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  • Neo4j 1.9.4 (REST Server,CYPHER) performance issue

    - by user2968943
    I have Neo4j 1.9.4 installed on 24 core 24Gb ram (centos) machine and for most queries CPU usage spikes goes to 200% with only few concurrent requests. Domain: some sort of social application where few types of nodes(profiles) with 3-30 text/array properties and 36 relationship types with at least 3 properties. Most of nodes currently has ~300-500 relationships. Current data set footprint(from console): LogicalLogSize=4294907 (32MB) ArrayStoreSize=1675520 (12MB) NodeStoreSize=1342170 (10MB) PropertyStoreSize=1739548 (13MB) RelationshipStoreSize=6395202 (48MB) StringStoreSize=1478400 (11MB) which is IMHO really small. most queries looks like this one(with more or less WITH .. MATCH .. statements and few queries with variable length relations but the often fast): START targetUser=node({id}), currentUser=node({current}) MATCH targetUser-[contact:InContactsRelation]->n, n-[:InLocationRelation]->l, n-[:InCategoryRelation]->c WITH currentUser, targetUser,n, l,c, contact.fav is not null as inFavorites MATCH n<-[followers?:InContactsRelation]-() WITH currentUser, targetUser,n, l,c,inFavorites, COUNT(followers) as numFollowers RETURN id(n) as id, n.name? as name, n.title? as title, n._class as _class, n.avatar? as avatar, n.avatar_type? as avatar_type, l.name as location__name, c.name as category__name, true as isInContacts, inFavorites as isInFavorites, numFollowers it runs in ~1s-3s(for first run) and ~1s-70ms (for consecutive and it depends on query) and there is about 5-10 queries runs for each impression. Another interesting behavior is when i try run query from console(neo4j) on my local machine many consecutive times(just press ctrl+enter for few seconds) it has almost constant execution time but when i do it on server it goes slower exponentially and i guess it somehow related with my problem. Problem: So my problem is that neo4j is very CPU greedy(for 24 core machine its may be not an issue but its obviously overkill for small project). First time i used AWS EC2 m1.large instance but over all performance was bad, during testing, CPU always was over 100%. Some relevant parts of configuration: neostore.nodestore.db.mapped_memory=1280M wrapper.java.maxmemory=8192 note: I already tried configuration where all memory related parameters where HIGH and it didn't worked(no change at all). Question: Where to digg? configuration? scheme? queries? what i'm doing wrong? if need more info(logs, configs) just ask ;)

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  • Connection hangs after time of inactivity

    - by Sinuhe
    In my application, Spring manages connection pool for database access. Hibernate uses these connections for its queries. At first glance, I have no problems with the pool: it works correctly with concurrent clients and a pool with only one connection. I can execute a lot of queries, so I think that I (or Spring) don't leave open connections. My problem appears after some time of inactivity (sometimes 30 minutes, sometimes more than 2 hours). Then, when Hibernate does some search, it lasts too much. Setting log4j level to TRACE, I get this logs: ... 18:27:01 DEBUG nsactionSynchronizationManager - Retrieved value [org.springframework.orm.hibernate3.SessionHolder@99abd7] for key [org.hibernate.impl.SessionFactoryImpl@7d2897] bound to thread [http-8080-Processor24] 18:27:01 DEBUG HibernateTransactionManager - Found thread-bound Session [org.hibernate.impl.SessionImpl@8878cd] for Hibernate transaction 18:27:01 DEBUG HibernateTransactionManager - Using transaction object [org.springframework.orm.hibernate3.HibernateTransactionManager$HibernateTransactionObject@1b2ffee] 18:27:01 DEBUG HibernateTransactionManager - Creating new transaction with name [com.acjoventut.service.GenericManager.findByExample]: PROPAGATION_REQUIRED,ISOLATION_DEFAULT 18:27:01 DEBUG HibernateTransactionManager - Preparing JDBC Connection of Hibernate Session [org.hibernate.impl.SessionImpl@8878cd] 18:27:01 TRACE SessionImpl - setting flush mode to: AUTO 18:27:01 DEBUG JDBCTransaction - begin 18:27:01 DEBUG ConnectionManager - opening JDBC connection Here it gets frozen for about 2 - 10 minutes. But then continues: 18:30:11 DEBUG JDBCTransaction - current autocommit status: true 18:30:11 DEBUG JDBCTransaction - disabling autocommit 18:30:11 TRACE JDBCContext - after transaction begin 18:30:11 DEBUG HibernateTransactionManager - Exposing Hibernate transaction as JDBC transaction [jdbc:oracle:thin:@212.31.39.50:30998:orcl, UserName=DEVELOP, Oracle JDBC driver] 18:30:11 DEBUG nsactionSynchronizationManager - Bound value [org.springframework.jdbc.datasource.ConnectionHolder@843a9d] for key [org.apache.commons.dbcp.BasicDataSource@7745fd] to thread [http-8080-Processor24] 18:30:11 DEBUG nsactionSynchronizationManager - Initializing transaction synchronization ... After that, it works with no problems, until another period of inactivity. IMHO, it seems like connection pool returns an invalid/closed connection, and when Hibernate realizes that, ask another connection to the pool. I don't know how can I solve this problem or things I can do for delimiting it. Any help achieving this will be appreciate. Thanks. EDIT: Well, it finally was due a firewall rule. Database detects the connection is lost, but pool (dbcp or c3p0) not. So, it tries to query the database with no success. What is still strange for me is that timeout period is very variable. Maybe the rule is specially strange or firewall doesn't work correctly. Anyway, I have no access to that machine and I can only wait for an explanation. :(

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  • SOAP WCF Webservice behaves differently when called locally or remotely

    - by Idriss
    I have a WCF SOAP 1.1 Webservice with the configuration specified below. A concurrent call to any method of this endpoint hangs until the other returns when called remotely (from another computer on the network). I cannot replicate this when these methods are called locally (with a client located on the same machine). I tried to increase the maxConcurrentCalls with no luck ... the service behavior seems to be different according to the client local/remote location. Any guess? Thanks, <?xml version="1.0" encoding="utf-8"?> <configuration> <system.serviceModel> <services> <service behaviorConfiguration="MyCustomBehavior" name="CONTOSO.CONTOSOServerApi.IContosoServiceApiImplV1"> <endpoint address="" binding="customBinding" bindingConfiguration="WebBinding" bindingNamespace="http://contoso.com" contract="CONTOSO.CONTOSOServerApiInterfaceV1.IContosoServiceApiV1" /> </service> </services> <behaviors> <serviceBehaviors> <behavior name="MyCustomBehavior"> <serviceMetadata httpGetEnabled="true" httpGetUrl="http://localhost:8080/MyEndPointV1" /> <serviceDebug httpHelpPageEnabled="false" includeExceptionDetailInFaults="true" /> <serviceThrottling maxConcurrentSessions="10000" maxConcurrentCalls="1000"/> <dataContractSerializer maxItemsInObjectGraph="2147483647" /> </behavior> </serviceBehaviors> </behaviors> <bindings> <customBinding> <binding name="WebBinding"> <textMessageEncoding messageVersion="Soap11" maxReadPoolSize="2147483647" maxWritePoolSize="2147483647"> <readerQuotas maxDepth="2147483647" maxStringContentLength="2147483647" maxArrayLength="2147483647" maxBytesPerRead="2147483647" maxNameTableCharCount="2147483647" /> </textMessageEncoding> <httpsTransport /> </binding> </customBinding> </bindings> </system.serviceModel> </configuration>

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  • GHC.Generics and Type Families

    - by jberryman
    This is a question related to my module here, and is simplified a bit. It's also related to this previous question, in which I oversimplified my problem and didn't get the answer I was looking for. I hope this isn't too specific, and please change the title if you can think if a better one. Background My module uses a concurrent chan, split into a read side and write side. I use a special class with an associated type synonym to support polymorphic channel "joins": {-# LANGUAGE TypeFamilies #-} class Sources s where type Joined s newJoinedChan :: IO (s, Messages (Joined s)) -- NOT EXPORTED --output and input sides of channel: data Messages a -- NOT EXPORTED data Mailbox a instance Sources (Mailbox a) where type Joined (Mailbox a) = a newJoinedChan = undefined instance (Sources a, Sources b)=> Sources (a,b) where type Joined (a,b) = (Joined a, Joined b) newJoinedChan = undefined -- and so on for tuples of 3,4,5... The code above allows us to do this kind of thing: example = do (mb , msgsA) <- newJoinedChan ((mb1, mb2), msgsB) <- newJoinedChan --say that: msgsA, msgsB :: Messages (Int,Int) --and: mb :: Mailbox (Int,Int) -- mb1,mb2 :: Mailbox Int We have a recursive action called a Behavior that we can run on the messages we pull out of the "read" end of the channel: newtype Behavior a = Behavior (a -> IO (Behavior a)) runBehaviorOn :: Behavior a -> Messages a -> IO () -- NOT EXPORTED This would allow us to run a Behavior (Int,Int) on either of msgsA or msgsB, where in the second case both Ints in the tuple it receives actually came through separate Mailboxes. This is all tied together for the user in the exposed spawn function spawn :: (Sources s) => Behavior (Joined s) -> IO s ...which calls newJoinedChan and runBehaviorOn, and returns the input Sources. What I'd like to do I'd like users to be able to create a Behavior of arbitrary product type (not just tuples) , so for instance we could run a Behavior (Pair Int Int) on the example Messages above. I'd like to do this with GHC.Generics while still having a polymorphic Sources, but can't manage to make it work. spawn :: (Sources s, Generic (Joined s), Rep (Joined s) ~ ??) => Behavior (Joined s) -> IO s The parts of the above example that are actually exposed in the API are the fst of the newJoinedChan action, and Behaviors, so an acceptable solution can modify one or all of runBehaviorOn or the snd of newJoinedChan. I'll also be extending the API above to support sums (not implemented yet) like Behavior (Either a b) so I hoped GHC.Generics would work for me. Questions Is there a way I can extend the API above to support arbitrary Generic a=> Behavior a? If not using GHC's Generics, are there other ways I can get the API I want with minimal end-user pain (i.e. they just have to add a deriving clause to their type)?

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  • Creating multiple heads in remote repository

    - by Jab
    We are looking to move our team (~10 developers) from SVN to mercurial. We are trying to figure out how to manage our workflow. In particular, we are trying to see if creating remote heads is the right solution. We currently have a very large repository with multiple, related projects. They share a lot of code, but pieces of the project are deployed by different teams (3 teams) independent of other portions of the code-base. So each team is working on concurrent large features. The way we currently handles this in SVN are branches. Team1 has a branch for Feature1, same deal for the other teams. When Team1 finishes their change, it gets merged into the trunk and deployed out. The other teams follow suite when their project is complete, merging of course. So my initial thought are using Named Branches for these situations. Team1 makes a Feature1 branch off of the default branch in Hg. Now, here is the question. Should the team PUSH that branch, in it's current/half-state to the repository. This will create a second head in the core repo. My initial reaction was "NO!" as it seems like a bad idea. Handling multiple heads on our repository just sounds awful, but there are some advantages... First, the teams want to setup Continuous Integration to build this branch during their development cycle(months long). This will only work if the CI can pull this branch from the repo. This is something we do now with SVN, copy a CI build and change the branch. Easy. Second, it makes it easier for any team member to jump onto the branch and start working. Without pushing to the core repo, they would have to receive a push from a developer on that team with the changeset information. It is also possible to lose local commits to hardware failure. The chances increase a lot if it's a branch by a single developer who has followed the "don't push until finished" approach. And lastly is just for ease of use. The developers can easily just commit and push on their branch at any time without consequence(as they do today, in their SVN branches). Is there a better way to handle this scenario that I may be missing? I just want a veteran's opinion before moving forward with the strategy. For bug fixes we like the general workflow of mecurial, anonymous branches that only consist of 1-2 commits. The simplicity is great for those cases. By the way, I've read this , great article which seems to favor Named branches.

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  • Does my TPL partitioner cause a deadlock?

    - by Scott Chamberlain
    I am starting to write my first parallel applications. This partitioner will enumerate over a IDataReader pulling chunkSize records at a time from the data-source. protected class DataSourcePartitioner<object[]> : System.Collections.Concurrent.Partitioner<object[]> { private readonly System.Data.IDataReader _Input; private readonly int _ChunkSize; public DataSourcePartitioner(System.Data.IDataReader input, int chunkSize = 10000) : base() { if (chunkSize < 1) throw new ArgumentOutOfRangeException("chunkSize"); _Input = input; _ChunkSize = chunkSize; } public override bool SupportsDynamicPartitions { get { return true; } } public override IList<IEnumerator<object[]>> GetPartitions(int partitionCount) { var dynamicPartitions = GetDynamicPartitions(); var partitions = new IEnumerator<object[]>[partitionCount]; for (int i = 0; i < partitionCount; i++) { partitions[i] = dynamicPartitions.GetEnumerator(); } return partitions; } public override IEnumerable<object[]> GetDynamicPartitions() { return new ListDynamicPartitions(_Input, _ChunkSize); } private class ListDynamicPartitions : IEnumerable<object[]> { private System.Data.IDataReader _Input; int _ChunkSize; private object _ChunkLock = new object(); public ListDynamicPartitions(System.Data.IDataReader input, int chunkSize) { _Input = input; _ChunkSize = chunkSize; } public IEnumerator<object[]> GetEnumerator() { while (true) { List<object[]> chunk = new List<object[]>(_ChunkSize); lock(_Input) { for (int i = 0; i < _ChunkSize; ++i) { if (!_Input.Read()) break; var values = new object[_Input.FieldCount]; _Input.GetValues(values); chunk.Add(values); } if (chunk.Count == 0) yield break; } var chunkEnumerator = chunk.GetEnumerator(); lock(_ChunkLock) //Will this cause a deadlock? { while (chunkEnumerator.MoveNext()) { yield return chunkEnumerator.Current; } } } } IEnumerator IEnumerable.GetEnumerator() { return ((IEnumerable<object[]>)this).GetEnumerator(); } } } I wanted IEnumerable object it passed back to be thread safe (the .Net example was so I am assuming PLINQ and TPL could need it) will the lock on _ChunkLock near the bottom help provide thread safety or will it cause a deadlock? From the documentation I could not tell if the lock would be released on the yeld return. Also if there is built in functionality to .net that will do what I am trying to do I would much rather use that. And if you find any other problems with the code I would appreciate it.

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  • SQL Server architecture guidance

    - by Liam
    Hi, We are designing a new version of our existing product on a new schema. Its an internal web application with possibly 100 concurrent users (max)This will run on a SQL Server 2008 database. On of the discussion items recently is whether we should have a single database of split the database for performance reasons across 2 separate databases. The database could grow anywhere from 50-100GB over 5 years. We are Developers and not DBAs so it would be nice to get some general guidance. [I know the answer is not simple as it depends on the schema, archiving policy, amount of data etc. ] Option 1 Single Main Database [This is my preferred option]. The plan would be to have all the tables in a single database and possibly to use file groups and partitioning to separate the data if required across multiple disks. [Use schema if appropriate]. This should deal with the performance concerns One of the comments wrt this was that the a single server instance would still be processing this data so there would still be a processing bottle neck. For reporting we could have a separate reporting DB but this is still being discussed. Option 2 Split the database into 2 separate databases DB1 - Customers, Accounts, Customer resources etc DB2 - This would contain the bulk of the data [i.e. Vehicle tracking data, financial transaction tables etc]. These tables would typically contain a lot of data. [It could reside on a separate server if required] This plan would involve keeping the main data in a smaller database [DB1] and retaining the [mainly] read only transaction type data in a separate DB [DB2]. The UI would mainly read from DB1 and thus be more responsive. [I'm aware that this option makes it harder for Referential Integrity to be enforced.] Points for consideration As we are at the design stage we can at least make proper use of indexes to deal performance issues so thats why option 1 to me is attractive and its more of a standard approach. For both options we are considering implementing an archiving database. Apologies for the long Question. In summary the question is 1 DB or 2? Thanks in advance, Liam

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  • SQL Server - Get Inserted Record Identity Value when Using a View's Instead Of Trigger

    - by CuppM
    For several tables that have identity fields, we are implementing a Row Level Security scheme using Views and Instead Of triggers on those views. Here is a simplified example structure: -- Table CREATE TABLE tblItem ( ItemId int identity(1,1) primary key, Name varchar(20) ) go -- View CREATE VIEW vwItem AS SELECT * FROM tblItem -- RLS Filtering Condition go -- Instead Of Insert Trigger CREATE TRIGGER IO_vwItem_Insert ON vwItem INSTEAD OF INSERT AS BEGIN -- RLS Security Checks on inserted Table -- Insert Records Into Table INSERT INTO tblItem (Name) SELECT Name FROM inserted; END go If I want to insert a record and get its identity, before implementing the RLS Instead Of trigger, I used: DECLARE @ItemId int; INSERT INTO tblItem (Name) VALUES ('MyName'); SELECT @ItemId = SCOPE_IDENTITY(); With the trigger, SCOPE_IDENTITY() no longer works - it returns NULL. I've seen suggestions for using the OUTPUT clause to get the identity back, but I can't seem to get it to work the way I need it to. If I put the OUTPUT clause on the view insert, nothing is ever entered into it. -- Nothing is added to @ItemIds DECLARE @ItemIds TABLE (ItemId int); INSERT INTO vwItem (Name) OUTPUT INSERTED.ItemId INTO @ItemIds VALUES ('MyName'); If I put the OUTPUT clause in the trigger on the INSERT statement, the trigger returns the table (I can view it from SQL Management Studio). I can't seem to capture it in the calling code; either by using an OUTPUT clause on that call or using a SELECT * FROM (). -- Modified Instead Of Insert Trigger w/ Output CREATE TRIGGER IO_vwItem_Insert ON vwItem INSTEAD OF INSERT AS BEGIN -- RLS Security Checks on inserted Table -- Insert Records Into Table INSERT INTO tblItem (Name) OUTPUT INSERTED.ItemId SELECT Name FROM inserted; END go -- Calling Code INSERT INTO vwItem (Name) VALUES ('MyName'); The only thing I can think of is to use the IDENT_CURRENT() function. Since that doesn't operate in the current scope, there's an issue of concurrent users inserting at the same time and messing it up. If the entire operation is wrapped in a transaction, would that prevent the concurrency issue? BEGIN TRANSACTION DECLARE @ItemId int; INSERT INTO tblItem (Name) VALUES ('MyName'); SELECT @ItemId = IDENT_CURRENT('tblItem'); COMMIT TRANSACTION Does anyone have any suggestions on how to do this better? I know people out there who will read this and say "Triggers are EVIL, don't use them!" While I appreciate your convictions, please don't offer that "suggestion".

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  • How to create a database deadlock using jdbc and JUNIT

    - by Isawpalmetto
    I am trying to create a database deadlock and I am using JUnit. I have two concurrent tests running which are both updating the same row in a table over and over again in a loop. My idea is that you update say row A in Table A and then row B in Table B over and over again in one test. Then at the same time you update row B table B and then row A Table A over and over again. From my understanding this should eventually result in a deadlock. Here is the code For the first test. public static void testEditCC() { try{ int rows = 0; int counter = 0; int large=10000000; Connection c=DataBase.getConnection(); while(counter<large) { int pid = 87855; int cCode = 655; String newCountry="Egypt"; int bpl = 0; stmt = c.createStatement(); rows = stmt.executeUpdate("UPDATE main " + //create lock on main table "SET BPL="+cCode+ "WHERE ID="+pid); rows = stmt.executeUpdate("UPDATE BPL SET DESCRIPTION='SomeWhere' WHERE ID=602"); //create lock on bpl table counter++; } assertTrue(rows == 1); //rows = stmt.executeUpdate("Insert into BPL (ID, DESCRIPTION) VALUES ("+cCode+", '"+newCountry+"')"); } catch(SQLException ex) { ex.printStackTrace(); //ex.getMessage(); } } And here is the code for the second test. public static void testEditCC() { try{ int rows = 0; int counter = 0; int large=10000000; Connection c=DataBase.getConnection(); while(counter<large) { int pid = 87855; int cCode = 655; String newCountry="Jordan"; int bpl = 0; stmt = c.createStatement(); //stmt.close(); rows = stmt.executeUpdate("UPDATE BPL SET DESCRIPTION='SomeWhere' WHERE ID=602"); //create lock on bpl table rows = stmt.executeUpdate("UPDATE main " + //create lock on main table "SET BPL="+cCode+ "WHERE ID="+pid); counter++; } assertTrue(rows == 1); //rows = stmt.executeUpdate("Insert into BPL (ID, DESCRIPTION) VALUES ("+cCode+", '"+newCountry+"')"); } catch(SQLException ex) { ex.printStackTrace(); } } I am running these two separate JUnit tests at the same time and am connecting to an apache Derby database that I am running in network mode within Eclipse. Can anyone help me figure out why a deadlock is not occurring? Perhaps I am using JUnit wrong.

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  • Random generates same number in java

    - by user1613360
    This is my java code. import java.io.*; import java.util.*; import java.util.concurrent.TimeUnit; class search { private int numelem; private int[] input=new int[100]; public void setNumofelem() { System.out.println("Enter the total numebr of elements"); Scanner yz=new Scanner(System.in); numelem=yz.nextInt(); } public void randomnumber() throws Exception { int max=500,min=1,n=numelem; Random rand = new Random(); for (int j=0;j < n;j++) { input[j]=rand.nextInt(max)+1; } } public void printinput() { int b=numelem,t=0; while(true) if(b!=0) { System.out.print(" "+input[t]); b--; t++; } else break; } } public class mycode { public static void main(String args[]) throws Exception { search a=new search(); a.setNumofelem(); a.randomnumber(); a.printinput(); } } Now the function randomnumber() just returns the same number.The function executes perfectly if I execute it as a separate java program but fails miserably if I call it using an object.I have also tried the following variations but nothing works everything return the same number. Variation 1: public void randomnumber() throws Exception { int max=500,min=1,n=numelem; Random rand = new Random(); for (int j=0;j < n;j++) { TimeUnit.SECONDS.sleep(1); input[j]=rand.nextInt(max)+1; } } Variation 2: public void randomnumber() throws Exception { int max=500,min=1,n=numelem; Random rand = new Random(); for (int j=0;j < n;j++) { rand.setSeed(System.nanoTime()); input[j]=rand.nextInt(max)+1; } } Variation 3: public void randomnumber() throws Exception { int max=500,min=1,n=numelem; Random rand = new Random(); for (int j=0;j < n;j++) { TimeUnit.SECONDS.sleep(1); rand.setSeed(System.nanoTime()); input[j]=rand.nextInt(max)+1; } } Sample input/Output: Enter the number of elements: 5 23 23 23 23 23 23

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  • Java Flow Control Problem

    - by Kyle_Solo
    I am programming a simple 2d game engine. I've decided how I'd like the engine to function: it will be composed of objects containing "events" that my main game loop will trigger when appropriate. A little more about the structure: Every GameObject has an updateEvent method. objectList is a list of all the objects that will receive update events. Only objects on this list have their updateEvent method called by the game loop. I’m trying to implement this method in the GameObject class (This specification is what I’d like the method to achieve): /** * This method removes a GameObject from objectList. The GameObject * should immediately stop executing code, that is, absolutely no more * code inside update events will be executed for the removed game object. * If necessary, control should transfer to the game loop. * @param go The GameObject to be removed */ public void remove(GameObject go) So if an object tries to remove itself inside of an update event, control should transfer back to the game engine: public void updateEvent() { //object's update event remove(this); System.out.println("Should never reach here!"); } Here’s what I have so far. It works, but the more I read about using exceptions for flow control the less I like it, so I want to see if there are alternatives. Remove Method public void remove(GameObject go) { //add to removedList //flag as removed //throw an exception if removing self from inside an updateEvent } Game Loop for(GameObject go : objectList) { try { if (!go.removed) { go.updateEvent(); } else { //object is scheduled to be removed, do nothing } } catch(ObjectRemovedException e) { //control has been transferred back to the game loop //no need to do anything here } } // now remove the objects that are in removedList from objectList 2 questions: Am I correct in assuming that the only way to implement the stop-right-away part of the remove method as described above is by throwing a custom exception and catching it in the game loop? (I know, using exceptions for flow control is like goto, which is bad. I just can’t think of another way to do what I want!) For the removal from the list itself, it is possible for one object to remove one that is farther down on the list. Currently I’m checking a removed flag before executing any code, and at the end of each pass removing the objects to avoid concurrent modification. Is there a better, preferably instant/non-polling way to do this?

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  • SwingWorker exceptions lost even when using wrapper classes

    - by Ti Strga
    I've been struggling with the usability problem of SwingWorker eating any exceptions thrown in the background task, for example, described on this SO thread. That thread gives a nice description of the problem, but doesn't discuss recovering the original exception. The applet I've been handed needs to propagate the exception upwards. But I haven't been able to even catch it. I'm using the SimpleSwingWorker wrapper class from this blog entry specifically to try and address this issue. It's a fairly small class but I'll repost it at the end here just for reference. The calling code looks broadly like try { // lots of code here to prepare data, finishing with SpecialDataHelper helper = new SpecialDataHelper(...stuff...); helper.execute(); } catch (Throwable e) { // used "Throwable" here in desperation to try and get // anything at all to match, including unchecked exceptions // // no luck, this code is never ever used :-( } The wrappers: class SpecialDataHelper extends SimpleSwingWorker { public SpecialDataHelper (SpecialData sd) { this.stuff = etc etc etc; } public Void doInBackground() throws Exception { OurCodeThatThrowsACheckedException(this.stuff); return null; } protected void done() { // called only when successful // never reached if there's an error } } The feature of SimpleSwingWorker is that the actual SwingWorker's done()/get() methods are automatically called. This, in theory, rethrows any exceptions that happened in the background. In practice, nothing is ever caught, and I don't even know why. The SimpleSwingWorker class, for reference, and with nothing elided for brevity: import java.util.concurrent.ExecutionException; import javax.swing.SwingWorker; /** * A drop-in replacement for SwingWorker<Void,Void> but will not silently * swallow exceptions during background execution. * * Taken from http://jonathangiles.net/blog/?p=341 with thanks. */ public abstract class SimpleSwingWorker { private final SwingWorker<Void,Void> worker = new SwingWorker<Void,Void>() { @Override protected Void doInBackground() throws Exception { SimpleSwingWorker.this.doInBackground(); return null; } @Override protected void done() { // Exceptions are lost unless get() is called on the // originating thread. We do so here. try { get(); } catch (final InterruptedException ex) { throw new RuntimeException(ex); } catch (final ExecutionException ex) { throw new RuntimeException(ex.getCause()); } SimpleSwingWorker.this.done(); } }; public SimpleSwingWorker() {} protected abstract Void doInBackground() throws Exception; protected abstract void done(); public void execute() { worker.execute(); } }

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  • Parallelism in .NET – Part 14, The Different Forms of Task

    - by Reed
    Before discussing Task creation and actual usage in concurrent environments, I will briefly expand upon my introduction of the Task class and provide a short explanation of the distinct forms of Task.  The Task Parallel Library includes four distinct, though related, variations on the Task class. In my introduction to the Task class, I focused on the most basic version of Task.  This version of Task, the standard Task class, is most often used with an Action delegate.  This allows you to implement for each task within the task decomposition as a single delegate. Typically, when using the new threading constructs in .NET 4 and the Task Parallel Library, we use lambda expressions to define anonymous methods.  The advantage of using a lambda expression is that it allows the Action delegate to directly use variables in the calling scope.  This eliminates the need to make separate Task classes for Action<T>, Action<T1,T2>, and all of the other Action<…> delegate types.  As an example, suppose we wanted to make a Task to handle the ”Show Splash” task from our earlier decomposition.  Even if this task required parameters, such as a message to display, we could still use an Action delegate specified via a lambda: // Store this as a local variable string messageForSplashScreen = GetSplashScreenMessage(); // Create our task Task showSplashTask = new Task( () => { // We can use variables in our outer scope, // as well as methods scoped to our class! this.DisplaySplashScreen(messageForSplashScreen); }); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This provides a huge amount of flexibility.  We can use this single form of task for any task which performs an operation, provided the only information we need to track is whether the task has completed successfully or not.  This leads to my first observation: Use a Task with a System.Action delegate for any task for which no result is generated. This observation leads to an obvious corollary: we also need a way to define a task which generates a result.  The Task Parallel Library provides this via the Task<TResult> class. Task<TResult> subclasses the standard Task class, providing one additional feature – the ability to return a value back to the user of the task.  This is done by switching from providing an Action delegate to providing a Func<TResult> delegate.  If we decompose our problem, and we realize we have one task where its result is required by a future operation, this can be handled via Task<TResult>.  For example, suppose we want to make a task for our “Check for Update” task, we could do: Task<bool> checkForUpdateTask = new Task<bool>( () => { return this.CheckWebsiteForUpdate(); }); Later, we would start this task, and perform some other work.  At any point in the future, we could get the value from the Task<TResult>.Result property, which will cause our thread to block until the task has finished processing: // This uses Task<bool> checkForUpdateTask generated above... // Start the task, typically on a background thread checkForUpdateTask.Start(); // Do some other work on our current thread this.DoSomeWork(); // Discover, from our background task, whether an update is available // This will block until our task completes bool updateAvailable = checkForUpdateTask.Result; This leads me to my second observation: Use a Task<TResult> with a System.Func<TResult> delegate for any task which generates a result. Task and Task<TResult> provide a much cleaner alternative to the previous Asynchronous Programming design patterns in the .NET framework.  Instead of trying to implement IAsyncResult, and providing BeginXXX() and EndXXX() methods, implementing an asynchronous programming API can be as simple as creating a method that returns a Task or Task<TResult>.  The client side of the pattern also is dramatically simplified – the client can call a method, then either choose to call task.Wait() or use task.Result when it needs to wait for the operation’s completion. While this provides a much cleaner model for future APIs, there is quite a bit of infrastructure built around the current Asynchronous Programming design patterns.  In order to provide a model to work with existing APIs, two other forms of Task exist.  There is a constructor for Task which takes an Action<Object> and a state parameter.  In addition, there is a constructor for creating a Task<TResult> which takes a Func<Object, TResult> as well as a state parameter.  When using these constructors, the state parameter is stored in the Task.AsyncState property. While these two overloads exist, and are usable directly, I strongly recommend avoiding this for new development.  The two forms of Task which take an object state parameter exist primarily for interoperability with traditional .NET Asynchronous Programming methodologies.  Using lambda expressions to capture variables from the scope of the creator is a much cleaner approach than using the untyped state parameters, since lambda expressions provide full type safety without introducing new variables.

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  • Parallelism in .NET – Part 15, Making Tasks Run: The TaskScheduler

    - by Reed
    In my introduction to the Task class, I specifically made mention that the Task class does not directly provide it’s own execution.  In addition, I made a strong point that the Task class itself is not directly related to threads or multithreading.  Rather, the Task class is used to implement our decomposition of tasks.  Once we’ve implemented our tasks, we need to execute them.  In the Task Parallel Library, the execution of Tasks is handled via an instance of the TaskScheduler class. The TaskScheduler class is an abstract class which provides a single function: it schedules the tasks and executes them within an appropriate context.  This class is the class which actually runs individual Task instances.  The .NET Framework provides two (internal) implementations of the TaskScheduler class. Since a Task, based on our decomposition, should be a self-contained piece of code, parallel execution makes sense when executing tasks.  The default implementation of the TaskScheduler class, and the one most often used, is based on the ThreadPool.  This can be retrieved via the TaskScheduler.Default property, and is, by default, what is used when we just start a Task instance with Task.Start(). Normally, when a Task is started by the default TaskScheduler, the task will be treated as a single work item, and run on a ThreadPool thread.  This pools tasks, and provides Task instances all of the advantages of the ThreadPool, including thread pooling for reduced resource usage, and an upper cap on the number of work items.  In addition, .NET 4 brings us a much improved thread pool, providing work stealing and reduced locking within the thread pool queues.  By using the default TaskScheduler, our Tasks are run asynchronously on the ThreadPool. There is one notable exception to my above statements when using the default TaskScheduler.  If a Task is created with the TaskCreationOptions set to TaskCreationOptions.LongRunning, the default TaskScheduler will generate a new thread for that Task, at least in the current implementation.  This is useful for Tasks which will persist for most of the lifetime of your application, since it prevents your Task from starving the ThreadPool of one of it’s work threads. The Task Parallel Library provides one other implementation of the TaskScheduler class.  In addition to providing a way to schedule tasks on the ThreadPool, the framework allows you to create a TaskScheduler which works within a specified SynchronizationContext.  This scheduler can be retrieved within a thread that provides a valid SynchronizationContext by calling the TaskScheduler.FromCurrentSynchronizationContext() method. This implementation of TaskScheduler is intended for use with user interface development.  Windows Forms and Windows Presentation Foundation both require any access to user interface controls to occur on the same thread that created the control.  For example, if you want to set the text within a Windows Forms TextBox, and you’re working on a background thread, that UI call must be marshaled back onto the UI thread.  The most common way this is handled depends on the framework being used.  In Windows Forms, Control.Invoke or Control.BeginInvoke is most often used.  In WPF, the equivelent calls are Dispatcher.Invoke or Dispatcher.BeginInvoke. As an example, say we’re working on a background thread, and we want to update a TextBlock in our user interface with a status label.  The code would typically look something like: // Within background thread work... string status = GetUpdatedStatus(); Dispatcher.BeginInvoke(DispatcherPriority.Normal, new Action( () => { statusLabel.Text = status; })); // Continue on in background method .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This works fine, but forces your method to take a dependency on WPF or Windows Forms.  There is an alternative option, however.  Both Windows Forms and WPF, when initialized, setup a SynchronizationContext in their thread, which is available on the UI thread via the SynchronizationContext.Current property.  This context is used by classes such as BackgroundWorker to marshal calls back onto the UI thread in a framework-agnostic manner. The Task Parallel Library provides the same functionality via the TaskScheduler.FromCurrentSynchronizationContext() method.  When setting up our Tasks, as long as we’re working on the UI thread, we can construct a TaskScheduler via: TaskScheduler uiScheduler = TaskScheduler.FromCurrentSynchronizationContext(); We then can use this scheduler on any thread to marshal data back onto the UI thread.  For example, our code above can then be rewritten as: string status = GetUpdatedStatus(); (new Task(() => { statusLabel.Text = status; })) .Start(uiScheduler); // Continue on in background method This is nice since it allows us to write code that isn’t tied to Windows Forms or WPF, but is still fully functional with those technologies.  I’ll discuss even more uses for the SynchronizationContext based TaskScheduler when I demonstrate task continuations, but even without continuations, this is a very useful construct. In addition to the two implementations provided by the Task Parallel Library, it is possible to implement your own TaskScheduler.  The ParallelExtensionsExtras project within the Samples for Parallel Programming provides nine sample TaskScheduler implementations.  These include schedulers which restrict the maximum number of concurrent tasks, run tasks on a single threaded apartment thread, use a new thread per task, and more.

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  • Using SQL Source Control with Fortress or Vault &ndash; Part 2

    - by AjarnMark
    In Part 1, I started talking about using Red-Gate’s newest version of SQL Source Control and how I really like it as a viable method to source control your database development.  It looks like this is going to turn into a little series where I will explain how we have done things in the past, and how life is different with SQL Source Control.  I will also explain some of my philosophy and methodology around deployment with these tools.  But for now, let’s talk about some of the good and the bad of the tool itself. More Kudos and Features I mentioned previously how impressed I was with the responsiveness of Red-Gate’s team.  I have been having an ongoing email conversation with Gyorgy Pocsi, and as I have run into problems or requested things behave a little differently, it has not been more than a day or two before a new Build is ready for me to download and test.  Quite impressive! I’m sure much of the requests I put in were already in the plans, so I can’t really take credit for them, but throughout this conversation, Red-Gate has implemented several features that were not in the first Early Access version.  Those include: Honoring the Fortress configuration option to require Work Item (Bug) IDs on check-ins. Adding the check-in comment text as a comment to the Work Item. Adding the list of checked-in files, along with the Fortress links for automatic History and DIFF view Updating the status of a Work Item on check-in (e.g. setting the item to Complete or, in our case “Dev-Complete”) Support for the Fortress 2.0 API, and not just the Vault Pro 5.1 API.  (See later notes regarding support for Fortress 2.0). These were all features that I felt we really needed to have in-place before I could honestly consider converting my team to using SQL Source Control on a regular basis.  Now that I have those, my only excuse is not wanting to switch boats on the team mid-stream.  So when we wrap up our current release in a few weeks, we will make the jump.  In the meantime, I will continue to bang on it to make sure it is stable.  It passed one test for stability when I did a test load of one of our larger database schemas into Fortress with SQL Source Control.  That database has about 150 tables, 200 User-Defined Functions and nearly 900 Stored Procedures.  The initial load to source control went smoothly and took just a brief amount of time. Warnings Remember that this IS still in pre-release stage and while I have not had any problems after that first hiccup I wrote about last time, you still need to treat it with a healthy respect.  As I understand it, the RTM is targeted for February.  There are a couple more features that I hope make it into the final release version, but if not, they’ll probably be coming soon thereafter.  Those are: A Browse feature to let me lookup the Work Item ID instead of having to remember it or look back in my Item details.  This is just a matter of convenience. I normally have my Work Item list open anyway, so I can easily look it up, but hey, why not make it even easier. A multi-line comment area.  The current space for writing check-in comments is a single-line text box.  I would like to have a multi-line space as I sometimes write lengthy commentary.  But I recognize that it is a struggle to get most developers to put in more than the word “fixed” as their comment, so this meets the need of the majority as-is, and it’s not a show-stopper for us. Merge.  SQL Source Control currently does not have a Merge feature.  If two or more people make changes to the same database object, you will get a warning of the conflict and have to choose which one wins (and then manually edit to include the others’ changes).  I think it unlikely you will run into actual conflicts in Stored Procedures and Functions, but you might with Views or Tables.  This will be nice to have, but I’m not losing any sleep over it.  And I have multiple tools at my disposal to do merges manually, so really not a show-stopper for us. Automation has its limits.  As cool as this automation is, it has its limits and there are some changes that you will be better off scripting yourself.  For example, if you are refactoring table definitions, and want to change a column name, you can write that as a quick sp_rename command and preserve the data within that column.  But because this tool is looking just at a before and after picture, it cannot tell that you just renamed a column.  To the tool, it looks like you dropped one column and added another.  This is not a knock against Red-Gate.  All automated scripting tools have this issue, unless the are actively monitoring your every step to know exactly what you are doing.  This means that when you go to Deploy your changes, SQL Compare will script the change as a column drop and add, or will attempt to rebuild the entire table.  Unfortunately, neither of these approaches will preserve the existing data in that column the way an sp_rename will, and so you are better off scripting that change yourself.  Thankfully, SQL Compare will produce warnings about the potential loss of data before it does the actual synchronization and give you a chance to intercept the script and do it yourself. Also, please note that the current official word is that SQL Source Control supports Vault Professional 5.1 and later.  Vault Professional is the new name for what was previously known as Fortress.  (You can read about the name change on SourceGear’s site.)  The last version of Fortress was 2.x, and the API for Fortress 2.x is different from the API for Vault Pro.  At my company, we are currently running Fortress 2.0, with plans to upgrade to Vault Pro early next year.  Gyorgy was able to come up with a work-around for me to be able to use SQL Source Control with Fortress 2.0, even though it is not officially supported.  If you are using Fortress 2.0 and want to use SQL Source Control, be aware that this is not officially supported, but it is working for us, and you can probably get the work-around instructions from Red-Gate if you’re really, really nice to them. Upcoming Topics Some of the other topics I will likely cover in this series over the next few weeks are: How we used to do source control back in the old days (a few weeks ago) before SQL Source Control was available to Vault users What happens when you restore a database that is linked to source control Handling multiple development branches of source code Concurrent Development practices and handling Conflicts Deployment Tips and Best Practices A recap after using the tool for a while

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  • General monitoring for SQL Server Analysis Services using Performance Monitor

    - by Testas
    A recent customer engagement required a setup of a monitoring solution for SSAS, due to the time restrictions placed upon this, native Windows Performance Monitor (Perfmon) and SQL Server Profiler Monitoring Tools was used as using a third party tool would have meant the customer providing an additional monitoring server that was not available.I wanted to outline the performance monitoring counters that was used to monitor the system on which SSAS was running. Due to the slow query performance that was occurring during certain scenarios, perfmon was used to establish if any pressure was being placed on the Disk, CPU or Memory subsystem when concurrent connections access the same query, and Profiler to pinpoint how the query was being managed within SSAS, profiler I will leave for another blogThis guide is not designed to provide a definitive list of what should be used when monitoring SSAS, different situations may require the addition or removal of counters as presented by the situation. However I hope that it serves as a good basis for starting your monitoring of SSAS. I would also like to acknowledge Chris Webb’s awesome chapters from “Expert Cube Development” that also helped shape my monitoring strategy:http://cwebbbi.spaces.live.com/blog/cns!7B84B0F2C239489A!6657.entrySimulating ConnectionsTo simulate the additional connections to the SSAS server whilst monitoring, I used ascmd to simulate multiple connections to the typical and worse performing queries that were identified by the customer. A similar sript can be downloaded from codeplex at http://www.codeplex.com/SQLSrvAnalysisSrvcs.     File name: ASCMD_StressTestingScripts.zip. Performance MonitorWithin performance monitor,  a counter log was created that contained the list of counters below. The important point to note when running the counter log is that the RUN AS property within the counter log properties should be changed to an account that has rights to the SSAS instance when monitoring MSAS counters. Failure to do so means that the counter log runs under the system account, no errors or warning are given while running the counter log, and it is not until you need to view the MSAS counters that they will not be displayed if run under the default account that has no right to SSAS. If your connection simulation takes hours, this could prove quite frustrating if not done beforehand JThe counters used……  Object Counter Instance Justification System Processor Queue legnth N/A Indicates how many threads are waiting for execution against the processor. If this counter is consistently higher than around 5 when processor utilization approaches 100%, then this is a good indication that there is more work (active threads) available (ready for execution) than the machine's processors are able to handle. System Context Switches/sec N/A Measures how frequently the processor has to switch from user- to kernel-mode to handle a request from a thread running in user mode. The heavier the workload running on your machine, the higher this counter will generally be, but over long term the value of this counter should remain fairly constant. If this counter suddenly starts increasing however, it may be an indicating of a malfunctioning device, especially if the Processor\Interrupts/sec\(_Total) counter on your machine shows a similar unexplained increase Process % Processor Time sqlservr Definately should be used if Processor\% Processor Time\(_Total) is maxing at 100% to assess the effect of the SQL Server process on the processor Process % Processor Time msmdsrv Definately should be used if Processor\% Processor Time\(_Total) is maxing at 100% to assess the effect of the SQL Server process on the processor Process Working Set sqlservr If the Memory\Available bytes counter is decreaing this counter can be run to indicate if the process is consuming larger and larger amounts of RAM. Process(instance)\Working Set measures the size of the working set for each process, which indicates the number of allocated pages the process can address without generating a page fault. Process Working Set msmdsrv If the Memory\Available bytes counter is decreaing this counter can be run to indicate if the process is consuming larger and larger amounts of RAM. Process(instance)\Working Set measures the size of the working set for each process, which indicates the number of allocated pages the process can address without generating a page fault. Processor % Processor Time _Total and individual cores measures the total utilization of your processor by all running processes. If multi-proc then be mindful only an average is provided Processor % Privileged Time _Total To see how the OS is handling basic IO requests. If kernel mode utilization is high, your machine is likely underpowered as it's too busy handling basic OS housekeeping functions to be able to effectively run other applications. Processor % User Time _Total To see how the applications is interacting from a processor perspective, a high percentage utilisation determine that the server is dealing with too many apps and may require increasing thje hardware or scaling out Processor Interrupts/sec _Total  The average rate, in incidents per second, at which the processor received and serviced hardware interrupts. Shoulr be consistant over time but a sudden unexplained increase could indicate a device malfunction which can be confirmed using the System\Context Switches/sec counter Memory Pages/sec N/A Indicates the rate at which pages are read from or written to disk to resolve hard page faults. This counter is a primary indicator of the kinds of faults that cause system-wide delays, this is the primary counter to watch for indication of possible insufficient RAM to meet your server's needs. A good idea here is to configure a perfmon alert that triggers when the number of pages per second exceeds 50 per paging disk on your system. May also want to see the configuration of the page file on the Server Memory Available Mbytes N/A is the amount of physical memory, in bytes, available to processes running on the computer. if this counter is greater than 10% of the actual RAM in your machine then you probably have more than enough RAM. monitor it regularly to see if any downward trend develops, and set an alert to trigger if it drops below 2% of the installed RAM. Physical Disk Disk Transfers/sec for each physical disk If it goes above 10 disk I/Os per second then you've got poor response time for your disk. Physical Disk Idle Time _total If Disk Transfers/sec is above  25 disk I/Os per second use this counter. which measures the percent time that your hard disk is idle during the measurement interval, and if you see this counter fall below 20% then you've likely got read/write requests queuing up for your disk which is unable to service these requests in a timely fashion. Physical Disk Disk queue legnth For the OLAP and SQL physical disk A value that is consistently less than 2 means that the disk system is handling the IO requests against the physical disk Network Interface Bytes Total/sec For the NIC Should be monitored over a period of time to see if there is anb increase/decrease in network utilisation Network Interface Current Bandwidth For the NIC is an estimate of the current bandwidth of the network interface in bits per second (BPS). MSAS 2005: Memory Memory Limit High KB N/A Shows (as a percentage) the high memory limit configured for SSAS in C:\Program Files\Microsoft SQL Server\MSAS10.MSSQLSERVER\OLAP\Config\msmdsrv.ini MSAS 2005: Memory Memory Limit Low KB N/A Shows (as a percentage) the low memory limit configured for SSAS in C:\Program Files\Microsoft SQL Server\MSAS10.MSSQLSERVER\OLAP\Config\msmdsrv.ini MSAS 2005: Memory Memory Usage KB N/A Displays the memory usage of the server process. MSAS 2005: Memory File Store KB N/A Displays the amount of memory that is reserved for the Cache. Note if total memory limit in the msmdsrv.ini is set to 0, no memory is reserved for the cache MSAS 2005: Storage Engine Query Queries from Cache Direct / sec N/A Displays the rate of queries answered from the cache directly MSAS 2005: Storage Engine Query Queries from Cache Filtered / Sec N/A Displays the Rate of queries answered by filtering existing cache entry. MSAS 2005: Storage Engine Query Queries from File / Sec N/A Displays the Rate of queries answered from files. MSAS 2005: Storage Engine Query Average time /query N/A Displays the average time of a query MSAS 2005: Connection Current connections N/A Displays the number of connections against the SSAS instance MSAS 2005: Connection Requests / sec N/A Displays the rate of query requests per second MSAS 2005: Locks Current Lock Waits N/A Displays thhe number of connections waiting on a lock MSAS 2005: Threads Query Pool job queue Length N/A The number of queries in the job queue MSAS 2005:Proc Aggregations Temp file bytes written/sec N/A Shows the number of bytes of data processed in a temporary file MSAS 2005:Proc Aggregations Temp file rows written/sec N/A Shows the number of bytes of data processed in a temporary file 

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  • SPARC T3-1 Record Results Running JD Edwards EnterpriseOne Day in the Life Benchmark with Added Batch Component

    - by Brian
    Using Oracle's SPARC T3-1 server for the application tier and Oracle's SPARC Enterprise M3000 server for the database tier, a world record result was produced running the Oracle's JD Edwards EnterpriseOne applications Day in the Life benchmark run concurrently with a batch workload. The SPARC T3-1 server based result has 25% better performance than the IBM Power 750 POWER7 server even though the IBM result did not include running a batch component. The SPARC T3-1 server based result has 25% better space/performance than the IBM Power 750 POWER7 server as measured by the online component. The SPARC T3-1 server based result is 5x faster than the x86-based IBM x3650 M2 server system when executing the online component of the JD Edwards EnterpriseOne 9.0.1 Day in the Life benchmark. The IBM result did not include a batch component. The SPARC T3-1 server based result has 2.5x better space/performance than the x86-based IBM x3650 M2 server as measured by the online component. The combination of SPARC T3-1 and SPARC Enterprise M3000 servers delivered a Day in the Life benchmark result of 5000 online users with 0.875 seconds of average transaction response time running concurrently with 19 Universal Batch Engine (UBE) processes at 10 UBEs/minute. The solution exercises various JD Edwards EnterpriseOne applications while running Oracle WebLogic Server 11g Release 1 and Oracle Web Tier Utilities 11g HTTP server in Oracle Solaris Containers, together with the Oracle Database 11g Release 2. The SPARC T3-1 server showed that it could handle the additional workload of batch processing while maintaining the same number of online users for the JD Edwards EnterpriseOne Day in the Life benchmark. This was accomplished with minimal loss in response time. JD Edwards EnterpriseOne 9.0.1 takes advantage of the large number of compute threads available in the SPARC T3-1 server at the application tier and achieves excellent response times. The SPARC T3-1 server consolidates the application/web tier of the JD Edwards EnterpriseOne 9.0.1 application using Oracle Solaris Containers. Containers provide flexibility, easier maintenance and better CPU utilization of the server leaving processing capacity for additional growth. A number of Oracle advanced technology and features were used to obtain this result: Oracle Solaris 10, Oracle Solaris Containers, Oracle Java Hotspot Server VM, Oracle WebLogic Server 11g Release 1, Oracle Web Tier Utilities 11g, Oracle Database 11g Release 2, the SPARC T3 and SPARC64 VII+ based servers. This is the first published result running both online and batch workload concurrently on the JD Enterprise Application server. No published results are available from IBM running the online component together with a batch workload. The 9.0.1 version of the benchmark saw some minor performance improvements relative to 9.0. When comparing between 9.0.1 and 9.0 results, the reader should take this into account when the difference between results is small. Performance Landscape JD Edwards EnterpriseOne Day in the Life Benchmark Online with Batch Workload This is the first publication on the Day in the Life benchmark run concurrently with batch jobs. The batch workload was provided by Oracle's Universal Batch Engine. System RackUnits Online Users Resp Time (sec) BatchConcur(# of UBEs) BatchRate(UBEs/m) Version SPARC T3-1, 1xSPARC T3 (1.65 GHz), Solaris 10 M3000, 1xSPARC64 VII+ (2.86 GHz), Solaris 10 4 5000 0.88 19 10 9.0.1 Resp Time (sec) — Response time of online jobs reported in seconds Batch Concur (# of UBEs) — Batch concurrency presented in the number of UBEs Batch Rate (UBEs/m) — Batch transaction rate in UBEs/minute. JD Edwards EnterpriseOne Day in the Life Benchmark Online Workload Only These results are for the Day in the Life benchmark. They are run without any batch workload. System RackUnits Online Users ResponseTime (sec) Version SPARC T3-1, 1xSPARC T3 (1.65 GHz), Solaris 10 M3000, 1xSPARC64 VII (2.75 GHz), Solaris 10 4 5000 0.52 9.0.1 IBM Power 750, 1xPOWER7 (3.55 GHz), IBM i7.1 4 4000 0.61 9.0 IBM x3650M2, 2xIntel X5570 (2.93 GHz), OVM 2 1000 0.29 9.0 IBM result from http://www-03.ibm.com/systems/i/advantages/oracle/, IBM used WebSphere Configuration Summary Hardware Configuration: 1 x SPARC T3-1 server 1 x 1.65 GHz SPARC T3 128 GB memory 16 x 300 GB 10000 RPM SAS 1 x Sun Flash Accelerator F20 PCIe Card, 92 GB 1 x 10 GbE NIC 1 x SPARC Enterprise M3000 server 1 x 2.86 SPARC64 VII+ 64 GB memory 1 x 10 GbE NIC 2 x StorageTek 2540 + 2501 Software Configuration: JD Edwards EnterpriseOne 9.0.1 with Tools 8.98.3.3 Oracle Database 11g Release 2 Oracle 11g WebLogic server 11g Release 1 version 10.3.2 Oracle Web Tier Utilities 11g Oracle Solaris 10 9/10 Mercury LoadRunner 9.10 with Oracle Day in the Life kit for JD Edwards EnterpriseOne 9.0.1 Oracle’s Universal Batch Engine - Short UBEs and Long UBEs Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and other manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE workload of 15 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large UBEs, and the QPROCESS queue for short UBEs run concurrently. One of the Oracle Solaris Containers ran 4 Long UBEs, while another Container ran 15 short UBEs concurrently. The mixed size UBEs ran concurrently from the SPARC T3-1 server with the 5000 online users driven by the LoadRunner. Oracle’s UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers and two Oracle Fusion Middleware WebLogic Servers 11g R1 coupled with two Oracle Fusion Middleware 11g Web Tier HTTP Server instances on the SPARC T3-1 server were hosted in four separate Oracle Solaris Containers to demonstrate consolidation of multiple application and web servers. See Also SPARC T3-1 oracle.com SPARC Enterprise M3000 oracle.com Oracle Solaris oracle.com JD Edwards EnterpriseOne oracle.com Oracle Database 11g Release 2 Enterprise Edition oracle.com Disclosure Statement Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 6/27/2011.

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  • Apache doesn't run multiple requests

    - by Reinderien
    I'm currently running this simple Python CGI script to test rudimentary IPC: #!/usr/bin/python -u import cgi, errno, fcntl, os, os.path, sys, time print("""Content-Type: text/html; charset=utf-8 <!doctype html> <html lang="en"> <head> <meta charset="utf-8" /> <title>IPC test</title> </head> <body> """) ftempname = '/tmp/ipc-messages' master = not os.path.exists(ftempname) if master: fmode = 'w' else: fmode = 'r' print('<p>Opening file</p>') sys.stdout.flush() ftemp = open(ftempname, fmode) print('<p>File opened</p>') if master: print('<p>Operating as master</p>') sys.stdout.flush() for i in range(10): print('<p>' + str(i) + '</p>') sys.stdout.flush() time.sleep(1) ftemp.close() os.remove(ftempname) else: print('<p>Operating as a slave</p>') ftemp.close() print(""" </body> </html>""") The 'server-push' portion works; that is, for the first request, I do see piecewise updates. However, while the first request is being serviced, subsequent requests are not started, only to be started after the first request has finished. Any ideas on why, and how to fix it? Edit: I see the same non-concurrent behaviour with vanilla PHP, running this: <!doctype html> <html lang="en"> <!-- $Id: $--> <head> <meta charset="utf-8" /> <title>IPC test</title> </head> <body> <p> <?php function echofl($str) { echo $str . "</b>\n"; ob_flush(); flush(); } define('tempfn', '/tmp/emailsync'); if (file_exists(tempfn)) $perms = 'r+'; else $perms = 'w'; assert($fsync = fopen(tempfn, $perms)); assert(chmod(tempfn, 0600)); if (!flock($fsync, LOCK_EX | LOCK_NB, $wouldblock)) { assert($wouldblock); $master = false; } else $master = true; if ($master) { echofl('Running as master.'); assert(fwrite($fsync, 'content') != false); assert(sleep(5) == 0); assert(flock($fsync, LOCK_UN)); } else { echofl('Running as slave.'); echofl(fgets($fsync)); } assert(fclose($fsync)); echofl('Done.'); ?> </p> </body> </html>

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  • Is the Cloud ready for an Enterprise Java web application? Seeking a JEE hosting advice.

    - by Jakub Holý
    Greetings to all the smart people around here! I'd like to ask whether it is feasible or a good idea at all to deploy a Java enterprise web application to a Cloud such as Amazon EC2. More exactly, I'm looking for infrastructure options for an application that shall handle few hundred users with long but neither CPU nor memory intensive sessions. I'm considering dedicated servers, virtual private servers (VPSs) and EC2. I've noticed that there is a project called JBoss Cloud so people are working on enabling such a deployment, on the other hand it doesn't seem to be mature yet and I'm not sure that the cloud is ready for this kind of applications, which differs from the typical cloud-based applications like Twitter. Would you recommend to deploy it to the cloud? What are the pros and cons? The application is a Java EE 5 web application whose main function is to enable users to compose their own customized Product by combining the available Parts. It uses stateless and stateful session beans and JPA for persistence of entities to a RDBMS and fetches information about Parts from the company's inventory system via a web service. Aside of external users it's used also by few internal ones, who are authenticated against the company's LDAP. The application should handle around 300-400 concurrent users building their product and should be reasonably scalable and available though these qualities are only of a medium importance at this stage. I've proposed an architecture consisting of a firewall (FW) and load balancer supporting sticky sessions and https (in the Cloud this would be replaced with EC2's Elastic Load Balancing service and FW on the app. servers, in a physical architecture the load-balancer would be a HW), then two physical clustered application servers combined with web servers (so that if one fails, a user doesn't loose his/her long built product) and finally a database server. The DB server would need a slave backup instance that can replace the master instance if it fails. This should provide reasonable availability and fault tolerance and provide good scalability as long as a single RDBMS can keep with the load, which should be OK for quite a while because most of the operations are done in the memory using a stateful bean and only occasionally stored or retrieved from the DB and the amount of data is low too. A problematic part could be the dependency on the remote inventory system webservice but with good caching of its outputs in the application it should be OK too. Unfortunately I've only vague idea of the system resources (memory size, number and speed of CPUs/cores) that such an "average Java EE application" for few hundred users needs. My rough and mostly unfounded estimate based on actual Amazon offerings is that 1.7GB and a single, 2-core "modern CPU" with speed around 2.5GHz (the High-CPU Medium Instance) should be sufficient for any of the two application servers (since we can handle higher load by provisioning more of them). Alternatively I would consider using the Large instance (64b, 7.5GB RAM, 2 cores at 1GHz) So my question is whether such a deployment to the cloud is technically and financially feasible or whether dedicated/VPS servers would be a better option and whether there are some real-world experiences with something similar. Thank you very much! /Jakub Holy PS: I've found the JBoss EAP in a Cloud Case Study that shows that it is possible to deploy a real-world Java EE application to the EC2 cloud but unfortunately there're no details regarding topology, instance types, or anything :-(

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  • mod_mono 'Service Temporarily Unavailable' issue

    - by Charlie Somerville
    I've deployed an ASP.NET web application on a Linux (Debian) server running Apache 2.2 and mod_mono 1.9 It's working well, however Mono occasionally segfaults and uses the entire CPU which causes the website to stop working and display 'Service Temporarily Unavailable' Killing mono fixes it, but obviously this isn't a good solution. I tailed the system log after this happened and I saw the following error messages from the kernel: Apr 20 01:49:37 charliesomerville kernel: [1596436.204158] mono[17909]: segfault at b645f671 ip b645f671 sp b4ffb604 error 4<6>mono[19047]: segfault at b645f66e ip b645f66e sp b4bf7604 error 4<6>mono[18017]: segfault at b645f66e ip b645f66e sp b52fe604 error 4<6>mono[19668]: segfault at b645f5e6 ip b645f5e6 sp b48f4604 error 4<6>mono[22565]: segfault at b645f674 ip b645f674 sp b45f1604 error 4<6>mono[17700]: segfault at b645f661 ip b645f661 sp b51fd604 error 4<6>mono[19596]: segfault at b645f5e6 ip b645f5e6 sp b49f5604 error 4 Apr 20 01:49:37 charliesomerville kernel: [1596436.208172] mono[23219]: segfault at b645f66e ip b645f66e sp b44f0604 error 4 At the end of Apache's error.log are the following errors: [Tue Apr 20 03:10:23 2010] [error] (70014)End of file found: read_data failed [Tue Apr 20 03:10:23 2010] [error] Command stream corrupted, last command was 1 [Tue Apr 20 03:10:23 2010] [error] Command stream corrupted, last command was 1 [Tue Apr 20 03:10:23 2010] [error] Command stream corrupted, last command was 1 System.ArgumentNullException: null key Parameter name: key at System.Collections.Hashtable.get_Item (System.Object key) [0x00000] at System.Runtime.Serialization.SerializationCallbacks.GetSerializationCallbacks (System.Type t) [0x00000] at System.Runtime.Serialization.ObjectManager.RaiseOnDeserializingEvent (System.Object obj) [0x00000] at System.Runtime.Serialization.Formatters.Binary.ObjectReader.ReadObjectContent (System.IO.BinaryReader reader, System.Runtime.Serialization.Formatters.Binary.TypeMetadata metadata, Int64 objectId, System.Object& objectInstance, System.Runtime.Serialization.SerializationInfo& info) [0x00000] at System.Runtime.Serialization.Formatters.Binary.ObjectReader.ReadObjectInstance (System.IO.BinaryReader reader, Boolean isRuntimeObject, Boolean hasTypeInfo, System.Int64& objectId, System.Object& value, System.Runtime.Serialization.SerializationInfo& info) [0x00000] at System.Runtime.Serialization.Formatters.Binary.ObjectReader.ReadObject (BinaryElement element, System.IO.BinaryReader reader, System.Int64& objectId, System.Object& value, System.Runtime.Serialization.SerializationInfo& info) [0x00000] at System.Runtime.Serialization.Formatters.Binary.ObjectReader.ReadNextObject (System.IO.BinaryReader reader) [0x00000] at System.Runtime.Serialization.Formatters.Binary.ObjectReader.ReadObjectGraph (System.IO.BinaryReader reader, Boolean readHeaders, System.Object& result, System.Runtime.Remoting.Messaging.Header[]& headers) [0x00000] at System.Runtime.Serialization.Formatters.Binary.BinaryFormatter.NoCheckDeserialize (System.IO.Stream serializationStream, System.Runtime.Remoting.Messaging.HeaderHandler handler) [0x00000] at System.Runtime.Serialization.Formatters.Binary.BinaryFormatter.Deserialize (System.IO.Stream serializationStream) [0x00000] at System.Runtime.Remoting.Channels.CADSerializer.DeserializeObject (System.IO.MemoryStream mem) [0x00000] at System.Runtime.Remoting.RemotingServices.GetDomainProxy (System.AppDomain domain) [0x00000] at System.AppDomain.CreateDomain (System.String friendlyName, System.Security.Policy.Evidence securityInfo, System.AppDomainSetup info) [0x00000] at System.Web.Hosting.ApplicationHost.CreateApplicationHost (System.Type hostType, System.String virtualDir, System.String physicalDir) [0x00000] at Mono.WebServer.VPathToHost.CreateHost (Mono.WebServer.ApplicationServer server, Mono.WebServer.WebSource webSource) [0x00000] at Mono.WebServer.ApplicationServer.GetApplicationForPath (System.String vhost, Int32 port, System.String path, Boolean defaultToRoot) [0x00000] at (wrapper remoting-invoke-with-check) Mono.WebServer.ApplicationServer:GetApplicationForPath (string,int,string,bool) at Mono.WebServer.ModMonoWorker.GetOrCreateApplication (System.String vhost, Int32 port, System.String filepath, System.String virt) [0x00000] at Mono.WebServer.ModMonoWorker.InnerRun (System.Object state) [0x00000] at Mono.WebServer.ModMonoWorker.Run (System.Object state) [0x00000] [Tue Apr 20 03:10:26 2010] [error] (70014)End of file found: read_data failed [Tue Apr 20 03:10:26 2010] [error] Command stream corrupted, last command was -1 Along with the above errors, Apache's error.log is packed with hundreds (if not thousands) of the following error: Maximum number (20) of concurrent mod_mono requests to /tmp/mod_mono_dashboard_default_2.lock reached. Droping request. At the moment, I'm thinking there might be something wrong with configuration here (it's basically running on out-of-the-box config)

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  • Does Test Driven Development (TDD) improve Quality and Correctness? (Part 1)

    - by David V. Corbin
    Since the dawn of the computer age, various methodologies have been introduced to improve quality and reduce cost. In this posting, I will by sharing my experiences with Test Driven Development; both its benefits and limitations. To start this topic, we need to agree on what TDD is. The first is to define each of the three words as used in this context. Test - An item or action which measures something in some quantifiable form. Driven - The primary motivation or focus of a series of activities (process) Development - All phases of a software project/product from concept through delivery. The above are very simple definitions that result in the following: "TDD is a process where the primary focus is on measuring and quantifying all aspects of the creation of a (software) product." There are many places where TDD is used outside of software development, even though it is not known by this name. Consider the (conventional) education process that most of us grew up on. The focus was to get the best grades as measured by different tests. Many of these tests measured rote memorization and not understanding of the subject matter. The result of this that many people graduated with high scores but without "quality and correctness" in their ability to utilize the subject matter (of course, the flip side is true where certain people DID understand the material but were not very good at taking this type of test). Returning to software development, let us look at some common scenarios. While these items are generally applicable regardless of platform, language and tools; the remainder of this post will utilize Microsoft Visual Studio and Team Foundation Server (TFS) for examples. It should be realized that everyone does at least some aspect of TDD. At the most rudimentary level, getting a program to compile involves a "pass/fail" measurement (is the syntax valid) that drives their ability to proceed further (run the program). Other developers may create "Unit Tests" in the belief that having a test for every method/property of a class and good code coverage is the goal of TDD. These items may be helpful and even important, but really only address a small aspect of the overall effort. To see TDD in a bigger view, lets identify the various activities that are part of the Software Development LifeCycle. These are going to be presented in a Waterfall style for simplicity, but each item also occurs within Iterative methodologies such as Agile/Scrum. the key ones here are: Requirements Gathering Architecture Design Implementation Quality Assurance Can each of these items be subjected to a process which establishes metrics (quantified metrics) that reflect both the quality and correctness of each item? It should be clear that conventional Unit Tests do not apply to all of these items; at best they can verify that a local aspect (e.g. a Class/Method) of implementation matches the (test writers perspective of) the appropriate design document. So what can we do? For each of area, the goal is to create tests that are quantifiable and durable. The ability to quantify the measurements (beyond a simple pass/fail) is critical to tracking progress(eventually measuring the level of success that has been achieved) and for providing clear information on what items need to be addressed (along with the appropriate time to address them - in varying levels of detail) . Durability is important so that the test can be reapplied (ideally in an automated fashion) over the entire cycle. Returning for a moment back to our "education example", one must also be careful of how the tests are organized and how the measurements are taken. If a test is in a multiple choice format, there is a significant statistical probability that a correct answer might be the result of a random guess. Also, in many situations, having the student simply provide a final answer can obscure many important elements. For example, on a math test, having the student simply provide a numeric answer (rather than showing the methodology) may result in a complete mismatch between the process and the result. It is hard to determine which is worse: The student who makes a simple arithmetric error at one step of a long process (resulting in a wrong answer) or The student who (without providing the "workflow") uses a completely invalid approach, yet still comes up with the right number. The "Wrong Process"/"Right Answer" is probably the single biggest problem in software development. Even very simple items can suffer from this. As an example consider the following code for a "straight line" calculation....Is it correct? (for Integral Points)         int Solve(int m, int b, int x) { return m * x + b; }   Most people would respond "Yes". But let's take the question one step further... Is it correct for all possible values of m,b,x??? (no fair if you cheated by being focused on the bolded text!)  Without additional information regarding constrains on "the possible values of m,b,x" the answer must be NO, there is the risk of overflow/wraparound that will produce an incorrect result! To properly answer this question (i.e. Test the Code), one MUST be able to backtrack from the implementation through the design, and architecture all the way back to the requirements. And the requirement itself must be tested against the stakeholder(s). It is only when the bounding conditions are defined that it is possible to determine if the code is "Correct" and has "Quality". Yet, how many of us (myself included) have written such code without even thinking about it. In many canses we (think we) "know" what the bounds are, and that the code will be correct. As we all know, requirements change, "code reuse" causes implementations to be applied to different scenarios, etc. This leads directly to the types of system failures that plague so many projects. This approach to TDD is much more holistic than ones which start by focusing on the details. The fundamental concepts still apply: Each item should be tested. The test should be defined/implemented before (or concurrent with) the definition/implementation of the actual item. We also add concepts that expand the scope and alter the style by recognizing: There are many things beside "lines of code" that benefit from testing (measuring/evaluating in a formal way) Correctness and Quality can not be solely measured by "correct results" In the future parts, we will examine in greater detail some of the techniques that can be applied to each of these areas....

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  • MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!

    - by Mat Keep
    0 0 1 1097 6254 Homework 52 14 7337 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary (aka TL/DR): Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build) In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release. Pace of Innovation It was only a couple of months ago that we announced the General Availability (GA) of MySQL Cluster 7.2, delivering 1 billion Queries per Minute, with 70x higher cross-shard JOIN performance, Memcached NoSQL key-value API and cross-data center replication.  This release has been a huge hit, with downloads and deployments quickly reaching record levels. The announcement of the first MySQL Cluster 7.3 Early Access lab release at today's MySQL Innovation Day event demonstrates the continued pace in Cluster development, and provides an opportunity for the community to evaluate and feedback on new features they want to see. What’s the Plan for MySQL Cluster 7.3? Well, Foreign Keys, as you may have gathered by now (!), and this is the focus of this first Labs Release. As with MySQL Cluster 7.2, we plan to publish a series of preview releases for 7.3 that will incrementally add new candidate features for a final GA release (subject to usual safe harbor statement below*), including: - New NoSQL APIs; - Features to automate the configuration and provisioning of multi-node clusters, on premise or in the cloud; - Performance and scalability enhancements; - Taking advantage of features in the latest MySQL 5.x Server GA. Design Rationale MySQL Cluster is designed as a “Not-Only-SQL” database. It combines attributes that enable users to blend the best of both relational and NoSQL technologies into solutions that deliver web scalability with 99.999% availability and real-time performance, including: Concurrent NoSQL and SQL access to the database; Auto-sharding with simple scale-out across commodity hardware; Multi-master replication with failover and recovery both within and across data centers; Shared-nothing architecture with no single point of failure; Online scaling and schema changes; ACID compliance and support for complex queries, across shards. Native support for Foreign Key constraints enables users to extend the benefits of MySQL Cluster into a broader range of use-cases, including: - Packaged applications in areas such as eCommerce and Web Content Management that prescribe databases with Foreign Key support. - In-house developments benefiting from Foreign Key constraints to simplify data models and eliminate the additional application logic needed to maintain data consistency and integrity between tables. Implementation The Foreign Key functionality is implemented directly within MySQL Cluster’s data nodes, allowing any client API accessing the cluster to benefit from them – whether using SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA or HTTP/REST.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation. An important difference to note with the Foreign Key implementation in InnoDB is that MySQL Cluster does not support the updating of Primary Keys from within the Data Nodes themselves - instead the UPDATE is emulated with a DELETE followed by an INSERT operation. Therefore an UPDATE operation will return an error if the parent reference is using a Primary Key, unless using CASCADE action, in which case the delete operation will result in the corresponding rows in the child table being deleted. The Engineering team plans to change this behavior in a subsequent preview release. Also note that when using InnoDB "NO ACTION" is identical to "RESTRICT". In the case of MySQL Cluster “NO ACTION” means “deferred check”, i.e. the constraint is checked before commit, allowing user-defined triggers to automatically make changes in order to satisfy the Foreign Key constraints. Configuration There is nothing special you have to do here – Foreign Key constraint checking is enabled by default. If you intend to migrate existing tables from another database or storage engine, for example from InnoDB, there are a couple of best practices to observe: 1. Analyze the structure of the Foreign Key graph and run the ALTER TABLE ENGINE=NDB in the correct sequence to ensure constraints are enforced 2. Alternatively drop the Foreign Key constraints prior to the import process and then recreate when complete. Getting Started Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  You can download MySQL Cluster 7.3 Labs Release with Foreign Keys today - (select the mysql-cluster-7.3-labs-June-2012 build) If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3) Post any questions to the MySQL Cluster forum where our Engineering team will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section of this blog. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. This first Labs Release of MySQL Cluster 7.3 gives you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases. * Safe Harbor Statement This information is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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  • Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. Performance Landscape Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time. PeopleSoft HRMS Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.988 0.539 32.4 128 SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.944 0.503 43.3 64 The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component. PeopleSoft HRMS Self-Service 9.1 Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) 2x SPARC T4-2 (db) 18,000 1.048 0.742 N/A N/A The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component. PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode) Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-4 (db) N/A N/A N/A 30.84 96 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 PeopleTools 8.52 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Micro Focus Server Express (COBOL v 5.1.00) Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Managementoracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

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  • Is RTD Stateless or Stateful?

    - by [email protected]
    Yes.   A stateless service is one where each request is an independent transaction that can be processed by any of the servers in a cluster.  A stateful service is one where state is kept in a server's memory from transaction to transaction, thus necessitating the proper routing of requests to the right server. The main advantage of stateless systems is simplicity of design. The main advantage of stateful systems is performance. I'm often asked whether RTD is a stateless or stateful service, so I wanted to clarify this issue in depth so that RTD's architecture will be properly understood. The short answer is: "RTD can be configured as a stateless or stateful service." The performance difference between stateless and stateful systems can be very significant, and while in a call center implementation it may be reasonable to use a pure stateless configuration, a web implementation that produces thousands of requests per second is practically impossible with a stateless configuration. RTD's performance is orders of magnitude better than most competing systems. RTD was architected from the ground up to achieve this performance. Features like automatic and dynamic compression of prediction models, automatic translation of metadata to machine code, lack of interpreted languages, and separation of model building from decisioning contribute to achieving this performance level. Because  of this focus on performance we decided to have RTD's default configuration work in a stateful manner. By being stateful RTD requests are typically handled in a few milliseconds when repeated requests come to the same session. Now, those readers that have participated in implementations of RTD know that RTD's architecture is also focused on reducing Total Cost of Ownership (TCO) with features like automatic model building, automatic time windows, automatic maintenance of database tables, automatic evaluation of data mining models, automatic management of models partitioned by channel, geography, etcetera, and hot swapping of configurations. How do you reconcile the need for a low TCO and the need for performance? How do you get the performance of a stateful system with the simplicity of a stateless system? The answer is that you make the system behave like a stateless system to the exterior, but you let it automatically take advantage of situations where being stateful is better. For example, one of the advantages of stateless systems is that you can route a message to any server in a cluster, without worrying about sending it to the same server that was handling the session in previous messages. With an RTD stateful configuration you can still route the message to any server in the cluster, so from the point of view of the configuration of other systems, it is the same as a stateless service. The difference though comes in performance, because if the message arrives to the right server, RTD can serve it without any external access to the session's state, thus tremendously reducing processing time. In typical implementations it is not rare to have high percentages of messages routed directly to the right server, while those that are not, are easily handled by forwarding the messages to the right server. This architecture usually provides the best of both worlds with performance and simplicity of configuration.   Configuring RTD as a pure stateless service A pure stateless configuration requires session data to be persisted at the end of handling each and every message and reloading that data at the beginning of handling any new message. This is of course, the root of the inefficiency of these configurations. This is also the reason why many "stateless" implementations actually do keep state to take advantage of a request coming back to the same server. Nevertheless, if the implementation requires a pure stateless decision service, this is easy to configure in RTD. The way to do it is: Mark every Integration Point to Close the session at the end of processing the message In the Session entity persist the session data on closing the session In the session entity check if a persisted version exists and load it An excellent solution for persisting the session data is Oracle Coherence, which provides a high performance, distributed cache that minimizes the performance impact of persisting and reloading the session. Alternatively, the session can be persisted to a local database. An interesting feature of the RTD stateless configuration is that it can cope with serializing concurrent requests for the same session. For example, if a web page produces two requests to the decision service, these requests could come concurrently to the decision services and be handled by different servers. Most stateless implementation would have the two requests step onto each other when saving the state, or fail one of the messages. When properly configured, RTD will make one message wait for the other before processing.   A Word on Context Using the context of a customer interaction typically significantly increases lift. For example, offer success in a call center could double if the context of the call is taken into account. For this reason, it is important to utilize the contextual information in decision making. To make the contextual information available throughout a session it needs to be persisted. When there is a well defined owner for the information then there is no problem because in case of a session restart, the information can be easily retrieved. If there is no official owner of the information, then RTD can be configured to persist this information.   Once again, RTD provides flexibility to ensure high performance when it is adequate to allow for some loss of state in the rare cases of server failure. For example, in a heavy use web site that serves 1000 pages per second the navigation history may be stored in the in memory session. In such sites it is typical that there is no OLTP that stores all the navigation events, therefore if an RTD server were to fail, it would be possible for the navigation to that point to be lost (note that a new session would be immediately established in one of the other servers). In most cases the loss of this navigation information would be acceptable as it would happen rarely. If it is desired to save this information, RTD would persist it every time the visitor navigates to a new page. Note that this practice is preferred whether RTD is configured in a stateless or stateful manner.  

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  • MySQL Memory usage

    - by Rob Stevenson-Leggett
    Our MySQL server seems to be using a lot of memory. I've tried looking for slow queries and queries with no index and have halved the peak CPU usage and Apache memory usage but the MySQL memory stays constantly at 2.2GB (~51% of available memory on the server). Here's the graph from Plesk. Running top in the SSH window shows the same figures. Does anyone have any ideas on why the memory usage is constant like this and not peaks and troughs with usage of the app? Here's the output of the MySQL Tuning Primer script: -- MYSQL PERFORMANCE TUNING PRIMER -- - By: Matthew Montgomery - MySQL Version 5.0.77-log x86_64 Uptime = 1 days 14 hrs 4 min 21 sec Avg. qps = 22 Total Questions = 3059456 Threads Connected = 13 Warning: Server has not been running for at least 48hrs. It may not be safe to use these recommendations To find out more information on how each of these runtime variables effects performance visit: http://dev.mysql.com/doc/refman/5.0/en/server-system-variables.html Visit http://www.mysql.com/products/enterprise/advisors.html for info about MySQL's Enterprise Monitoring and Advisory Service SLOW QUERIES The slow query log is enabled. Current long_query_time = 1 sec. You have 6 out of 3059477 that take longer than 1 sec. to complete Your long_query_time seems to be fine BINARY UPDATE LOG The binary update log is NOT enabled. You will not be able to do point in time recovery See http://dev.mysql.com/doc/refman/5.0/en/point-in-time-recovery.html WORKER THREADS Current thread_cache_size = 0 Current threads_cached = 0 Current threads_per_sec = 2 Historic threads_per_sec = 0 Threads created per/sec are overrunning threads cached You should raise thread_cache_size MAX CONNECTIONS Current max_connections = 100 Current threads_connected = 14 Historic max_used_connections = 20 The number of used connections is 20% of the configured maximum. Your max_connections variable seems to be fine. INNODB STATUS Current InnoDB index space = 6 M Current InnoDB data space = 18 M Current InnoDB buffer pool free = 0 % Current innodb_buffer_pool_size = 8 M Depending on how much space your innodb indexes take up it may be safe to increase this value to up to 2 / 3 of total system memory MEMORY USAGE Max Memory Ever Allocated : 2.07 G Configured Max Per-thread Buffers : 274 M Configured Max Global Buffers : 2.01 G Configured Max Memory Limit : 2.28 G Physical Memory : 3.84 G Max memory limit seem to be within acceptable norms KEY BUFFER Current MyISAM index space = 4 M Current key_buffer_size = 7 M Key cache miss rate is 1 : 40 Key buffer free ratio = 81 % Your key_buffer_size seems to be fine QUERY CACHE Query cache is supported but not enabled Perhaps you should set the query_cache_size SORT OPERATIONS Current sort_buffer_size = 2 M Current read_rnd_buffer_size = 256 K Sort buffer seems to be fine JOINS Current join_buffer_size = 132.00 K You have had 16 queries where a join could not use an index properly You should enable "log-queries-not-using-indexes" Then look for non indexed joins in the slow query log. If you are unable to optimize your queries you may want to increase your join_buffer_size to accommodate larger joins in one pass. Note! This script will still suggest raising the join_buffer_size when ANY joins not using indexes are found. OPEN FILES LIMIT Current open_files_limit = 1024 files The open_files_limit should typically be set to at least 2x-3x that of table_cache if you have heavy MyISAM usage. Your open_files_limit value seems to be fine TABLE CACHE Current table_cache value = 64 tables You have a total of 426 tables You have 64 open tables. Current table_cache hit rate is 1% , while 100% of your table cache is in use You should probably increase your table_cache TEMP TABLES Current max_heap_table_size = 16 M Current tmp_table_size = 32 M Of 15134 temp tables, 9% were created on disk Effective in-memory tmp_table_size is limited to max_heap_table_size. Created disk tmp tables ratio seems fine TABLE SCANS Current read_buffer_size = 128 K Current table scan ratio = 2915 : 1 read_buffer_size seems to be fine TABLE LOCKING Current Lock Wait ratio = 1 : 142213 Your table locking seems to be fine The app is a facebook game with about 50-100 concurrent users. Thanks, Rob

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