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  • Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

    - by Thanos Terentes Printzios
    In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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  • Performance Test and TCP tuning

    - by Mithir
    We are in the process of performance testing an application which receives tcp requests converts them to soap requests (WCF-httpBinding) which other services work on. The server is Windows Server 2008 R2. The TCP requests are received by TcpListener instance (.NET C#). There are 3 http-binded WCF services running on the same server. We have built a performance test client which goal is to simulate multiple concurrent requests(each request has to be different and recognizable by the application). We built a test running 150 requests that run on the same time (by 150 different threads), and we noticed straight away that some requests get the TCP connection slowly, but once they get it, they act fast. A single request writes twice on the same connection- request and an application ack. Although a single request+ack can take about 150ms, the 150 test takes about 7 seconds. The Problem When we try to run this test from 2 different computers we lose requests. some clients requests are getting no connection was made because the target machine actively refused it So I got here and got convinced it was because of the backlog. I changed the TcpListener parameters and did the registry AFD backlog changes written here but it still didn't work, so I inserted all of the TCP tuning suggested plus some netsh commands which were recommended, but still no change, we still get that error. Is there anything else I need to know? Are there any other solutions?

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  • SQL SERVER – What is Page Life Expectancy (PLE) Counter

    - by pinaldave
    During performance tuning consultation there are plenty of counters and values, I often come across. Today we will quickly talk about Page Life Expectancy counter, which is commonly known as PLE as well. You can find the value of the PLE by running following query. SELECT [object_name], [counter_name], [cntr_value] FROM sys.dm_os_performance_counters WHERE [object_name] LIKE '%Manager%' AND [counter_name] = 'Page life expectancy' The recommended value of the PLE counter is 300 seconds. I have seen on busy system this value to be as low as even 45 seconds and on unused system as high as 1250 seconds. Page Life Expectancy is number of seconds a page will stay in the buffer pool without references. In simple words, if your page stays longer in the buffer pool (area of the memory cache) your PLE is higher, leading to higher performance as every time request comes there are chances it may find its data in the cache itself instead of going to hard drive to read the data. Now check your system and post back what is this counter value for you during various time of the day. Is this counter any way relates to performance issues for your system? Note: There are various other counters which are important to discuss during the performance tuning and this counter is not everything. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL Profiler: Read/Write units

    - by Ian Boyd
    i've picked a query out of SQL Server Profiler that says it took 1,497 reads: EventClass: SQL:BatchCompleted TextData: SELECT Transactions.... CPU: 406 Reads: 1497 Writes: 0 Duration: 406 So i've taken this query into Query Analyzer, so i may try to reduce the number of reads. But when i turn on SET STATISTICS IO ON to see the IO activity for the query, i get nowhere close to one thousand reads: Table Scan Count Logical Reads =================== ========== ============= FintracTransactions 4 20 LCDs 2 4 LCTs 2 4 FintracTransacti... 0 0 Users 1 2 MALs 0 0 Patrons 0 0 Shifts 1 2 Cages 1 1 Windows 1 3 Logins 1 3 Sessions 1 6 Transactions 1 7 Which if i do my math right, there is a total of 51 reads; not 1,497. So i assume Reads in SQL Profiler is an arbitrary metric. Does anyone know the conversion of SQL Server Profiler Reads to IO Reads? See also SQL Profiler CPU / duration unit Query Analyzer VS. Query Profiler Reads, Writes, and Duration Discrepencies

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  • Logging library for (c++) games

    - by Klaim
    I know a lot of logging libraries but didn't test a lot of them. (GoogleLog, Pantheios, the coming boost::log library...) In games, especially in remote multiplayer and multithreaded games, logging is vital to debugging, even if you remove all logs in the end. Let's say I'm making a PC game (not console) that needs logs (multiplayer and multithreaded and/or multiprocess) and I have good reasons for looking for a library for logging (like, I don't have time or I'm not confident in my ability to write one correctly for my case). Assuming that I need : performance ease of use (allow streaming or formating or something like that) reliable (don't leak or crash!) cross-platform (at least Windows, MacOSX, Linux/Ubuntu) Wich logging library would you recommand? Currently, I think that boost::log is the most flexible one (you can even log to remotely!), but have not good performance update: is for high performance, but isn't released yet. Pantheios is often cited but I don't have comparison points on performance and usage. I've used my own lib for a long time but I know it don't manage multithreading so it's a big problem, even if it's fast enough. Google Log seems interesting, I just need to test it but if you already have compared those libs and more, your advice might be of good use. Games are often performance demanding while complex to debug so it would be good to know logging libraries that, in our specific case, have clear advantages.

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  • Free eBook with SQL Server performance tips and nuggets

    - by Claire Brooking
    I’ve often found that the kind of tips that turn out to be helpful are the ones that encourage me to make a small step outside of a routine. No dramatic changes – just a quick suggestion that changes an approach. As a languages student at university, one of the best I spotted came from outside the lecture halls and ended up saving me time (and lots of huffing and puffing) – the use of a rainbow of sticky notes for well-used pages and letter categories in my dictionary. Simple, but armed with a heavy dictionary that could double up as a step stool, those markers were surprisingly handy. When the Simple-Talk editors told me about a book they were planning that would give a series of tips for developers on how to improve database performance, we all agreed it needed to contain a good range of pointers for big-hitter performance topics. But we wanted to include some of the smaller, time-saving nuggets too. We hope we’ve struck a good balance. The 45 Database Performance Tips eBook covers different tips to help you avoid code that saps performance, whether that’s the ‘gotchas’ to be aware of when using Object to Relational Mapping (ORM) tools, or what to be aware of for indexes, database design, and T-SQL. The eBook is also available to download with SQL Prompt from Red Gate. We often hear that it’s the productivity-boosting side of SQL Prompt that makes it useful for everyday coding. So when a member of the SQL Prompt team mentioned an idea to make the most of tab history, a new feature in SQL Prompt 6 for SQL Server Management Studio, we were intrigued. Now SQL Prompt can save tabs we have been working on in SSMS as a way to maintain an active template for queries we often recycle. When we need to reuse the same code again, we search for our saved tab (and we can also customize its name to speed up the search) to get started. We hope you find the eBook helpful, and as always on Simple-Talk, we’d love to hear from you too. If you have a performance tip for SQL Server you’d like to share, email Melanie on the Simple-Talk team ([email protected]) and we’ll publish a collection in a follow-up post.

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  • When is assembler faster than C?

    - by Adam Bellaire
    One of the stated reasons for knowing assembler is that, on occasion, it can be employed to write code that will be more performant than writing that code in a higher-level language, C in particular. However, I've also heard it stated many times that although that's not entirely false, the cases where assembler can actually be used to generate more performant code are both extremely rare and require expert knowledge of and experience with assembler. This question doesn't even get into the fact that assembler instructions will be machine-specific and non-portable, or any of the other aspects of assembler. There are plenty of good reasons for knowing assembler besides this one, of course, but this is meant to be a specific question soliciting examples and data, not an extended discourse on assembler versus higher-level languages. Can anyone provide some specific examples of cases where assembler will be faster than well-written C code using a modern compiler, and can you support that claim with profiling evidence? I am pretty confident these cases exist, but I really want to know exactly how esoteric these cases are, since it seems to be a point of some contention.

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario   Conventional Structures   Columnstore   Δ SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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  • NSMutableArray Vs Stack

    - by Chandan Shetty SP
    I am developing 2D game for iphone in Objectice-C.In this project I need to use stack, I can do it using STL(Standard template library) stacks or NSMutableArray, since this stack is widely used in the game which one is more efficient? @interface CarElement : NSObject { std::stack<myElement*> *mBats; } or @interface CarElement : NSObject { NSMutableArray *mBats; } Thanks,

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  • Mysql 100% CPU + Slow query

    - by felipeclopes
    I'm using the RDS database from amazon with a some very big tables, and yesterday I started to face 100% CPU utilisation on the server and a bunch of slow query logs that were not happening before. I tried to check the queries that were running and faced this result from the explain command +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | businesses | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index; Using temporary; Using filesort | | 1 | SIMPLE | activities_businesses | ref | PRIMARY,index_activities_users_on_business_id,index_tweets_users_on_tweet_id_and_business_id | index_activities_users_on_business_id | 9 | const | 2252 | Using index condition; Using where | | 1 | SIMPLE | activities_b_taggings_975e9c4 | ref | taggings_idx | taggings_idx | 782 | const,myapp_production.activities_businesses.id,const | 1 | Using index condition; Using where | | 1 | SIMPLE | activities | eq_ref | PRIMARY,index_activities_on_created_at | PRIMARY | 8 | myapp_production.activities_businesses.activity_id | 1 | Using where | +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ Also checkin in the process list, I got something like this: +----+-----------------+-------------------------------------+----------------------------+---------+------+--------------+------------------------------------------------------------------------------------------------------+ | Id | User | Host | db | Command | Time | State | Info | +----+-----------------+-------------------------------------+----------------------------+---------+------+--------------+------------------------------------------------------------------------------------------------------+ | 1 | my_app | my_ip:57152 | my_app_production | Sleep | 0 | | NULL | | 2 | my_app | my_ip:57153 | my_app_production | Sleep | 2 | | NULL | | 3 | rdsadmin | localhost:49441 | NULL | Sleep | 9 | | NULL | | 6 | my_app | my_other_ip:47802 | my_app_production | Sleep | 242 | | NULL | | 7 | my_app | my_other_ip:47807 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 8 | my_app | my_other_ip:47809 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 9 | my_app | my_other_ip:47810 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 10 | my_app | my_other_ip:47811 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 11 | my_app | my_other_ip:47813 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | ... So based on the numbers, it looks like there is no reason to have a slow query, since the worst execution plan is the one that goes through 2k rows which is not much. Edit 1 Another information that might be useful is the slow query_log SET timestamp=1401457485; SELECT my_query... # User@Host: myapp[myapp] @ ip-10-195-55-233.ec2.internal [IP] Id: 435 # Query_time: 95.830497 Lock_time: 0.000178 Rows_sent: 0 Rows_examined: 1129387 Edit 2 After profiling, I got this result. The result have approximately 250 rows with two columns each. +----------------------+----------+ | state | duration | +----------------------+----------+ | Sending data | 272 | | removing tmp table | 0 | | optimizing | 0 | | Creating sort index | 0 | | init | 0 | | cleaning up | 0 | | executing | 0 | | checking permissions | 0 | | freeing items | 0 | | Creating tmp table | 0 | | query end | 0 | | statistics | 0 | | end | 0 | | System lock | 0 | | Opening tables | 0 | | logging slow query | 0 | | Sorting result | 0 | | starting | 0 | | closing tables | 0 | | preparing | 0 | +----------------------+----------+ Edit 3 Adding query as requested SELECT activities.share_count, activities.created_at FROM `activities_businesses` INNER JOIN `businesses` ON `businesses`.`id` = `activities_businesses`.`business_id` INNER JOIN `activities` ON `activities`.`id` = `activities_businesses`.`activity_id` JOIN taggings activities_b_taggings_975e9c4 ON activities_b_taggings_975e9c4.taggable_id = activities_businesses.id AND activities_b_taggings_975e9c4.taggable_type = 'ActivitiesBusiness' AND activities_b_taggings_975e9c4.tag_id = 104 AND activities_b_taggings_975e9c4.created_at >= '2014-04-30 13:36:44' WHERE ( businesses.id = 1 ) AND ( activities.created_at > '2014-04-30 13:36:44' ) AND ( activities.created_at < '2014-05-30 12:27:03' ) ORDER BY activities.created_at; Edit 4 There may be a chance that the indexes are not being applied due to difference in column type between the taggings and the activities_businesses, on the taggable_id column. mysql> SHOW COLUMNS FROM activities_businesses; +-------------+------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | activity_id | bigint(20) | YES | MUL | NULL | | | business_id | bigint(20) | YES | MUL | NULL | | +-------------+------------+------+-----+---------+----------------+ 3 rows in set (0.01 sec) mysql> SHOW COLUMNS FROM taggings; +---------------+--------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+--------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | tag_id | int(11) | YES | MUL | NULL | | | taggable_id | bigint(20) | YES | | NULL | | | taggable_type | varchar(255) | YES | | NULL | | | tagger_id | int(11) | YES | | NULL | | | tagger_type | varchar(255) | YES | | NULL | | | context | varchar(128) | YES | | NULL | | | created_at | datetime | YES | | NULL | | +---------------+--------------+------+-----+---------+----------------+ So it is examining way more rows than it shows in the explain query, probably because some indexes are not being applied. Do you guys can help m with that?

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  • Divide and conquer method to compute roots [SOLVED]

    - by hellsoul153
    Hello, Knowing that we can use Divide-and-Conquer algorithm to compute large exponents, for exemple 2 exp 100 = 2 exp(50) * 2 exp(50), which is quite more efficient, is this method efficient using roots ? For exemple 2 exp (1/100) = (2 exp(1/50)) exp(1/50) ? In other words, I'm wondering if (n exp(1/x)) is more efficient to (n exp(1/y)) for x < y and where x and y are integers.

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  • Improving the performance of JDeveloper11g (part 2) and JVMs in general

    - by asantaga
    Just received an email from one of our JVM developers who read my blog entry on Performance tuning JDeveloper11g and he's confirmed that all of the above parameters are totally supported :-) He's also provided a description of the parameters so we can learn what magic is actually being applied. - -XX:+AggressiveOpts -- this enables the latest and greatest JVM optimizations. It will likely help most Java applications. It's fully supported. The downside of it is that because it has the latest and greatest optimizations, there is some small probability that it may not offer as good of an experience. As those features enabled with this command line option have "matured", they are made the default in a future JDK release. So, you can think of this command line option as the place where the newest optimizations get introduced. Some time later they are moved out from under AggressiveOpts to become default behavior. -XX:+OptimizeStringConcat -- only works with the -server JVM. It may be enabled by the default in a future JDK 7 update release. This option delays the construction of a StringBuilder/StringBuffer and attempts to avoid re-sizing the underlying char[] by attempting to detect the size of the char[] to allocate based on what's being appended to the StringBuilder/StringBuffer. -XX:+UseStringCache -- I would not suggest using this unless you knew that JDeveloper allocated the same string over and over again. And, the string that's allocated over and over again is one of the first 100,000 allocated strings. In short, I'd recommend against using it. And, in fact, in Java 7 (currently) does not include this feature. -XX:+UseCompressedOops -- applicable to 64-bit JVMs. And, if you're using a 64-bit JVM, I'd suggest you use it. It's auto enabled in JDK 7 64-bit JVMs and later JDK 6 64-bit JVMs enable it by default too. -XX:+UseGCOverheadLimit -- by default this option is already enabled. One other command line option to consider is -XX:+TieredCompilation for a JDK 6 Update 25 or later, or JDK 7. This gives you the startup of a -client JVM and the peak performance of a -server JVM. Awesome-ness!  Finally, Charlies also pointed out to me a "new" book he's just published where he goes into the details of JVM tuning, a must for all Fusion Middleware tuning exercises..  (click the book)  Thanks Charlie!

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  • What driver for nVIDIA GeForce MX440?

    - by ubufan
    I have recently installed (clean install) Ubuntu 12.10 on a desktop PC with nVIDIA GeForce MX440 (AGP 8x) and I have problems with Unity. Although I can see the desktop, however i can't see unity bar and icons. So, I decided to install lubuntu-desktop to see the performance. And yes! I choose lubuntu-desktop from Log On screen and the performance is definetely much better and has nothing to do with the aforementioned on unity. The system has native drivers from the Ubuntu installation. I didn't touch anything in xorg configuration. I also remember that I have managed to have the best performance with this graphic card on my previous Ubuntu 9.10 system, by editing some values in /etc/X11/xorg.conf file. But I can't remember that options, because I formatted the / partition! My question is: Which is the most suitable driver for this card, in order to load the unity feature and have better performance on it?

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  • What is the most efficient way to handle points / small vectors in JavaScript?

    - by Chris
    Currently I'm creating an web based (= JavaScript) application thata is using a lot of "points" (= small, fixed size vectors). There are basically two obvious ways of representing them: var pointA = [ xValue, yValue ]; and var pointB = { x: xValue, y: yValue }; So translating my point a bit would look like: var pointAtrans = [ pointA[0] + 3, pointA[1] + 4 ]; var pointBtrans = { x: pointB.x + 3, pointB.y + 4 }; Both are easy to handle from a programmer point of view (the object variant is a bit more readable, especially as I'm mostly dealing with 2D data, seldom with 3D and hardly with 4D - but never more. It'll allways fit into x,y,z and w) But my question is now: What is the most efficient way from the language perspective - theoretically and in real implementations? What are the memory requirements? What are the setup costs of an array vs. an object? ... My target browsers are FireFox and the Webkit based ones (Chromium, Safari), but it wouldn't hurt to have a great (= fast) experience under IE and Opera as well...

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  • Hardware Requirements & Tuning - Flash Media Server 3.5 Interactive

    - by Anthony Kanago
    I am trying to spec out a server to purchase (physically, not rented from someone like softlayer.com) to run an intranet instace of Flash Media Server 3.5 Interactive. In general, the server will likely be fielding somewhere on the order of 400 connections at a time at the upper limit. Of course, should this increase, we don't want to be stuck. While the decision is not final, we will likely be running the server on Red Hat rather than Windows. The server will be run on gigabit ethernet. I have two related questions: What sort of hardware would I need realistically to support this? What advice can you offer for settings in tuning FMS/the OS to be performant to this level? We are looking for a bare minimum that will run this effectively to save on costs. Realistically, the average number of connections will be fairly low (50-150) by comparison with that upper limit estimate. To reiterate: we just want to be cautious in not getting caught when we need more power, but we also need a low-cost solution (doesn't everyone?) and that may take priority. Windows and RedHat are the two officially supported operating systems. Since FMS is stated to be 32-bit only, I'm sticking with a 32-bit OS. The hardware requirements listed by Adobe on their website are: 3.2GHz Intel® Pentium® 4 processor (dual Intel Xeon® or faster recommended) 2GB of RAM (4GB recommended) 1Gb Ethernet card So what realistically do I need for those sorts of connection numbers, and what can I due to tune things up to get more out of less hardware? Thanks!

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  • How to test web application performance from other continent?

    - by Thomas Einwaller
    We are hosting our web application http://timr.com on a server located in Germany. The server handles a high load of traffic very well and everything works as desired in terms of performance and load times. However we sometimes get complaints from our overseas users (US, South America) that the experience slow page loading times. What would be the best way to test the performance of a web application "as if you are on another continent"? I want to make sure that the distance between the server and the user is no problem?

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  • MacBook Pro for Windows development via virtualization. Performance?

    - by webworm
    I am a Windows/Web developer by profession and I have been considering a MacBook Pro as a replacement for my current development machine. I am impressed by the build quality, the uni-body construction and performance specs of the MacBook Pro. I am specifically interested in the 13.3" MacBook Pro running Core 2 Duo 2.4 GHz processor with 4 GB RAM. What I am wondering is this ... what performance can I expect running SQL Server 2008, IIS, and Visual Studio 2010 within a virtual environment (VMWare Fusion and Windows 7) on the above mentioned MacBook Pro? I like the 13.3" model as the size is more portable, but am I expecting to much from a core 2 duo processor? Would I need to look at the next step up in MacBook Pro using the core i5 processor? Thanks!

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  • Terrible Performance with SATA Drives on Dell PowerEdge, steps to troubleshoot?

    - by Tom
    I had asked this question earlier and the question went missing so here it is again. Bought a DELL Poweredge 2950 to use as in-house QA Server. Disk performance is beyond terrible, 1000-4000 ms response time on the drive with our SQL Server database .mdf. Sql Server disk queue upwards of 300 at times. I'm a software guy, can anyone help me with steps to determine the issue? I don't know what RAID controller it has, how can I determine that? I'm speculating it could be BIOS issue. Perhaps the server used to have another kind of drive in it and when I added SATA the ??? buffer size is wrong??? Perhaps I chose wrong options (chose defaults) when setting up the RAID 1 arrays? I thought RAID 1 was a performance array?

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  • How to partition a 1 TB drive for performance on a windows development machine?

    - by dip
    I saw a similar question for linux, but nothing for windows. I'm getting a new 1TB drive for my dev box @ work. The OS will be Windows 7 Pro with 8GB of RAM and just the single 1TB drive. Backups are not a concern, and I won't be storing large multimedia files. I want the fastest possible performance for general windows usage and for compilation. I will defrag nightly with a smart defragger liker perfectdisk. Should I just go with a single partition, or is there some way I can lay things out for the best performance?

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  • Tuning up a MySQL server

    - by NinjaCat
    I inherited a mysql server, and so I've started with running the MySQLTuner.pl script. I am not a MySQL expert but I can see that there is definitely a mess here. I'm not looking to go after every single thing that needs fixing and tuning, but I do want to grab the major, low hanging fruit. Total Memory on the system is: 512MB. Yes, I know it's low, but it's what we have for the time being. Here's what the script had to say: General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries When making adjustments, make tmp_table_size/max_heap_table_size equal Reduce your SELECT DISTINCT queries without LIMIT clauses Increase table_cache gradually to avoid file descriptor limits Your applications are not closing MySQL connections properly Variables to adjust: query_cache_limit (> 1M, or use smaller result sets) tmp_table_size (> 16M) max_heap_table_size (> 16M) table_cache (> 64) innodb_buffer_pool_size (>= 326M) For the variables that it recommends that I adjust, I don't even see most of them in the mysql.cnf file. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] innodb_buffer_pool_size = 220M innodb_flush_log_at_trx_commit = 2 innodb_file_per_table = 1 innodb_thread_concurrency = 32 skip-locking big-tables max_connections = 50 innodb_lock_wait_timeout = 600 slave_transaction_retries = 10 innodb_table_locks = 0 innodb_additional_mem_pool_size = 20M user = mysql socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp skip-external-locking bind-address = localhost key_buffer = 16M max_allowed_packet = 16M thread_stack = 192K thread_cache_size = 4 myisam-recover = BACKUP query_cache_limit = 1M query_cache_size = 16M log_error = /var/log/mysql/error.log expire_logs_days = 10 max_binlog_size = 100M skip-locking innodb_file_per_table = 1 big-tables [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] [isamchk] key_buffer = 16M !includedir /etc/mysql/conf.d/

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  • Does a dedicated video card improve HTML5 websites, Skype or Flash games performance?

    - by Kiewic
    I have read that having a dedicated video card (GPU) improves performance if you use your computer to play video games. I guess to make this happen, video games or apps must be using especial libraries designed to share the workload with the GPU, maybe Direct X or OpenGL, I don't know. Am I wrong? So, can HTML5 websites, Adobe Illustrator, Flash games (Zynga games), Skype or Netflix benefit from a dedicated video card? I usually do the previous activities simultaneously. Should I consider changing from an integrated video card to a dedicated card if I want to improve performance? Thanks.

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  • Troubleshooting High-CPU Utilization for SQL Server

    - by Susantha Bathige
    The objective of this FAQ is to outline the basic steps in troubleshooting high CPU utilization on  a server hosting a SQL Server instance. The first and the most common step if you suspect high CPU utilization (or are alerted for it) is to login to the physical server and check the Windows Task Manager. The Performance tab will show the high utilization as shown below: Next, we need to determine which process is responsible for the high CPU consumption. The Processes tab of the Task Manager will show this information: Note that to see all processes you should select Show processes from all user. In this case, SQL Server (sqlserver.exe) is consuming 99% of the CPU (a normal benchmark for max CPU utilization is about 50-60%). Next we examine the scheduler data. Scheduler is a component of SQLOS which evenly distributes load amongst CPUs. The query below returns the important columns for CPU troubleshooting. Note – if your server is under severe stress and you are unable to login to SSMS, you can use another machine’s SSMS to login to the server through DAC – Dedicated Administrator Connection (see http://msdn.microsoft.com/en-us/library/ms189595.aspx for details on using DAC) SELECT scheduler_id ,cpu_id ,status ,runnable_tasks_count ,active_workers_count ,load_factor ,yield_count FROM sys.dm_os_schedulers WHERE scheduler_id See below for the BOL definitions for the above columns. scheduler_id – ID of the scheduler. All schedulers that are used to run regular queries have ID numbers less than 1048576. Those schedulers that have IDs greater than or equal to 1048576 are used internally by SQL Server, such as the dedicated administrator connection scheduler. cpu_id – ID of the CPU with which this scheduler is associated. status – Indicates the status of the scheduler. runnable_tasks_count – Number of workers, with tasks assigned to them that are waiting to be scheduled on the runnable queue. active_workers_count – Number of workers that are active. An active worker is never preemptive, must have an associated task, and is either running, runnable, or suspended. current_tasks_count - Number of current tasks that are associated with this scheduler. load_factor – Internal value that indicates the perceived load on this scheduler. yield_count – Internal value that is used to indicate progress on this scheduler.                                                                 Now to interpret the above data. There are four schedulers and each assigned to a different CPU. All the CPUs are ready to accept user queries as they all are ONLINE. There are 294 active tasks in the output as per the current_tasks_count column. This count indicates how many activities currently associated with the schedulers. When a  task is complete, this number is decremented. The 294 is quite a high figure and indicates all four schedulers are extremely busy. When a task is enqueued, the load_factor  value is incremented. This value is used to determine whether a new task should be put on this scheduler or another scheduler. The new task will be allocated to less loaded scheduler by SQLOS. The very high value of this column indicates all the schedulers have a high load. There are 268 runnable tasks which mean all these tasks are assigned a worker and waiting to be scheduled on the runnable queue.   The next step is  to identify which queries are demanding a lot of CPU time. The below query is useful for this purpose (note, in its current form,  it only shows the top 10 records). SELECT TOP 10 st.text  ,st.dbid  ,st.objectid  ,qs.total_worker_time  ,qs.last_worker_time  ,qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) st CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC This query as total_worker_time as the measure of CPU load and is in descending order of the  total_worker_time to show the most expensive queries and their plans at the top:      Note the BOL definitions for the important columns: total_worker_time - Total amount of CPU time, in microseconds, that was consumed by executions of this plan since it was compiled. last_worker_time - CPU time, in microseconds, that was consumed the last time the plan was executed.   I re-ran the same query again after few seconds and was returned the below output. After few seconds the SP dbo.TestProc1 is shown in fourth place and once again the last_worker_time is the highest. This means the procedure TestProc1 consumes a CPU time continuously each time it executes.      In this case, the primary cause for high CPU utilization was a stored procedure. You can view the execution plan by clicking on query_plan column to investigate why this is causing a high CPU load. I have used SQL Server 2008 (SP1) to test all the queries used in this article.

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