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  • Enterprise Performance Management: Driving Management Excellence

    Extending operational excellence to management excellence is the new strategic imperative for organizations large and small, all around the world. Management Excellence is a strategy for organizations to differentiate from their competition, by being smarter, more agile and more aligned. Tune into this conversation with John Kopcke, Senior Vice President of Oracle’s Enterprise Performance Management Global Business Unit to learn how leading companies are integrating their management processes and using Oracle’s EPM System to achieve management excellence.

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  • Advanced MySQL Replication - Improving Performance

    MySQL Replication can be made quite reliable and robust if the right tools are used to keep it running smoothly--but what if enormous loads on the primary server are overloading the slave server. Are there ways to speed up performance, so the slave can keep up?

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  • SQL SERVER – DMV – sys.dm_exec_query_optimizer_info – Statistics of Optimizer

    - by pinaldave
    Incredibly, SQL Server has so much information to share with us. Every single day, I am amazed with this SQL Server technology. Sometimes I find several interesting information by just querying few of the DMV. And when I present this info in front of my client during performance tuning consultancy, they are surprised with my findings. Today, I am going to share one of the hidden gems of DMV with you, the one which I frequently use to understand what’s going on under the hood of SQL Server. SQL Server keeps the record of most of the operations of the Query Optimizer. We can learn many interesting details about the optimizer which can be utilized to improve the performance of server. SELECT * FROM sys.dm_exec_query_optimizer_info WHERE counter IN ('optimizations', 'elapsed time','final cost', 'insert stmt','delete stmt','update stmt', 'merge stmt','contains subquery','tables', 'hints','order hint','join hint', 'view reference','remote query','maximum DOP', 'maximum recursion level','indexed views loaded', 'indexed views matched','indexed views used', 'indexed views updated','dynamic cursor request', 'fast forward cursor request') All occurrence values are cumulative and are set to 0 at system restart. All values for value fields are set to NULL at system restart. I have removed a few of the internal counters from the script above, and kept only documented details. Let us check the result of the above query. As you can see, there is so much vital information that is revealed in above query. I can easily say so many things about how many times Optimizer was triggered and what the average time taken by it to optimize my queries was. Additionally, I can also determine how many times update, insert or delete statements were optimized. I was able to quickly figure out that my client was overusing the Query Hints using this dynamic management view. If you have been reading my blog, I am sure you are aware of my series related to SQL Server Views SQL SERVER – The Limitations of the Views – Eleven and more…. With this, I can take a quick look and figure out how many times Views were used in various solutions within the query. Moreover, you can easily know what fraction of the optimizations has been involved in tuning server. For example, the following query would tell me, in total optimizations, what the fraction of time View was “reference“. As this View also includes system Views and DMVs, the number is a bit higher on my machine. SELECT (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'view reference') / (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'optimizations') AS ViewReferencedFraction Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Performance Tuning Tips for Apache

    Apache is one of the most successful open source projects of our times. A big advantage of this popularity is that over the years people have spent a great deal of time fine tuning the software for better performance. Read on to learn more.

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  • New Exadata Book Available Soon

    - by Rob Reynolds
    Oracle Press is set to released the first book on data warehouse performance and Exadata on March 14th. Achieving Extreme Performance with Oracle Exadata , by my colleagues Rick Greenwald, Robert Stackowiak, Maqsood Alam, and Mans Bhuller will be available at your favorite booksellers next week. I've seen a sneak peak of the content in this book and its a great way to fully grasp the power of Exadata and how to best apply it to achieve extreme data warehouse performance. From the publisher's description: Achieving Extreme Performance with Oracle Exadata and the Sun Oracle Database Machine is filled with best practices for deployments, hardware sizing, architecting the database machine environments for maximum availability, and backup and recovery. Oracle Database 11gR2 features used within these offerings, as well as migration options and paths for Oracle and non-Oracle databases to Oracle Exadata are covered. This Oracle Press guide also discusses architecture, administration, maintenance, monitoring, and tuning of Oracle Exadata Storage Servers and the Sun Oracle Database Machine. If your company is considering Exadata, or if you need more horsepower out of your data warehouse, I highly recommend grabbing a copy of this book next week.

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  • Windows Azure Use Case: High-Performance Computing (HPC)

    - by BuckWoody
    This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: High-Performance Computing (also called Technical Computing) at its most simplistic is a layout of computer workloads where a “head node” accepts work requests, and parses them out to “worker nodes'”. This is useful in cases such as scientific simulations, drug research, MatLab work and where other large compute loads are required. It’s not the immediate-result type computing many are used to; instead, a “job” or group of work requests is sent to a cluster of computers and the worker nodes work on individual parts of the calculations and return the work to the scheduler or head node for the requestor in a batch-request fashion. This is typical to the way that many mainframe computing use-cases work. You can use commodity-based computers to create an HPC Cluster, such as the Linux application called Beowulf, and Microsoft has a server product for HPC using standard computers, called the Windows Compute Cluster that you can read more about here. The issue with HPC (from any vendor) that some organization have is the amount of compute nodes they need. Having too many results in excess infrastructure, including computers, buildings, storage, heat and so on. Having too few means that the work is slower, and takes longer to return a result to the calling application. Unless there is a consistent level of work requested, predicting the number of nodes is problematic. Implementation: Recently, Microsoft announced an internal partnership between the HPC group (Now called the Technical Computing Group) and Windows Azure. You now have two options for implementing an HPC environment using Windows. You can extend the current infrastructure you have for HPC by adding in Compute Nodes in Windows Azure, using a “Broker Node”.  You can then purchase time for adding machines, and then stop paying for them when the work is completed. This is a common pattern in groups that have a constant need for HPC, but need to “burst” that load count under certain conditions. The second option is to install only a Head Node and a Broker Node onsite, and host all Compute Nodes in Windows Azure. This is often the pattern for organizations that need HPC on a scheduled and periodic basis, such as financial analysis or actuarial table calculations. References: Blog entry on Hybrid HPC with Windows Azure: http://blogs.msdn.com/b/ignitionshowcase/archive/2010/12/13/high-performance-computing-on-premise-and-in-the-windows-azure-cloud.aspx  Links for further research on HPC, includes Windows Azure information: http://blogs.msdn.com/b/ncdevguy/archive/2011/02/16/handy-links-for-hpc-and-azure.aspx 

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  • SQL SERVER – Public Training and Private Training – Differences and Similarities

    - by pinaldave
    Earlier this year, I was on Road SQL Server Seminars. I did many SQL Server Performance Trainings and SQL Server Performance Consultations throughout the year but I feel the most rewarding exercise is always the one when instructor learns something from students, too. I was just talking to my wife, Nupur – she manages my logistics and administration related activities – and she pointed out that this year I have done 62% consultations and 38% trainings. I was bit surprised as I thought the numbers would be reversed. Every time I review the year, I think of training done at organizations. Well, I cannot argue with reality, I have done more consultations (some would call them projects) than training. I told my wife that I enjoy consultations more than training. She promptly asked me a question which was not directly related but made me think for long time, and in the end resulted in this blog post. Nupur asked me: what do I enjoy the most, public training or private training? I had a long conversation with her on this subject. I am not going to write long blog post which can change your life here. This is rather a small post condensing my one hour discussion into 200 words. Public Training is fun because… There are lots of different kinds of attendees There are always vivid questions Lots of questions on questions Less interest in theory and more interest in demos Good opportunity of future business Private Training is fun because… There is a focused interest One question is discussed deeply because of existing company issues More interest in “how it happened” concepts – under the hood operations Good connection with attendees This is also a good opportunity of future business Here I will stop my monologue and I want to open up this question to all of you: Question to Attendees - Which one do you enjoy the most – Public Training or Private Training? Question to Trainers - What do you enjoy the most – Public Training or Private Training? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, SQLAuthority News, T SQL, Technology

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  • Of C# Iterators and Performance

    - by James Michael Hare
    Some of you reading this will be wondering, "what is an iterator" and think I'm locked in the world of C++.  Nope, I'm talking C# iterators.  No, not enumerators, iterators.   So, for those of you who do not know what iterators are in C#, I will explain it in summary, and for those of you who know what iterators are but are curious of the performance impacts, I will explore that as well.   Iterators have been around for a bit now, and there are still a bunch of people who don't know what they are or what they do.  I don't know how many times at work I've had a code review on my code and have someone ask me, "what's that yield word do?"   Basically, this post came to me as I was writing some extension methods to extend IEnumerable<T> -- I'll post some of the fun ones in a later post.  Since I was filtering the resulting list down, I was using the standard C# iterator concept; but that got me wondering: what are the performance implications of using an iterator versus returning a new enumeration?   So, to begin, let's look at a couple of methods.  This is a new (albeit contrived) method called Every(...).  The goal of this method is to access and enumeration and return every nth item in the enumeration (including the first).  So Every(2) would return items 0, 2, 4, 6, etc.   Now, if you wanted to write this in the traditional way, you may come up with something like this:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         List<T> newList = new List<T>();         int count = 0;           foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 newList.Add(i);             }         }           return newList;     }     So basically this method takes any IEnumerable<T> and returns a new IEnumerable<T> that contains every nth item.  Pretty straight forward.   The problem?  Well, Every<T>(...) will construct a list containing every nth item whether or not you care.  What happens if you were searching this result for a certain item and find that item after five tries?  You would have generated the rest of the list for nothing.   Enter iterators.  This C# construct uses the yield keyword to effectively defer evaluation of the next item until it is asked for.  This can be very handy if the evaluation itself is expensive or if there's a fair chance you'll never want to fully evaluate a list.   We see this all the time in Linq, where many expressions are chained together to do complex processing on a list.  This would be very expensive if each of these expressions evaluated their entire possible result set on call.    Let's look at the same example function, this time using an iterator:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         int count = 0;         foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 yield return i;             }         }     }   Notice it does not create a new return value explicitly, the only evidence of a return is the "yield return" statement.  What this means is that when an item is requested from the enumeration, it will enter this method and evaluate until it either hits a yield return (in which case that item is returned) or until it exits the method or hits a yield break (in which case the iteration ends.   Behind the scenes, this is all done with a class that the CLR creates behind the scenes that keeps track of the state of the iteration, so that every time the next item is asked for, it finds that item and then updates the current position so it knows where to start at next time.   It doesn't seem like a big deal, does it?  But keep in mind the key point here: it only returns items as they are requested. Thus if there's a good chance you will only process a portion of the return list and/or if the evaluation of each item is expensive, an iterator may be of benefit.   This is especially true if you intend your methods to be chainable similar to the way Linq methods can be chained.    For example, perhaps you have a List<int> and you want to take every tenth one until you find one greater than 10.  We could write that as:       List<int> someList = new List<int>();         // fill list here         someList.Every(10).TakeWhile(i => i <= 10);     Now is the difference more apparent?  If we use the first form of Every that makes a copy of the list.  It's going to copy the entire list whether we will need those items or not, that can be costly!    With the iterator version, however, it will only take items from the list until it finds one that is > 10, at which point no further items in the list are evaluated.   So, sounds neat eh?  But what's the cost is what you're probably wondering.  So I ran some tests using the two forms of Every above on lists varying from 5 to 500,000 integers and tried various things.    Now, iteration isn't free.  If you are more likely than not to iterate the entire collection every time, iterator has some very slight overhead:   Copy vs Iterator on 100% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 5 Copy 5 5 5 Iterator 5 50 50 Copy 28 50 50 Iterator 27 500 500 Copy 227 500 500 Iterator 247 5000 5000 Copy 2266 5000 5000 Iterator 2444 50,000 50,000 Copy 24,443 50,000 50,000 Iterator 24,719 500,000 500,000 Copy 250,024 500,000 500,000 Iterator 251,521   Notice that when iterating over the entire produced list, the times for the iterator are a little better for smaller lists, then getting just a slight bit worse for larger lists.  In reality, given the number of items and iterations, the result is near negligible, but just to show that iterators come at a price.  However, it should also be noted that the form of Every that returns a copy will have a left-over collection to garbage collect.   However, if we only partially evaluate less and less through the list, the savings start to show and make it well worth the overhead.  Let's look at what happens if you stop looking after 80% of the list:   Copy vs Iterator on 80% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 4 Copy 5 5 4 Iterator 5 50 40 Copy 27 50 40 Iterator 23 500 400 Copy 215 500 400 Iterator 200 5000 4000 Copy 2099 5000 4000 Iterator 1962 50,000 40,000 Copy 22,385 50,000 40,000 Iterator 19,599 500,000 400,000 Copy 236,427 500,000 400,000 Iterator 196,010       Notice that the iterator form is now operating quite a bit faster.  But the savings really add up if you stop on average at 50% (which most searches would typically do):     Copy vs Iterator on 50% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 2 Copy 5 5 2 Iterator 4 50 25 Copy 25 50 25 Iterator 16 500 250 Copy 188 500 250 Iterator 126 5000 2500 Copy 1854 5000 2500 Iterator 1226 50,000 25,000 Copy 19,839 50,000 25,000 Iterator 12,233 500,000 250,000 Copy 208,667 500,000 250,000 Iterator 122,336   Now we see that if we only expect to go on average 50% into the results, we tend to shave off around 40% of the time.  And this is only for one level deep.  If we are using this in a chain of query expressions it only adds to the savings.   So my recommendation?  If you have a resonable expectation that someone may only want to partially consume your enumerable result, I would always tend to favor an iterator.  The cost if they iterate the whole thing does not add much at all -- and if they consume only partially, you reap some really good performance gains.   Next time I'll discuss some of my favorite extensions I've created to make development life a little easier and maintainability a little better.

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  • 12/12 Live Webcast: Introducing Next-Generation Enterprise Auditing and Database Firewall

    - by jgelhaus
    Join Oracle Security gurus to hear how Oracle products monitor Oracle and non-Oracle database traffic, detect unauthorized activity including SQL injection attacks, and block internal and external threats from reaching the database. Hear how organizations such as TransUnion Interactive and SquareTwo Financial rely on Oracle to monitor and secure their Oracle and non-Oracle database environments. Register for the webcast here.

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  • Monitoring Database disk space

    - by Michael Freidgeim
    An article Data files: To Autogrow Or Not To Autogrow? recommends NOT to rely on auto-grow, because it causing delays in unplanned times.We should mtonitor database files(both data and log), and if they close to max capacity, manually increase the size. However it doesn't give references, how to monitor the free space inside databases. I've tried to look how to do it. It can be done manually using   execute sp_spaceused for the database in question or  sp_SOS (can be downloaded from http://searchsqlserver.techtarget.com/tip/Find-size-of-SQL-Server-tables-and-other-objects-with-stored-procedure)Alternatively you can run SQL commands as suggested in Http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=82359 by Michael Valentine Jonesselect [FREE_SPACE_MB] = convert(decimal(12,2),round((a.size-fileproperty(a.name,'SpaceUsed'))/128.000,2)) from dbo.sysfiles aMore useful article Monitor database file sizes with SQL Server Jobs describes how to setup monitoring Finally I found the excellent articleManaging Database Data Usage With Custom Space Alerts, that can be followed even support personnel without much DBA experience.

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  • Google I/O 2012 - Building High Performance Mobile Web Applications

    Google I/O 2012 - Building High Performance Mobile Web Applications Ryan Fioravanti Learn what it takes to build an HTML5 mobile app that will wow your users. This session will focus on speed, offline support, UI layouts, and the tools necessary to set up a productive development environment. Come to this session if you're looking to make a killer mobile web app that stands out amongst the competition. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 33 0 ratings Time: 49:43 More in Science & Technology

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  • SQL SERVER – Core Concepts – Elasticity, Scalability and ACID Properties – Exploring NuoDB an Elastically Scalable Database System

    - by pinaldave
    I have been recently exploring Elasticity and Scalability attributes of databases. You can see that in my earlier blog posts about NuoDB where I wanted to look at Elasticity and Scalability concepts. The concepts are very interesting, and intriguing as well. I have discussed these concepts with my friend Joyti M and together we have come up with this interesting read. The goal of this article is to answer following simple questions What is Elasticity? What is Scalability? How ACID properties vary from NOSQL Concepts? What are the prevailing problems in the current database system architectures? Why is NuoDB  an innovative and welcome change in database paradigm? Elasticity This word’s original form is used in many different ways and honestly it does do a decent job in holding things together over the years as a person grows and contracts. Within the tech world, and specifically related to software systems (database, application servers), it has come to mean a few things - allow stretching of resources without reaching the breaking point (on demand). What are resources in this context? Resources are the usual suspects – RAM/CPU/IO/Bandwidth in the form of a container (a process or bunch of processes combined as modules). When it is about increasing resources the simplest idea which comes to mind is the addition of another container. Another container means adding a brand new physical node. When it is about adding a new node there are two questions which comes to mind. 1) Can we add another node to our software system? 2) If yes, does adding new node cause downtime for the system? Let us assume we have added new node, let us see what the new needs of the system are when a new node is added. Balancing incoming requests to multiple nodes Synchronization of a shared state across multiple nodes Identification of “downstate” and resolution action to bring it to “upstate” Well, adding a new node has its advantages as well. Here are few of the positive points Throughput can increase nearly horizontally across the node throughout the system Response times of application will increase as in-between layer interactions will be improved Now, Let us put the above concepts in the perspective of a Database. When we mention the term “running out of resources” or “application is bound to resources” the resources can be CPU, Memory or Bandwidth. The regular approach to “gain scalability” in the database is to look around for bottlenecks and increase the bottlenecked resource. When we have memory as a bottleneck we look at the data buffers, locks, query plans or indexes. After a point even this is not enough as there needs to be an efficient way of managing such large workload on a “single machine” across memory and CPU bound (right kind of scheduling)  workload. We next move on to either read/write separation of the workload or functionality-based sharing so that we still have control of the individual. But this requires lots of planning and change in client systems in terms of knowing where to go/update/read and for reporting applications to “aggregate the data” in an intelligent way. What we ideally need is an intelligent layer which allows us to do these things without us getting into managing, monitoring and distributing the workload. Scalability In the context of database/applications, scalability means three main things Ability to handle normal loads without pressure E.g. X users at the Y utilization of resources (CPU, Memory, Bandwidth) on the Z kind of hardware (4 processor, 32 GB machine with 15000 RPM SATA drives and 1 GHz Network switch) with T throughput Ability to scale up to expected peak load which is greater than normal load with acceptable response times Ability to provide acceptable response times across the system E.g. Response time in S milliseconds (or agreed upon unit of measure) – 90% of the time The Issue – Need of Scale In normal cases one can plan for the load testing to test out normal, peak, and stress scenarios to ensure specific hardware meets the needs. With help from Hardware and Software partners and best practices, bottlenecks can be identified and requisite resources added to the system. Unfortunately this vertical scale is expensive and difficult to achieve and most of the operational people need the ability to scale horizontally. This helps in getting better throughput as there are physical limits in terms of adding resources (Memory, CPU, Bandwidth and Storage) indefinitely. Today we have different options to achieve scalability: Read & Write Separation The idea here is to do actual writes to one store and configure slaves receiving the latest data with acceptable delays. Slaves can be used for balancing out reads. We can also explore functional separation or sharing as well. We can separate data operations by a specific identifier (e.g. region, year, month) and consolidate it for reporting purposes. For functional separation the major disadvantage is when schema changes or workload pattern changes. As the requirement grows one still needs to deal with scale need in manual ways by providing an abstraction in the middle tier code. Using NOSQL solutions The idea is to flatten out the structures in general to keep all values which are retrieved together at the same store and provide flexible schema. The issue with the stores is that they are compromising on mostly consistency (no ACID guarantees) and one has to use NON-SQL dialect to work with the store. The other major issue is about education with NOSQL solutions. Would one really want to make these compromises on the ability to connect and retrieve in simple SQL manner and learn other skill sets? Or for that matter give up on ACID guarantee and start dealing with consistency issues? Hybrid Deployment – Mac, Linux, Cloud, and Windows One of the challenges today that we see across On-premise vs Cloud infrastructure is a difference in abilities. Take for example SQL Azure – it is wonderful in its concepts of throttling (as it is shared deployment) of resources and ability to scale using federation. However, the same abilities are not available on premise. This is not a mistake, mind you – but a compromise of the sweet spot of workloads, customer requirements and operational SLAs which can be supported by the team. In today’s world it is imperative that databases are available across operating systems – which are a commodity and used by developers of all hues. An Ideal Database Ability List A system which allows a linear scale of the system (increase in throughput with reasonable response time) with the addition of resources A system which does not compromise on the ACID guarantees and require developers to learn new paradigms A system which does not force fit a new way interacting with database by learning Non-SQL dialect A system which does not force fit its mechanisms for providing availability across its various modules. Well NuoDB is the first database which has all of the above abilities and much more. In future articles I will cover my hands-on experience with it. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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  • Announcing: Oracle Database 11g R2 Certification on Oracle Linux 6

    - by Monica Kumar
    Oracle Announces the Certification of the Oracle Database on Oracle Linux 6 and Red Hat Enterprise Linux 6 Yesterday we announced the certification of Oracle Database 11g R2 with Oracle Linux 6 and Unbreakable Enterprise Kernel. Here are the key highlights: Oracle Database 11g Release 2 (R2) and Oracle Fusion Middleware 11g Release 1 (R1) are immediately available on Oracle Linux 6 with the Unbreakable Enterprise Kernel. Oracle Database 11g R2 and Oracle Fusion Middleware 11g R1 will be available on Red Hat Enterprise Linux 6 (RHEL6) and Oracle Linux 6 with the Red Hat Compatible Kernel in 90 days. Oracle offers direct Linux support to customers running RHEL6, Oracle Linux 6, or a combination of both. Oracle Linux will continue to maintain compatibility with Red Hat Linux. Read the full press release. 

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  • Android XML Parser Performance

    Shane Conder will show us how different XML parsers affect performance with Android and the answers might surprise you. The article provides developers with data for choosing a particular XML parser and Android code that demonstrates all three parsers.

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  • When to use shared libraries for a web framework?

    - by CamelBlues
    tl;dr: I've found myself hosting a bunch of sites running on the same web framework (symfony 1.4). Would it be helpful if I moved all of the shared library code into the same directory and shared it across the sites? more I see some advantages to this: Each site takes up less disk space Library updates (an unlikely scenario) can take place across all sites I also see some disadvantages, mostly in terms of a single point of failure and the inability to have sites using different versions of the framework. My real concern, though, is performance. I hypothesize that I will see a performance increase, since the PHP code will already be cached for all sites when they call the framework. Is this a correct hypothesis?

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  • Oracle ETPM v2.3.1 Examachine Performance Benchmark Data Sheet

    - by Paula Speranza-Hadley
    Oracle Tax is pleased to announce the exceptional results of the Oracle ETPM v2.3.1 Examachine performance benchmark.   The benchmark achieved the following results:  · Processed8M outpayments and 2M payments in  6 hours · Processed 1M forms in 4 hours · Near  linear scalability of batch processing For the complete data sheet, please click on the following link:  https://blogs.oracle.com/tax/resource/OracleETPMv231ExamachinePerformanceBenchmarkDataSheet.pdf

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  • Using Live Data in Database Development Work

    - by Phil Factor
    Guest Editorial for Simple-Talk Newsletter... in which Phil Factor reacts with some exasperation when coming across a report that a majority of companies were still using financial and personal data for both developing and testing database applications. If you routinely test your development work using real production data that contains personal or financial information, you are probably being irresponsible, and at worst, risking a heavy financial penalty for your company. Surprisingly, over 80% of financial companies still do this. Plenty of data breaches and fraud have happened from the use of real data for testing, and a data breach is a nightmare for any organisation that suffers one. The cost of each data breach averages out at around $7.2 million in the US in notification, escalation, credit monitoring, fines, litigation, legal costs, and lost business due to customer churn, £1.9 million in the UK. 70% of data breaches are done from within the organisation. Real data can be exploited in a number of ways for malicious or criminal purposes. It isn't just the obvious use of items such as name and address, date of birth, social security number, and credit card and bank account numbers: Data can be exploited in many subtle ways, so there are excellent reasons to ensure that a high priority is given to the detection and prevention of any data breaches. You'll never successfully guess all the ways that real data can be exploited maliciously, or the ease with which it can be accessed. It would be silly to argue that developers never need access to a copy of the database containing live data. Developers sometimes need to track a bug that can only be replicated on the data from the live database. However, it has to be done in a very restrictive harness. The law makes no distinction between development and production databases when a data breach occurs, so the data has to be held with all appropriate security measures in place. In Europe, the use of personal data for testing requires the explicit consent of the people whose data is being held. There are federal standards such as GLBA, PCI DSS and HIPAA, and most US States have privacy legislation. The task of ensuring compliance and tight security in such circumstances is an expensive and time-consuming overhead. The developer is likely to suffer investigation if a data breach occurs, even if the company manages to stay in business. Ironically, the use of copies of live data isn't usually the most effective way to develop or test your data. Data is usually time-specific and isn't usually current by the time it is used for testing, Existing data doesn't help much for new functionality, and every time the data is refreshed from production, any test data is likely to be overwritten. Also, it is not always going to test all the 'edge' conditions that are likely to flush out bugs. You still have the task of simulating the dynamics of actual usage of the database, and here you have no alternative to creating 'spoofed' data. Because of the complexities of relational data, It used to be that there was no realistic alternative to developing and testing with live data. However, this is no longer the case. Real data can be obfuscated, or it can be created entirely from scratch. The latter process used to be impractical, now that there are plenty of third-party tools to choose from. The process of obfuscation isn't risk free. The process must access the live data, and the success of the obfuscation process has to be carefully monitored. Database data security isn't an exciting topic to you or I, but to a hacker it can be an all-consuming obsession, especially if there is financial or political gain involved. This is not the sort of adversary one would wish for and it is far better to accept, and work with, security restrictions that exist for using live data in database development work, especially when the tools exist to create large realistic database test data that can be better for several aspects of testing.

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  • Multithreded UI desktop application issues

    - by igor
    I am involved into development a rich UI project: desktop windows application. Application uses asynchronous invocations and in its turn it should be ready to process external messages (events). The problem is clear: at first time it was built as a simple prototype and it was not stress tested and all was fine. Then application was grown: the number of calls to server and number of events from server are high and performance is low. What is more users noticed that sometimes performance is extremal low. Asynchronous invocations based on thread pool (BeginInvoke, EndInvoke), external events are going from WCF service (.NET 3.5). My goal is synchronization of all tasks and putting priorities to every executions in desktop application. My question is: is there any practice how to reach my goal: patterns, task priority list, others? What should I do at first, second and next times? Thanks

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  • Multithreaded UI desktop application issues

    - by igor
    I am involved into development a rich UI project: desktop windows application. Application uses asynchronous invocations and in its turn it should be ready to process external messages (events). The problem is clear: at first time it was built as a simple prototype and it was not stress tested and all was fine. Then application was grown: the number of calls to server and number of events from server are high and performance is low. What is more users noticed that sometimes performance is extremal low. Asynchronous invocations based on thread pool (BeginInvoke, EndInvoke), external events are going from WCF service (.NET 3.5). My goal is synchronization of all tasks and putting priorities to every executions in desktop application. My question is: is there any practice how to reach my goal: patterns, task priority list, others? What should I do at first, second and next times? Thanks

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  • Announcement: Oracle Database Appliance 2.4 patch update now available

    - by uwes
    The Oracle Database Appliance 2.4 patch is now available from My Oracle Support (MOS).  If you search for the Oracle Database Appliance 2.4.0.0.0 Kit under Patches it will display the newly uploaded bundles. The patch highlights include: Normal redundancy (double-mirroring) option providing 6TB of usable storage Enhanced Diagnostics - Trace File Analyzer and ODACHK Also, if you review the README, you may see content that says:        "The grid infrastructure and database patching, both are rolling upgradable. During our patching, we patch the node 1 first and when completed, we patch the node 2." I would like to clarify that the 'infrastructure' updates (OS, Firmware, ILOM, etc) will require a  short downtime of the ODA while it is applied.  When you update the grid infrastructure (--gi), the appliance manager verifies that the infrastructure was updated so you cannot just patch the GI without first updating the infrastructure. The high level update patch steps include (but not limited to): Download patch update to your ODA The --infra (infrastructure) is updated and ODA Databases are down and the ODA is/may be rebooted ODA and GI/Databases are restarted Issue the command to update the Grid Infrastructure/databases (The order of the steps are completed automatically and you cannot control when the nodes are brought up and down during the patching) Node 1 -- shutdown databases and GI Node 1 -- patch GI/database Node 1 -- bring up databases and GI Node 2 -- shutdown databases and GI Node 2 -- patch GI/database Node 2 -- bring up databases and GI A replay from Friday's with Sohan on the 2.4 release can be found here.  The PDF of the presentation is here. The Data Sheet, WP, and 2.4 Configurator are available on the ODA OTN site.

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  • Oracle Database 11g Release 2: Optimized for SAP

    - by jenny.gelhausen
    With the release of Oracle Database 11g Release 2 Enterprise Edition, Oracle has further enhanced its long-standing commitment to joint Oracle and SAP AG customers. Get more details on the release. The Oracle Database Insider sat down with Gerhard Kuppler, senior director Corporate SAP Account at Oracle, to find out just how much Oracle Database 11g Release 2 can impact SAP customers. Check out the interview details.

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  • Unable to add users to Microsoft Dynamics CRM 4.0 after database restore

    - by Wes Weeks
    Working with a client in our Multi-tenant CRM environment who was doing a database migration into CRM and as part of the process, a backup of their Organization_MSCRM database was taken just prior to starting the migration in case it needed to be restored and run a second time. In this case it did, so I restored the database and let the client know he should be good to go.  A few hours later I received a call that they were unable to add some new users, they would appear as available when using the add multiple user wizard, but anyone added would not be added to CRM.  It was also disucussed that these users had been added to CRM initally AFTER the database backup had been taken. I turned on tracing and tried to add the users through both the single user form and multiple user interface and was unable to do so.  The error message in the logs wasn't much help: Unexpected error adding user [email protected]: Microsoft.Crm.CrmException: INVALID_WRPC_TOKEN: Validate WRPC Token: WRPCTokenState=Invalid, TOKEN_EXPIRY=4320, IGNORE_TOKEN=False Searching on Google or bing didn't offer any assitance.  Apparently not a very common problem, or no one has been able to resolve. I did some searching in the MSCRM_CONFIG database and found that their are several user tables there and after getting my head around the structure found that there were enties here for users that were not part of the restored DB.  It seems that new users are added to both the Orgnaization_MSCRM and MSCRM_CONFIG and after the restore these were out of sync. I needed to remove the extra entries in order to address.  Restoring the MSCRM_CONFIG database was not an option as other clients could have been adding users at this point and to restore would risk breaking their instances of CRM.  Long story short, I was finally able to generate a script to remove the bad entries and when I tried to add users again, I was succesful.  In case someone else out there finds themselves in a similar situation, here is the script I used to delete the bad entries. DECLARE @UsersToDelete TABLE (   UserId uniqueidentifier )   Insert Into @UsersToDelete(UserId) Select UserId from [MSCRM_CONFIG].[dbo].[SystemUserOrganizations] Where CrmuserId Not in (select systemuserid from Organization_MSCRM.dbo.SystemUserBase) And OrganizationId = '00000000-643F-E011-0000-0050568572A1' --Id From the Organization table for this instance   Delete From [MSCRM_CONFIG].[dbo].[SystemUserAuthentication]   Where UserId in (Select UserId From @UsersToDelete)   Delete From [MSCRM_CONFIG].[dbo].[SystemUserOrganizations] Where UserId in (Select UserId From @UsersToDelete)   Delete From [MSCRM_CONFIG].[dbo].[SystemUser] Where Id in (Select UserId From @UsersToDelete)

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  • The Database as Intellectual Property

    - by Jonathan Kehayias
    Every so often, a question shows up on the forums in the form of, “How do I prevent anyone from accessing my database schema, including local administrators and sysadmins in SQL Server?”  I usually laugh a little shake my head when I read a question like this because it demonstrates an complete lack of understanding of the power an administrator has over SQL Server.  The simple answer is this: If you don’t want your database schema to ever be accessed or known, don’t distribute your database....(read more)

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  • Add a database to use with locate command

    - by Pedro Teran
    i would like to know if anyone knows how I can create a database of a file system on my computer. so I can choose this data base to search for files on this file system efficiently. I ask this question since in man locate I found that I can choose a database for a different file system. Also would be grate if /var/lib/mlocate/mlocate.db database can have the data of 2 disks any approach ideas or others would be greatly appreciated

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