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  • how to avoid or minimise use of check/conditional statement?

    - by Muneeb Nasir
    I have scenario, where i got stream and i need to check for some value. if i got my any new value i have to store it in any of data structure. well it seems very easy, i can place conditional statement if-else or can use contain method of set/map to check either received is new or not. but the problem is checking will effect my application performance, in stream i'll receive hundreds for value in second, if i start checking each and every value i received than for sure it effect performance. Any body can suggest me any mechanism or algorithm that solve my issue. either by bypassing checks or atleast minimize them?

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  • Database Partitioning and Multiple Data Source Considerations

    - by Jeffrey McDaniel
    With the release of P6 Reporting Database 3.0 partitioning was added as a feature to help with performance and data management.  Careful investigation of requirements should be conducting prior to installation to help improve overall performance throughout the lifecycle of the data warehouse, preventing future maintenance that would result in data loss. Before installation try to determine how many data sources and partitions will be required along with the ranges.  In P6 Reporting Database 3.0 any adjustments outside of defaults must be made in the scripts and changes will require new ETL runs for each data source.  Considerations: 1. Standard Edition or Enterprise Edition of Oracle Database.   If you aren't using Oracle Enterprise Edition Database; the partitioning feature is not available. Multiple Data sources are only supported on Enterprise Edition of Oracle   Database. 2. Number of Data source Ids for partitioning during configuration.   This setting will specify how many partitions will be allocated for tables containing data source information.  This setting requires some evaluation prior to installation as       there are repercussions if you don't estimate correctly.   For example, if you configured the software for only 2 data sources and the partition setting was set to 2, however along came a 3rd data source.  The necessary steps to  accommodate this change are as follows: a) By default, 3 partitions are configured in the Reporting Database scripts. Edit the create_star_tables_part.sql script located in <installation directory>\star\scripts   and search for partition.  You’ll see P1, P2, P3.  Add additional partitions and sub-partitions for P4 and so on. These will appear in several areas.  (See P6 Reporting Database 3.0 Installation and Configuration guide for more information on this and how to adjust partition ranges). b) Run starETL -r.  This will recreate each table with the new partition key.  The effect of this step is that all tables data will be lost except for history related tables.   c) Run starETL for each of the 3 data sources (with the data source # (starETL.bat "-s2" -as defined in P6 Reporting Database 3.0 Installation and Configuration guide) The best strategy for this setting is to overestimate based on possible growth.  If during implementation it is deemed that there are atleast 2 data sources with possibility for growth, it is a better idea to set this setting to 4 or 5, allowing room for the future and preventing a ‘start over’ scenario. 3. The Number of Partitions and the Number of Months per Partitions are not specific to multi-data source.  These settings work in accordance to a sub partition of larger tables with regard to time related data.  These settings are dataset specific for optimization.  The number of months per partition is self explanatory, optimally the smaller the partition, the better query performance so if the dataset has an extremely large number of spread/history records, a lower number of months is optimal.  Working in accordance with this setting is the number of partitions, this will determine how many "buckets" will be created per the number of months setting.  For example, if you kept the default for # of partitions of 3, and select 2 months for each partitions you would end up with: -1st partition, 2 months -2nd partition, 2 months -3rd partition, all the remaining records Therefore with records to this setting, it is important to analyze your source db spread ranges and history settings when determining the proper number of months per partition and number of partitions to optimize performance.  Also be aware the DBA will need to monitor when these partition ranges will fill up and when additional partitions will need to be added.  If you get to the final range partition and there are no additional range partitions all data will be included into the last partition. 

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  • Oracle Exadata X3 Launch Webcast

    - by Cinzia Mascanzoni
    Available on-demand, this webcast covers everything your partners need to know about Oracle’s next-generation database machine. They will learn how to improve performance by storing multiple databases in memory, lower power and cooling costs by 30%, and easily deploy a cloud-based database service. Exadata X3 combines massive memory and low-cost disks to deliver the highest performance at the lowest cost. Partners won’t want to miss this webcast. Invite them to watch today! View and share the replay.

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  • Configuring MySQL Cluster Data Nodes

    - by Mat Keep
    0 0 1 692 3948 Homework 32 9 4631 14.0 Normal 0 false false false EN-US JA 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-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} In my previous blog post, I discussed the enhanced performance and scalability delivered by extensions to the multi-threaded data nodes in MySQL Cluster 7.2. In this post, I’ll share best practices on the configuration of data nodes to achieve optimum performance on the latest generations of multi-core, multi-thread CPU designs. Configuring the Data Nodes The configuration of data node threads can be managed in two ways via the config.ini file: - Simply set MaxNoOfExecutionThreads to the appropriate number of threads to be run in the data node, based on the number of threads presented by the processors used in the host or VM. - Use the new ThreadConfig variable that enables users to configure both the number of each thread type to use and also which CPUs to bind them too. The flexible configuration afforded by the multi-threaded data node enhancements means that it is possible to optimise data nodes to use anything from a single CPU/thread up to a 48 CPU/thread server. Co-locating the MySQL Server with a single data node can fully utilize servers with 64 – 80 CPU/threads. It is also possible to co-locate multiple data nodes per server, but this is now only required for very large servers with 4+ CPU sockets dense multi-core processors. 24 Threads and Beyond! An example of how to make best use of a 24 CPU/thread server box is to configure the following: - 8 ldm threads - 4 tc threads - 3 recv threads - 3 send threads - 1 rep thread for asynchronous replication. Each of those threads should be bound to a CPU. It is possible to bind the main thread (schema management domain) and the IO threads to the same CPU in most installations. In the configuration above, we have bound threads to 20 different CPUs. We should also protect these 20 CPUs from interrupts by using the IRQBALANCE_BANNED_CPUS configuration variable in /etc/sysconfig/irqbalance and setting it to 0x0FFFFF. The reason for doing this is that MySQL Cluster generates a lot of interrupt and OS kernel processing, and so it is recommended to separate activity across CPUs to ensure conflicts with the MySQL Cluster threads are eliminated. When booting a Linux kernel it is also possible to provide an option isolcpus=0-19 in grub.conf. The result is that the Linux scheduler won't use these CPUs for any task. Only by using CPU affinity syscalls can a process be made to run on those CPUs. By using this approach, together with binding MySQL Cluster threads to specific CPUs and banning CPUs IRQ processing on these tasks, a very stable performance environment is created for a MySQL Cluster data node. On a 32 CPU/Thread server: - Increase the number of ldm threads to 12 - Increase tc threads to 6 - Provide 2 more CPUs for the OS and interrupts. - The number of send and receive threads should, in most cases, still be sufficient. On a 40 CPU/Thread server, increase ldm threads to 16, tc threads to 8 and increment send and receive threads to 4. On a 48 CPU/Thread server it is possible to optimize further by using: - 12 tc threads - 2 more CPUs for the OS and interrupts - Avoid using IO threads and main thread on same CPU - Add 1 more receive thread. Summary As both this and the previous post seek to demonstrate, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs. A big thanks to Mikael Ronstrom, Senior MySQL Architect at Oracle, for his work in developing these enhancements and best practices. You can download MySQL Cluster 7.2 today and try out all of these enhancements. The Getting Started guides are an invaluable aid to quickly building a Proof of Concept Don’t forget to check out the MySQL Cluster 7.2 New Features whitepaper to discover everything that is new in the latest GA release

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 13

    - by MarkPearl
    Learning Outcomes Explain the advantages of using a large number of registers Discuss the way in which compilers optimize register usage Discuss the evolution of CISC machines Describe the characteristics of RISC architecture Discuss the RISC vs. CISC controversy Describe the way in which RISC and CISC design principles can be combined Instruction Execution Characteristics To understand the the line of reasoning of RISC advocates, we need a brief overview of instruction execution characteristics. These include… Operations Operands Procedure Calls These three sections can be studied in depth in the textbook at pages 503 - 505 A number of groups have come up with the conclusion that the attempt to make the instruction set architecture closer to HLLs (High Level Languages) is not the most effective design strategy. Rather HLL’s can be best supported by optimizing performance of the most time-consuming features of typical HLL programs. Generally 3 main characteristics came up to improve performance… Use a large number of registers or use a compiler to optimize register usage Careful attention needs to be paid to the design of instruction pipelines A simplified (reduced) instruction set is indicated The use of a large register optimization One of the most important design principles of RISC machines is the use of a large number of registers. The concept of register windows and the use of a large register file versus the use of cache memory are discussed. On the face of it, the use of a large set of registers should decrease the need to access memory. The design task is to organize the registers in such a fashion that this goal is realized. Read page 507 – 510 for a detailed explanation. Compiler-based register optimization   Reduced Instructions Set Architecture There are two advantages to smaller programs… Because the program takes up less memory, there is a savings in that resource (this was more compelling when memory was more expensive) Smaller programs should improve performance, and this will happen in two ways – fewer instructions means fewer instruction bytes to be fetched and in a paging environment smaller programs occupy fewer pages, reducing page faults. Certain characteristics are common to RISC processors… One instruction per cycle Register-to-register operations Simple addressing modes Simple instruction formats RISC vs. CISC After initial enthusiasm for RISC machines, there has been a growing realization that RISC designs may benefit from the inclusion of some CISC features CISC designs may benefit from the inclusion of some RISC features

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  • My Oracle Support Accreditation for Database and Enterprise Manager

    - by A. G.
    Have you actively used My Oracle Support for 6-9 months? Take your expertise to the next level—become accredited! By completing the accreditation learning series, you can increase your proficiency with My Oracle Support’s core functions and build skills to help you leverage Oracle solutions, tools, and knowledge that enable productivity. Accreditation learning paths are available for Oracle Database and Enterprise Manager, which focus on product-specific best practices, recommendations, and tool enablement—up leveling your capabilities with these Oracle products. Course topics include:   Oracle Database Staying informed  Install Patching Upgrade Performance Security Scalability Enterprise Manager Staying informed  Supportability Certification Patching Upgrade Performance Diagnostic Tools Troubleshooting Visit the My Oracle Support Accreditation Index and get started with the Level 1 My Oracle Support Accreditation path and product-specific Level 2 learning paths for Oracle Database and Enterprise Manager.

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  • DOMDocument programming: a lot of little dilemmas, how to solve them?

    - by Peter Krauss
    I need elegance and performance: how to decide by the "best implementation" for each DOM algorithm that I face. This simple "DOMNodeList grouper" illustrate many little dilemmas: use iterator_to_array or "populate an array", when not all items need to be copied. use clone operator, cloneNode method or import method? use parentNode::method() or documentElement::method? (see here) first removeChild or first replaceChild, no avoids "side effects"? ... My position, today, is only "do an arbitrary choice and follow it in all implementations" (like a "Convention over configuration" principle)... But, there are another considerations? About performance, there are some article showing benchmarks? PS: this is a generic DOM question, any language (PHP, Javascript, Python, etc.) have the problem.

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  • New Development Snapshot

    I got a little side tracked by the investigation of the Google Collections test suite performance issue, reported by Albert Strasheim in the comments to the previous snapshot. This caused me to do some work on exception handling (unfortunately without any performance benefit to the Google Collections test suite) which, in turn, triggered something I've been wanting to do for while, namely to introduce a stub version of IKVM.OpenJDK.Core.dll which can...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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  • Counting product releases if you work on the backend/online services?

    - by stackoverflowuser2010
    I am trying to update my resume, and I would like to count the number of "product releases" that I was directly involved in with a company. It would seem to serve as a performance metric. The problem is that I was working on the backend of a very large distributed system, like along the lines of Hadoop or other huge database. We had regular 6-month major releases and other minor releases. My manager kept saying that "shipped" these releases, but "shipping" a product to me sounds like releasing single pieces of software, like Microsoft would ship Office 11 or something. Any ideas on "product releases" for backend service engineers, or any other type of performance metric?

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  • Automatic Statistics Update Slows Down SQL Server 2005

    I have a database which has several tables that have very heavy write operations. These table are very large and some are over a hundred gigabytes. I noticed performance of this database is getting slower and after some investigation we suspect that the Auto Update Statistics function is causing a performance degradation. Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

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  • On Comparing Tables in SQL Server

    How do you compare two SQL tables? Every SQL Developer or DBA knows the answer, which is 'it depends'. It is not just the size of the table or the type of data in it but what you want to achieve. Phil Factor sets about to cover the basics and point out some snags and advantages to the various techniques. FREE eBook – "45 Database Performance Tips for Developers"Improve your database performance with 45 tips from SQL Server MVPs and industry experts. Get the eBook here.

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  • Setting Up and Running Summary Advisor on an Exalytics Machine (Oracle-by-Example)

    - by Saresh
    If you are running Oracle BI on an Exalytics machine, you can use Summary Advisor to identify the aggregates that will increase query performance. Summary Advisor intelligently recommends an optimal list of aggregate tables based on query patterns that will achieve maximum query performance gain while meeting specific resource constraints. Summary Advisor then generates an aggregate creation script that can be run to create the recommended aggregate tables. Aggregate tables reduce query times by storing precomputed results for queries that include rolled-up data. This tutorial covers steps to set up, configure, and run Summary Advisor on an Exalytics machine using TimesTen database as a target for storing aggregates. You can find the Oracle By Example (OBE) in the Oracle Learning Library (OLL). The content in OLL is available to all customers, partners, and employees.

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  • Partner Webcast – Oracle Weblogic 12c for New Projects - 07 Nov 2013

    - by Roxana Babiciu
    Fast-growing organizations need to stay agile in the face of changing customer, business or market requirements.Oracle WebLogic Server 12c is the industry's best application server platform that allows you to quickly develop and deploy reliable, secure, scalable and manageable enterprise Java EE applications. WebLogic Server Java EE applications are based on standardized, modular components. WebLogic Server provides a complete set of services for those modules and handles many details of application behavior automatically, without requiring programming.New project applications are created by Java programmers, Web designers, and application assemblers. Programmers and designers create modules that implement the business and presentation logic for the application. Application assemblers assemble the modules into applications that are ready to deploy on WebLogic Server. Build and run high-performance enterprise applications and services with Oracle WebLogic Server 12c, available in three editions to meet the needs of traditional and cloud IT environments. Join us, in this webcast, as we will show you how WebLogic Server 12c helps you building and deploying enterprise Java EE applications with support for new features for lowering cost of operations, improving performance, enhancing scalability. Read more here

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  • What techniques can I use to render very large numbers of objects more efficiently in OpenGL?

    - by Luke
    You can think of my application as drawing a very large ball-and-stick diagram (or graph). At times, this graph can get very large, where the number of elements even outnumbers the pixels on the screen. Currently I am simply passing all of my textures (as GL_POINTS) and lines to the graphics card using VBO's. When the number of elements outnumbers the number of pixels, is this the most efficient way to do this? Or should I do some calculations on the CPU side before handing everything over to the GPU? If it matters, I do use GL_DEPTH_TEST and GL_ALPHA_TEST. I do some alpha blending, but probably not enough to make a huge performance difference. My scene can be static at times, but the user has control over a typical arc-ball camera and can pan, rotate, or zoom. It is during these operations that performance degradation is noticeable.

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  • Free ebook: Troubleshooting SQL Server: A Guide for the Accidental DBA

    We spend much of our working life helping solve SQL Server-related performance problems, hands-on, during consulting, or on online forums. We've seen a few weird-and-wonderful issues but, mainly, it’s the same problems and misconceptions time-and-again. This is our attempt to describe, diagnose, and solve the most common problems with SQL Server 2005, 2008, and 2008 R2. And it's free. "It really helped us isolate where we were experiencing a bottleneck"- John Q Martin, SQL Server DBA. Get started with SQL Monitor today to solve tricky performance problems - download a free trial

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