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  • MS SQL Query Sum of subquery

    - by San
    Hello , I need a help i getting following output from the query . SELECT ARG_CONSUMER, cast(ARG_TOTALAMT as float)/100 AS 'Total', (SELECT SUM(cast(DAMT as float))/100 FROM DEBT WHERE DDATE >= ARG.ARG_ORIGDATE AND DDATE <= ARG.ARG_LASTPAYDATE AND DTYPE IN ('CSH','CNTP','DDR','NBP') AND DCONSUMER = ARG.ARG_CONSUMER ) AS 'Paid' FROM ARGMASTER ARG WHERE ARG_STATUS = '1' Current output is a list of all records... But what i want to achieve here is count of arg consumers Total of ARG_TOTALAMT total of that subquery PAID difference between PAID & Total amount. I am able to achieve first two i.e. count of consumers & total of ARG _ TOTALAMT... but i am confused about sum of of ...i.e. sum (SELECT SUM(cast(DAMT as float))/100 FROM DEBT WHERE DDATE >= ARG.ARG_ORIGDATE AND DDATE <= ARG.ARG_LASTPAYDATE AND DTYPE IN ('CSH','CNTP','DDR','NBP') AND DCONSUMER = ARG.ARG_CONSUMER) AS 'Paid' Please advice

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  • C# performance analysis- how to count CPU cycles?

    - by Lirik
    Is this a valid way to do performance analysis? I want to get nanosecond accuracy and determine the performance of typecasting: class PerformanceTest { static double last = 0.0; static List<object> numericGenericData = new List<object>(); static List<double> numericTypedData = new List<double>(); static void Main(string[] args) { double totalWithCasting = 0.0; double totalWithoutCasting = 0.0; for (double d = 0.0; d < 1000000.0; ++d) { numericGenericData.Add(d); numericTypedData.Add(d); } Stopwatch stopwatch = new Stopwatch(); for (int i = 0; i < 10; ++i) { stopwatch.Start(); testWithTypecasting(); stopwatch.Stop(); totalWithCasting += stopwatch.ElapsedTicks; stopwatch.Start(); testWithoutTypeCasting(); stopwatch.Stop(); totalWithoutCasting += stopwatch.ElapsedTicks; } Console.WriteLine("Avg with typecasting = {0}", (totalWithCasting/10)); Console.WriteLine("Avg without typecasting = {0}", (totalWithoutCasting/10)); Console.ReadKey(); } static void testWithTypecasting() { foreach (object o in numericGenericData) { last = ((double)o*(double)o)/200; } } static void testWithoutTypeCasting() { foreach (double d in numericTypedData) { last = (d * d)/200; } } } The output is: Avg with typecasting = 468872.3 Avg without typecasting = 501157.9 I'm a little suspicious... it looks like there is nearly no impact on the performance. Is casting really that cheap?

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  • Poor Ruby on Rails performance when using nested :include

    - by Jeremiah Peschka
    I have three models that look something like this: class Bucket < ActiveRecord::Base has_many :entries end class Entry < ActiveRecord::Base belongs_to :submission belongs_to :bucket end class Submission < ActiveRecord::Base has_many :entries belongs_to :user end class User < ActiveRecord::Base has_many :submissions end When I retrieve a collection of entries doing something like: @entries = Entry.find(:all, :conditions => ['entries.bucket_id = ?', @bucket], :include => :submission) The performance is pretty quick although I get a large number of extra queries because the view uses the Submission.user object. However, if I add the user to the :include statement, the performance becomes terrible and it takes over a minute to return a total of 50 entries and submissions spread across 5 users. When I run the associated SQL commands, they complete in well under a second. @entries = Entry.find(:all, :conditions => ['entries.bucket_id = ?', @bucket], :include => {:submission => :user}) Why would this second command have such terrible performance compared to the first?

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  • best way to set up a VM for development (regarding performance)

    - by raticulin
    I am trying to set up a clean vm I will use in many of my devs. Hopefully I will use it many times and for a long time, so I want to get it right and set it up so performance is as good as possible. I have searched for a list of things to do, but strangely found only older posts, and none here. My requirements are: My host is Vista 32b, and guest is Windows2008 64b, using Vmware Workstation. The VM should also be able to run on a Vmware ESX I cannot move to other products (VirtualBox etc), but info about performance of each one is welcomed for reference. Anyway I guess most advices would apply to other OSs and other VM products. I need network connectivity to my LAN Guest will run many java processes, a DB and perform lots of file I/O What I have found so far is: HOWTO: Squeeze Every Last Drop of Performance Out of Your Virtual PCs: it's and old post, and about Virtual PC, but I guess most things still apply (and also apply to vmware). I guess it makes a difference to disable all unnecessary services, but the ones mentioned in 1 seem like too few, I specifically always disable Windows Search. Any other service I should disable?

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  • Rails performance tests "rake test:benchmark" and "rake test:profile" give me errors

    - by go minimal
    I'm trying to run a blank default performance test with Ruby 1.9 and Rails 2.3.5 and I just can't get it to work! What am I missing here??? rails testapp cd testapp script/generate scaffold User name:string rake db:migrate rake test:benchmark - /usr/local/bin/ruby19 -I"lib:test" "/usr/local/lib/ruby19/gems/1.9.1/gems/rake-0.8.7/lib/rake/rake_test_loader.rb" "test/performance/browsing_test.rb" -- --benchmark Loaded suite /usr/local/lib/ruby19/gems/1.9.1/gems/rake-0.8.7/lib/rake/rake_test_loader Started /usr/local/lib/ruby19/gems/1.9.1/gems/activesupport-2.3.5/lib/active_support/dependencies.rb:105:in `rescue in const_missing': uninitialized constant BrowsingTest::STARTED (NameError) from /usr/local/lib/ruby19/gems/1.9.1/gems/activesupport-2.3.5/lib/active_support/dependencies.rb:94:in `const_missing' from /usr/local/lib/ruby19/gems/1.9.1/gems/activesupport-2.3.5/lib/active_support/testing/performance.rb:38:in `run' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:415:in `block (2 levels) in run_test_suites' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:409:in `each' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:409:in `block in run_test_suites' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:408:in `each' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:408:in `run_test_suites' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:388:in `run' from /usr/local/lib/ruby19/1.9.1/minitest/unit.rb:329:in `block in autorun' rake aborted! Command failed with status (1): [/usr/local/bin/ruby19 -I"lib:test" "/usr/l...]

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  • Java Performance measurement

    - by portoalet
    Hi, I am doing some Java performance comparison between my classes, and wondering if there is some sort of Java Performance Framework to make writing performance measurement code easier? I.e, what I am doing now is trying to measure what effect does it have having a method as "synchronized" as in PseudoRandomUsingSynch.nextInt() compared to using an AtomicInteger as my "synchronizer". So I am trying to measure how long it takes to generate random integers using 3 threads accessing a synchronized method looping for say 10000 times. I am sure there is a much better way doing this. Can you please enlighten me? :) public static void main( String [] args ) throws InterruptedException, ExecutionException { PseudoRandomUsingSynch rand1 = new PseudoRandomUsingSynch((int)System.currentTimeMillis()); int n = 3; ExecutorService execService = Executors.newFixedThreadPool(n); long timeBefore = System.currentTimeMillis(); for(int idx=0; idx<100000; ++idx) { Future<Integer> future = execService.submit(rand1); Future<Integer> future1 = execService.submit(rand1); Future<Integer> future2 = execService.submit(rand1); int random1 = future.get(); int random2 = future1.get(); int random3 = future2.get(); } long timeAfter = System.currentTimeMillis(); long elapsed = timeAfter - timeBefore; out.println("elapsed:" + elapsed); } the class public class PseudoRandomUsingSynch implements Callable<Integer> { private int seed; public PseudoRandomUsingSynch(int s) { seed = s; } public synchronized int nextInt(int n) { byte [] s = DonsUtil.intToByteArray(seed); SecureRandom secureRandom = new SecureRandom(s); return ( secureRandom.nextInt() % n ); } @Override public Integer call() throws Exception { return nextInt((int)System.currentTimeMillis()); } } Regards

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  • Java performance issue

    - by Colby77
    Hi, I've got a question related to java performance and method execution. In my app there are a lot of place where I have to validate some parameter, so I've written a Validator class and put all the validation methods into it. Here is an example: public class NumberValidator { public static short shortValidator(String s) throws ValidationException{ try{ short sh = Short.parseShort(s); if(sh < 1){ throw new ValidationException(); } return sh; }catch (Exception e) { throw new ValidationException("The parameter is wrong!"); } } ... But I'm thinking about that. Is this OK? It's OO and modularized, but - considering performance - is it a good idea? What if I had awful lot of invocation at the same time? The snippet above is short and fast, but there are some methods that take more time. What happens when there are a lot of calling to a static method or an instance method in the same class and the method is not synchronized? All the calling methods have to fall in line and the JVM executes them sequentially? Is it a good idea to have some class that are identical to the above-mentioned and randomly call their identical methods? I think it is not, because "Don't repeat yourself " and "Duplication is Evil" etc. But what about performance? Thanks is advance.

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  • Need guidelines for optimizing WebGL performance by minimizing shader changes

    - by brainjam
    I'm trying to get an idea of the practicality of WebGL for rendering large architectural interior scenes, consisting of 100K's of triangles. These triangles are distributed over many objects, and there are many materials in the scene. On the other hand, there are no moving parts. And the materials tend to be fairly simple, mostly based on texture maps. There is a lot of texture map sharing .. for example all the chairs in scene will share a common map. There is also some multitexturing - up to three textures overlaid in a material. I've been doing a little experimentation and reading, and gather that frequently switching materials during a rendering pass will slow things down. For example, a scene with 200K triangles will have significant performance differences, depending on whether there are 10 or 1000 objects, assuming that each time an object is displayed a new material is set up. So it seems that if performance is important the scene should be sorted by materials so as to minimize material switching. What I'm looking for is guidelines on how to think of the overhead of various state changes, and where do I get the biggest bang for the buck. For example, what are the relative performance costs of, say, gl.useProgram(), gl.uniformMatrix4fv(), gl.drawElements() should I try to write ubershaders to minimize shader switching? should I try to aggregate geometry to minimize the number of gl.drawElements() calls I realize that mileage may vary depending on browser, OS, and graphics hardware. And I'm also not looking for heroic measures. Just some guidelines from people who have already had some experience in making scenes fast. I'll add that while I've had some experience with fixed-pipeline OpenGL programming in the past, I'm rather new to the WebGL/OpenGL ES 2.0 way of doing things.

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  • Improving I/O performance in C++ programs[external merge sort]

    - by Ajay
    I am currently working on a project involving external merge-sort using replacement-selection and k-way merge. I have implemented the project in C++[runs on linux]. Its very simple and right now deals with only fixed sized records. For reading & writing I use (i/o)fstream classes. After executing the program for few iterations, I noticed that I/O read blocks for requests of size more than 4K(typical block size). Infact giving buffer sizes greater than 4K causes performance to decrease. The output operations does not seem to need buffering, linux seemed to take care of buffering output. So I issue a write(record) instead of maintaining special buffer of writes and then flushing them out at once using write(records[]). But the performance of the application does not seem to be great. How could I improve the performance? Should I maintain special I/O threads to take care of reading blocks or are there existing C++ classes providing this abstraction already?(Something like BufferedInputStream in java)

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  • Essbase Analytics Link (EAL) - Performance of some operation of EAL could be improved by tuning of EAL Data Synchronization Server (DSS) parameters

    - by Ahmed Awan
    Generally, performance of some operation of EAL (Essbase Analytics Link) could be improved by tuning of EAL Data Synchronization Server (DSS) parameters. a. Expected that DSS machine will be 64-bit machine with 4-8 cores and 5-8 GB of RAM dedicated to DSS. b. To change DSS configuration - open EAL Configuration Tool on DSS machine.     ->Next:     and define: "Job Units" as <Number of Cores dedicated to DSS> * 1.5 "Max Memory Size" (if this is 64-bit machine) - ~1G for each Job Unit. If DSS machine is 32-bit - max memory size is 2600 MB. "Data Store Size" - depends on number of bridges and volume of HFM applications, but in most cases 50000 MB is enough. This volume should be available in defined "Data Store Dir" driver.   Continue with configuration and finish it. After that, DSS should be restarted to take new definitions.  

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  • Why is Python used for high-performance/scientific computing (but Ruby isn't)?

    - by Cyclops
    There's a quote from a PyCon 2011 talk that goes: At least in our shop (Argonne National Laboratory) we have three accepted languages for scientific computing. In this order they are C/C++, Fortran in all its dialects, and Python. You’ll notice the absolute and total lack of Ruby, Perl, Java. It was in the more general context of high-performance computing. Granted the quote is only from one shop, but another question about languages for HPC, also lists Python as one to learn (and not Ruby). Now, I can understand C/C++ and Fortran being used in that problem-space (and Perl/Java not being used). But I'm surprised that there would be a major difference in Python and Ruby use for HPC, given that they are fairly similar. (Note - I'm a fan of Python, but have nothing against Ruby). Is there some specific reason why the one language took off? Is it about the libraries available? Some specific language features? The community? Or maybe just historical contigency, and it could have gone the other way?

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  • Information about rendering, batches, the graphical card, performance etc. + XNA?

    - by Aidiakapi
    I know the title is a bit vague but it's hard to describe what I'm really looking for, but here goes. When it comes to CPU rendering, performance is mostly easy to estimate and straightforward, but when it comes to the GPU due to my lack of technical background information, I'm clueless. I'm using XNA so it'd be nice if theory could be related to that. So what I actually wanna know is, what happens when and where (CPU/GPU) when you do specific draw actions? What is a batch? What influence do effects, projections etc have? Is data persisted on the graphics card or is it transferred over every step? When there's talk about bandwidth, are you talking about a graphics card internal bandwidth, or the pipeline from CPU to GPU? Note: I'm not actually looking for information on how the drawing process happens, that's the GPU's business, I'm interested on all the overhead that precedes that. I'd like to understand what's going on when I do action X, to adapt my architectures and practices to that. Any articles (possibly with code examples), information, links, tutorials that give more insight in how to write better games are very much appreciated. Thanks :)

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  • Higher Performance With Spritesheets Than With Rotating Using C# and XNA 4.0?

    - by Manuel Maier
    I would like to know what the performance difference is between using multiple sprites in one file (sprite sheets) to draw a game-character being able to face in 4 directions and using one sprite per file but rotating that character to my needs. I am aware that the sprite sheet method restricts the character to only be able to look into predefined directions, whereas the rotation method would give the character the freedom of "looking everywhere". Here's an example of what I am doing: Single Sprite Method Assuming I have a 64x64 texture that points north. So I do the following if I wanted it to point east: spriteBatch.Draw( _sampleTexture, new Rectangle(200, 100, 64, 64), null, Color.White, (float)(Math.PI / 2), Vector2.Zero, SpriteEffects.None, 0); Multiple Sprite Method Now I got a sprite sheet (128x128) where the top-left 64x64 section contains a sprite pointing north, top-right 64x64 section points east, and so forth. And to make it point east, i do the following: spriteBatch.Draw( _sampleSpritesheet, new Rectangle(400, 100, 64, 64), new Rectangle(64, 0, 64, 64), Color.White); So which of these methods is using less CPU-time and what are the pro's and con's? Is .NET/XNA optimizing this in any way (e.g. it notices that the same call was done last frame and then just uses an already rendered/rotated image thats still in memory)?

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  • JPA : optimize EJB-QL query involving large many-to-many join table

    - by Fabien
    Hi all. I'm using Hibernate Entity Manager 3.4.0.GA with Spring 2.5.6 and MySql 5.1. I have a use case where an entity called Artifact has a reflexive many-to-many relation with itself, and the join table is quite large (1 million lines). As a result, the HQL query performed by one of the methods in my DAO takes a long time. Any advice on how to optimize this and still use HQL ? Or do I have no choice but to switch to a native SQL query that would perform a join between the table ARTIFACT and the join table ARTIFACT_DEPENDENCIES ? Here is the problematic query performed in the DAO : @SuppressWarnings("unchecked") public List<Artifact> findDependentArtifacts(Artifact artifact) { Query query = em.createQuery("select a from Artifact a where :artifact in elements(a.dependencies)"); query.setParameter("artifact", artifact); List<Artifact> list = query.getResultList(); return list; } And the code for the Artifact entity : package com.acme.dependencytool.persistence.model; import java.util.ArrayList; import java.util.List; import javax.persistence.CascadeType; import javax.persistence.Column; import javax.persistence.Entity; import javax.persistence.FetchType; import javax.persistence.GeneratedValue; import javax.persistence.Id; import javax.persistence.JoinColumn; import javax.persistence.JoinTable; import javax.persistence.ManyToMany; import javax.persistence.Table; import javax.persistence.UniqueConstraint; @Entity @Table(name = "ARTIFACT", uniqueConstraints={@UniqueConstraint(columnNames={"GROUP_ID", "ARTIFACT_ID", "VERSION"})}) public class Artifact { @Id @GeneratedValue @Column(name = "ID") private Long id = null; @Column(name = "GROUP_ID", length = 255, nullable = false) private String groupId; @Column(name = "ARTIFACT_ID", length = 255, nullable = false) private String artifactId; @Column(name = "VERSION", length = 255, nullable = false) private String version; @ManyToMany(cascade=CascadeType.ALL, fetch=FetchType.EAGER) @JoinTable( name="ARTIFACT_DEPENDENCIES", joinColumns = @JoinColumn(name="ARTIFACT_ID", referencedColumnName="ID"), inverseJoinColumns = @JoinColumn(name="DEPENDENCY_ID", referencedColumnName="ID") ) private List<Artifact> dependencies = new ArrayList<Artifact>(); public Long getId() { return id; } public void setId(Long id) { this.id = id; } public String getGroupId() { return groupId; } public void setGroupId(String groupId) { this.groupId = groupId; } public String getArtifactId() { return artifactId; } public void setArtifactId(String artifactId) { this.artifactId = artifactId; } public String getVersion() { return version; } public void setVersion(String version) { this.version = version; } public List<Artifact> getDependencies() { return dependencies; } public void setDependencies(List<Artifact> dependencies) { this.dependencies = dependencies; } } Thanks in advance. EDIT 1 : The DDLs are generated automatically by Hibernate EntityMananger based on the JPA annotations in the Artifact entity. I have no explicit control on the automaticaly-generated join table, and the JPA annotations don't let me explicitly set an index on a column of a table that does not correspond to an actual Entity (in the JPA sense). So I guess the indexing of table ARTIFACT_DEPENDENCIES is left to the DB, MySQL in my case, which apparently uses a composite index based on both clumns but doesn't index the column that is most relevant in my query (DEPENDENCY_ID). mysql describe ARTIFACT_DEPENDENCIES; +---------------+------------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +---------------+------------+------+-----+---------+-------+ | ARTIFACT_ID | bigint(20) | NO | MUL | NULL | | | DEPENDENCY_ID | bigint(20) | NO | MUL | NULL | | +---------------+------------+------+-----+---------+-------+ EDIT 2 : When turning on showSql in the Hibernate session, I see many occurences of the same type of SQL query, as below : select dependenci0_.ARTIFACT_ID as ARTIFACT1_1_, dependenci0_.DEPENDENCY_ID as DEPENDENCY2_1_, artifact1_.ID as ID1_0_, artifact1_.ARTIFACT_ID as ARTIFACT2_1_0_, artifact1_.GROUP_ID as GROUP3_1_0_, artifact1_.VERSION as VERSION1_0_ from ARTIFACT_DEPENDENCIES dependenci0_ left outer join ARTIFACT artifact1_ on dependenci0_.DEPENDENCY_ID=artifact1_.ID where dependenci0_.ARTIFACT_ID=? Here's what EXPLAIN in MySql says about this type of query : mysql explain select dependenci0_.ARTIFACT_ID as ARTIFACT1_1_, dependenci0_.DEPENDENCY_ID as DEPENDENCY2_1_, artifact1_.ID as ID1_0_, artifact1_.ARTIFACT_ID as ARTIFACT2_1_0_, artifact1_.GROUP_ID as GROUP3_1_0_, artifact1_.VERSION as VERSION1_0_ from ARTIFACT_DEPENDENCIES dependenci0_ left outer join ARTIFACT artifact1_ on dependenci0_.DEPENDENCY_ID=artifact1_.ID where dependenci0_.ARTIFACT_ID=1; +----+-------------+--------------+--------+-------------------+-------------------+---------+---------------------------------------------+------+-------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+--------------+--------+-------------------+-------------------+---------+---------------------------------------------+------+-------+ | 1 | SIMPLE | dependenci0_ | ref | FKEA2DE763364D466 | FKEA2DE763364D466 | 8 | const | 159 | | | 1 | SIMPLE | artifact1_ | eq_ref | PRIMARY | PRIMARY | 8 | dependencytooldb.dependenci0_.DEPENDENCY_ID | 1 | | +----+-------------+--------------+--------+-------------------+-------------------+---------+---------------------------------------------+------+-------+ EDIT 3 : I tried setting the FetchType to LAZY in the JoinTable annotation, but I then get the following exception : Hibernate: select artifact0_.ID as ID1_, artifact0_.ARTIFACT_ID as ARTIFACT2_1_, artifact0_.GROUP_ID as GROUP3_1_, artifact0_.VERSION as VERSION1_ from ARTIFACT artifact0_ where artifact0_.GROUP_ID=? and artifact0_.ARTIFACT_ID=? 51545 [btpool0-2] ERROR org.hibernate.LazyInitializationException - failed to lazily initialize a collection of role: com.acme.dependencytool.persistence.model.Artifact.dependencies, no session or session was closed org.hibernate.LazyInitializationException: failed to lazily initialize a collection of role: com.acme.dependencytool.persistence.model.Artifact.dependencies, no session or session was closed at org.hibernate.collection.AbstractPersistentCollection.throwLazyInitializationException(AbstractPersistentCollection.java:380) at org.hibernate.collection.AbstractPersistentCollection.throwLazyInitializationExceptionIfNotConnected(AbstractPersistentCollection.java:372) at org.hibernate.collection.AbstractPersistentCollection.readSize(AbstractPersistentCollection.java:119) at org.hibernate.collection.PersistentBag.size(PersistentBag.java:248) at com.acme.dependencytool.server.DependencyToolServiceImpl.createArtifactViewBean(DependencyToolServiceImpl.java:93) at com.acme.dependencytool.server.DependencyToolServiceImpl.createArtifactViewBean(DependencyToolServiceImpl.java:109) at com.acme.dependencytool.server.DependencyToolServiceImpl.search(DependencyToolServiceImpl.java:48) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at com.google.gwt.user.server.rpc.RPC.invokeAndEncodeResponse(RPC.java:527) at com.google.gwt.user.server.rpc.RemoteServiceServlet.processCall(RemoteServiceServlet.java:166) at com.google.gwt.user.server.rpc.RemoteServiceServlet.doPost(RemoteServiceServlet.java:86) at javax.servlet.http.HttpServlet.service(HttpServlet.java:637) at javax.servlet.http.HttpServlet.service(HttpServlet.java:717) at org.mortbay.jetty.servlet.ServletHolder.handle(ServletHolder.java:487) at org.mortbay.jetty.servlet.ServletHandler.handle(ServletHandler.java:362) at org.mortbay.jetty.security.SecurityHandler.handle(SecurityHandler.java:216) at org.mortbay.jetty.servlet.SessionHandler.handle(SessionHandler.java:181) at org.mortbay.jetty.handler.ContextHandler.handle(ContextHandler.java:729) at org.mortbay.jetty.webapp.WebAppContext.handle(WebAppContext.java:405) at org.mortbay.jetty.handler.HandlerWrapper.handle(HandlerWrapper.java:152) at org.mortbay.jetty.handler.RequestLogHandler.handle(RequestLogHandler.java:49) at org.mortbay.jetty.handler.HandlerWrapper.handle(HandlerWrapper.java:152) at org.mortbay.jetty.Server.handle(Server.java:324) at org.mortbay.jetty.HttpConnection.handleRequest(HttpConnection.java:505) at org.mortbay.jetty.HttpConnection$RequestHandler.content(HttpConnection.java:843) at org.mortbay.jetty.HttpParser.parseNext(HttpParser.java:647) at org.mortbay.jetty.HttpParser.parseAvailable(HttpParser.java:205) at org.mortbay.jetty.HttpConnection.handle(HttpConnection.java:380) at org.mortbay.io.nio.SelectChannelEndPoint.run(SelectChannelEndPoint.java:395) at org.mortbay.thread.QueuedThreadPool$PoolThread.run(QueuedThreadPool.java:488)

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  • Very large database, very small portion most being retrieved in real time

    - by mingyeow
    Hi folks, I have an interesting database problem. I have a DB that is 150GB in size. My memory buffer is 8GB. Most of my data is rarely being retrieved, or mainly being retrieved by backend processes. I would very much prefer to keep them around because some features require them. Some of it (namely some tables, and some identifiable parts of certain tables) are used very often in a user facing manner How can I make sure that the latter is always being kept in memory? (there is more than enough space for these) More info: We are on Ruby on rails. The database is MYSQL, our tables are stored using INNODB. We are sharding the data across 2 partitions. Because we are sharding it, we store most of our data using JSON blobs, while indexing only the primary keys

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  • SQL SERVER – Guest Posts – Feodor Georgiev – The Context of Our Database Environment – Going Beyond the Internal SQL Server Waits – Wait Type – Day 21 of 28

    - by pinaldave
    This guest post is submitted by Feodor. Feodor Georgiev is a SQL Server database specialist with extensive experience of thinking both within and outside the box. He has wide experience of different systems and solutions in the fields of architecture, scalability, performance, etc. Feodor has experience with SQL Server 2000 and later versions, and is certified in SQL Server 2008. In this article Feodor explains the server-client-server process, and concentrated on the mutual waits between client and SQL Server. This is essential in grasping the concept of waits in a ‘global’ application plan. Recently I was asked to write a blog post about the wait statistics in SQL Server and since I had been thinking about writing it for quite some time now, here it is. It is a wide-spread idea that the wait statistics in SQL Server will tell you everything about your performance. Well, almost. Or should I say – barely. The reason for this is that SQL Server is always a part of a bigger system – there are always other players in the game: whether it is a client application, web service, any other kind of data import/export process and so on. In short, the SQL Server surroundings look like this: This means that SQL Server, aside from its internal waits, also depends on external waits and settings. As we can see in the picture above, SQL Server needs to have an interface in order to communicate with the surrounding clients over the network. For this communication, SQL Server uses protocol interfaces. I will not go into detail about which protocols are best, but you can read this article. Also, review the information about the TDS (Tabular data stream). As we all know, our system is only as fast as its slowest component. This means that when we look at our environment as a whole, the SQL Server might be a victim of external pressure, no matter how well we have tuned our database server performance. Let’s dive into an example: let’s say that we have a web server, hosting a web application which is using data from our SQL Server, hosted on another server. The network card of the web server for some reason is malfunctioning (think of a hardware failure, driver failure, or just improper setup) and does not send/receive data faster than 10Mbs. On the other end, our SQL Server will not be able to send/receive data at a faster rate either. This means that the application users will notify the support team and will say: “My data is coming very slow.” Now, let’s move on to a bit more exciting example: imagine that there is a similar setup as the example above – one web server and one database server, and the application is not using any stored procedure calls, but instead for every user request the application is sending 80kb query over the network to the SQL Server. (I really thought this does not happen in real life until I saw it one day.) So, what happens in this case? To make things worse, let’s say that the 80kb query text is submitted from the application to the SQL Server at least 100 times per minute, and as often as 300 times per minute in peak times. Here is what happens: in order for this query to reach the SQL Server, it will have to be broken into a of number network packets (according to the packet size settings) – and will travel over the network. On the other side, our SQL Server network card will receive the packets, will pass them to our network layer, the packets will get assembled, and eventually SQL Server will start processing the query – parsing, allegorizing, generating the query execution plan and so on. So far, we have already had a serious network overhead by waiting for the packets to reach our Database Engine. There will certainly be some processing overhead – until the database engine deals with the 80kb query and its 20 subqueries. The waits you see in the DMVs are actually collected from the point the query reaches the SQL Server and the packets are assembled. Let’s say that our query is processed and it finally returns 15000 rows. These rows have a certain size as well, depending on the data types returned. This means that the data will have converted to packages (depending on the network size package settings) and will have to reach the application server. There will also be waits, however, this time you will be able to see a wait type in the DMVs called ASYNC_NETWORK_IO. What this wait type indicates is that the client is not consuming the data fast enough and the network buffers are filling up. Recently Pinal Dave posted a blog on Client Statistics. What Client Statistics does is captures the physical flow characteristics of the query between the client(Management Studio, in this case) and the server and back to the client. As you see in the image, there are three categories: Query Profile Statistics, Network Statistics and Time Statistics. Number of server roundtrips–a roundtrip consists of a request sent to the server and a reply from the server to the client. For example, if your query has three select statements, and they are separated by ‘GO’ command, then there will be three different roundtrips. TDS Packets sent from the client – TDS (tabular data stream) is the language which SQL Server speaks, and in order for applications to communicate with SQL Server, they need to pack the requests in TDS packets. TDS Packets sent from the client is the number of packets sent from the client; in case the request is large, then it may need more buffers, and eventually might even need more server roundtrips. TDS packets received from server –is the TDS packets sent by the server to the client during the query execution. Bytes sent from client – is the volume of the data set to our SQL Server, measured in bytes; i.e. how big of a query we have sent to the SQL Server. This is why it is best to use stored procedures, since the reusable code (which already exists as an object in the SQL Server) will only be called as a name of procedure + parameters, and this will minimize the network pressure. Bytes received from server – is the amount of data the SQL Server has sent to the client, measured in bytes. Depending on the number of rows and the datatypes involved, this number will vary. But still, think about the network load when you request data from SQL Server. Client processing time – is the amount of time spent in milliseconds between the first received response packet and the last received response packet by the client. Wait time on server replies – is the time in milliseconds between the last request packet which left the client and the first response packet which came back from the server to the client. Total execution time – is the sum of client processing time and wait time on server replies (the SQL Server internal processing time) Here is an illustration of the Client-server communication model which should help you understand the mutual waits in a client-server environment. Keep in mind that a query with a large ‘wait time on server replies’ means the server took a long time to produce the very first row. This is usual on queries that have operators that need the entire sub-query to evaluate before they proceed (for example, sort and top operators). However, a query with a very short ‘wait time on server replies’ means that the query was able to return the first row fast. However a long ‘client processing time’ does not necessarily imply the client spent a lot of time processing and the server was blocked waiting on the client. It can simply mean that the server continued to return rows from the result and this is how long it took until the very last row was returned. The bottom line is that developers and DBAs should work together and think carefully of the resource utilization in the client-server environment. From experience I can say that so far I have seen only cases when the application developers and the Database developers are on their own and do not ask questions about the other party’s world. I would recommend using the Client Statistics tool during new development to track the performance of the queries, and also to find a synchronous way of utilizing resources between the client – server – client. Here is another example: think about similar setup as above, but add another server to the game. Let’s say that we keep our media on a separate server, and together with the data from our SQL Server we need to display some images on the webpage requested by our user. No matter how simple or complicated the logic to get the images is, if the images are 500kb each our users will get the page slowly and they will still think that there is something wrong with our data. Anyway, I don’t mean to get carried away too far from SQL Server. Instead, what I would like to say is that DBAs should also be aware of ‘the big picture’. I wrote a blog post a while back on this topic, and if you are interested, you can read it here about the big picture. And finally, here are some guidelines for monitoring the network performance and improving it: Run a trace and outline all queries that return more than 1000 rows (in Profiler you can actually filter and sort the captured trace by number of returned rows). This is not a set number; it is more of a guideline. The general thought is that no application user can consume that many rows at once. Ask yourself and your fellow-developers: ‘why?’. Monitor your network counters in Perfmon: Network Interface:Output queue length, Redirector:Network errors/sec, TCPv4: Segments retransmitted/sec and so on. Make sure to establish a good friendship with your network administrator (buy them coffee, for example J ) and get into a conversation about the network settings. Have them explain to you how the network cards are setup – are they standalone, are they ‘teamed’, what are the settings – full duplex and so on. Find some time to read a bit about networking. In this short blog post I hope I have turned your attention to ‘the big picture’ and the fact that there are other factors affecting our SQL Server, aside from its internal workings. As a further reading I would still highly recommend the Wait Stats series on this blog, also I would recommend you have the coffee break conversation with your network admin as soon as possible. This guest post is written by Feodor Georgiev. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL

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  • Edinburgh this Thurs (25th) - Rob Carrol talks about how to build a high performance, scalable repor

    - by tonyrogerson
    Scottish Area SQL Server User Group Meeting, Edinburgh - Thursday 25th March An evening of SQL Server 2008 Reporting Services Scalability and Performance with Rob Carrol, see how to build a high performance, scalable reporting platform and the tuning techniques required to ensure that report performance remains optimal as your platform grows. Pizza and drinks will be provided! Register at http://www.sqlserverfaq.com/events/221/SQL-Server-2008-Reporting-Services-Scalability-and-Performance.aspx...(read more)

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  • Exchange 2010 - resolving Calendar Attendant\Requests Failed

    - by marcwenger
    On my mailbox server, I am receiving the alert: MSExchange Calendar Attendant\Requests Failed Or in Solarwinds Requests Failed (Calendar Attendant) for Exchange 2010 Mailbox Role Counters (Advanced) on *servername* All I know is this figure should be 0 at all times. Currently I am at 2 and this is the only alert on the Exchange servers. No where I can find how to resolve this. How can I fix this? thank you

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  • Need help tuning Mysql and linux server

    - by Newtonx
    We have multi-user application (like MailChimp,Constant Contact) . Each of our customers has it's own contact's list (from 5 to 100.000 contacts). Everything is stored in one BIG database (currently 25G). Since we released our product we have the following data history. 5 years of data history : - users/customers (200+) - contacts (40 million records) - campaigns - campaign_deliveries (73.843.764 records) - campaign_queue ( 8 millions currently ) As we get more users and table records increase our system/web app is getting slower and slower . Some queries takes too long to execute . SCHEMA Table contacts --------------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------------+------------------+------+-----+---------+----------------+ | contact_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | client_id | int(10) unsigned | YES | | NULL | | | name | varchar(60) | YES | | NULL | | | mail | varchar(60) | YES | MUL | NULL | | | verified | int(1) | YES | | 0 | | | owner | int(10) unsigned | NO | MUL | 0 | | | date_created | date | YES | MUL | NULL | | | geolocation | varchar(100) | YES | | NULL | | | ip | varchar(20) | YES | MUL | NULL | | +---------------------+------------------+------+-----+---------+----------------+ Table campaign_deliveries +---------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+------------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | newsletter_id | int(10) unsigned | NO | MUL | 0 | | | contact_id | int(10) unsigned | NO | MUL | 0 | | | sent_date | date | YES | MUL | NULL | | | sent_time | time | YES | MUL | NULL | | | smtp_server | varchar(20) | YES | | NULL | | | owner | int(5) | YES | MUL | NULL | | | ip | varchar(20) | YES | MUL | NULL | | +---------------+------------------+------+-----+---------+----------------+ Table campaign_queue +---------------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+------------------+------+-----+---------+----------------+ | queue_id | int(10) unsigned | NO | PRI | NULL | auto_increment | | newsletter_id | int(10) unsigned | NO | MUL | 0 | | | owner | int(10) unsigned | NO | MUL | 0 | | | date_to_send | date | YES | | NULL | | | contact_id | int(11) | NO | MUL | NULL | | | date_created | date | YES | | NULL | | +---------------+------------------+------+-----+---------+----------------+ Slow queries LOG -------------------------------------------- Query_time: 350 Lock_time: 1 Rows_sent: 1 Rows_examined: 971004 SELECT COUNT(*) as total FROM contacts WHERE (contacts.owner = 70 AND contacts.verified = 1); Query_time: 235 Lock_time: 1 Rows_sent: 1 Rows_examined: 4455209 SELECT COUNT(*) as total FROM contacts WHERE (contacts.owner = 2); How can we optimize it ? Queries should take no more than 30 secs to execute? Can we optimize it and keep all data in one BIG database or should we change app's structure and set one single database to each user ? Thanks

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  • How do I objectively measure an application's load on a server

    - by Joe
    All, I'm not even sure where to begin looking for resources to answer my question, and I realize that speculation about this kind of thing is highly subjective. I need help determining what class of server I should purchase to host a MS Silverlight application with a MSSQL server back-end on a Windows Server 2008 platform. It's an interactive program, so I can't simply generate a list of URLs to test against, and run it with 1000 simultaneous users. What tools are out there to help me determine what kind of load the application will put on a server at varying levels of concurrent users? Would you all suggest separating the SQL server form the web server, to better differentiate the generated load on the different parts of the stack?

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  • Server configurations for hosting MySQL database

    - by shyam
    I have a web application which uses a MySQL database hosted on a virtual server. I've been using this server when I started the application and when the database was really small. Now it has grown and the server is not able to handle the db, causing frequent db errors. I'm planning to get a server and I need suggestions for that. Like I said, the db is now 9 GB, and is growing considerably fast. There are a number of tables with millions of rows, which are frequently updated and queried. The most frequent error the db shows is Lock wait timeout exceeded. Previously there used to be "The total number of locks exceeds the lock table size" errors too, but I could avoid it by increasing Innodb buffer pool size. Please suggest what configurations should I look for in the server I should buy. I read somewhere that the db should ideally have a buffer pool size greater than the size of its data, so in my case I guess I'd need memory gt 9 GB. What other things should I look for in the server? Just tell me if I should give you more info about the

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  • Find out which task is generating a lot of context switches on linux

    - by Gaks
    According to vmstat, my Linux server (2xCore2 Duo 2.5 GHz) is constantly doing around 20k context switches per second. # vmstat 3 procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu---- r b swpd free buff cache si so bi bo in cs us sy id wa 2 0 7292 249472 82340 2291972 0 0 0 0 0 0 7 13 79 0 0 0 7292 251808 82344 2291968 0 0 0 184 24 20090 1 1 99 0 0 0 7292 251876 82344 2291968 0 0 0 83 17 20157 1 0 99 0 0 0 7292 251876 82344 2291968 0 0 0 73 12 20116 1 0 99 0 ... but uptime shows small load: load average: 0.01, 0.02, 0.01 and top doesn't show any process with high %CPU usage. How do I find out what exactly is generating those context switches? Which process/thread? I tried to analyze pidstat output: # pidstat -w 10 1 12:39:13 PID cswch/s nvcswch/s Command 12:39:23 1 0.20 0.00 init 12:39:23 4 0.20 0.00 ksoftirqd/0 12:39:23 7 1.60 0.00 events/0 12:39:23 8 1.50 0.00 events/1 12:39:23 89 0.50 0.00 kblockd/0 12:39:23 90 0.30 0.00 kblockd/1 12:39:23 995 0.40 0.00 kirqd 12:39:23 997 0.60 0.00 kjournald 12:39:23 1146 0.20 0.00 svscan 12:39:23 2162 5.00 0.00 kjournald 12:39:23 2526 0.20 2.00 postgres 12:39:23 2530 1.00 0.30 postgres 12:39:23 2534 5.00 3.20 postgres 12:39:23 2536 1.40 1.70 postgres 12:39:23 12061 10.59 0.90 postgres 12:39:23 14442 1.50 2.20 postgres 12:39:23 15416 0.20 0.00 monitor 12:39:23 17289 0.10 0.00 syslogd 12:39:23 21776 0.40 0.30 postgres 12:39:23 23638 0.10 0.00 screen 12:39:23 25153 1.00 0.00 sshd 12:39:23 25185 86.61 0.00 daemon1 12:39:23 25190 12.19 35.86 postgres 12:39:23 25295 2.00 0.00 screen 12:39:23 25743 9.99 0.00 daemon2 12:39:23 25747 1.10 3.00 postgres 12:39:23 26968 5.09 0.80 postgres 12:39:23 26969 5.00 0.00 postgres 12:39:23 26970 1.10 0.20 postgres 12:39:23 26971 17.98 1.80 postgres 12:39:23 27607 0.90 0.40 postgres 12:39:23 29338 4.30 0.00 screen 12:39:23 31247 4.10 23.58 postgres 12:39:23 31249 82.92 34.77 postgres 12:39:23 31484 0.20 0.00 pdflush 12:39:23 32097 0.10 0.00 pidstat Looks like some postgresql tasks are doing 10 context swiches per second, but it doesn't all sum up to 20k anyway. Any idea how to dig a little deeper for an answer?

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  • Changing memory allocator to Jemalloc Centos 6

    - by Brian Lovett
    After reading this blog post about the impact of memory allocators like jemalloc on highly threaded applications, I wanted to test things on a larger scale on some of our cluster of servers. We run sphinx, and apache using threads, and on 24 core machines. Installing jemalloc was simple enough. We are running Centos 6, so yum install jemalloc jemalloc-devel did the trick. My question is, how do we change everything on the system over to using jemalloc instead of the default malloc built into Centos. Research pointed me at this as a potential option: LD_PRELOAD=$LD_PRELOAD:/usr/lib64/libjemalloc.so.1 Would this be sufficient to get everything using jemalloc?

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  • Benchmark for website speed optimization

    - by gowri
    I working on website speed optimization. I mostly used 3 tools for analyzing speed of optimization. Speed analyzing Tools: Google pagespeed tool Yslow Firefox extenstion Web Page Performance Test I am measuring performance using above tool and benchmark result as below like before and after. Before optimization : Google PageSpeed Insights score : 53/100 Web Page Performance Test : 55/100 (First View : 10.710s, Repeat view : 6.387s ) Yahoo Overall performance score : 68 Stage 1 After optimization : Google PageSpeed Insights score : 88/100 Web Page Performance Test : 88/100 (First View : 6.733s, Repeat view : 1.908s ) Yahoo Overall performance score : 80 My question is ? Am i doing correct way ? What is the best way of benchmark for speed optimization ? Is there any standard ? Is there any much better tool for analyzing speed ?

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