of the LOUI (Louisville Informatics Institute) Initiative, a Statewide Informatics Network, which will improve public healthcare and lower cost through the use of novel technology and next generation analytics, decision support and innovative outcomes-based payment systems. ---------- News Limited Country/Region: Australia Industry: News/Media FMW Products: WebCenter Sites Single platform running websites for 50% of Australia's newspapers News Corp is running half of Australia's newspaper websites on this shared platform powered by Oracle WebCenter Sites and have overtaken their nearest competitors and are now leading in terms of monthly page impressions. At peak they have over 250 editors on the system publishing in real-time.Sites include: www.newsspace.com.au, www.news.com.au, www.theaustralian.com.au and many others ------ Life Technologies Corp. Country/Region: Carlsbad, CA, USAIndustry: Life SciencesFMW Products: WebCenter Portal, SOA Suite Life Technologies Corp. is a global biotechnology tools company dedicated to improving the human condition with innovative life science products. They were awarded an innovation award for their solution utilizing WebCenter Portal for remotely monitoring & repairing biotech instruments. They deployed WebCenter as a portal that accesses Life Technologies cloud based service monitoring system where all customer deployed instruments can be remotely monitored and proactively repaired.  The portal provides alerts from these cloud based monitoring services directly to the customer and to Life Technologies Field Engineers.  The Portal provides insight into the instruments and services customers purchased for the purpose of analyzing and anticipating future customer needs and creating targeted sales and service programs. ----- China Mobile Jiangsu China Mobile Jiangsu is one of the biggest subsidiaries of China Mobile. It has over 25,000 employees and 40 million mobile subscribers. Country/Region: Jiangsu, China Industry: Telecommunications FMW Products: WebCenter Portal, WebCenter Content, JDeveloper, SOA Suite, IdM They were awarded an Innovation Award for their new employee platform powered by WebCenter Portal is designed to serve their 25,000+ employees and help them drive collaboration & productivity. JSMCC (Chian Mobile Jiangsu) Employee Enterprise Portal and Collaboration Platform. It is one of the China Mobile’s most important IT innovation projects. The new platform is designed to serve for JSMCC’s 25000+ employees and to help them improve the working efficiency, changing their traditional working mode to social ways, encouraging employees on business collaboration and innovation. The solution is built on top of Oracle WebCenter Portal Framework and WebCenter Spaces while also leveraging Weblogic Server, UCM, OID, OAM, SES, IRM and Oracle Database 11g. By providing rich collaboration services, knowledge management services, sensitive document protection services, unified user identity management services, unified information search services and personalized information integration capabilities, the working efficiency of JSMCC employees has been greatly improved. Main Functionality : Information portal, office automation integration, personal space, group space, team collaboration with web2.0 services, unified search engine for multiple data sources, document management and protection. SSO for multiple platforms. -------- LADWP – Los Angeles Department for Water and Power Los Angeles Department of Water and Power (LADWP) is the largest public utility company in United States with over 1.6 Million customers. LADWP provides water and power for millions of residential & commercial customers in Southern California. LADWP also bills most of these customers for sanitation services provided by another city department. Country/Region: US – Los Angeles, CA Industry: Public Utility FMW Products: WebCenter Portal, WebCenter Content, JDeveloper, SOA Suite, IdM The new infrastructure consists of: Oracle WebCenter Portal including mobile portal Oracle WebCenter Content for Content Management and Digital Asset Management (DAM) Oracle OAM (IDM, OVD, OAM) integrated with AD for enterprise identity management Oracle Siebel for CRM Oracle DB Oracle SOA Suite for integration of various subsystems and back end systems  The new portal's features include: Complete Graphical redesign based on best practices in UI Design for high usability Customer Self Service implemented through MyAccount (Bill Pay, Payment History, Bill History, Usage Analysis, Service Request Management) Financial Assistance Programs (CRM, WebCenter) Customer Rebate Programs (CRM, WebCenter) Turn On/Off/Transfer of services (Commercial & Residential) Outage Reporting eNotification (SMS, email) Multilingual (English & Spanish) – using WebCenter multi-language support Section 508 (ADA) Compliant Search – Using WebCenter SES (Secured Enterprise Search) Distributed Authorship in WebCenter Content Mobile Access (any Mobile Browser)

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  • Should I move big data blobs in JSON or in separate binary connection?

    - by Amagrammer
    QUESTION: Is it better to send large data blobs in JSON for simplicity, or send them as binary data over a separate connection? If the former, can you offer tips on how to optimize the JSON to minimize size? If the latter, is it worth it to logically connect the JSON data to the binary data using an identifier that appears in both, e.g., as "data" : "< unique identifier " in the JSON and with the first bytes of the data blob being < unique identifier ? CONTEXT: My iPhone application needs to receive JSON data over the 3G network. This means that I need to think seriously about efficiency of data transfer, as well as the load on the CPU. Most of the data transfers will be relatively small packets of text data for which JSON is a natural format and for which there is no point in worrying much about efficiency. However, some of the most critical transfers will be big blobs of binary data -- definitely at least 100 kilobytes of data, and possibly closer to 1 megabyte as customers accumulate a longer history with the product. (Note: I will be caching what I can on the iPhone itself, but the data still has to be transferred at least once.) It is NOT streaming data. I will probably use a third-party JSON SDK -- the one I am using during development is here. Thanks

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  • Objective-C Implementation Pointers

    - by Dwaine Bailey
    Hi, I am currently writing an XML parser that parses a lot of data, with a lot of different nodes (the XML isn't designed by me, and I have no control over the content...) Anyway, it currently takes an unacceptably long time to download and read in (about 13 seconds) and so I'm looking for ways to increase the efficiency of the read. I've written a function to create hash values, so that the program no longer has to do a lot of string comparison (just NSUInteger comparison), but this still isn't reducing the complexity of the read in... So I thought maybe I could create an array of IMPs so that, I could then go something like: for(int i = 0; i < [hashValues count]; i ++) { if(currHash == [[hashValues objectAtIndex:i] unsignedIntValue]) { [impArray objectAtIndex:i]; } } Or something like that. The only problem is that I don't know how to actually make the call to the IMP function? I've read that I perform the selector that an IMP defines by going IMP tImp = [impArray objectAtIndex:i]; tImp(self, @selector(methodName)); But, if I need to know the name of the selector anyway, what's the point? Can anybody help me out with what I want to do? Or even just some more ways to increase the efficiency of the parser...

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  • Representing complex scheduled reoccurance in a database

    - by David Pfeffer
    I have the interesting problem of representing complex schedule data in a database. As a guideline, I need to be able to represent the entirety of what the iCalendar -- ics -- format can represent, but in a database. I'm not actually implementing anything relating to ics, but it gives a good scope of the type of rules I need to be able to model. I need to allow allow representation of a single event or a reoccurring event based on multiple times per day, days of the week, week of a month, month, year, or some combination of those. For example, the third Thursday in November annually, or the 25th of December annually, or every two weeks starting November 2 and continuing until September 8 the following year. I don't care about insertion efficiency but query efficiency is critical. The operation I will be doing most often is providing either a single date/time or a date/time range, and trying to determine if the defined schedule matches any part of the date/time range. Other operations can be slower. For example, given January 15, 2010 at 10:00 AM through January 15, 2010 at 11:00 AM, find all schedules that match at least part of that time. (i.e. a schedule that covers 10:30 - 11:00 still matches.) Any suggestions? I looked at http://stackoverflow.com/questions/1016170/how-would-one-represent-scheduled-events-in-an-rdbms but it doesn't cover the scope of the type of reoccurance rules I'd like to model.

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  • Move to php in windows? Concern, hints, "please don't do!"?

    - by Daniel
    I am considering to move frome Microsoft languages to PHP (just for web dev) which has quite an interesting syntax, a perlish look (but a wider programmer base) and it allows me to reuse the web without reinventing it. I have some concerns too. I would be more than happy to gather some wisdom from stackoverflow community, (challenge to my opinions warmly welcome). Here are my doubts. Efficiency. Cgi are slow, what I am supposed to use? Fastcgi? Or what else? Efficiency + stability. Is PHP on windows really stable and a good choice in terms of performances? Database. I use very often MSSQL (I regret, i like it). Could I widely and efficiently interface PHP with MSSQL (using smartly stored pro, for example). XSLT + XML performance. I work quite a lot with XML and XSLT and I really find the MS xml parser a great software component. Are parser used in PHP fast, reliable and efficient (I am interested mainly in DOM, not SAX)? Objects. Is the PHP object programming model valid end efficient? 6 Regex. How efficient is PHP processing regexp? Many thanks for your advices.

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  • PHP shell_exec() - Run directly, or perform a cron (bash/php) and include MySQL layer?

    - by Jimbo
    Sorry if the title is vague - I wasn't quite sure how to word it! What I'm Doing I'm running a Linux command to output data into a variable, parse the data, and output it as an array. Array values will be displayed on a page using PHP, and this PHP page output is requested via AJAX every 10 seconds so, in effect, the data will be retrieved and displayed/updated every 10 seconds. There could be as many as 10,000 characters being parsed on every request, although this is usually much lower. Alternative Idea I want to know if there is a better* alternative method of retrieving this data every 10 seconds, as multiple users (<10) will be having this command executed automatically for them. A cronjob running on the server could execute either bash or php (which is faster?) to grab the data and store it in a MySQL database. Then, any AJAX calls to the PHP output would return values in the MySQL database rather than making a direct call to execute server code every 10 seconds. Why? I know there are security concerns with running execs directly from PHP, and (I hope this isn't micro-optimisation) I'm worried about CPU usage on the server. The server is running a sempron processor. Yes, they do still exist. Having this only execute when the user is on the page (idea #1) means that the server isn't running code that doesn't need to be run. However, is this slow and insecure? Just in case the type of linux command may be of assistance in determining it's efficiency: shell_exec("transmission-remote $host:$port --auth $username:$password -l"); I'm hoping that there are differences in efficiency and level of security with the two methods I have outlined above, and that this isn't just micro-micro-optimisation. If there are alternative methods that are better*, I'd love to learn about these! :)

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  • Difference between Xen PV, Xen KVM and HVM?

    - by JP19
    Hi, I know that Xen is usually better than OpenVZ as the provider cannot oversell in Xen. However, what is the difference between Xen PV, Xen KVM and HVM (I was going through this provider's specs? Which one is better for what purposes and why? Edit: For an end-user who will just be hosting websites, which is better? From efficiency or other point of view, is there any advantage of one over the other?

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  • What PSU would be needed for a mid-range computer?

    - by iconiK
    I am building a mid-range computer primarily for gaming and graphic design. With the following components, what power supply unit would be good, in terms of having ample power for future expansion, with good efficiency and quiet operation, but most important, reliability in the long (5+ years) run? Gigabyt GA-H67MA-UD2H LGA 1155 Intel Core i5 2300 2.8GHz Crucial CT2KIT51264BA1339 2x4GB Kit ASUS HD 6850 DirectCU Intel X25-V 40GB SSD 2xSeagate 7200.12 1TB HDD RAID 1 Antec NSK-3480 µATX Case

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  • Cheap and Secure Proxy

    - by jack
    Hi I'm looking for cheap secure proxy providers that support vpn http socks like this one http://www.your-freedom.net/. Because I wish to compare their efficiency. YF(http://www.your-freedom.net/) doesn't provide my satisfaction on speed they provide after purchasing the account. Their try-before-buy account has much more speed than the purchased one. Thanks.

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  • Are there disadvantages to using Outlook's Cached Exchange Mode?

    - by Roee Adler
    Since I found out about Outlook's "Cached Exchange Mode" I've been using it, and I also set it up on every PC I come across. I think it's a great feature that improves the efficiency of of every Outlook user, and I don't understand why it's not ON by default. My question is - are there any disadvantages to using Cached Exchange Mode? (Besides the obvious fact that it consumes a bit more space, which I don't see as a big issue nowadays)

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  • Revolutionary brand powder packing machine price from affecting marketplace boom and put on uniform in addition to a lengthy service life

    - by user74606
    In mining in stone crushing, our machinery company's encounter becomes much more apparent. As a consequence of production capacity in between 600~800t/h of mining stone crusher, stone is mine Mobile Cone Crushing Plant Price 25~40 times, effectively solved the initially mining stone crusher operation because of low yield prices, no upkeep problems. Full chunk of mining stone crusher. Maximum particle size for crushing 1000x1200mm, an effective answer for the original side is mine stone provide, storing significant chunks of stone can not use complications in mines. Completed goods granularity is modest, only 2~15mm, an effective option for the original mine stone size, generally blocking chute production was an issue even the grinding machine. Two types of material mixed great uniformity, desulfurization of mining stone by adding weight considerably. Present quantity added is often reached 60%, effectively minimizing the cost of raw supplies. Electrical energy consumption has fallen. Dropped 1~2KWh/t tons of mining stone electrical energy consumption, annual electricity savings of one hundred,000 yuan. Efficient labor intensity of workers and also the atmosphere. Due to mine stone powder packing machine price a high degree of automation, with out human make contact with supplies, workers working circumstances enhanced significantly. Positive aspects, and along with mine for stone crushing, CS series cone Crusher has the following efficiency traits. CS series cone Crusher Chamber is divided into 3 unique designs, the user is usually chosen in accordance with the scenario on site crushing efficiency is high, uniform item size, grain shape, rolling mortar wall friction and put on uniform in addition to a extended service life of crushing cavity-. CS series cone Crusher utilizes a one of a kind dust-proof seal, sealing dependable, properly extend the service life of the lubricant replacement cycle and parts. CS series Sprial Sand washer price manufacture of important components to choose unique materials. Each and every stroke left rolling mortar wall of broken cone distances, by permitting a lot more products into the crushing cavity, as well as the formation of big discharge volume, speed of supplies by way of the crushing Chamber. This machine makes use of the principle of crushing cavity, also as unique laminated crushing, particle fragmentation, so that the completed product drastically improved the proportions of a cube, needle-shaped stones to lower particle levels extra evenly.

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  • Are there disagvantages to using Outlook's Chached Exchange Mode?

    - by Rax Olgud
    Since I found out about Outlook's "Cached Exchange Mode" I've been using it, and I also set it up on every PC I come across. I think it's a great feature that improves the efficiency of of every Outlook user, and I don't understand why it's not ON by default. My question is - are there any disadvantages to using Cached Exchange Mode? (Besides the obvious fact that it consumes a bit more space, which I don't see as a big issue nowadays)

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  • How can virtualization be efficient?

    - by pestaa
    As I understand, the virtual machine and the guest OS doubles the amount of abstraction layers (that are computationally relevant) between the user interface and the pure power of the hardware. Some of the said abstraction layers are (emulated) hardware, drivers, IO interfaces, etc. Top-notch virtualization solutions like Xen probably eliminate a few of these complexities, but I still wonder how efficiency is achieved in these environments; and whether manageable cloud servers are really worth the performance price.

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  • Technical details for Server 2012 de-duplication feature

    - by syneticon-dj
    Now that Windows Server 2012 comes with de-duplication features for NTFS volumes I am having a hard time finding technical details about it. I can deduce from the TechNet documentation that the de-duplication action itself is an asynchronous process - not unlike how the SIS Groveler used to work - but there is virtually no detail about the implementation (algorithms used, resources needed, even the info on performance considerations is nothing but a bunch rule-of-thumb-style recommendations). Insights and pointers are greatly appreciated, a comparison to Solaris' ZFS de-duplication efficiency for a set of scenarios would be wonderful.

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  • What’s Your Tax Strategy? Automate the Tax Transfer Pricing Process!

    - by tobyehatch
    Does your business operate in multiple countries? Well, whether you like it or not, many local and international tax authorities inspect your tax strategy.  Legal, effective tax planning is perceived as a “moral” issue. CEOs are being asked to testify on their process of tax transfer pricing between multinational legal entities.  Marc Seewald, Senior Director of Product Management for EPM Applications specializing in all tax subjects and Product Manager for Oracle Hyperion Tax Provisioning, and Bart Stoehr, Senior Director of Product Strategy for Oracle Hyperion Profitability and Cost Management joined me for a discussion/podcast on this interesting subject.  So what exactly is “tax transfer pricing”? Marc defined it this way. “Tax transfer pricing is a profit allocation methodology required to be used by multinational corporations. Specifically, the ultimate goal of the transfer pricing is to ensure that the global multinational pays their fair share of income tax in each of their local markets. Specifically, it prevents companies from unfairly moving profit from ‘high tax’ countries to ‘low tax’ countries.” According to Marc, in today’s global economy, profitability can be significantly impacted by goods and services exchanged between the related divisions within a single multinational company.  To ensure that these cost allocations are done fairly, there are rules that govern the process. These rules ensure that intercompany allocations fairly represent the actual nature of the businesses activity- as if two divisions were unrelated - and provide a clear audit trail of how the costs have been allocated to prove that allocations fall within reasonable ranges.  What are the repercussions of improper tax transfer pricing? How important is it? Tax transfer pricing allocations can materially impact the amount of overall corporate income taxes paid by a company worldwide, in some cases by hundreds of millions of dollars!  Since so much tax revenue is at stake, revenue agencies like the IRS, and international regulatory bodies like the Organization for Economic Cooperation and Development (OECD) are pushing to reform and clarify reporting for tax transfer pricing. Most recently the OECD announced an “Action Plan for Base Erosion and Profit Shifting”. As Marc explained, the times are changing and companies need to be responsive to this issue. “It feels like every other week there is another company being accused of avoiding taxes,” said Marc. Most recently, Caterpillar was accused of avoiding billions of dollars in taxes. In the last couple of years, Apple, GE, Ikea, and Starbucks, have all been accused of tax avoidance. It’s imperative that companies like these have a clear and auditable tax transfer process that enables them to justify tax transfer pricing allocations and avoid steep penalties and bad publicity. Transparency and efficiency are what is needed when it comes to the tax transfer pricing process. Bart explained that tax transfer pricing is driving a deeper inspection of profit recognition specifically focused on the tax element of profit.  However, allocations needed to support tax profitability are nearly identical in process to allocations taking place in other parts of the finance organization. For example, the methods and processes necessary to arrive at tax profitability by legal entity are no different than those used to arrive at fully loaded profitability for a product line. In fact, there is a great opportunity for alignment across these two different functions.So it seems that tax transfer pricing should be reflected in profitability in general. Bart agreed and told us more about some of the critical sub-processes of an overall tax transfer pricing process within the Oracle solution for tax transfer pricing.  “First, there is a ton of data preparation, enrichment and pre-allocation data analysis that is managed in the Oracle Hyperion solution. This serves as the “data staging” to the next, critical sub-processes.  From here, we leverage the Oracle EPM platform’s ability to re-use dimensions and legal entity driver data and financial data with Oracle Hyperion Profitability and Cost Management (HPCM).  Within HPCM, we manage the driver data, define the legal entity to legal entity allocation rules (like cost plus), and have the option to test out multiple, simultaneous tax transfer pricing what-if scenarios.  Once processed, a tax expert can evaluate the effectiveness of any one scenario result versus another via a variance analysis configured with HPCM’s pre-packaged reporting capability known as Oracle Hyperion SmartView for Office.”   Further, Bart explained that the ability to visibly demonstrate how a cost or revenue has been allocated is really helpful and auditable.  “HPCM’s Traceability Maps are that visual representation of all allocation flows that have been executed and is the tax transfer analyst’s best friend in maintaining clear documentation for tax transfer pricing audits. Simply click and drill as you inspect the chain of allocation definitions and results. Once final, the post-allocated tax data can be compared to the GL to create invoices and journal entries for posting to your GL system of choice.  Of course, there is a framework for overall governance of the journal entries, allocation percentages, and reporting to include necessary approvals.” Lastly, Marc explained that the key value in using the Oracle Hyperion solution for tax transfer pricing is that it keeps everything in alignment in one single place. Specifically, Oracle Hyperion effectively becomes the single book of record for the GAAP, management, and the tax set of books. There are many benefits to having one source of the truth. These include EFFICIENCY, CONTROLS and TRANSPARENCY.So, what’s your tax strategy? Why not automate the tax transfer pricing process!To listen to the entire podcast, click here.To learn more about Oracle Hyperion Profitability and Cost Management (HPCM), click here.

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  • Oracle Delivers Oracle Social Services Suite

    - by michael.seback
    Oracle Delivers Oracle Social Services Suite with New Releases of Siebel CRM Public Sector 8.2 and Oracle Policy Automation 10 Continuing its leadership and commitment to provide key innovations specifically created for social services agencies, Oracle today released the new Oracle Social Services Suite that includes updated versions of Oracle's Siebel CRM Public Sector 8.2 and Oracle Policy Automation 10. "Oracle's commitment to our social services customers is indisputable with the introduction of Oracle Social Services Suite and the latest innovations from Oracle's Siebel CRM Public Sector 8.2 and Oracle Policy Automation 10," said Anthony Lye, Senior Vice President of CRM, Oracle. "Social service agencies have not only many of the most complex jobs to perform with limited time and funding, but also some of the most important for our society, especially when children are involved. The technology advances Oracle provides will help these agencies increase their own efficiency and save costs, while helping to improve the outcome for their clients." read more

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  • Week 16: Integrate This - Introducing Oracle Enterprise Manager 11g

    - by sandra.haan
    Spring in New York City is a wonderful time of year, but if you're out walking around in Central Park it means you missed the most exciting thing happening in the city today -Oracle's announcement of the launch of Enterprise Manager 11g at the Guggenheim. You can catch-up on what you missed here and listen in as Judson talks about the partner opportunity with Enterprise Manager 11g: Learn how Oracle Enterprise Manager 11g can help you drive agility and efficiency through its unique, integrated IT management capabilities and check out the Enterprise Manager Knowledge Zone to get engaged with OPN. Learn more and get the full scoop from today's press release. Until the next time, The OPN Communications Team

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  • Smart Grid Gurus

    - by caroline.yu
    Join Paul Fetherland, AMI director at Hawaiian Electric Company (HECO) and Keith Sturkie, vice president of Information Technology, Mid-Carolina Electric Cooperative (MCEC) on Thursday, April 29 at 12 p.m. EDT for the free "Smart Grid Gurus" Webcast. In this Webcast, underwritten by Oracle Utilities, Intelligent Utility will profile Paul Fetherland and Keith Sturkie to examine how they ended up in their respective positions and how they are making smarter grids a reality at their companies. By attending, you will: Gain insight from the paths taken and lessons learned by HECO and MCEC as these two utilities add more grid intelligence to their operations Identify the keys to driving AMI deployment, increasing operational and productivity gains, and targeting new goals on the technology roadmap Learn why HECO is taking a careful, measured approach to AMI deployment, and how Hawaii's established renewable portfolio standard of 40% and an energy efficiency standard of 30%, both by 2030, impact its efforts Discover how MCEC's 45,000-meter AMI deployment, completed in 2005, reduced field trips for high-usage complaints by 90% in the first year, and MCEC's immediate goals for future technology implementation To register, please follow this link.

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  • Not to miss! Today’s web seminar on content integration with Oracle Apps

    - by Lance Shaw
    Hello everyone.  The first web seminar in a three-part series kicks off later today, focused on the value of delivering and controlling the flow of content in the context of your most critical business applications.   If you are using Oracle E-Business Suite, PeopleSoft Enterprise, JD Edwards EnterpriseOne or Siebel CRM, we heartily recommend you investigate the value of centralizing the delivery of scanned images, forms, faxes and digital documents within those processes.  The improvements in efficiency and productivity can result in some impressive cost savings. One customer recently reported that they had realized an impressive ROI of 180% and that the investment in this new technology had paid for itself in a mere 6 months.  We hope you can spare some time today to join us at 1pm Eastern Time / 10am Pacific Time / 18:00 GMT. We think you will find it time well spent.   Click here to attend.  We look forward to seeing you there!

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  • Look for Oracle at the 2010 ISM San Diego Conference

    - by [email protected]
    Oracle is sponsoring and exhibiting at ISM's 95th Annual International Supply Management Conference and Educational Exhibit on April 25th through 28th.   Be sure to catch our presentation with Hackett that explores how procurement can use payables to boost an organization's balance and income statements. Pierre Mitchell from Hackett will be sharing groundbreaking new research that identifies explicit links between a strategic approach to supplier payments and world-class performance.   If your organization can benefit from increased margin, improved working capital, greater efficiency, and reduced risk, then you can't afford to miss this session. We'll be presenting on Monday at 5:00pm in Exhibit  Hall D.       Some of Oracle's top talent will be available to answer your questions in booth number 527. It is a great opportunity to learn about Oracle's innovations for supplier management, spend classification, invoice automation, and On Demand delivery of procurement applications.  

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  • Understanding G1 GC Logs

    - by poonam
    The purpose of this post is to explain the meaning of GC logs generated with some tracing and diagnostic options for G1 GC. We will take a look at the output generated with PrintGCDetails which is a product flag and provides the most detailed level of information. Along with that, we will also look at the output of two diagnostic flags that get enabled with -XX:+UnlockDiagnosticVMOptions option - G1PrintRegionLivenessInfo that prints the occupancy and the amount of space used by live objects in each region at the end of the marking cycle and G1PrintHeapRegions that provides detailed information on the heap regions being allocated and reclaimed. We will be looking at the logs generated with JDK 1.7.0_04 using these options. Option -XX:+PrintGCDetails Here's a sample log of G1 collection generated with PrintGCDetails. 0.522: [GC pause (young), 0.15877971 secs] [Parallel Time: 157.1 ms] [GC Worker Start (ms): 522.1 522.2 522.2 522.2 Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] [Processed Buffers : 2 2 3 2 Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] [GC Worker Other (ms): 0.3 0.3 0.3 0.3 Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] [Clear CT: 0.1 ms] [Other: 1.5 ms] [Choose CSet: 0.0 ms] [Ref Proc: 0.3 ms] [Ref Enq: 0.0 ms] [Free CSet: 0.3 ms] [Eden: 12M(12M)->0B(10M) Survivors: 0B->2048K Heap: 13M(64M)->9739K(64M)] [Times: user=0.59 sys=0.02, real=0.16 secs] This is the typical log of an Evacuation Pause (G1 collection) in which live objects are copied from one set of regions (young OR young+old) to another set. It is a stop-the-world activity and all the application threads are stopped at a safepoint during this time. This pause is made up of several sub-tasks indicated by the indentation in the log entries. Here's is the top most line that gets printed for the Evacuation Pause. 0.522: [GC pause (young), 0.15877971 secs] This is the highest level information telling us that it is an Evacuation Pause that started at 0.522 secs from the start of the process, in which all the regions being evacuated are Young i.e. Eden and Survivor regions. This collection took 0.15877971 secs to finish. Evacuation Pauses can be mixed as well. In which case the set of regions selected include all of the young regions as well as some old regions. 1.730: [GC pause (mixed), 0.32714353 secs] Let's take a look at all the sub-tasks performed in this Evacuation Pause. [Parallel Time: 157.1 ms] Parallel Time is the total elapsed time spent by all the parallel GC worker threads. The following lines correspond to the parallel tasks performed by these worker threads in this total parallel time, which in this case is 157.1 ms. [GC Worker Start (ms): 522.1 522.2 522.2 522.2Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] The first line tells us the start time of each of the worker thread in milliseconds. The start times are ordered with respect to the worker thread ids – thread 0 started at 522.1ms and thread 1 started at 522.2ms from the start of the process. The second line tells the Avg, Min, Max and Diff of the start times of all of the worker threads. [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] This gives us the time spent by each worker thread scanning the roots (globals, registers, thread stacks and VM data structures). Here, thread 0 took 1.6ms to perform the root scanning task and thread 1 took 1.5 ms. The second line clearly shows the Avg, Min, Max and Diff of the times spent by all the worker threads. [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] Update RS gives us the time each thread spent in updating the Remembered Sets. Remembered Sets are the data structures that keep track of the references that point into a heap region. Mutator threads keep changing the object graph and thus the references that point into a particular region. We keep track of these changes in buffers called Update Buffers. The Update RS sub-task processes the update buffers that were not able to be processed concurrently, and updates the corresponding remembered sets of all regions. [Processed Buffers : 2 2 3 2Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] This tells us the number of Update Buffers (mentioned above) processed by each worker thread. [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] These are the times each worker thread had spent in scanning the Remembered Sets. Remembered Set of a region contains cards that correspond to the references pointing into that region. This phase scans those cards looking for the references pointing into all the regions of the collection set. [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] These are the times spent by each worker thread copying live objects from the regions in the Collection Set to the other regions. [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] Termination time is the time spent by the worker thread offering to terminate. But before terminating, it checks the work queues of other threads and if there are still object references in other work queues, it tries to steal object references, and if it succeeds in stealing a reference, it processes that and offers to terminate again. [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] This gives the number of times each thread has offered to terminate. [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] These are the times in milliseconds at which each worker thread stopped. [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] These are the total lifetimes of each worker thread. [GC Worker Other (ms): 0.3 0.3 0.3 0.3Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] These are the times that each worker thread spent in performing some other tasks that we have not accounted above for the total Parallel Time. [Clear CT: 0.1 ms] This is the time spent in clearing the Card Table. This task is performed in serial mode. [Other: 1.5 ms] Time spent in the some other tasks listed below. The following sub-tasks (which individually may be parallelized) are performed serially. [Choose CSet: 0.0 ms] Time spent in selecting the regions for the Collection Set. [Ref Proc: 0.3 ms] Total time spent in processing Reference objects. [Ref Enq: 0.0 ms] Time spent in enqueuing references to the ReferenceQueues. [Free CSet: 0.3 ms] Time spent in freeing the collection set data structure. [Eden: 12M(12M)->0B(13M) Survivors: 0B->2048K Heap: 14M(64M)->9739K(64M)] This line gives the details on the heap size changes with the Evacuation Pause. This shows that Eden had the occupancy of 12M and its capacity was also 12M before the collection. After the collection, its occupancy got reduced to 0 since everything is evacuated/promoted from Eden during a collection, and its target size grew to 13M. The new Eden capacity of 13M is not reserved at this point. This value is the target size of the Eden. Regions are added to Eden as the demand is made and when the added regions reach to the target size, we start the next collection. Similarly, Survivors had the occupancy of 0 bytes and it grew to 2048K after the collection. The total heap occupancy and capacity was 14M and 64M receptively before the collection and it became 9739K and 64M after the collection. Apart from the evacuation pauses, G1 also performs concurrent-marking to build the live data information of regions. 1.416: [GC pause (young) (initial-mark), 0.62417980 secs] ….... 2.042: [GC concurrent-root-region-scan-start] 2.067: [GC concurrent-root-region-scan-end, 0.0251507] 2.068: [GC concurrent-mark-start] 3.198: [GC concurrent-mark-reset-for-overflow] 4.053: [GC concurrent-mark-end, 1.9849672 sec] 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.090: [GC concurrent-cleanup-start] 4.091: [GC concurrent-cleanup-end, 0.0002721] The first phase of a marking cycle is Initial Marking where all the objects directly reachable from the roots are marked and this phase is piggy-backed on a fully young Evacuation Pause. 2.042: [GC concurrent-root-region-scan-start] This marks the start of a concurrent phase that scans the set of root-regions which are directly reachable from the survivors of the initial marking phase. 2.067: [GC concurrent-root-region-scan-end, 0.0251507] End of the concurrent root region scan phase and it lasted for 0.0251507 seconds. 2.068: [GC concurrent-mark-start] Start of the concurrent marking at 2.068 secs from the start of the process. 3.198: [GC concurrent-mark-reset-for-overflow] This indicates that the global marking stack had became full and there was an overflow of the stack. Concurrent marking detected this overflow and had to reset the data structures to start the marking again. 4.053: [GC concurrent-mark-end, 1.9849672 sec] End of the concurrent marking phase and it lasted for 1.9849672 seconds. 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] This corresponds to the remark phase which is a stop-the-world phase. It completes the left over marking work (SATB buffers processing) from the previous phase. In this case, this phase took 0.0030184 secs and out of which 0.0000254 secs were spent on Reference processing. 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] Cleanup phase which is again a stop-the-world phase. It goes through the marking information of all the regions, computes the live data information of each region, resets the marking data structures and sorts the regions according to their gc-efficiency. In this example, the total heap size is 138M and after the live data counting it was found that the total live data size dropped down from 117M to 106M. 4.090: [GC concurrent-cleanup-start] This concurrent cleanup phase frees up the regions that were found to be empty (didn't contain any live data) during the previous stop-the-world phase. 4.091: [GC concurrent-cleanup-end, 0.0002721] Concurrent cleanup phase took 0.0002721 secs to free up the empty regions. Option -XX:G1PrintRegionLivenessInfo Now, let's look at the output generated with the flag G1PrintRegionLivenessInfo. This is a diagnostic option and gets enabled with -XX:+UnlockDiagnosticVMOptions. G1PrintRegionLivenessInfo prints the live data information of each region during the Cleanup phase of the concurrent-marking cycle. 26.896: [GC cleanup ### PHASE Post-Marking @ 26.896### HEAP committed: 0x02e00000-0x0fe00000 reserved: 0x02e00000-0x12e00000 region-size: 1048576 Cleanup phase of the concurrent-marking cycle started at 26.896 secs from the start of the process and this live data information is being printed after the marking phase. Committed G1 heap ranges from 0x02e00000 to 0x0fe00000 and the total G1 heap reserved by JVM is from 0x02e00000 to 0x12e00000. Each region in the G1 heap is of size 1048576 bytes. ### type address-range used prev-live next-live gc-eff### (bytes) (bytes) (bytes) (bytes/ms) This is the header of the output that tells us about the type of the region, address-range of the region, used space in the region, live bytes in the region with respect to the previous marking cycle, live bytes in the region with respect to the current marking cycle and the GC efficiency of that region. ### FREE 0x02e00000-0x02f00000 0 0 0 0.0 This is a Free region. ### OLD 0x02f00000-0x03000000 1048576 1038592 1038592 0.0 Old region with address-range from 0x02f00000 to 0x03000000. Total used space in the region is 1048576 bytes, live bytes as per the previous marking cycle are 1038592 and live bytes with respect to the current marking cycle are also 1038592. The GC efficiency has been computed as 0. ### EDEN 0x03400000-0x03500000 20992 20992 20992 0.0 This is an Eden region. ### HUMS 0x0ae00000-0x0af00000 1048576 1048576 1048576 0.0### HUMC 0x0af00000-0x0b000000 1048576 1048576 1048576 0.0### HUMC 0x0b000000-0x0b100000 1048576 1048576 1048576 0.0### HUMC 0x0b100000-0x0b200000 1048576 1048576 1048576 0.0### HUMC 0x0b200000-0x0b300000 1048576 1048576 1048576 0.0### HUMC 0x0b300000-0x0b400000 1048576 1048576 1048576 0.0### HUMC 0x0b400000-0x0b500000 1001480 1001480 1001480 0.0 These are the continuous set of regions called Humongous regions for storing a large object. HUMS (Humongous starts) marks the start of the set of humongous regions and HUMC (Humongous continues) tags the subsequent regions of the humongous regions set. ### SURV 0x09300000-0x09400000 16384 16384 16384 0.0 This is a Survivor region. ### SUMMARY capacity: 208.00 MB used: 150.16 MB / 72.19 % prev-live: 149.78 MB / 72.01 % next-live: 142.82 MB / 68.66 % At the end, a summary is printed listing the capacity, the used space and the change in the liveness after the completion of concurrent marking. In this case, G1 heap capacity is 208MB, total used space is 150.16MB which is 72.19% of the total heap size, live data in the previous marking was 149.78MB which was 72.01% of the total heap size and the live data as per the current marking is 142.82MB which is 68.66% of the total heap size. Option -XX:+G1PrintHeapRegions G1PrintHeapRegions option logs the regions related events when regions are committed, allocated into or are reclaimed. COMMIT/UNCOMMIT events G1HR COMMIT [0x6e900000,0x6ea00000]G1HR COMMIT [0x6ea00000,0x6eb00000] Here, the heap is being initialized or expanded and the region (with bottom: 0x6eb00000 and end: 0x6ec00000) is being freshly committed. COMMIT events are always generated in order i.e. the next COMMIT event will always be for the uncommitted region with the lowest address. G1HR UNCOMMIT [0x72700000,0x72800000]G1HR UNCOMMIT [0x72600000,0x72700000] Opposite to COMMIT. The heap got shrunk at the end of a Full GC and the regions are being uncommitted. Like COMMIT, UNCOMMIT events are also generated in order i.e. the next UNCOMMIT event will always be for the committed region with the highest address. GC Cycle events G1HR #StartGC 7G1HR CSET 0x6e900000G1HR REUSE 0x70500000G1HR ALLOC(Old) 0x6f800000G1HR RETIRE 0x6f800000 0x6f821b20G1HR #EndGC 7 This shows start and end of an Evacuation pause. This event is followed by a GC counter tracking both evacuation pauses and Full GCs. Here, this is the 7th GC since the start of the process. G1HR #StartFullGC 17G1HR UNCOMMIT [0x6ed00000,0x6ee00000]G1HR POST-COMPACTION(Old) 0x6e800000 0x6e854f58G1HR #EndFullGC 17 Shows start and end of a Full GC. This event is also followed by the same GC counter as above. This is the 17th GC since the start of the process. ALLOC events G1HR ALLOC(Eden) 0x6e800000 The region with bottom 0x6e800000 just started being used for allocation. In this case it is an Eden region and allocated into by a mutator thread. G1HR ALLOC(StartsH) 0x6ec00000 0x6ed00000G1HR ALLOC(ContinuesH) 0x6ed00000 0x6e000000 Regions being used for the allocation of Humongous object. The object spans over two regions. G1HR ALLOC(SingleH) 0x6f900000 0x6f9eb010 Single region being used for the allocation of Humongous object. G1HR COMMIT [0x6ee00000,0x6ef00000]G1HR COMMIT [0x6ef00000,0x6f000000]G1HR COMMIT [0x6f000000,0x6f100000]G1HR COMMIT [0x6f100000,0x6f200000]G1HR ALLOC(StartsH) 0x6ee00000 0x6ef00000G1HR ALLOC(ContinuesH) 0x6ef00000 0x6f000000G1HR ALLOC(ContinuesH) 0x6f000000 0x6f100000G1HR ALLOC(ContinuesH) 0x6f100000 0x6f102010 Here, Humongous object allocation request could not be satisfied by the free committed regions that existed in the heap, so the heap needed to be expanded. Thus new regions are committed and then allocated into for the Humongous object. G1HR ALLOC(Old) 0x6f800000 Old region started being used for allocation during GC. G1HR ALLOC(Survivor) 0x6fa00000 Region being used for copying old objects into during a GC. Note that Eden and Humongous ALLOC events are generated outside the GC boundaries and Old and Survivor ALLOC events are generated inside the GC boundaries. Other Events G1HR RETIRE 0x6e800000 0x6e87bd98 Retire and stop using the region having bottom 0x6e800000 and top 0x6e87bd98 for allocation. Note that most regions are full when they are retired and we omit those events to reduce the output volume. A region is retired when another region of the same type is allocated or we reach the start or end of a GC(depending on the region). So for Eden regions: For example: 1. ALLOC(Eden) Foo2. ALLOC(Eden) Bar3. StartGC At point 2, Foo has just been retired and it was full. At point 3, Bar was retired and it was full. If they were not full when they were retired, we will have a RETIRE event: 1. ALLOC(Eden) Foo2. RETIRE Foo top3. ALLOC(Eden) Bar4. StartGC G1HR CSET 0x6e900000 Region (bottom: 0x6e900000) is selected for the Collection Set. The region might have been selected for the collection set earlier (i.e. when it was allocated). However, we generate the CSET events for all regions in the CSet at the start of a GC to make sure there's no confusion about which regions are part of the CSet. G1HR POST-COMPACTION(Old) 0x6e800000 0x6e839858 POST-COMPACTION event is generated for each non-empty region in the heap after a full compaction. A full compaction moves objects around, so we don't know what the resulting shape of the heap is (which regions were written to, which were emptied, etc.). To deal with this, we generate a POST-COMPACTION event for each non-empty region with its type (old/humongous) and the heap boundaries. At this point we should only have Old and Humongous regions, as we have collapsed the young generation, so we should not have eden and survivors. POST-COMPACTION events are generated within the Full GC boundary. G1HR CLEANUP 0x6f400000G1HR CLEANUP 0x6f300000G1HR CLEANUP 0x6f200000 These regions were found empty after remark phase of Concurrent Marking and are reclaimed shortly afterwards. G1HR #StartGC 5G1HR CSET 0x6f400000G1HR CSET 0x6e900000G1HR REUSE 0x6f800000 At the end of a GC we retire the old region we are allocating into. Given that its not full, we will carry on allocating into it during the next GC. This is what REUSE means. In the above case 0x6f800000 should have been the last region with an ALLOC(Old) event during the previous GC and should have been retired before the end of the previous GC. G1HR ALLOC-FORCE(Eden) 0x6f800000 A specialization of ALLOC which indicates that we have reached the max desired number of the particular region type (in this case: Eden), but we decided to allocate one more. Currently it's only used for Eden regions when we extend the young generation because we cannot do a GC as the GC-Locker is active. G1HR EVAC-FAILURE 0x6f800000 During a GC, we have failed to evacuate an object from the given region as the heap is full and there is no space left to copy the object. This event is generated within GC boundaries and exactly once for each region from which we failed to evacuate objects. When Heap Regions are reclaimed ? It is also worth mentioning when the heap regions in the G1 heap are reclaimed. All regions that are in the CSet (the ones that appear in CSET events) are reclaimed at the end of a GC. The exception to that are regions with EVAC-FAILURE events. All regions with CLEANUP events are reclaimed. After a Full GC some regions get reclaimed (the ones from which we moved the objects out). But that is not shown explicitly, instead the non-empty regions that are left in the heap are printed out with the POST-COMPACTION events.

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  • Learn how Oracle storage efficiencies can help your budget

    - by jenny.gelhausen
    Mark Your Calendar! Live Webcast: Next Generation Storage Management Solutions Wednesday, March 24th, 2010 at 9:00am PT or your local time Please plan to join us for this webcast where Forrester senior analyst Andrew Reichman will discuss the pillars of storage efficiency, how to measure and improve it, and how this can help your business immediately alleviate budget pressures. Joining Mr. Reichman are Phil Stephenson, Senior Principal Product Manager at Oracle, and Matthew Baier, Oracle Product Director, who will explain to you the next generation storage capabilities available in Oracle Database 11g and Oracle Exadata. Register for this March 24th live wecast today! var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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