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• VirtualBox 4.2.14 is now available

  - by user12611829

  The VirtualBox development team has just released version 4.2.14, and it is now available for download. This is a maintenance release for version 4.2 and contains quite a few fixes. Here is the list from the official Changelog. VMM: another TLB invalidation fix for non-present pages VMM: fixed a performance regression (4.2.8 regression; bug #11674) GUI: fixed a crash on shutdown GUI: prevent stuck keys under certain conditions on Windows hosts (bugs #2613, #6171) VRDP: fixed a rare crash on the guest screen resize VRDP: allow to change VRDP parameters (including enabling/disabling the server) if the VM is paused USB: fixed passing through devices on Mac OS X host to a VM with 2 or more virtual CPUs (bug #7462) USB: fixed hang during isochronous transfer with certain devices (4.1 regression; Windows hosts only; bug #11839) USB: properly handle orphaned URBs (bug #11207) BIOS: fixed function for returning the PCI interrupt routing table (fixes NetWare 6.x guests) BIOS: don't use the ENTER / LEAVE instructions in the BIOS as these don't work in the real mode as set up by certain guests (e.g. Plan 9 and QNX 4) DMI: allow to configure DmiChassisType (bug #11832) Storage: fixed lost writes if iSCSI is used with snapshots and asynchronous I/O (bug #11479) Storage: fixed accessing certain VHDX images created by Windows 8 (bug #11502) Storage: fixed hang when creating a snapshot using Parallels disk images (bug #9617) 3D: seamless + 3D fixes (bug #11723) 3D: version 4.2.12 was not able to read saved states of older versions under certain conditions (bug #11718) Main/Properties: don't create a guest property for non-running VMs if the property does not exist and is about to be removed (bug #11765) Main/Properties: don't forget to make new guest properties persistent after the VM was terminated (bug #11719) Main/Display: don't lose seamless regions during screen resize Main/OVF: don't crash during import if the client forgot to call Appliance::interpret() (bug #10845) Main/OVF: don't create invalid appliances by stripping the file name if the VM name is very long (bug #11814) Main/OVF: don't fail if the appliance contains multiple file references (bug #10689) Main/Metrics: fixed Solaris file descriptor leak Settings: limit depth of snapshot tree to 250 levels, as more will lead to decreased performance and may trigger crashes VBoxManage: fixed setting the parent UUID on diff images using sethdparentuuid Linux hosts: work around for not crashing as a result of automatic NUMA balancing which was introduced in Linux 3.8 (bug #11610) Windows installer: force the installation of the public certificate in background (i.e. completely prevent user interaction) if the --silent command line option is specified Windows Additions: fixed problems with partial install in the unattended case Windows Additions: fixed display glitch with the Start button in seamless mode for some themes Windows Additions: Seamless mode and auto-resize fixes Windows Additions: fixed trying to to retrieve new auto-logon credentials if current ones were not processed yet Windows Additions installer: added the /with_wddm switch to select the experimental WDDM driver by default Linux Additions: fixed setting own timed out and aborted texts in information label of the lightdm greeter Linux Additions: fixed compilation against Linux 3.2.0 Ubuntu kernels (4.2.12 regression as a side effect of the Debian kernel build fix; bug #11709) X11 Additions: reduced the CPU load of VBoxClient in drag'and'drop mode OS/2 Additions: made the mouse wheel work (bug #6793) Guest Additions: fixed problems copying and pasting between two guests on an X11 host (bug #11792) The full changelog can be found here. You can download binaries for Solaris, Linux, Windows and MacOS hosts at http://www.virtualbox.org/wiki/Downloads Technocrati Tags: Oracle Virtualization VirtualBox

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• NUMA-aware placement of communication variables

  - by Dave

  For classic NUMA-aware programming I'm typically most concerned about simple cold, capacity and compulsory misses and whether we can satisfy the miss by locally connected memory or whether we have to pull the line from its home node over the coherent interconnect -- we'd like to minimize channel contention and conserve interconnect bandwidth. That is, for this style of programming we're quite aware of where memory is homed relative to the threads that will be accessing it. Ideally, a page is collocated on the node with the thread that's expected to most frequently access the page, as simple misses on the page can be satisfied without resorting to transferring the line over the interconnect. The default "first touch" NUMA page placement policy tends to work reasonable well in this regard. When a virtual page is first accessed, the operating system will attempt to provision and map that virtual page to a physical page allocated from the node where the accessing thread is running. It's worth noting that the node-level memory interleaving granularity is usually a multiple of the page size, so we can say that a given page P resides on some node N. That is, the memory underlying a page resides on just one node. But when thinking about accesses to heavily-written communication variables we normally consider what caches the lines underlying such variables might be resident in, and in what states. We want to minimize coherence misses and cache probe activity and interconnect traffic in general. I don't usually give much thought to the location of the home NUMA node underlying such highly shared variables. On a SPARC T5440, for instance, which consists of 4 T2+ processors connected by a central coherence hub, the home node and placement of heavily accessed communication variables has very little impact on performance. The variables are frequently accessed so likely in M-state in some cache, and the location of the home node is of little consequence because a requester can use cache-to-cache transfers to get the line. Or at least that's what I thought. Recently, though, I was exploring a simple shared memory point-to-point communication model where a client writes a request into a request mailbox and then busy-waits on a response variable. It's a simple example of delegation based on message passing. The server polls the request mailbox, and having fetched a new request value, performs some operation and then writes a reply value into the response variable. As noted above, on a T5440 performance is insensitive to the placement of the communication variables -- the request and response mailbox words. But on a Sun/Oracle X4800 I noticed that was not the case and that NUMA placement of the communication variables was actually quite important. For background an X4800 system consists of 8 Intel X7560 Xeons . Each package (socket) has 8 cores with 2 contexts per core, so the system is 8x8x2. Each package is also a NUMA node and has locally attached memory. Every package has 3 point-to-point QPI links for cache coherence, and the system is configured with a twisted ladder "mobius" topology. The cache coherence fabric is glueless -- there's not central arbiter or coherence hub. The maximum distance between any two nodes is just 2 hops over the QPI links. For any given node, 3 other nodes are 1 hop distant and the remaining 4 nodes are 2 hops distant. Using a single request (client) thread and a single response (server) thread, a benchmark harness explored all permutations of NUMA placement for the two threads and the two communication variables, measuring the average round-trip-time and throughput rate between the client and server. In this benchmark the server simply acts as a simple transponder, writing the request value plus 1 back into the reply field, so there's no particular computation phase and we're only measuring communication overheads. In addition to varying the placement of communication variables over pairs of nodes, we also explored variations where both variables were placed on one page (and thus on one node) -- either on the same cache line or different cache lines -- while varying the node where the variables reside along with the placement of the threads. The key observation was that if the client and server threads were on different nodes, then the best placement of variables was to have the request variable (written by the client and read by the server) reside on the same node as the client thread, and to place the response variable (written by the server and read by the client) on the same node as the server. That is, if you have a variable that's to be written by one thread and read by another, it should be homed with the writer thread. For our simple client-server model that means using split request and response communication variables with unidirectional message flow on a given page. This can yield up to twice the throughput of less favorable placement strategies. Our X4800 uses the QPI 1.0 protocol with source-based snooping. Briefly, when node A needs to probe a cache line it fires off snoop requests to all the nodes in the system. Those recipients then forward their response not to the original requester, but to the home node H of the cache line. H waits for and collects the responses, adjudicates and resolves conflicts and ensures memory-model ordering, and then sends a definitive reply back to the original requester A. If some node B needed to transfer the line to A, it will do so by cache-to-cache transfer and let H know about the disposition of the cache line. A needs to wait for the authoritative response from H. So if a thread on node A wants to write a value to be read by a thread on node B, the latency is dependent on the distances between A, B, and H. We observe the best performance when the written-to variable is co-homed with the writer A. That is, we want H and A to be the same node, as the writer doesn't need the home to respond over the QPI link, as the writer and the home reside on the very same node. With architecturally informed placement of communication variables we eliminate at least one QPI hop from the critical path. Newer Intel processors use the QPI 1.1 coherence protocol with home-based snooping. As noted above, under source-snooping a requester broadcasts snoop requests to all nodes. Those nodes send their response to the home node of the location, which provides memory ordering, reconciles conflicts, etc., and then posts a definitive reply to the requester. In home-based snooping the snoop probe goes directly to the home node and are not broadcast. The home node can consult snoop filters -- if present -- and send out requests to retrieve the line if necessary. The 3rd party owner of the line, if any, can respond either to the home or the original requester (or even to both) according to the protocol policies. There are myriad variations that have been implemented, and unfortunately vendor terminology doesn't always agree between vendors or with the academic taxonomy papers. The key is that home-snooping enables the use of a snoop filter to reduce interconnect traffic. And while home-snooping might have a longer critical path (latency) than source-based snooping, it also may require fewer messages and less overall bandwidth. It'll be interesting to reprise these experiments on a platform with home-based snooping. While collecting data I also noticed that there are placement concerns even in the seemingly trivial case when both threads and both variables reside on a single node. Internally, the cores on each X7560 package are connected by an internal ring. (Actually there are multiple contra-rotating rings). And the last-level on-chip cache (LLC) is partitioned in banks or slices, which with each slice being associated with a core on the ring topology. A hardware hash function associates each physical address with a specific home bank. Thus we face distance and topology concerns even for intra-package communications, although the latencies are not nearly the magnitude we see inter-package. I've not seen such communication distance artifacts on the T2+, where the cache banks are connected to the cores via a high-speed crossbar instead of a ring -- communication latencies seem more regular.

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• 6 Facts About GlassFish Announcement

  - by Bruno.Borges

  Since Oracle announced the end of commercial support for future Oracle GlassFish Server versions, the Java EE world has started wondering what will happen to GlassFish Server Open Source Edition. Unfortunately, there's a lot of misleading information going around. So let me clarify some things with facts, not FUD. Fact #1 - GlassFish Open Source Edition is not dead GlassFish Server Open Source Edition will remain the reference implementation of Java EE. The current trunk is where an implementation for Java EE 8 will flourish, and this will become the future GlassFish 5.0. Calling "GlassFish is dead" does no good to the Java EE ecosystem. The GlassFish Community will remain strong towards the future of Java EE. Without revenue-focused mind, this might actually help the GlassFish community to shape the next version, and set free from any ties with commercial decisions. Fact #2 - OGS support is not over As I said before, GlassFish Server Open Source Edition will continue. Main change is that there will be no more future commercial releases of Oracle GlassFish Server. New and existing OGS 2.1.x and 3.1.x commercial customers will continue to be supported according to the Oracle Lifetime Support Policy. In parallel, I believe there's no other company in the Java EE business that offers commercial support to more than one build of a Java EE application server. This new direction can actually help customers and partners, simplifying decision through commercial negotiations. Fact #3 - WebLogic is not always more expensive than OGS Oracle GlassFish Server ("OGS") is a build of GlassFish Server Open Source Edition bundled with a set of commercial features called GlassFish Server Control and license bundles such as Java SE Support. OGS has at the moment of this writing the pricelist of U$ 5,000 / processor. One information that some bloggers are mentioning is that WebLogic is more expensive than this. Fact 3.1: it is not necessarily the case. The initial edition of WebLogic is called "Standard Edition" and falls into a policy where some “Standard Edition” products are licensed on a per socket basis. As of current pricelist, US$ 10,000 / socket. If you do the math, you will realize that WebLogic SE can actually be significantly more cost effective than OGS, and a customer can save money if running on a CPU with 4 cores or more for example. Quote from the price list: “When licensing Oracle programs with Standard Edition One or Standard Edition in the product name (with the exception of Java SE Support, Java SE Advanced, and Java SE Suite), a processor is counted equivalent to an occupied socket; however, in the case of multi-chip modules, each chip in the multi-chip module is counted as one occupied socket.” For more details speak to your Oracle sales representative - this is clearly at list price and every customer typically has a relationship with Oracle (like they do with other vendors) and different contractual details may apply. And although OGS has always been production-ready for Java EE applications, it is no secret that WebLogic has always been more enterprise, mission critical application server than OGS since BEA. Different editions of WLS provide features and upgrade irons like the WebLogic Diagnostic Framework, Work Managers, Side by Side Deployment, ADF and TopLink bundled license, Web Tier (Oracle HTTP Server) bundled licensed, Fusion Middleware stack support, Oracle DB integration features, Oracle RAC features (such as GridLink), Coherence Management capabilities, Advanced HA (Whole Service Migration and Server Migration), Java Mission Control, Flight Recorder, Oracle JDK support, etc. Fact #4 - There’s no major vendor supporting community builds of Java EE app servers There are no major vendors providing support for community builds of any Open Source application server. For example, IBM used to provide community support for builds of Apache Geronimo, not anymore. Red Hat does not commercially support builds of WildFly and if I remember correctly, never supported community builds of former JBoss AS. Oracle has never commercially supported GlassFish Server Open Source Edition builds. Tomitribe appears to be the exception to the rule, offering commercial support for Apache TomEE. Fact #5 - WebLogic and GlassFish share several Java EE implementations It has been no secret that although GlassFish and WebLogic share some JSR implementations (as stated in the The Aquarium announcement: JPA, JSF, WebSockets, CDI, Bean Validation, JAX-WS, JAXB, and WS-AT) and WebLogic understands GlassFish deployment descriptors, they are not from the same codebase. Fact #6 - WebLogic is not for GlassFish what JBoss EAP is for WildFly WebLogic is closed-source offering. It is commercialized through a license-based plus support fee model. OGS although from an Open Source code, has had the same commercial model as WebLogic. Still, one cannot compare GlassFish/WebLogic to WildFly/JBoss EAP. It is simply not the same case, since Oracle has had two different products from different codebases. The comparison should be limited to GlassFish Open Source / Oracle GlassFish Server versus WildFly / JBoss EAP. But the message now is much clear: Oracle will commercially support only the proprietary product WebLogic, and invest on GlassFish Server Open Source Edition as the reference implementation for the Java EE platform and future Java EE 8, as a developer-friendly community distribution, and encourages community participation through Adopt a JSR and contributions to GlassFish. In comparison Oracle's decision has pretty much the same goal as to when IBM killed support for Websphere Community Edition; and to when Red Hat decided to change the name of JBoss Community Edition to WildFly, simplifying and clarifying marketing message and leaving the commercial field wide open to JBoss EAP only. Oracle can now, as any other vendor has already been doing, focus on only one commercial offer. Some users are saying they will now move to WildFly, but it is important to note that Red Hat does not offer commercial support for WildFly builds. Although the future JBoss EAP versions will come from the same codebase as WildFly, the builds will definitely not be the same, nor sharing 100% of their functionalities and bug fixes. This means there will be no company running a WildFly build in production with support from Red Hat. This discussion has also raised an important and interesting information: Oracle offers a free for developers OTN License for WebLogic. For other environments this is different, but please note this is the same policy Red Hat applies to JBoss EAP, as stated in their download page and terms. Oracle had the same policy for OGS. TL;DR; GlassFish Server Open Source Edition isn’t dead. Current and new OGS 2.x/3.x customers will continue to have support (respecting LSP). WebLogic is not necessarily more expensive than OGS. Oracle will focus on one commercially supported Java EE application server, like other vendors also limit themselves to support one build/product only. Community builds are hardly supported. Commercially supported builds of Open Source products are not exactly from the same codebase as community builds. What's next for GlassFish and the Java EE community? There are conversations in place to tackle some of the community desires, most of them stated by Markus Eisele in his blog post. We will keep you posted.

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• Decoding the SQL Server Index Structure

  A deep dive into the implementation of indexes in SQL Server 2008 R2. This is information that you must know in order to tune your queries for optimum performance. Partial scans of indexes are now possible! SQL Server monitoring made easy "Keeping an eye on our many SQL Server instances is much easier with SQL Response." Mike Lile.Download a free trial of SQL Response now.

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• Business Strategy - Google Case Study

  Business strategy defined by SMBTN.com is a term used in business planning that implies a careful selection and application of resources to obtain a competitive advantage in anticipation of future events or trends. In more general terms business strategy is positioning a company so that it has the greatest competitive advantage over others in the markets and industries that they participate in. This process involves making corporate decisions regarding which markets to provide goods and services, pricing, acceptable quality levels, and how to interact with others in the marketplace. The primary objective of business strategy is to create and increase value for all of its shareholders and stakeholders through the creation of customer value. According to InformationWeek.com, Google has a distinctive technology advantage over its competitors like Microsoft, eBay, Amazon, Yahoo. Google utilizes custom high-performance systems which are cost efficient because they can scale to extreme workloads. This hardware allows for a huge cost advantage over its competitors. In addition, InformationWeek.com interviewed Stephen Arnold who stated that Google’s programmers are 50%-100% more productive compared to programmers working for their competitors.  He based this theory on Google’s competitors having to spend up to four times as much just to keep up. In addition to Google’s technological advantage, they also have developed a decentralized management schema where employees report directly to multiple managers and team project leaders. This allows for the responsibility of the technology department to be shared amongst multiple senior level engineers and removes the need for a singular department head to oversee the activities of the department.  This is a unique approach from the standard management style. Typically a department head like a CIO or CTO would oversee the department’s global initiatives and business functionality.  This would then be passed down and administered through middle management and implemented by programmers, business analyst, network administrators and Database administrators. It goes without saying that an IT professional’s responsibilities would be directed by Google’s technological advantage and management strategy.  Simply because they work within the department, and would have to design, develop, and support the high-performance systems and would have to report multiple managers and project leaders on a regular basis. Since Google was established and driven by new and immerging technology, all other departments would be directly impacted by the technology department.  In fact, they would have to cater to the technology department since it is a huge driving for in the success of Google. Reference: http://www.smbtn.com/smallbusinessdictionary/#b http://www.informationweek.com/news/software/linux/showArticle.jhtml?articleID=192300292&pgno=1&queryText=&isPrev=

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• A System Monitoring Tool Primer

  <b>CertCities:</b> "Linux comes with a number of utilities that can be used to monitor one or more of these performance parameters. The following sections introduce a few of these utilities and show how to understand the information presented by them"

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• Heroku Postgres: A New SQL Database-as-a-Service

  Idera, a Houston-based company known worldwide for its SQL Server solutions in the realms of backup and recovery, performance monitoring, auditing, security, and more, recently announced that it had won five of SQL Server Magazine's 2011 Community Choice Awards. SQL Server Magazine, a publication produced by Penton Media, offers SQL Server users, both beginning and advanced, a host of hands-on information delivered by SQL Server experts. The magazine presented Idera with 2011 Community Choice Awards for five separate products which will only serve to boost the already strong reputation of it...

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• A Real-Time HPC Approach for Optimizing Multicore Architectures

  Complex math is at the heart of many of the biggest technical challenges. With multicore processors, the type of calculations that would have required a supercomputer can now be performed in real-time, embedded environments. High-performance computing - Supercomputer - Real-time computing - Operating system - Companies

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• An XEvent a Day (26 of 31) – Configuring Session Options

  - by Jonathan Kehayias

  There are 7 Session level options that can be configured in Extended Events that affect the way an Event Session operates.  These options can impact performance and should be considered when configuring an Event Session.  I have made use of a few of these periodically throughout this months blog posts, and in today’s blog post I’ll cover each of the options separately, and provide further information about their usage.  Mike Wachal from the Extended Events team at Microsoft, talked...(read more)

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• An XEvent a Day (28 of 31) – Tracking Page Compression Operations

  - by Jonathan Kehayias

  The Database Compression feature in SQL Server 2008 Enterprise Edition can provide some significant reductions in storage requirements for SQL Server databases, and in the right implementations and scenarios performance improvements as well.  There isn’t really a whole lot of information about the operations of database compression that is documented as being available in the DMV’s or SQL Trace.  Paul Randal pointed out on Twitter today that sys.dm_db_index_operational_stats() provides...(read more)

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• T-SQL User-Defined Functions: the good, the bad, and the ugly (part 4)

  - by Hugo Kornelis

  Scalar user-defined functions are bad for performance. I already showed that for T-SQL scalar user-defined functions without and with data access, and for most CLR scalar user-defined functions without data access , and in this blog post I will show that CLR scalar user-defined functions with data access fit into that picture. First attempt Sticking to my simplistic example of finding the triple of an integer value by reading it from a pre-populated lookup table and following the standard recommendations...(read more)

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• 9/18 Live Webcast: Three Compelling Reasons to Upgrade to Oracle Database 11g - Still time to register

  - by jgelhaus

  If you or your organization is still working with Oracle Database 10g or an even older version, now is the time to upgrade. Oracle Database 11g offers a wide variety of advantages to enhance your operation. Join us 10 am PT / 1pm ET September 18th for this live Webcast and learn about what you’re missing: the business, operational, and technical benefits. With Oracle Database 11g, you can: Upgrade with zero downtime Improve application performance and database security Reduce the amount of storage required Save time and money Register today 

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• On-Demand Webcast: Managing Oracle Exadata with Oracle Enterprise Manager 11g

  - by Scott McNeil

  Watch this on-demand webcast and discover how Oracle Enterprise Manager 11g's unique management capabilities allow you to efficiently manage all stages of Oracle Exadata's lifecycle, from testing applications on Exadata to deployment. You'll learn how to: Maximize and predict database performance Drive down IT operational costs through automation Ensure service quality with proactive management Register today and unlock the potential of Oracle Exadata for your enterprise. Register Now!

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• London User Group Meetings this week (19th/20th May); 26th May-Agile Data Warehousing; 17th June-Kim

  - by tonyrogerson

  Got two user group meetings in London for you, we've also started the Cuppa Corner sessions - the first 3 are up on the site - A trip to First Normal Form, Lookup and Cache Transform in SSIS and Pipeline Limiter in SSIS - we are aiming for at least one per week. WhereScape are doing a breakfast meeting on Agile techniques to Data Warehousing and Kimberly Tripp and Paul Randal are over in June for a 1 day master class. Finally a 3 day performance and monitoring workshop on 22- 24th June in London...(read more)

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• Installing PowerDNS (With MySQL Backend) And Poweradmin On Ubuntu 9.10

  <b>Howtoforge:</b> "This article shows how you can install the PowerDNS nameserver (with MySQL backend) and the Poweradmin control panel for PowerDNS on an Ubuntu 9.10 system. PowerDNS is a high-performance, authoritative-only nameserver"

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• SQL SERVER – Get 2 of My Books FREE at Koenig Tech Day – Where Technologies Converge!

  - by pinaldave

  As a regular reader of my blog – you must be aware of that I love to write books and talk about various subjects of my book. The founders of Koenig Solutions are my very old friends, I know them for many years. They have been my biggest supporter of my books. Coming weekend they have a technology event at their Bangalore Location. Every attendee of the technology event will get a set of two books worth Rs. 450 – ‘SQL Server Interview Questions And Answers‘ and ‘SQL Wait Stats Joes 2 Pros‘. I am going to cover a couple of topics of the books and present  as well. I am very confident that every attendee will be having a great time. I will be covering following subjects: SQL Server Tricks and Tips for Blazing Fast Performance Slow Running Queries (SQL) are the most common problem that developers face while working with SQL Server. While it is easy to blame the SQL Server for unsatisfactory performance, however the issue often persists with the way queries have been written, and how SQL Server has been set up. The session will focus on the ways of identifying problems that slow down SQL Servers, and tricks to fix them. Developers will walk out with scripts and knowledge that can be applied to their servers, immediately post the session. After the session is over – I will point to what exact location in the book where you can continue for the further learning. I am pretty excited, this is more like book reading but in entire different format. The one day event will cover four technologies in four separate interactive sessions on: Microsoft SQL Server Security VMware/Virtualization ASP.NET MVC Date of the event: Dec 15, 2012 9 AM to 6PM. Location of the event:  Koenig Solutions Ltd. # 47, 4th Block, 100 feet Road, 3rd Floor, Opp to Shanthi Sagar, Koramangala, Bangalore- 560034 Mobile : 09008096122 Office : 080- 41127140 Organizers have informed me that there are very limited seats for this event and technical session based on my book will start at Sharp 9 AM. If you show up late there are chances that you will not get any seats. Registration for the event is a MUST. Please visit this link for further information. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, SQLAuthority News, T SQL, Technology

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• PASS Data Architecture VC presents Neil Hambly on Improve Data Quality & Integrity using Constraints

  On Tuesday June 19th 12PM noon Central, Neil Hambly will discuss "Leveraging the power of constraints to improve both data quality and performance of your databases." What are your servers really trying to tell you? Find out with new SQL Monitor 3.0, an easy-to-use tool built for no-nonsense database professionals.For effortless insights into SQL Server, download a free trial today.

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• Operations Manager SQL monitoring issue?

  - by merrillaldrich

  We're in the early stages of implementing System Center Operations Manager 2007 R2, and from what I've see so far it looks really good. I am still interested to see the depth of performance counter information that it'll collect and store, but haven't been able to really dig into that just yet. There is one issue I am seeing and I don't know if others have come across this (could not find much online about it either): computing a database file free space alert rule is a little complicated, and it...(read more)

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• External File Upload Optimizations for Windows Azure

  - by rgillen

  [Cross posted from here: http://rob.gillenfamily.net/post/External-File-Upload-Optimizations-for-Windows-Azure.aspx] I’m wrapping up a bit of the work we’ve been doing on data movement optimizations for cloud computing and the latest set of data yielded some interesting points I thought I’d share. The work done here is not really rocket science but may, in some ways, be slightly counter-intuitive and therefore seemed worthy of posting. Summary: for those who don’t like to read detailed posts or don’t have time, the synopsis is that if you are uploading data to Azure, block your data (even down to 1MB) and upload in parallel. Set your block size based on your source file size, but if you must choose a fixed value, use 1MB. Following the above will result in significant performance gains… upwards of 10x-24x and a reduction in overall file transfer time of upwards of 90% (eg, uploading a 1GB file averaged 46.37 minutes prior to optimizations and averaged 1.86 minutes afterwards). Detail: For those of you who want more detail, or think that the claims at the end of the preceding paragraph are over-reaching, what follows is information and code supporting these claims. As the title would indicate, these tests were run from our research facility pointing to the Azure cloud (specifically US North Central as it is physically closest to us) and do not represent intra-cloud results… we have performed intra-cloud tests and the overall results are similar in notion but the data rates are significantly different as well as the tipping points for the various block sizes… this will be detailed separately). We started by building a very simple console application that would loop through a directory and upload each file to Azure storage. This application used the shipping storage client library from the 1.1 version of the azure tools. The only real variation from the client library is that we added code to collect and record the duration (in ms) and size (in bytes) for each file transferred. The code is available here. We then created a directory that had a collection of files for the following sizes: 2KB, 32KB, 64KB, 128KB, 512KB, 1MB, 5MB, 10MB, 25MB, 50MB, 100MB, 250MB, 500MB, 750MB, and 1GB (50 files for each size listed). These files contained randomly-generated binary data and do not benefit from compression (a separate discussion topic). Our file generation tool is available here. The baseline was established by running the application described above against the directory containing all of the data files. This application uploads the files in a random order so as to avoid transferring all of the files of a given size sequentially and thereby spreading the affects of periodic Internet delays across the collection of results.  We then ran some scripts to split the resulting data and generate some reports. The raw data collected for our non-optimized tests is available via the links in the Related Resources section at the bottom of this post. For each file size, we calculated the average upload time (and standard deviation) and the average transfer rate (and standard deviation). As you likely are aware, transferring data across the Internet is susceptible to many transient delays which can cause anomalies in the resulting data. It is for this reason that we randomized the order of source file processing as well as executed the tests 50x for each file size. We expect that these steps will yield a sufficiently balanced set of results. Once the baseline was collected and analyzed, we updated the test harness application with some methods to split the source file into user-defined block sizes and then to upload those blocks in parallel (using the PutBlock() method of Azure storage). The parallelization was handled by simply relying on the Parallel Extensions to .NET to provide a Parallel.For loop (see linked source for specific implementation details in Program.cs, line 173 and following… less than 100 lines total). Once all of the blocks were uploaded, we called PutBlockList() to assemble/commit the file in Azure storage. For each block transferred, the MD5 was calculated and sent ensuring that the bits that arrived matched was was intended. The timer for the blocked/parallelized transfer method wraps the entire process (source file splitting, block transfer, MD5 validation, file committal). A diagram of the process is as follows: We then tested the affects of blocking & parallelizing the transfers by running the updated application against the same source set and did a parameter sweep on the block size including 256KB, 512KB, 1MB, 2MB, and 4MB (our assumption was that anything lower than 256KB wasn’t worth the trouble and 4MB is the maximum size of a block supported by Azure). The raw data for the parallel tests is available via the links in the Related Resources section at the bottom of this post. This data was processed and then compared against the single-threaded / non-optimized transfer numbers and the results were encouraging. The Excel version of the results is available here. Two semi-obvious points need to be made prior to reviewing the data. The first is that if the block size is larger than the source file size you will end up with a “negative optimization” due to the overhead of attempting to block and parallelize. The second is that as the files get smaller, the clock-time cost of blocking and parallelizing (overhead) is more apparent and can tend towards negative optimizations. For this reason (and is supported in the raw data provided in the linked worksheet) the charts and dialog below ignore source file sizes less than 1MB. (click chart for full size image) The chart above illustrates some interesting points about the results: When the block size is smaller than the source file, performance increases but as the block size approaches and then passes the source file size, you see decreasing benefit to the point of negative gains (see the values for the 1MB file size) For some of the moderately-sized source files, small blocks (256KB) are best As the size of the source file gets larger (see values for 50MB and up), the smallest block size is not the most efficient (presumably due, at least in part, to the increased number of blocks, increased number of individual transfer requests, and reassembly/committal costs). Once you pass the 250MB source file size, the difference in rate for 1MB to 4MB blocks is more-or-less constant The 1MB block size gives the best average improvement (~16x) but the optimal approach would be to vary the block size based on the size of the source file.    (click chart for full size image) The above is another view of the same data as the prior chart just with the axis changed (x-axis represents file size and plotted data shows improvement by block size). It again highlights the fact that the 1MB block size is probably the best overall size but highlights the benefits of some of the other block sizes at different source file sizes. This last chart shows the change in total duration of the file uploads based on different block sizes for the source file sizes. Nothing really new here other than this view of the data highlights the negative affects of poorly choosing a block size for smaller files.   Summary What we have found so far is that blocking your file uploads and uploading them in parallel results in significant performance improvements. Further, utilizing extension methods and the Task Parallel Library (.NET 4.0) make short work of altering the shipping client library to provide this functionality while minimizing the amount of change to existing applications that might be using the client library for other interactions.   Related Resources Source code for upload test application Source code for random file generator ODatas feed of raw data from non-optimized transfer tests Experiment Metadata Experiment Datasets 2KB Uploads 32KB Uploads 64KB Uploads 128KB Uploads 256KB Uploads 512KB Uploads 1MB Uploads 5MB Uploads 10MB Uploads 25MB Uploads 50MB Uploads 100MB Uploads 250MB Uploads 500MB Uploads 750MB Uploads 1GB Uploads Raw Data OData feeds of raw data from blocked/parallelized transfer tests Experiment Metadata Experiment Datasets Raw Data 256KB Blocks 512KB Blocks 1MB Blocks 2MB Blocks 4MB Blocks Excel worksheet showing summarizations and comparisons

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• Outstanding SQL Saturday

  - by merrillaldrich

  I had the privilege to attend the SQL Saturday held in Redmond today, and it was really outstanding. Among the many sessions, I especially enjoyed and took a lot of useful information away from Greg Larsen’s Dynamic Management Views session, Kalen Delaney’s Compression Session – I am planning to implement 2008 Enterprise compression on my company’s data warehouse later this year – Remus Rusanu’s session on Service Broker to process NAP data, and Matt Masson’s presentation on high performance SSIS...(read more)

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• What is new in Oracle SOA Suite 11g R1 PS6? by Shanny Anoep

  - by JuergenKress

  Oracle has released a new version 11.1.1.7.0 for their Oracle Fusion Middleware product line. This version includes Patch Set #6 (PS6) for Oracle SOA Suite 11g R1, with a big list of improvements and fixes for each component in that suite. In this post we will highlight some of the interesting updates with regards to troubleshooting, performance, reliability and scalability. Infrastructure/Purging scripts Database growth is a common problem for large-scale Oracle SOA Suite deployments. Oracle already provides multiple purging strategies for the SOA Suite runtime database. This patch set includes two new scripts for purging most of the runtime data: Table Recreation Script (TRS): This script can be used to reclaim as much database space as possible, while still retaining the open instances. It can be used as a corrective action for databases that grew excessively, for example when purging was not performed at all. This should be used as a single corrective action only; the script does not replace the normal purging scripts. Truncate script: Remove all records from the SOA Suite runtime tables without dropping the tables. This script can be used for cloning SOA Suite environments without copying the instance data, or for recreating test scenarios by cleaning all the runtime data. The Oracle SOA Suite Administrator's guide contains a table with the available purging strategies. Diagnostic dumps Using WLST you could already dump diagnostic information about various components of the SOA Suite. This version adds support to retrieve more information on BPEL and Adapters from the command-line. Diagnostic dumps for BPEL New diagnostic dumps are available for BPEL to get information on thread pools, average processing time for BPEL components, and average waiting times for asynchronous instances. This information can be very useful for performance analysis or troubleshooting. With WLST this information can be retrieved from the command-line and included for monitoring or reporting. Read the full article here. SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Facebook Wiki Mix Forum Technorati Tags: SOA Suite PS6,SOA Community,Oracle SOA,Oracle BPM,Community,OPN,Jürgen Kress

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• SQLAuthority News Three Posts on Reporting T-SQL Tuesday #005

  If you are following my blog, you already know that I am more of T-SQL and Performance Tuning type of person. I do have a good understanding of Business Intelligence suit and I also do certain training sessions on the same subject. When I was writing the blog post for T-SQL Tuesday #005 Reporting, [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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• Partner Blog Series: PwC Perspectives - The Gotchas, The Do's and Don'ts for IDM Implementations

  - by Tanu Sood

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mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Arial; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} table.MsoTableMediumList1Accent6 {mso-style-name:"Medium List 1 - Accent 6"; mso-tstyle-rowband-size:1; mso-tstyle-colband-size:1; mso-style-priority:65; mso-style-unhide:no; border-top:solid #E0301E 1.0pt; mso-border-top-themecolor:accent6; border-left:none; border-bottom:solid #E0301E 1.0pt; mso-border-bottom-themecolor:accent6; border-right:none; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Georgia","serif"; color:black; mso-themecolor:text1; mso-ansi-language:EN-GB;} table.MsoTableMediumList1Accent6FirstRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:first-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:cell-none; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; font-family:"Arial Narrow","sans-serif"; mso-ascii-font-family:Georgia; mso-ascii-theme-font:major-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:major-fareast; mso-hansi-font-family:Georgia; mso-hansi-theme-font:major-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:major-bidi;} table.MsoTableMediumList1Accent6LastRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:last-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:1.0pt solid #E0301E; mso-tstyle-border-top-themecolor:accent6; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; color:#968C6D; mso-themecolor:text2; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6FirstCol {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:first-column; mso-style-priority:65; mso-style-unhide:no; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6LastCol {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:last-column; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:1.0pt solid #E0301E; mso-tstyle-border-top-themecolor:accent6; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6OddColumn {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:odd-column; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-shading:#F7CBC7; mso-tstyle-shading-themecolor:accent6; mso-tstyle-shading-themetint:63;} table.MsoTableMediumList1Accent6OddRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:odd-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-shading:#F7CBC7; mso-tstyle-shading-themecolor:accent6; mso-tstyle-shading-themetint:63;} It is generally accepted among business communities that technology by itself is not a silver bullet to all problems, but when it is combined with leading practices, strategy, careful planning and execution, it can create a recipe for success. This post attempts to highlight some of the best practices along with dos & don’ts that our practice has accumulated over the years in the identity & access management space in general, and also in the context of R2, in particular. Best Practices The following section illustrates the leading practices in “How” to plan, implement and sustain a successful OIM deployment, based on our collective experience. Planning is critical, but often overlooked A common approach to planning an IAM program that we identify with our clients is the three step process involving a current state assessment, a future state roadmap and an executable strategy to get there. It is extremely beneficial for clients to assess their current IAM state, perform gap analysis, document the recommended controls to address the gaps, align future state roadmap to business initiatives and get buy in from all stakeholders involved to improve the chances of success. When designing an enterprise-wide solution, the scalability of the technology must accommodate the future growth of the enterprise and the projected identity transactions over several years. Aligning the implementation schedule of OIM to related information technology projects increases the chances of success. As a baseline, it is recommended to match hardware specifications to the sizing guide for R2 published by Oracle. Adherence to this will help ensure that the hardware used to support OIM will not become a bottleneck as the adoption of new services increases. If your Organization has numerous connected applications that rely on reconciliation to synchronize the access data into OIM, consider hosting dedicated instances to handle reconciliation. Finally, ensure the use of clustered environment for development and have at least three total environments to help facilitate a controlled migration to production. If your Organization is planning to implement role based access control, we recommend performing a role mining exercise and consolidate your enterprise roles to keep them manageable. In addition, many Organizations have multiple approval flows to control access to critical roles, applications and entitlements. If your Organization falls into this category, we highly recommend that you limit the number of approval workflows to a small set. Most Organizations have operations managed across data centers with backend database synchronization, if your Organization falls into this category, ensure that the overall latency between the datacenters when replicating the databases is less than ten milliseconds to ensure that there are no front office performance impacts. Ingredients for a successful implementation During the development phase of your project, there are a number of guidelines that can be followed to help increase the chances for success. Most implementations cannot be completed without the use of customizations. If your implementation requires this, it’s a good practice to perform code reviews to help ensure quality and reduce code bottlenecks related to performance. We have observed at our clients that the development process works best when team members adhere to coding leading practices. Plan for time to correct coding defects and ensure developers are empowered to report their own bugs for maximum transparency. Many organizations struggle with defining a consistent approach to managing logs. This is particularly important due to the amount of information that can be logged by OIM. We recommend Oracle Diagnostics Logging (ODL) as an alternative to be used for logging. ODL allows log files to be formatted in XML for easy parsing and does not require a server restart when the log levels are changed during troubleshooting. Testing is a vital part of any large project, and an OIM R2 implementation is no exception. We suggest that at least one lower environment should use production-like data and connectors. Configurations should match as closely as possible. For example, use secure channels between OIM and target platforms in pre-production environments to test the configurations, the migration processes of certificates, and the additional overhead that encryption could impose. Finally, we ask our clients to perform database backups regularly and before any major change event, such as a patch or migration between environments. In the lowest environments, we recommend to have at least a weekly backup in order to prevent significant loss of time and effort. Similarly, if your organization is using virtual machines for one or more of the environments, it is recommended to take frequent snapshots so that rollbacks can occur in the event of improper configuration. Operate & sustain the solution to derive maximum benefits When migrating OIM R2 to production, it is important to perform certain activities that will help achieve a smoother transition. At our clients, we have seen that splitting the OIM tables into their own tablespaces by categories (physical tables, indexes, etc.) can help manage database growth effectively. If we notice that a client hasn’t enabled the Oracle-recommended indexing in the applicable database, we strongly suggest doing so to improve performance. Additionally, we work with our clients to make sure that the audit level is set to fit the organization’s auditing needs and sometimes even allocate UPA tables and indexes into their own table-space for better maintenance. Finally, many of our clients have set up schedules for reconciliation tables to be archived at regular intervals in order to keep the size of the database(s) reasonable and result in optimal database performance. For our clients that anticipate availability issues with target applications, we strongly encourage the use of the offline provisioning capabilities of OIM R2. This reduces the provisioning process for a given target application dependency on target availability and help avoid broken workflows. To account for this and other abnormalities, we also advocate that OIM’s monitoring controls be configured to alert administrators on any abnormal situations. Within OIM R2, we have begun advising our clients to utilize the ‘profile’ feature to encapsulate multiple commonly requested accounts, roles, and/or entitlements into a single item. By setting up a number of profiles that can be searched for and used, users will spend less time performing the same exact steps for common tasks. We advise our clients to follow the Oracle recommended guides for database and application server tuning which provides a good baseline configuration. It offers guidance on database connection pools, connection timeouts, user interface threads and proper handling of adapters/plug-ins. All of these can be important configurations that will allow faster provisioning and web page response times. Many of our clients have begun to recognize the value of data mining and a remediation process during the initial phases of an implementation (to help ensure high quality data gets loaded) and beyond (to support ongoing maintenance and business-as-usual processes). A successful program always begins with identifying the data elements and assigning a classification level based on criticality, risk, and availability. It should finish by following through with a remediation process. Dos & Don’ts Here are the most common dos and don'ts that we socialize with our clients, derived from our experience implementing the solution. Dos Don’ts Scope the project into phases with realistic goals. Look for quick wins to show success and value to the stake holders. Avoid “boiling the ocean” and trying to integrate all enterprise applications in the first phase. Establish an enterprise ID (universal unique ID across the enterprise) earlier in the program. Avoid major UI customizations that require code changes. Have a plan in place to patch during the project, which helps alleviate any major issues or roadblocks (product and database). Avoid publishing all the target entitlements if you don't anticipate their usage during access request. Assess your current state and prepare a roadmap to address your operations, tactical and strategic goals, align it with your business priorities. Avoid integrating non-production environments with your production target systems. Defer complex integrations to the later phases and take advantage of lessons learned from previous phases Avoid creating multiple accounts for the same user on the same system, if there is an opportunity to do so. Have an identity and access data quality initiative built into your plan to identify and remediate data related issues early on. Avoid creating complex approval workflows that would negative impact productivity and SLAs. Identify the owner of the identity systems with fair IdM knowledge and empower them with authority to make product related decisions. This will help ensure overcome any design hurdles. Avoid creating complex designs that are not sustainable long term and would need major overhaul during upgrades. Shadow your internal or external consulting resources during the implementation to build the necessary product skills needed to operate and sustain the solution. Avoid treating IAM as a point solution and have appropriate level of communication and training plan for the IT and business users alike. Conclusion In our experience, Identity programs will struggle with scope, proper resourcing, and more. We suggest that companies consider the suggestions discussed in this post and leverage them to help enable their identity and access program. This concludes PwC blog series on R2 for the month and we sincerely hope that the information we have shared thus far has been beneficial. For more information or if you have questions, you can reach out to Rex Thexton, Senior Managing Director, PwC and or Dharma Padala, Director, PwC. We look forward to hearing from you. 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:12.0pt; mso-para-margin-left:0in; line-height:12.0pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Arial","sans-serif"; mso-ascii-font-family:Arial; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Arial; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Meet the Writers: Dharma Padala is a Director in the Advisory Security practice within PwC.  He has been implementing medium to large scale Identity Management solutions across multiple industries including utility, health care, entertainment, retail and financial sectors.   Dharma has 14 years of experience in delivering IT solutions out of which he has been implementing Identity Management solutions for the past 8 years. Praveen Krishna is a Manager in the Advisory Security practice within PwC.  Over the last decade Praveen has helped clients plan, architect and implement Oracle identity solutions across diverse industries.  His experience includes delivering security across diverse topics like network, infrastructure, application and data where he brings a holistic point of view to problem solving. Scott MacDonald is a Director in the Advisory Security practice within PwC.  He has consulted for several clients across multiple industries including financial services, health care, automotive and retail.   Scott has 10 years of experience in delivering Identity Management solutions. John Misczak is a member of the Advisory Security practice within PwC.  He has experience implementing multiple Identity and Access Management solutions, specializing in Oracle Identity Manager and Business Process Engineering Language (BPEL).

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• What good books are out there on program execution models? [on hold]

  - by murungu

  Can anyone out there name a few books that address the topic of program execution models?? I want a book that can answer questions such as... What is the difference between interpreted and compiled languages and what are the performance consequences at runtime?? What is the difference between lazy evaluation, eager evaluation and short circuit evaluation?? Why would one choose to use one evaluation strategy over another?? How do you simulate lazy evaluation in a language that favours eager evaluation??

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• Google I/O 2010 - Google Analytics APIs: End to end

  Google I/O 2010 - Google Analytics APIs: End to end Google I/O 2010 - Google Analytics APIs: End to end Google APIs 201 Nick Mihailovski Google Analytics measures performance of your website. Learn advanced techniques on how to use our tracking, processing and data export APIs as we walk you through an example of creating a most visited pages web element for your website. For all I/O 2010 sessions, please go to code.google.com From: GoogleDevelopers Views: 6 0 ratings Time: 55:42 More in Science & Technology

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