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  • How do I defer execution of some Ruby code until later and run it on demand in this scenario?

    - by Kyle Kaitan
    I've got some code that looks like the following. First, there's a simple Parser class for parsing command-line arguments with options. class Parser def initialize(&b); ...; end # Create new parser. def parse(args = ARGV); ...; end # Consume command-line args. def opt(...); ...; end # Declare supported option. def die(...); ...; end # Validation handler. end Then I have my own Parsers module which holds some metadata about parsers that I want to track. module Parsers ParserMap = {} def self.make_parser(kind, desc, &b) b ||= lambda {} module_eval { ParserMap[kind] = {:desc => "", :validation => lambda {} } ParserMap[kind][:desc] = desc # Create new parser identified by `<Kind>Parser`. Making a Parser is very # expensive, so we defer its creation until it's actually needed later # by wrapping it in a lambda and calling it when we actually need it. const_set(name_for_parser(kind), lambda { Parser.new(&b) }) } end # ... end Now when you want to add a new parser, you can call make_parser like so: make_parser :db, "login to database" do # Options that this parser knows how to parse. opt :verbose, "be verbose with output messages" opt :uid, "user id" opt :pwd, "password" end Cool. But there's a problem. We want to optionally associate validation with each parser, so that we can write something like: validation = lambda { |parser, opts| parser.die unless opts[:uid] && opts[:pwd] # Must provide login. } The interface contract with Parser says that we can't do any validation until after Parser#parse has been called. So, we want to do the following: Associate an optional block with every Parser we make with make_parser. We also want to be able to run this block, ideally as a new method called Parser#validate. But any on-demand method is equally suitable. How do we do that?

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  • Detecting Hyper-Threading state

    - by jchang
    To interpret performance counters and execution statistics correctly, it is necessary to know state of Hyper-Threading. In principle, at low overall CPU utilization, for non-parallel execution plans, it should not matter whether HT is enabled or not. Of course, DBA life is never that simple. The state of HT does matter at high over utilization and in parallel execution plans depending on the DOP. SQL Server does seem to try to allocate threads on distinct physical cores at intermediate DOP (DOP less...(read more)

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  • Symfony Form render with Self Referenced Entity

    - by benarth
    I have an Entity containing Self-Referenced mapping. class Category { /** * @var integer * * @ORM\Column(name="id", type="integer") * @ORM\Id * @ORM\GeneratedValue(strategy="AUTO") */ private $id; /** * @var string * * @ORM\Column(name="name", type="string", length=100) */ private $name; /** * @ORM\OneToMany(targetEntity="Category", mappedBy="parent") */ private $children; /** * @ORM\ManyToOne(targetEntity="Category", inversedBy="children") * @ORM\JoinColumn(name="parent_id", referencedColumnName="id") */ private $parent; } In my CategoryType I have this : public function buildForm(FormBuilderInterface $builder, array $options) { $plan = $this->plan; $builder->add('name'); $builder->add('parent', 'entity', array( 'class' => 'xxxBundle:Category', 'property' => 'name', 'empty_value' => 'Choose a parent category', 'required' => false, 'query_builder' => function(EntityRepository $er) use ($plan) { return $er->createQueryBuilder('u') ->where('u.plan = :plan') ->setParameter('plan', $plan) ->orderBy('u.id', 'ASC'); }, )); } Actually, when I render the form field Category this is something like Cat1 Cat2 Cat3 Subcat1 Subcat2 Cat4 I would like to know if it's possible and how to display something more like, a kind of a simple tree representation : Cat1 Cat2 Cat3 -- Subcat1 -- Subcat2 Cat4 Regards.

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  • Best way to limit results in MySQL with user subcategories

    - by JM4
    I am trying to essentially solve for the following: 1) Find all users in the system who ONLY have programID 1. 2) Find all users in the system who have programID 1 AND any other active program. My tables structures (in very simple terms are as follows): users userID | Name ================ 1 | John Smith 2 | Lewis Black 3 | Mickey Mantle 4 | Babe Ruth 5 | Tommy Bahama plans ID | userID | plan | status --------------------------- 1 | 1 | 1 | 1 2 | 1 | 2 | 1 3 | 1 | 3 | 1 4 | 2 | 1 | 1 5 | 2 | 3 | 1 6 | 3 | 1 | 0 7 | 3 | 2 | 1 8 | 3 | 3 | 1 9 | 3 | 4 | 1 10 | 4 | 2 | 1 11 | 4 | 4 | 1 12 | 5 | 1 | 1 I know I can easily find all members with a specific plan with something like the following: SELECT * FROM users a JOIN plans b ON (a.userID = b.userID) WHERE b.plan = 1 AND b.status = 1 but this will only tell me which users have an 'active' plan 1. How can I tell who ONLY has plan 1 (in this case only userID 5) and how to tell who has plan 1 AND any other active plan? Update: This is not to get a count, I will actually need the original member information, including all the plans they have so a COUNT(*) response may not be what I'm trying to achieve.

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  • Please advise on VPS config choice (with SQL Server Express)

    - by tjeuten
    Hi all, I might be interested in getting a VPS hosting plan for some small personal sites and .NET projects. Was thinking of Softsys Bronze Plan, as my current shared host plan is with them too. The stuff I want to host has grown beyond the capabilities of a Shared hosting plan, and I also want more control over the IIS/ASP.NET configuration, that's why I'm considering VPS. The main config details would be: Hyper-V 30 GB of diskspace 1 GB of RAM More info here: http://www.softsyshosting.com/Windows-VPS-HyperV.aspx Does anyone have experience with this plan (or something similar from another host), and maybe could answer these couple of questions: Bronze has a total diskspace of 30GB. Is the OS part of this quota or not ? If so, how much does a base configuration with Windows 2008 take up in diskspace ? Would you advise Windows 2008 R2 or Normal. Or would you advise to use Windows 2003 with this config. I'm planning on running a SQL Server Express install too. Would 1 GB of RAM be enough for both the Windows 2008 (R2) and SQL Express. The database load will not be that very high (a couple of 1000 records returned each day). The DB will most likely be far away from the 4GB limit, that's why I'd go for a SQL Express instead of paying extra licensing costs for a SQL Web install. But I'm more concerned about performance. Would you recommend Softsys as a VPS host ? I've been with them for one year for my Shared hosting plan, and have no complaints so far. Also, as I have no VPS experience, what are the pitfalls I need to be aware of, in terms of performance mainly, but maybe in other areas too ? Mathieu

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  • Strange Play Framework 2.2 exceptions after trying to add MySQL / slick

    - by Mike Cialowicz
    I'm working on a Play 2.2 application, and things have gone a bit south on me since I've tried adding my DB layer. Below are my build.sbt dependencies. As you can see I use mysql-connector-java and play-slick: libraryDependencies ++= Seq( jdbc, anorm, cache, "joda-time" % "joda-time" % "2.3", "mysql" % "mysql-connector-java" % "5.1.26", "com.typesafe.play" %% "play-slick" % "0.5.0.8", "com.aetrion.flickr" % "flickrapi" % "1.1" ) My application.conf has some similarly simple DB stuff in it: db.default.url="jdbc:mysql://localhost/myDb" db.default.driver="com.mysql.jdbc.Driver" db.default.user="root" db.default.pass="" This is what it looks like when my Play server starts: [info] play - Listening for HTTP on /0:0:0:0:0:0:0:0:9000 (Server started, use Ctrl+D to stop and go back to the console...) [info] Compiling 1 Scala source to C:\bbq\cats\in\space [info] play - database [default] connected at jdbc:mysql://localhost/myDb [info] play - Application started (Dev) So, it appears that Play can connect to the MySQL DB just fine (I think). However, I get this exception when I make any request to my server: [error] p.nettyException - Exception caught in Netty java.lang.NoSuchMethodError: akka.actor.ActorSystem.dispatcher()Lscala/concurren t/ExecutionContext; at play.core.Invoker$.<init>(Invoker.scala:24) ~[play_2.10.jar:2.2.0] at play.core.Invoker$.<clinit>(Invoker.scala) ~[play_2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$Implicits$.defaultContext$lzycompu te(Execution.scala:7) ~[play_2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$Implicits$.defaultContext(Executio n.scala:6) ~[play_2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$.<init>(Execution.scala:10) ~[play _2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$.<clinit>(Execution.scala) ~[play_ 2.10.jar:2.2.0] The odd thing is that the 2nd request (to the exact same URL, same controller, no changes) comes back with a different error: [error] p.nettyException - Exception caught in Netty java.lang.NoClassDefFoundError: Could not initialize class play.api.libs.concurr ent.Execution$ at play.core.server.netty.PlayDefaultUpstreamHandler.handleAction$1(Play DefaultUpstreamHandler.scala:194) ~[play_2.10.jar:2.2.0] at play.core.server.netty.PlayDefaultUpstreamHandler.messageReceived(Pla yDefaultUpstreamHandler.scala:169) ~[play_2.10.jar:2.2.0] at com.typesafe.netty.http.pipelining.HttpPipeliningHandler.messageRecei ved(HttpPipeliningHandler.java:62) ~[netty-http-pipelining.jar:na] at org.jboss.netty.handler.codec.http.HttpContentDecoder.messageReceived (HttpContentDecoder.java:108) ~[netty-3.6.5.Final.jar:na] at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:29 6) ~[netty-3.6.5.Final.jar:na] at org.jboss.netty.handler.codec.frame.FrameDecoder.unfoldAndFireMessage Received(FrameDecoder.java:459) ~[netty-3.6.5.Final.jar:na] The URL / controller that I'm requesting just renders a static web page and doesn't do anything of any significance. It was working just fine before I started adding my DB layer. I'm rather stuck. Any help would be greatly appreciated, thanks. I'm using Scala 2.10.2, Play 2.2.0, and MySQL Server 5.6.14.0 (community edition).

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  • Get ID of the object saved with association

    - by Pravin
    Hi, Here is my scenario: I have three models Subscriber, Subscription, Plan, with has_many :through relationship between Subscriber and Plans. A subscriber can have multiple plans with one active plan. Whenever a subscriber selects a plan I save it using accepts_nested_attributes_for :subscriptions. I get one plan from the form. Now my problem is I want to get the ID of the record created in subscriptions table.

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  • javax.naming.InvalidNameException using Oracle BPM and weblogic when accessing directory

    - by alfredozn
    We are getting this exception when we start our cluster (2 managed servers, 1 admin), we have deployed only the ears corresponding to the OBPM 10.3.1 SP1 in a weblogic 10.3. When the server cluster starts, one of the managed servers (the first to start) get overloaded and ran out of connections to the directory DB because of this repeatedly error. It looks like the engine is trying to get the info from the LDAP server but I don't know why it is building a wrong query. fuego.directory.DirectoryRuntimeException: Exception [javax.naming.InvalidNameException: CN=Alvarez Guerrero Bernardo DEL:ca9ef28d-3b94-4e8f-a6bd-8c880bb3791b,CN=Deleted Objects,DC=corp: [LDAP: error code 34 - 0000208F: NameErr: DSID-031001BA, problem 2006 (BAD_NAME), data 8349, best match of: 'CN=Alvarez Guerrero Bernardo DEL:ca9ef28d-3b94-4e8f-a6bd-8c880bb3791b,CN=Deleted Objects,DC=corp,dc=televisa,dc=com,dc=mx' ^@]; remaining name 'CN=Alvarez Guerrero Bernardo DEL:ca9ef28d-3b94-4e8f-a6bd-8c880bb3791b,CN=Deleted Objects,DC=corp']. at fuego.directory.DirectoryRuntimeException.wrapException(DirectoryRuntimeException.java:85) at fuego.directory.hybrid.ldap.JNDIQueryExecutor.selectById(JNDIQueryExecutor.java:163) at fuego.directory.hybrid.ldap.JNDIQueryExecutor.selectById(JNDIQueryExecutor.java:110) at fuego.directory.hybrid.ldap.Repository.selectById(Repository.java:38) at fuego.directory.hybrid.msad.MSADGroupValueProvider.getAssignedParticipantsInternal(MSADGroupValueProvider.java:124) at fuego.directory.hybrid.msad.MSADGroupValueProvider.getAssignedParticipants(MSADGroupValueProvider.java:70) at fuego.directory.hybrid.ldap.Group$7.getValue(Group.java:149) at fuego.directory.hybrid.ldap.Group$7.getValue(Group.java:152) at fuego.directory.hybrid.ldap.LDAPResult.getValue(LDAPResult.java:76) at fuego.directory.hybrid.ldap.LDAPOrganizationGroupAccessor.setInfo(LDAPOrganizationGroupAccessor.java:352) at fuego.directory.hybrid.ldap.LDAPOrganizationGroupAccessor.build(LDAPOrganizationGroupAccessor.java:121) at fuego.directory.hybrid.ldap.LDAPOrganizationGroupAccessor.build(LDAPOrganizationGroupAccessor.java:114) at fuego.directory.hybrid.ldap.LDAPOrganizationGroupAccessor.fetchGroup(LDAPOrganizationGroupAccessor.java:94) at fuego.directory.hybrid.HybridGroupAccessor.fetchGroup(HybridGroupAccessor.java:146) at sun.reflect.GeneratedMethodAccessor66.invoke(Unknown Source) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at fuego.directory.provider.DirectorySessionImpl$AccessorProxy.invoke(DirectorySessionImpl.java:756) at $Proxy66.fetchGroup(Unknown Source) at fuego.directory.DirOrganizationalGroup.fetch(DirOrganizationalGroup.java:275) at fuego.metadata.GroupManager.loadGroup(GroupManager.java:225) at fuego.metadata.GroupManager.find(GroupManager.java:57) at fuego.metadata.ParticipantManager.addNestedGroups(ParticipantManager.java:621) at fuego.metadata.ParticipantManager.buildCompleteRoleAssignments(ParticipantManager.java:527) at fuego.metadata.Participant$RoleTransitiveClousure.build(Participant.java:760) at fuego.metadata.Participant$RoleTransitiveClousure.access$100(Participant.java:692) at fuego.metadata.Participant.buildRoles(Participant.java:401) at fuego.metadata.Participant.updateMembers(Participant.java:372) at fuego.metadata.Participant.<init>(Participant.java:64) at fuego.metadata.Participant.createUncacheParticipant(Participant.java:84) at fuego.server.persistence.jdbc.JdbcProcessInstancePersMgr.loadItems(JdbcProcessInstancePersMgr.java:1706) at fuego.server.persistence.Persistence.loadInstanceItems(Persistence.java:838) at fuego.server.AbstractInstanceService.readInstance(AbstractInstanceService.java:791) at fuego.ejbengine.EJBInstanceService.getLockedROImpl(EJBInstanceService.java:218) at fuego.server.AbstractInstanceService.getLockedROImpl(AbstractInstanceService.java:892) at fuego.server.AbstractInstanceService.getLockedImpl(AbstractInstanceService.java:743) at fuego.server.AbstractInstanceService.getLockedImpl(AbstractInstanceService.java:730) at fuego.server.AbstractInstanceService.getLocked(AbstractInstanceService.java:144) at fuego.server.AbstractInstanceService.getLocked(AbstractInstanceService.java:162) at fuego.server.AbstractInstanceService.unselectAllItems(AbstractInstanceService.java:454) at fuego.server.execution.ToDoItemUnselect.execute(ToDoItemUnselect.java:105) at fuego.server.execution.DefaultEngineExecution$AtomicExecutionTA.runTransaction(DefaultEngineExecution.java:304) at fuego.transaction.TransactionAction.startNestedTransaction(TransactionAction.java:527) at fuego.transaction.TransactionAction.startTransaction(TransactionAction.java:548) at fuego.transaction.TransactionAction.start(TransactionAction.java:212) at fuego.server.execution.DefaultEngineExecution.executeImmediate(DefaultEngineExecution.java:123) at fuego.server.execution.DefaultEngineExecution.executeAutomaticWork(DefaultEngineExecution.java:62) at fuego.server.execution.EngineExecution.executeAutomaticWork(EngineExecution.java:42) at fuego.server.execution.ToDoItem.executeAutomaticWork(ToDoItem.java:261) at fuego.ejbengine.ItemExecutionBean$1.execute(ItemExecutionBean.java:223) at fuego.server.execution.DefaultEngineExecution$AtomicExecutionTA.runTransaction(DefaultEngineExecution.java:304) at fuego.transaction.TransactionAction.startBaseTransaction(TransactionAction.java:470) at fuego.transaction.TransactionAction.startTransaction(TransactionAction.java:551) at fuego.transaction.TransactionAction.start(TransactionAction.java:212) at fuego.server.execution.DefaultEngineExecution.executeImmediate(DefaultEngineExecution.java:123) at fuego.server.execution.EngineExecution.executeImmediate(EngineExecution.java:66) at fuego.ejbengine.ItemExecutionBean.processMessage(ItemExecutionBean.java:209) at fuego.ejbengine.ItemExecutionBean.onMessage(ItemExecutionBean.java:120) at weblogic.ejb.container.internal.MDListener.execute(MDListener.java:466) at weblogic.ejb.container.internal.MDListener.transactionalOnMessage(MDListener.java:371) at weblogic.ejb.container.internal.MDListener.onMessage(MDListener.java:327) at weblogic.jms.client.JMSSession.onMessage(JMSSession.java:4547) at weblogic.jms.client.JMSSession.execute(JMSSession.java:4233) at weblogic.jms.client.JMSSession.executeMessage(JMSSession.java:3709) at weblogic.jms.client.JMSSession.access$000(JMSSession.java:114) at weblogic.jms.client.JMSSession$UseForRunnable.run(JMSSession.java:5058) at weblogic.work.SelfTuningWorkManagerImpl$WorkAdapterImpl.run(SelfTuningWorkManagerImpl.java:516) at weblogic.work.ExecuteThread.execute(ExecuteThread.java:201) at weblogic.work.ExecuteThread.run(ExecuteThread.java:173) Caused by: javax.naming.InvalidNameException: CN=Alvarez Guerrero Bernardo DEL:ca9ef28d-3b94-4e8f-a6bd-8c880bb3791b,CN=Deleted Objects,DC=corp: [LDAP: error code 34 - 0000208F: NameErr: DSID-031001BA, problem 2006 (BAD_NAME), data 8349, best match of: 'CN=Alvarez Guerrero Bernardo DEL:ca9ef28d-3b94-4e8f-a6bd-8c880bb3791b,CN=Deleted Objects,DC=corp,dc=televisa,dc=com,dc=mx' ^@]; remaining name 'CN=Alvarez Guerrero Bernardo DEL:ca9ef28d-3b94-4e8f-a6bd-8c880bb3791b,CN=Deleted Objects,DC=corp' at com.sun.jndi.ldap.LdapCtx.processReturnCode(LdapCtx.java:2979) at com.sun.jndi.ldap.LdapCtx.processReturnCode(LdapCtx.java:2794) at com.sun.jndi.ldap.LdapCtx.searchAux(LdapCtx.java:1826) at com.sun.jndi.ldap.LdapCtx.c_search(LdapCtx.java:1749) at com.sun.jndi.toolkit.ctx.ComponentDirContext.p_search(ComponentDirContext.java:368) at com.sun.jndi.toolkit.ctx.PartialCompositeDirContext.search(PartialCompositeDirContext.java:338) at com.sun.jndi.toolkit.ctx.PartialCompositeDirContext.search(PartialCompositeDirContext.java:321) at javax.naming.directory.InitialDirContext.search(InitialDirContext.java:248) at fuego.jndi.FaultTolerantLdapContext.search(FaultTolerantLdapContext.java:612) at fuego.directory.hybrid.ldap.JNDIQueryExecutor.selectById(JNDIQueryExecutor.java:136) ... 67 more

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  • maven sonar problem

    - by senzacionale
    I want to use sonar for analysis but i can't get any data in localhost:9000 <?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd"> <modelVersion>4.0.0</modelVersion> <artifactId>KIS</artifactId> <groupId>KIS</groupId> <version>1.0</version> <build> <plugins> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-antrun-plugin</artifactId> <version>1.4</version> <executions> <execution> <id>compile</id> <phase>compile</phase> <configuration> <tasks> <property name="compile_classpath" refid="maven.compile.classpath"/> <property name="runtime_classpath" refid="maven.runtime.classpath"/> <property name="test_classpath" refid="maven.test.classpath"/> <property name="plugin_classpath" refid="maven.plugin.classpath"/> <ant antfile="${basedir}/build.xml"> <target name="maven-compile"/> </ant> </tasks> </configuration> <goals> <goal>run</goal> </goals> </execution> </executions> </plugin> </plugins> </build> </project> output when running sonar: jar file is empty [INFO] Executed tasks [INFO] [resources:testResources {execution: default-testResources}] [WARNING] Using platform encoding (Cp1250 actually) to copy filtered resources, i.e. build is platform dependent! [INFO] skip non existing resourceDirectory J:\ostalo_6i\KIS deploy\ANT\src\test\resources [INFO] [compiler:testCompile {execution: default-testCompile}] [INFO] No sources to compile [INFO] [surefire:test {execution: default-test}] [INFO] No tests to run. [INFO] [jar:jar {execution: default-jar}] [WARNING] JAR will be empty - no content was marked for inclusion! [INFO] Building jar: J:\ostalo_6i\KIS deploy\ANT\target\KIS-1.0.jar [INFO] [install:install {execution: default-install}] [INFO] Installing J:\ostalo_6i\KIS deploy\ANT\target\KIS-1.0.jar to C:\Documents and Settings\MitjaG\.m2\repository\KIS\KIS\1.0\KIS-1.0.jar [INFO] ------------------------------------------------------------------------ [INFO] Building Unnamed - KIS:KIS:jar:1.0 [INFO] task-segment: [sonar:sonar] (aggregator-style) [INFO] ------------------------------------------------------------------------ [INFO] [sonar:sonar {execution: default-cli}] [INFO] Sonar host: http://localhost:9000 [INFO] Sonar version: 2.1.2 [INFO] [sonar-core:internal {execution: default-internal}] [INFO] Database dialect class org.sonar.api.database.dialect.Oracle [INFO] ------------- Analyzing Unnamed - KIS:KIS:jar:1.0 [INFO] Selected quality profile : KIS, language=java [INFO] Configure maven plugins... [INFO] Sensor SquidSensor... [INFO] Sensor SquidSensor done: 16 ms [INFO] Sensor JavaSourceImporter... [INFO] Sensor JavaSourceImporter done: 0 ms [INFO] Sensor AsynchronousMeasuresSensor... [INFO] Sensor AsynchronousMeasuresSensor done: 15 ms [INFO] Sensor SurefireSensor... [INFO] parsing J:\ostalo_6i\KIS deploy\ANT\target\surefire-reports [INFO] Sensor SurefireSensor done: 47 ms [INFO] Sensor ProfileSensor... [INFO] Sensor ProfileSensor done: 16 ms [INFO] Sensor ProjectLinksSensor... [INFO] Sensor ProjectLinksSensor done: 0 ms [INFO] Sensor VersionEventsSensor... [INFO] Sensor VersionEventsSensor done: 31 ms [INFO] Sensor CpdSensor... [INFO] Sensor CpdSensor done: 0 ms [INFO] Sensor Maven dependencies... [INFO] Sensor Maven dependencies done: 16 ms [INFO] Execute decorators... [INFO] ANALYSIS SUCCESSFUL, you can browse http://localhost:9000 [INFO] Database optimization... [INFO] Database optimization done: 172 ms [INFO] ------------------------------------------------------------------------ [INFO] BUILD SUCCESSFUL [INFO] ------------------------------------------------------------------------ [INFO] Total time: 6 minutes 16 seconds [INFO] Finished at: Fri Jun 11 08:28:26 CEST 2010 [INFO] Final Memory: 24M/43M [INFO] ------------------------------------------------------------------------ any idea why, i successfully compile with maven ant plugin java project.

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  • So…is it a Seek or a Scan?

    - by Paul White
    You’re probably most familiar with the terms ‘Seek’ and ‘Scan’ from the graphical plans produced by SQL Server Management Studio (SSMS).  The image to the left shows the most common ones, with the three types of scan at the top, followed by four types of seek.  You might look to the SSMS tool-tip descriptions to explain the differences between them: Not hugely helpful are they?  Both mention scans and ranges (nothing about seeks) and the Index Seek description implies that it will not scan the index entirely (which isn’t necessarily true). Recall also yesterday’s post where we saw two Clustered Index Seek operations doing very different things.  The first Seek performed 63 single-row seeking operations; and the second performed a ‘Range Scan’ (more on those later in this post).  I hope you agree that those were two very different operations, and perhaps you are wondering why there aren’t different graphical plan icons for Range Scans and Seeks?  I have often wondered about that, and the first person to mention it after yesterday’s post was Erin Stellato (twitter | blog): Before we go on to make sense of all this, let’s look at another example of how SQL Server confusingly mixes the terms ‘Scan’ and ‘Seek’ in different contexts.  The diagram below shows a very simple heap table with two columns, one of which is the non-clustered Primary Key, and the other has a non-unique non-clustered index defined on it.  The right hand side of the diagram shows a simple query, it’s associated query plan, and a couple of extracts from the SSMS tool-tip and Properties windows. Notice the ‘scan direction’ entry in the Properties window snippet.  Is this a seek or a scan?  The different references to Scans and Seeks are even more pronounced in the XML plan output that the graphical plan is based on.  This fragment is what lies behind the single Index Seek icon shown above: You’ll find the same confusing references to Seeks and Scans throughout the product and its documentation. Making Sense of Seeks Let’s forget all about scans for a moment, and think purely about seeks.  Loosely speaking, a seek is the process of navigating an index B-tree to find a particular index record, most often at the leaf level.  A seek starts at the root and navigates down through the levels of the index to find the point of interest: Singleton Lookups The simplest sort of seek predicate performs this traversal to find (at most) a single record.  This is the case when we search for a single value using a unique index and an equality predicate.  It should be readily apparent that this type of search will either find one record, or none at all.  This operation is known as a singleton lookup.  Given the example table from before, the following query is an example of a singleton lookup seek: Sadly, there’s nothing in the graphical plan or XML output to show that this is a singleton lookup – you have to infer it from the fact that this is a single-value equality seek on a unique index.  The other common examples of a singleton lookup are bookmark lookups – both the RID and Key Lookup forms are singleton lookups (an RID lookup finds a single record in a heap from the unique row locator, and a Key Lookup does much the same thing on a clustered table).  If you happen to run your query with STATISTICS IO ON, you will notice that ‘Scan Count’ is always zero for a singleton lookup. Range Scans The other type of seek predicate is a ‘seek plus range scan’, which I will refer to simply as a range scan.  The seek operation makes an initial descent into the index structure to find the first leaf row that qualifies, and then performs a range scan (either backwards or forwards in the index) until it reaches the end of the scan range. The ability of a range scan to proceed in either direction comes about because index pages at the same level are connected by a doubly-linked list – each page has a pointer to the previous page (in logical key order) as well as a pointer to the following page.  The doubly-linked list is represented by the green and red dotted arrows in the index diagram presented earlier.  One subtle (but important) point is that the notion of a ‘forward’ or ‘backward’ scan applies to the logical key order defined when the index was built.  In the present case, the non-clustered primary key index was created as follows: CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col ASC) ) ; Notice that the primary key index specifies an ascending sort order for the single key column.  This means that a forward scan of the index will retrieve keys in ascending order, while a backward scan would retrieve keys in descending key order.  If the index had been created instead on key_col DESC, a forward scan would retrieve keys in descending order, and a backward scan would return keys in ascending order. A range scan seek predicate may have a Start condition, an End condition, or both.  Where one is missing, the scan starts (or ends) at one extreme end of the index, depending on the scan direction.  Some examples might help clarify that: the following diagram shows four queries, each of which performs a single seek against a column holding every integer from 1 to 100 inclusive.  The results from each query are shown in the blue columns, and relevant attributes from the Properties window appear on the right: Query 1 specifies that all key_col values less than 5 should be returned in ascending order.  The query plan achieves this by seeking to the start of the index leaf (there is no explicit starting value) and scanning forward until the End condition (key_col < 5) is no longer satisfied (SQL Server knows it can stop looking as soon as it finds a key_col value that isn’t less than 5 because all later index entries are guaranteed to sort higher). Query 2 asks for key_col values greater than 95, in descending order.  SQL Server returns these results by seeking to the end of the index, and scanning backwards (in descending key order) until it comes across a row that isn’t greater than 95.  Sharp-eyed readers may notice that the end-of-scan condition is shown as a Start range value.  This is a bug in the XML show plan which bubbles up to the Properties window – when a backward scan is performed, the roles of the Start and End values are reversed, but the plan does not reflect that.  Oh well. Query 3 looks for key_col values that are greater than or equal to 10, and less than 15, in ascending order.  This time, SQL Server seeks to the first index record that matches the Start condition (key_col >= 10) and then scans forward through the leaf pages until the End condition (key_col < 15) is no longer met. Query 4 performs much the same sort of operation as Query 3, but requests the output in descending order.  Again, we have to mentally reverse the Start and End conditions because of the bug, but otherwise the process is the same as always: SQL Server finds the highest-sorting record that meets the condition ‘key_col < 25’ and scans backward until ‘key_col >= 20’ is no longer true. One final point to note: seek operations always have the Ordered: True attribute.  This means that the operator always produces rows in a sorted order, either ascending or descending depending on how the index was defined, and whether the scan part of the operation is forward or backward.  You cannot rely on this sort order in your queries of course (you must always specify an ORDER BY clause if order is important) but SQL Server can make use of the sort order internally.  In the four queries above, the query optimizer was able to avoid an explicit Sort operator to honour the ORDER BY clause, for example. Multiple Seek Predicates As we saw yesterday, a single index seek plan operator can contain one or more seek predicates.  These seek predicates can either be all singleton seeks or all range scans – SQL Server does not mix them.  For example, you might expect the following query to contain two seek predicates, a singleton seek to find the single record in the unique index where key_col = 10, and a range scan to find the key_col values between 15 and 20: SELECT key_col FROM dbo.Example WHERE key_col = 10 OR key_col BETWEEN 15 AND 20 ORDER BY key_col ASC ; In fact, SQL Server transforms the singleton seek (key_col = 10) to the equivalent range scan, Start:[key_col >= 10], End:[key_col <= 10].  This allows both range scans to be evaluated by a single seek operator.  To be clear, this query results in two range scans: one from 10 to 10, and one from 15 to 20. Final Thoughts That’s it for today – tomorrow we’ll look at monitoring singleton lookups and range scans, and I’ll show you a seek on a heap table. Yes, a seek.  On a heap.  Not an index! If you would like to run the queries in this post for yourself, there’s a script below.  Thanks for reading! IF OBJECT_ID(N'dbo.Example', N'U') IS NOT NULL BEGIN DROP TABLE dbo.Example; END ; -- Test table is a heap -- Non-clustered primary key on 'key_col' CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col) ) ; -- Non-unique non-clustered index on the 'data' column CREATE NONCLUSTERED INDEX [IX dbo.Example data] ON dbo.Example (data) ; -- Add 100 rows INSERT dbo.Example WITH (TABLOCKX) ( key_col, data ) SELECT key_col = V.number, data = V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 100 ; -- ================ -- Singleton lookup -- ================ ; -- Single value equality seek in a unique index -- Scan count = 0 when STATISTIS IO is ON -- Check the XML SHOWPLAN SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 32 ; -- =========== -- Range Scans -- =========== ; -- Query 1 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col <= 5 ORDER BY E.key_col ASC ; -- Query 2 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col > 95 ORDER BY E.key_col DESC ; -- Query 3 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 10 AND E.key_col < 15 ORDER BY E.key_col ASC ; -- Query 4 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 20 AND E.key_col < 25 ORDER BY E.key_col DESC ; -- Final query (singleton + range = 2 range scans) SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 10 OR E.key_col BETWEEN 15 AND 20 ORDER BY E.key_col ASC ; -- === TIDY UP === DROP TABLE dbo.Example; © 2011 Paul White email: [email protected] twitter: @SQL_Kiwi

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  • Table Variables: an empirical approach.

    - by Phil Factor
    It isn’t entirely a pleasant experience to publish an article only to have it described on Twitter as ‘Horrible’, and to have it criticized on the MVP forum. When this happened to me in the aftermath of publishing my article on Temporary tables recently, I was taken aback, because these critics were experts whose views I respect. What was my crime? It was, I think, to suggest that, despite the obvious quirks, it was best to use Table Variables as a first choice, and to use local Temporary Tables if you hit problems due to these quirks, or if you were doing complex joins using a large number of rows. What are these quirks? Well, table variables have advantages if they are used sensibly, but this requires some awareness by the developer about the potential hazards and how to avoid them. You can be hit by a badly-performing join involving a table variable. Table Variables are a compromise, and this compromise doesn’t always work out well. Explicit indexes aren’t allowed on Table Variables, so one cannot use covering indexes or non-unique indexes. The query optimizer has to make assumptions about the data rather than using column distribution statistics when a table variable is involved in a join, because there aren’t any column-based distribution statistics on a table variable. It assumes a reasonably even distribution of data, and is likely to have little idea of the number of rows in the table variables that are involved in queries. However complex the heuristics that are used might be in determining the best way of executing a SQL query, and they most certainly are, the Query Optimizer is likely to fail occasionally with table variables, under certain circumstances, and produce a Query Execution Plan that is frightful. The experienced developer or DBA will be on the lookout for this sort of problem. In this blog, I’ll be expanding on some of the tests I used when writing my article to illustrate the quirks, and include a subsequent example supplied by Kevin Boles. A simplified example. We’ll start out by illustrating a simple example that shows some of these characteristics. We’ll create two tables filled with random numbers and then see how many matches we get between the two tables. We’ll forget indexes altogether for this example, and use heaps. We’ll try the same Join with two table variables, two table variables with OPTION (RECOMPILE) in the JOIN clause, and with two temporary tables. It is all a bit jerky because of the granularity of the timing that isn’t actually happening at the millisecond level (I used DATETIME). However, you’ll see that the table variable is outperforming the local temporary table up to 10,000 rows. Actually, even without a use of the OPTION (RECOMPILE) hint, it is doing well. What happens when your table size increases? The table variable is, from around 30,000 rows, locked into a very bad execution plan unless you use OPTION (RECOMPILE) to provide the Query Analyser with a decent estimation of the size of the table. However, if it has the OPTION (RECOMPILE), then it is smokin’. Well, up to 120,000 rows, at least. It is performing better than a Temporary table, and in a good linear fashion. What about mixed table joins, where you are joining a temporary table to a table variable? You’d probably expect that the query analyzer would throw up its hands and produce a bad execution plan as if it were a table variable. After all, it knows nothing about the statistics in one of the tables so how could it do any better? Well, it behaves as if it were doing a recompile. And an explicit recompile adds no value at all. (we just go up to 45000 rows since we know the bigger picture now)   Now, if you were new to this, you might be tempted to start drawing conclusions. Beware! We’re dealing with a very complex beast: the Query Optimizer. It can come up with surprises What if we change the query very slightly to insert the results into a Table Variable? We change nothing else and just measure the execution time of the statement as before. Suddenly, the table variable isn’t looking so much better, even taking into account the time involved in doing the table insert. OK, if you haven’t used OPTION (RECOMPILE) then you’re toast. Otherwise, there isn’t much in it between the Table variable and the temporary table. The table variable is faster up to 8000 rows and then not much in it up to 100,000 rows. Past the 8000 row mark, we’ve lost the advantage of the table variable’s speed. Any general rule you may be formulating has just gone for a walk. What we can conclude from this experiment is that if you join two table variables, and can’t use constraints, you’re going to need that Option (RECOMPILE) hint. Count Dracula and the Horror Join. These tables of integers provide a rather unreal example, so let’s try a rather different example, and get stuck into some implicit indexing, by using constraints. What unusual words are contained in the book ‘Dracula’ by Bram Stoker? Here we get a table of all the common words in the English language (60,387 of them) and put them in a table. We put them in a Table Variable with the word as a primary key, a Table Variable Heap and a Table Variable with a primary key. We then take all the distinct words used in the book ‘Dracula’ (7,558 of them). We then create a table variable and insert into it all those uncommon words that are in ‘Dracula’. i.e. all the words in Dracula that aren’t matched in the list of common words. To do this we use a left outer join, where the right-hand value is null. The results show a huge variation, between the sublime and the gorblimey. If both tables contain a Primary Key on the columns we join on, and both are Table Variables, it took 33 Ms. If one table contains a Primary Key, and the other is a heap, and both are Table Variables, it took 46 Ms. If both Table Variables use a unique constraint, then the query takes 36 Ms. If neither table contains a Primary Key and both are Table Variables, it took 116383 Ms. Yes, nearly two minutes!! If both tables contain a Primary Key, one is a Table Variables and the other is a temporary table, it took 113 Ms. If one table contains a Primary Key, and both are Temporary Tables, it took 56 Ms.If both tables are temporary tables and both have primary keys, it took 46 Ms. Here we see table variables which are joined on their primary key again enjoying a  slight performance advantage over temporary tables. Where both tables are table variables and both are heaps, the query suddenly takes nearly two minutes! So what if you have two heaps and you use option Recompile? If you take the rogue query and add the hint, then suddenly, the query drops its time down to 76 Ms. If you add unique indexes, then you've done even better, down to half that time. Here are the text execution plans.So where have we got to? Without drilling down into the minutiae of the execution plans we can begin to create a hypothesis. If you are using table variables, and your tables are relatively small, they are faster than temporary tables, but as the number of rows increases you need to do one of two things: either you need to have a primary key on the column you are using to join on, or else you need to use option (RECOMPILE) If you try to execute a query that is a join, and both tables are table variable heaps, you are asking for trouble, well- slow queries, unless you give the table hint once the number of rows has risen past a point (30,000 in our first example, but this varies considerably according to context). Kevin’s Skew In describing the table-size, I used the term ‘relatively small’. Kevin Boles produced an interesting case where a single-row table variable produces a very poor execution plan when joined to a very, very skewed table. In the original, pasted into my article as a comment, a column consisted of 100000 rows in which the key column was one number (1) . To this was added eight rows with sequential numbers up to 9. When this was joined to a single-tow Table Variable with a key of 2 it produced a bad plan. This problem is unlikely to occur in real usage, and the Query Optimiser team probably never set up a test for it. Actually, the skew can be slightly less extreme than Kevin made it. The following test showed that once the table had 54 sequential rows in the table, then it adopted exactly the same execution plan as for the temporary table and then all was well. Undeniably, real data does occasionally cause problems to the performance of joins in Table Variables due to the extreme skew of the distribution. We've all experienced Perfectly Poisonous Table Variables in real live data. As in Kevin’s example, indexes merely make matters worse, and the OPTION (RECOMPILE) trick does nothing to help. In this case, there is no option but to use a temporary table. However, one has to note that once the slight de-skew had taken place, then the plans were identical across a huge range. Conclusions Where you need to hold intermediate results as part of a process, Table Variables offer a good alternative to temporary tables when used wisely. They can perform faster than a temporary table when the number of rows is not great. For some processing with huge tables, they can perform well when only a clustered index is required, and when the nature of the processing makes an index seek very effective. Table Variables are scoped to the batch or procedure and are unlikely to hang about in the TempDB when they are no longer required. They require no explicit cleanup. Where the number of rows in the table is moderate, you can even use them in joins as ‘Heaps’, unindexed. Beware, however, since, as the number of rows increase, joins on Table Variable heaps can easily become saddled by very poor execution plans, and this must be cured either by adding constraints (UNIQUE or PRIMARY KEY) or by adding the OPTION (RECOMPILE) hint if this is impossible. Occasionally, the way that the data is distributed prevents the efficient use of Table Variables, and this will require using a temporary table instead. Tables Variables require some awareness by the developer about the potential hazards and how to avoid them. If you are not prepared to do any performance monitoring of your code or fine-tuning, and just want to pummel out stuff that ‘just runs’ without considering namby-pamby stuff such as indexes, then stick to Temporary tables. If you are likely to slosh about large numbers of rows in temporary tables without considering the niceties of processing just what is required and no more, then temporary tables provide a safer and less fragile means-to-an-end for you.

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  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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  • Performance considerations for common SQL queries

    - by Jim Giercyk
    Originally posted on: http://geekswithblogs.net/NibblesAndBits/archive/2013/10/16/performance-considerations-for-common-sql-queries.aspxSQL offers many different methods to produce the same results.  There is a never-ending debate between SQL developers as to the “best way” or the “most efficient way” to render a result set.  Sometimes these disputes even come to blows….well, I am a lover, not a fighter, so I decided to collect some data that will prove which way is the best and most efficient.  For the queries below, I downloaded the test database from SQLSkills:  http://www.sqlskills.com/sql-server-resources/sql-server-demos/.  There isn’t a lot of data, but enough to prove my point: dbo.member has 10,000 records, and dbo.payment has 15,554.  Our result set contains 6,706 records. The following queries produce an identical result set; the result set contains aggregate payment information for each member who has made more than 1 payment from the dbo.payment table and the first and last name of the member from the dbo.member table.   /*************/ /* Sub Query  */ /*************/ SELECT  a.[Member Number] ,         m.lastname ,         m.firstname ,         a.[Number Of Payments] ,         a.[Average Payment] ,         a.[Total Paid] FROM    ( SELECT    member_no 'Member Number' ,                     AVG(payment_amt) 'Average Payment' ,                     SUM(payment_amt) 'Total Paid' ,                     COUNT(Payment_No) 'Number Of Payments'           FROM      dbo.payment           GROUP BY  member_no           HAVING    COUNT(Payment_No) > 1         ) a         JOIN dbo.member m ON a.[Member Number] = m.member_no         /***************/ /* Cross Apply  */ /***************/ SELECT  ca.[Member Number] ,         m.lastname ,         m.firstname ,         ca.[Number Of Payments] ,         ca.[Average Payment] ,         ca.[Total Paid] FROM    dbo.member m         CROSS APPLY ( SELECT    member_no 'Member Number' ,                                 AVG(payment_amt) 'Average Payment' ,                                 SUM(payment_amt) 'Total Paid' ,                                 COUNT(Payment_No) 'Number Of Payments'                       FROM      dbo.payment                       WHERE     member_no = m.member_no                       GROUP BY  member_no                       HAVING    COUNT(Payment_No) > 1                     ) ca /********/                    /* CTEs  */ /********/ ; WITH    Payments           AS ( SELECT   member_no 'Member Number' ,                         AVG(payment_amt) 'Average Payment' ,                         SUM(payment_amt) 'Total Paid' ,                         COUNT(Payment_No) 'Number Of Payments'                FROM     dbo.payment                GROUP BY member_no                HAVING   COUNT(Payment_No) > 1              ),         MemberInfo           AS ( SELECT   p.[Member Number] ,                         m.lastname ,                         m.firstname ,                         p.[Number Of Payments] ,                         p.[Average Payment] ,                         p.[Total Paid]                FROM     dbo.member m                         JOIN Payments p ON m.member_no = p.[Member Number]              )     SELECT  *     FROM    MemberInfo /************************/ /* SELECT with Grouping   */ /************************/ SELECT  p.member_no 'Member Number' ,         m.lastname ,         m.firstname ,         COUNT(Payment_No) 'Number Of Payments' ,         AVG(payment_amt) 'Average Payment' ,         SUM(payment_amt) 'Total Paid' FROM    dbo.payment p         JOIN dbo.member m ON m.member_no = p.member_no GROUP BY p.member_no ,         m.lastname ,         m.firstname HAVING  COUNT(Payment_No) > 1   We can see what is going on in SQL’s brain by looking at the execution plan.  The Execution Plan will demonstrate which steps and in what order SQL executes those steps, and what percentage of batch time each query takes.  SO….if I execute all 4 of these queries in a single batch, I will get an idea of the relative time SQL takes to execute them, and how it renders the Execution Plan.  We can settle this once and for all.  Here is what SQL did with these queries:   Not only did the queries take the same amount of time to execute, SQL generated the same Execution Plan for each of them.  Everybody is right…..I guess we can all finally go to lunch together!  But wait a second, I may not be a fighter, but I AM an instigator.     Let’s see how a table variable stacks up.  Here is the code I executed: /********************/ /*  Table Variable  */ /********************/ DECLARE @AggregateTable TABLE     (       member_no INT ,       AveragePayment MONEY ,       TotalPaid MONEY ,       NumberOfPayments MONEY     ) INSERT  @AggregateTable         SELECT  member_no 'Member Number' ,                 AVG(payment_amt) 'Average Payment' ,                 SUM(payment_amt) 'Total Paid' ,                 COUNT(Payment_No) 'Number Of Payments'         FROM    dbo.payment         GROUP BY member_no         HAVING  COUNT(Payment_No) > 1   SELECT  at.member_no 'Member Number' ,         m.lastname ,         m.firstname ,         at.NumberOfPayments 'Number Of Payments' ,         at.AveragePayment 'Average Payment' ,         at.TotalPaid 'Total Paid' FROM    @AggregateTable at         JOIN dbo.member m ON m.member_no = at.member_no In the interest of keeping things in groupings of 4, I removed the last query from the previous batch and added the table variable query.  Here’s what I got:     Since we first insert into the table variable, then we read from it, the Execution Plan renders 2 steps.  BUT, the combination of the 2 steps is only 22% of the batch.  It is actually faster than the other methods even though it is treated as 2 separate queries in the Execution Plan.  The argument I often hear against Table Variables is that SQL only estimates 1 row for the table size in the Execution Plan.  While this is true, the estimate does not come in to play until you read from the table variable.  In this case, the table variable had 6,706 rows, but it still outperformed the other queries.  People argue that table variables should only be used for hash or lookup tables.  The fact is, you have control of what you put IN to the variable, so as long as you keep it within reason, these results suggest that a table variable is a viable alternative to sub-queries. If anyone does volume testing on this theory, I would be interested in the results.  My suspicion is that there is a breaking point where efficiency goes down the tubes immediately, and it would be interesting to see where the threshold is. Coding SQL is a matter of style.  If you’ve been around since they introduced DB2, you were probably taught a little differently than a recent computer science graduate.  If you have a company standard, I strongly recommend you follow it.    If you do not have a standard, generally speaking, there is no right or wrong answer when talking about the efficiency of these types of queries, and certainly no hard-and-fast rule.  Volume and infrastructure will dictate a lot when it comes to performance, so your results may vary in your environment.  Download the database and try it!

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  • .NET 4: &ldquo;Slim&rdquo;-style performance boost!

    - by Vitus
    RTM version of .NET 4 and Visual Studio 2010 is available, and now we can do some test with it. Parallel Extensions is one of the most valuable part of .NET 4.0. It’s a set of good tools for easily consuming multicore hardware power. And it also contains some “upgraded” sync primitives – Slim-version. For example, it include updated variant of widely known ManualResetEvent. For people, who don’t know about it: you can sync concurrency execution of some pieces of code with this sync primitive. Instance of ManualResetEvent can be in 2 states: signaled and non-signaled. Transition between it possible by Set() and Reset() methods call. Some shortly explanation: Thread 1 Thread 2 Time mre.Reset(); mre.WaitOne(); //code execution 0 //wating //code execution 1 //wating //code execution 2 //wating //code execution 3 //wating mre.Set(); 4 //code execution //… 5 Upgraded version of this primitive is ManualResetEventSlim. The idea in decreasing performance cost in case, when only 1 thread use it. Main concept in the “hybrid sync schema”, which can be done as following:   internal sealed class SimpleHybridLock : IDisposable { private Int32 m_waiters = 0; private AutoResetEvent m_waiterLock = new AutoResetEvent(false);   public void Enter() { if (Interlocked.Increment(ref m_waiters) == 1) return; m_waiterLock.WaitOne(); }   public void Leave() { if (Interlocked.Decrement(ref m_waiters) == 0) return; m_waiterLock.Set(); }   public void Dispose() { m_waiterLock.Dispose(); } } It’s a sample from Jeffry Richter’s book “CLR via C#”, 3rd edition. Primitive SimpleHybridLock have two public methods: Enter() and Leave(). You can put your concurrency-critical code between calls of these methods, and it would executed in only one thread at the moment. Code is really simple: first thread, called Enter(), increase counter. Second thread also increase counter, and suspend while m_waiterLock is not signaled. So, if we don’t have concurrent access to our lock, “heavy” methods WaitOne() and Set() will not called. It’s can give some performance bonus. ManualResetEvent use the similar idea. Of course, it have more “smart” technics inside, like a checking of recursive calls, and so on. I want to know a real difference between classic ManualResetEvent realization, and new –Slim. I wrote a simple “benchmark”: class Program { static void Main(string[] args) { ManualResetEventSlim mres = new ManualResetEventSlim(false); ManualResetEventSlim mres2 = new ManualResetEventSlim(false);   ManualResetEvent mre = new ManualResetEvent(false);   long total = 0; int COUNT = 50;   for (int i = 0; i < COUNT; i++) { mres2.Reset(); Stopwatch sw = Stopwatch.StartNew();   ThreadPool.QueueUserWorkItem((obj) => { //Method(mres, true); Method2(mre, true); mres2.Set(); }); //Method(mres, false); Method2(mre, false);   mres2.Wait(); sw.Stop();   Console.WriteLine("Pass {0}: {1} ms", i, sw.ElapsedMilliseconds); total += sw.ElapsedMilliseconds; }   Console.WriteLine(); Console.WriteLine("==============================="); Console.WriteLine("Done in average=" + total / (double)COUNT); Console.ReadLine(); }   private static void Method(ManualResetEventSlim mre, bool value) { for (int i = 0; i < 9000000; i++) { if (value) { mre.Set(); } else { mre.Reset(); } } }   private static void Method2(ManualResetEvent mre, bool value) { for (int i = 0; i < 9000000; i++) { if (value) { mre.Set(); } else { mre.Reset(); } } } } I use 2 concurrent thread (the main thread and one from thread pool) for setting and resetting ManualResetEvents, and try to run test COUNT times, and calculate average execution time. Here is the results (I get it on my dual core notebook with T7250 CPU and Windows 7 x64): ManualResetEvent ManualResetEventSlim Difference is obvious and serious – in 10 times! So, I think preferable way is using ManualResetEventSlim, because not always on calling Set() and Reset() will be called “heavy” methods for working with Windows kernel-mode objects. It’s a small and nice improvement! ;)

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  • Does it take time to deallocate memory?

    - by jm1234567890
    I have a C++ program which, during execution, will allocate about 3-8Gb of memory to store a hash table (I use tr1/unordered_map) and various other data structures. However, at the end of execution, there will be a long pause before returning to shell. For example, at the very end of my main function I have std::cout << "End of execution" << endl; But the execution of my program will go something like $ ./program do stuff... End of execution [long pause of maybe 2 min] $ -- returns to shell Is this expected behavior or am I doing something wrong? I'm guessing that the program is deallocating the memory at the end. But, commercial applications which use large amounts of memory (such as photoshop) do not exhibit this pause when you close the application. Please advise :)

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  • NHibernate and Composite Key References

    - by Rich
    I have a weird situation. I have three entities, Company, Employee, Plan and Participation (in retirement plan). Company PK: Company ID Plan PK: Company ID, Plan ID Employee PK: Company ID, SSN, Employee ID Participation PK: Company ID, SSN, Plan ID The problem is in linking the employee to the participation. From a DB perspective, participation should have Employee ID in the PK (it's not even in table). But it doesn't. NHibernate won't let me map the "has many" because the link expects 3 columns (since Employee PK has 3 columns), but I'd only provide 2. Any ideas on how to do this?

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  • Master Note for Generic Data Warehousing

    - by lajos.varady(at)oracle.com
    ++++++++++++++++++++++++++++++++++++++++++++++++++++ The complete and the most recent version of this article can be viewed from My Oracle Support Knowledge Section. Master Note for Generic Data Warehousing [ID 1269175.1] ++++++++++++++++++++++++++++++++++++++++++++++++++++In this Document   Purpose   Master Note for Generic Data Warehousing      Components covered      Oracle Database Data Warehousing specific documents for recent versions      Technology Network Product Homes      Master Notes available in My Oracle Support      White Papers      Technical Presentations Platforms: 1-914CU; This document is being delivered to you via Oracle Support's Rapid Visibility (RaV) process and therefore has not been subject to an independent technical review. Applies to: Oracle Server - Enterprise Edition - Version: 9.2.0.1 to 11.2.0.2 - Release: 9.2 to 11.2Information in this document applies to any platform. Purpose Provide navigation path Master Note for Generic Data Warehousing Components covered Read Only Materialized ViewsQuery RewriteDatabase Object PartitioningParallel Execution and Parallel QueryDatabase CompressionTransportable TablespacesOracle Online Analytical Processing (OLAP)Oracle Data MiningOracle Database Data Warehousing specific documents for recent versions 11g Release 2 (11.2)11g Release 1 (11.1)10g Release 2 (10.2)10g Release 1 (10.1)9i Release 2 (9.2)9i Release 1 (9.0)Technology Network Product HomesOracle Partitioning Advanced CompressionOracle Data MiningOracle OLAPMaster Notes available in My Oracle SupportThese technical articles have been written by Oracle Support Engineers to provide proactive and top level information and knowledge about the components of thedatabase we handle under the "Database Datawarehousing".Note 1166564.1 Master Note: Transportable Tablespaces (TTS) -- Common Questions and IssuesNote 1087507.1 Master Note for MVIEW 'ORA-' error diagnosis. For Materialized View CREATE or REFRESHNote 1102801.1 Master Note: How to Get a 10046 trace for a Parallel QueryNote 1097154.1 Master Note Parallel Execution Wait Events Note 1107593.1 Master Note for the Oracle OLAP OptionNote 1087643.1 Master Note for Oracle Data MiningNote 1215173.1 Master Note for Query RewriteNote 1223705.1 Master Note for OLTP Compression Note 1269175.1 Master Note for Generic Data WarehousingWhite Papers Transportable Tablespaces white papers Database Upgrade Using Transportable Tablespaces:Oracle Database 11g Release 1 (February 2009) Platform Migration Using Transportable Database Oracle Database 11g and 10g Release 2 (August 2008) Database Upgrade using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007) Platform Migration using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007)Parallel Execution and Parallel Query white papers Best Practices for Workload Management of a Data Warehouse on the Sun Oracle Database Machine (June 2010) Effective resource utilization by In-Memory Parallel Execution in Oracle Real Application Clusters 11g Release 2 (Feb 2010) Parallel Execution Fundamentals in Oracle Database 11g Release 2 (November 2009) Parallel Execution with Oracle Database 10g Release 2 (June 2005)Oracle Data Mining white paper Oracle Data Mining 11g Release 2 (March 2010)Partitioning white papers Partitioning with Oracle Database 11g Release 2 (September 2009) Partitioning in Oracle Database 11g (June 2007)Materialized Views and Query Rewrite white papers Oracle Materialized Views  and Query Rewrite (May 2005) Improving Performance using Query Rewrite in Oracle Database 10g (December 2003)Database Compression white papers Advanced Compression with Oracle Database 11g Release 2 (September 2009) Table Compression in Oracle Database 10g Release 2 (May 2005)Oracle OLAP white papers On-line Analytic Processing with Oracle Database 11g Release 2 (September 2009) Using Oracle Business Intelligence Enterprise Edition with the OLAP Option to Oracle Database 11g (July 2008)Generic white papers Enabling Pervasive BI through a Practical Data Warehouse Reference Architecture (February 2010) Optimizing and Protecting Storage with Oracle Database 11g Release 2 (November 2009) Oracle Database 11g for Data Warehousing and Business Intelligence (August 2009) Best practices for a Data Warehouse on Oracle Database 11g (September 2008)Technical PresentationsA selection of ObE - Oracle by Examples documents: Generic Using Basic Database Functionality for Data Warehousing (10g) Partitioning Manipulating Partitions in Oracle Database (11g Release 1) Using High-Speed Data Loading and Rolling Window Operations with Partitioning (11g Release 1) Using Partitioned Outer Join to Fill Gaps in Sparse Data (10g) Materialized View and Query Rewrite Using Materialized Views and Query Rewrite Capabilities (10g) Using the SQLAccess Advisor to Recommend Materialized Views and Indexes (10g) Oracle OLAP Using Microsoft Excel With Oracle 11g Cubes (how to analyze data in Oracle OLAP Cubes using Excel's native capabilities) Using Oracle OLAP 11g With Oracle BI Enterprise Edition (Creating OBIEE Metadata for OLAP 11g Cubes and querying those in BI Answers) Building OLAP 11g Cubes Querying OLAP 11g Cubes Creating Interactive APEX Reports Over OLAP 11g CubesSelection of presentations from the BIWA website:Extreme Data Warehousing With Exadata  by Hermann Baer (July 2010) (slides 2.5MB, recording 54MB)Data Mining Made Easy! Introducing Oracle Data Miner 11g Release 2 New "Work flow" GUI   by Charlie Berger (May 2010) (slides 4.8MB, recording 85MB )Best Practices for Deploying a Data Warehouse on Oracle Database 11g  by Maria Colgan (December 2009)  (slides 3MB, recording 18MB, white paper 3MB )

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  • IntelliTrace As a Learning Tool for MVC2 in a VS2010 Project

    - by Sam Abraham
    IntelliTrace is a new feature in Visual Studio 2010 Ultimate Edition. I see this valuable tool as a “Program Execution Recorder” that captures information about events and calls taking place as soon as we hit the VS2010 play (Start Debugging) button or the F5 key. Many online resources already discuss IntelliTrace and the benefit it brings to both developers and testers alike so I see no value of just repeating this information.  In this brief blog entry, I would like to share with you how I will be using IntelliTrace in my upcoming talk at the Ft Lauderdale ArcSig .Net User Group Meeting on April 20th 2010 (check http://www.fladotnet.com for more information), as a learning tool to demonstrate the internals of the lifecycle of an MVC2 application.  I will also be providing some helpful links that cover IntelliTrace in more detail at the end of my article for reference. IntelliTrace is setup by default to only capture execution events. Microsoft did such a great job on optimizing its recording process that I haven’t even felt the slightest performance hit with IntelliTrace running as I was debugging my solutions and projects.  For my purposes here however, I needed to capture more information beyond execution events, so I turned on the option for capturing calls in addition to events as shown in Figures 1 and 2. Changing capture options will require us to stop our debugging session and start over for the new settings to take place. Figure 1 – Access IntelliTrace options via the Tools->Options menu items Figure 2 – Change IntelliTrace Options to capture call information as well as events Notice the warning with regards to potentially degrading performance when selecting to capture call information in addition to the default events-only setting. I have found this warning to be sure true. My subsequent tests showed slowness in page load times compared to rendering those same exact pages with the “event-only” option selected. Execution recording is auto-started along with the new debugging session of our project. At this point, we can simply interact with the application and continue executing normally until we decide to “playback” the code we have executed so far.  For code replay, first step is to “break” the current execution as show in Figure 3.   Figure 3 – Break to replay recording A few tries later, I found a good process to quickly find and demonstrate the MVC2 page lifecycle. First-off, we start with the event view as shown in Figure 4 until we find an interesting event that needs further studying.  Figure 4 – Going through IntelliTrace’s events and picking as specific entry of interest We now can, for instance, study how the highlighted HTTP GET request is being handled, by clicking on the “Calls View” for that particular event. Notice that IntelliTrace shows us all calls that took place in servicing that GET request. Double clicking on any call takes us to a more granular view of the call stack within that clicked call, up until getting to a specific line of code where we can do a line-by-line replay of the execution from that point onwards using F10 or F11 just like our typical good old VS2008 debugging helped us accomplish. Figure 5 – switching to call view on an event of interest Figure 6 – Double clicking on call shows a more granular view of the call stack. In conclusion, the introduction of IntelliTrace as a new addition to the VS developers’ tool arsenal enhances development and debugging experience and effectively tackles the “no-repro” problem. It will also hopefully enhance my audience’s experience listening to me speaking about  an MVC2 page lifecycle which I can now easily visually demonstrate, thereby improving the probability of keeping everybody awake a little longer. IntelliTrace References: http://msdn.microsoft.com/en-us/magazine/ee336126.aspx http://msdn.microsoft.com/en-us/library/dd264944(VS.100).aspx

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  • Add data to Django form class using modelformset_factory

    - by dean
    I have a problem where I need to display a lot of forms for detail data for a hierarchical data set. I want to display some relational fields as labels for the forms and I'm struggling with a way to do this in a more robust way. Here is the code... class Category(models.Model): name = models.CharField(max_length=160) class Item(models.Model): category = models.ForeignKey('Category') name = models.CharField(max_length=160) weight = models.IntegerField(default=0) class Meta: ordering = ('category','weight','name') class BudgetValue(models.Model): value = models.IntegerField() plan = models.ForeignKey('Plan') item = models.ForeignKey('Item') I use the modelformset_factory to create a formset of budgetvalue forms for a particular plan. What I'd like is item name and category name for each BudgetValue. When I iterate through the forms each one will be labeled properly. class BudgetValueForm(forms.ModelForm): item = forms.ModelChoiceField(queryset=Item.objects.all(),widget=forms.HiddenInput()) plan = forms.ModelChoiceField(queryset=Plan.objects.all(),widget=forms.HiddenInput()) category = "" < assign dynamically on form creation > item = "" < assign dynamically on form creation > class Meta: model = BudgetValue fields = ('item','plan','value') What I started out with is just creating a dictionary of budgetvalue.item.category.name, budgetvalue.item.name, and the form for each budget value. This gets passed to the template and I render it as I intended. I'm assuming that the ordering of the forms in the formset and the querset used to genererate the formset keep the budgetvalues in the same order and the dictionary is created correctly. That is the budgetvalue.item.name is associated with the correct form. This scares me and I'm thinking there has to be a better way. Any help would be greatly appreciated.

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  • need some concrete examples on user stories, tasks and how they relate to functional and technical specifications

    - by gideon
    Little heads up, Im the only lonely dev building/planning/mocking my project as I go. Ive come up with a preview release that does only the core aspects of the system, with good business value and I've coded most of the UI as dirty throw-able mockups over nicely abstracted and very minimal base code. In the end I know quite well what my clients want on the whole. I can't take agile-ish cowboying anymore because Im completely dis-organized and have no paper plan and since my clients are happy, things are getting more complex with more features and ideas. So I started using and learning Agile & Scrum Here are my problems: I know what a functional spec is.(sample): Do all user stories and/or scenarios become part of the functional spec? I know what user stories and tasks are. Are these kinda user stories? I dont see any Business Value reason added to them. I made a mind map using freemind, I had problems like this: Actor : Finance Manager Can Add a Financial Plan into the system because well thats the point of it? What Business Value reason do I add for things like this? Example : A user needs to be able to add a blog article (in the blogger app) because..?? Its the point of a blogger app, it centers around that feature? How do I go into the finer details and system definitions: Actor: Finance Manager Action: Adds a finance plan. This adding is a complicated process with lots of steps. What User Story will describe what a finance plan in the system is ?? I can add it into the functional spec under definitions explaining what a finance plan is and how one needs to add it into the system, but how do I get to the backlog planning from there? Example: A Blog Article is mostly a textual document that can be written in rich text in the system. To add a blog article one must...... But how do you create backlog list/features out of this? Where are the user stories for what a blog article is and how one adds/removes it? Finally, I'm a little confused about the relations between functional specs and user stories. Will my spec contain user stories in them with UI mockups? Now will these user stories then branch out tasks which will make up something like a technical specification? Example : EditorUser Can add a blog article. Use XML to store blog article. Add a form to add blog. Add Windows Live Writer Support. That would be agile tasks but would that also be part of/or form the technical specs? Some concrete examples/answers of my questions would be nice!!

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  • SQL SERVER – Subquery or Join – Various Options – SQL Server Engine knows the Best

    - by pinaldave
    This is followup post of my earlier article SQL SERVER – Convert IN to EXISTS – Performance Talk, after reading all the comments I have received I felt that I could write more on the same subject to clear few things out. First let us run following four queries, all of them are giving exactly same resultset. USE AdventureWorks GO -- use of = SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID = ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of in SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID IN ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of exists SELECT * FROM HumanResources.Employee E WHERE EXISTS ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- Use of Join SELECT * FROM HumanResources.Employee E INNER JOIN HumanResources.EmployeeAddress EA ON E.EmployeeID = EA.EmployeeID GO Let us compare the execution plan of the queries listed above. Click on image to see larger image. It is quite clear from the execution plan that in case of IN, EXISTS and JOIN SQL Server Engines is smart enough to figure out what is the best optimal plan of Merge Join for the same query and execute the same. However, in the case of use of Equal (=) Operator, SQL Server is forced to use Nested Loop and test each result of the inner query and compare to outer query, leading to cut the performance. Please note that here I no mean suggesting that Nested Loop is bad or Merge Join is better. This can very well vary on your machine and amount of resources available on your computer. When I see Equal (=) operator used in query like above, I usually recommend to see if user can use IN or EXISTS or JOIN. As I said, this can very much vary on different system. What is your take in above query? I believe SQL Server Engines is usually pretty smart to figure out what is ideal execution plan and use it. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • [Visual Studio Extension Of The Day] Test Scribe for Visual Studio Ultimate 2010 and Test Professional 2010

    - by Hosam Kamel
      Test Scribe is a documentation power tool designed to construct documents directly from the TFS for test plan and test run artifacts for the purpose of discussion, reporting etc... . Known Issues/Limitations Customizing the generated report by changing the template, adding comments, including attachments etc… is not supported While opening a test plan summary document in  Office 2007, if you get the warning: “The file Test Plan Summary cannot be opened because there are problems with the contents” (with Details: ‘The file is corrupt and cannot be opened’), click ‘OK’. Then, click ‘Yes’ to recover the contents of the document. This will then open the document in Office 2007. The same problem is not found in Office 2010. Generated documents are stored by default in the “My documents” folder. The output path of the generated report cannot be modified. Exporting word documents for individual test suites or test cases in a test plan is not supported. Download it from Visual Studio Extension Manager Originally posted at "Hosam Kamel| Developer & Platform Evangelist" http://blogs.msdn.com/hkamel

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  • How to Use USER_DEFINED Activity in OWB Process Flow

    - by Jinggen He
    Process Flow is a very important component of Oracle Warehouse Builder. With Process Flow, we can create and control the ETL process by setting all kinds of activities in a well-constructed flow. In Oracle Warehouse Builder 11gR2, there are 28 kinds of activities, which fall into three categories: Control activities, OWB specific activities and Utility activities. For more information about Process Flow activities, please refer to OWB online doc. Most of those activities are pre-defined for some specific use. For example, the Mapping activity allows execution an OWB mapping in Process Flow and the FTP activity allows an interaction between the local host and a remote FTP server. Besides those activities for specific purposes, the User Defined activity enables you to incorporate into a Process Flow an activity that is not defined within Warehouse Builder. So the User Defined activity brings flexibility and extensibility to Process Flow. In this article, we will take an amazing tour of using the User Defined activity. Let's start. Enable execution of User Defined activity Let's start this section from creating a very simple Process Flow, which contains a Start activity, a User Defined activity and an End Success activity. Leave all parameters of activity USER_DEFINED unchanged except that we enter /tmp/test.sh into the Value column of the COMMAND parameter. Then let's create the shell script test.sh in /tmp directory. Here is the content of /tmp/test.sh (this article is demonstrating a scenario in Linux system, and /tmp/test.sh is a Bash shell script): echo Hello World! > /tmp/test.txt Note: don't forget to grant the execution privilege on /tmp/test.sh to OS Oracle user. For simplicity, we just use the following command. chmod +x /tmp/test.sh OK, it's so simple that we’ve almost done it. Now deploy the Process Flow and run it. For a newly installed OWB, we will come across an error saying "RPE-02248: For security reasons, activity operator Shell has been disabled by the DBA". See below. That's because, by default, the User Defined activity is DISABLED. Configuration about this can be found in <ORACLE_HOME>/owb/bin/admin/Runtime.properties: property.RuntimePlatform.0.NativeExecution.Shell.security_constraint=DISABLED The property can be set to three different values: NATIVE_JAVA, SCHEDULER and DISBALED. Where NATIVE_JAVA uses the Java 'Runtime.exec' interface, SCHEDULER uses a DBMS Scheduler external job submitted by the Control Center repository owner which is executed by the default operating system user configured by the DBA. DISABLED prevents execution via these operators. We enable the execution of User Defined activity by setting: property.RuntimePlatform.0.NativeExecution.Shell.security_constraint= NATIVE_JAVA Restart the Control Center service for the change of setting to take effect. cd <ORACLE_HOME>/owb/rtp/sql sqlplus OWBSYS/<password of OWBSYS> @stop_service.sql sqlplus OWBSYS/<password of OWBSYS> @start_service.sql And then run the Process Flow again. We will see that the Process Flow completes successfully. The execution of /tmp/test.sh successfully generated a file /tmp/test.txt, containing the line Hello World!. Pass parameters to User Defined Activity The Process Flow created in the above section has a drawback: the User Defined activity doesn't accept any information from OWB nor does it give any meaningful results back to OWB. That's to say, it lacks interaction. Maybe, sometimes such a Process Flow can fulfill the business requirement. But for most of the time, we need to get the User Defined activity executed according to some information prior to that step. In this section, we will see how to pass parameters to the User Defined activity and pass them into the to-be-executed shell script. First, let's see how to pass parameters to the script. The User Defined activity has an input parameter named PARAMETER_LIST. This is a list of parameters that will be passed to the command. Parameters are separated from one another by a token. The token is taken as the first character on the PARAMETER_LIST string, and the string must also end in that token. Warehouse Builder recommends the '?' character, but any character can be used. For example, to pass 'abc,' 'def,' and 'ghi' you can use the following equivalent: ?abc?def?ghi? or !abc!def!ghi! or |abc|def|ghi| If the token character or '\' needs to be included as part of the parameter, then it must be preceded with '\'. For example '\\'. If '\' is the token character, then '/' becomes the escape character. Let's configure the PARAMETER_LIST parameter as below: And modify the shell script /tmp/test.sh as below: echo $1 is saying hello to $2! > /tmp/test.txt Re-deploy the Process Flow and run it. We will see that the generated /tmp/test.txt contains the following line: Bob is saying hello to Alice! In the example above, the parameters passed into the shell script are static. This case is not so useful because: instead of passing parameters, we can directly write the value of the parameters in the shell script. To make the case more meaningful, we can pass two dynamic parameters, that are obtained from the previous activity, to the shell script. Prepare the Process Flow as below: The Mapping activity MAPPING_1 has two output parameters: FROM_USER, TO_USER. The User Defined activity has two input parameters: FROM_USER, TO_USER. All the four parameters are of String type. Additionally, the Process Flow has two string variables: VARIABLE_FOR_FROM_USER, VARIABLE_FOR_TO_USER. Through VARIABLE_FOR_FROM_USER, the input parameter FROM_USER of USER_DEFINED gets value from output parameter FROM_USER of MAPPING_1. We achieve this by binding both parameters to VARIABLE_FOR_FROM_USER. See the two figures below. In the same way, through VARIABLE_FOR_TO_USER, the input parameter TO_USER of USER_DEFINED gets value from output parameter TO_USER of MAPPING_1. Also, we need to change the PARAMETER_LIST of the User Defined activity like below: Now, the shell script is getting input from the Mapping activity dynamically. Deploy the Process Flow and all of its necessary dependees then run the Process Flow. We see that the generated /tmp/test.txt contains the following line: USER B is saying hello to USER A! 'USER B' and 'USER A' are two outputs of the Mapping execution. Write the shell script within Oracle Warehouse Builder In the previous section, the shell script is located in the /tmp directory. But sometimes, when the shell script is small, or for the sake of maintaining consistency, you may want to keep the shell script inside Oracle Warehouse Builder. We can achieve this by configuring these three parameters of a User Defined activity properly: COMMAND: Set the path of interpreter, by which the shell script will be interpreted. PARAMETER_LIST: Set it blank. SCRIPT: Enter the shell script content. Note that in Linux the shell script content is passed into the interpreter as standard input at runtime. About how to actually pass parameters to the shell script, we can utilize variable substitutions. As in the following figure, ${FROM_USER} will be replaced by the value of the FROM_USER input parameter of the User Defined activity. So will the ${TO_USER} symbol. Besides the custom substitution variables, OWB also provide some system pre-defined substitution variables. You can refer to the online document for that. Deploy the Process Flow and run it. We see that the generated /tmp/test.txt contains the following line: USER B is saying hello to USER A! Leverage the return value of User Defined activity All of the previous sections are connecting the User Defined activity to END_SUCCESS with an unconditional transition. But what should we do if we want different subsequent activities for different shell script execution results? 1.  The simplest way is to add three simple-conditioned out-going transitions for the User Defined activity just like the figure below. In the figure, to simplify the scenario, we connect the User Defined activity to three End activities. Basically, if the shell script ends successfully, the whole Process Flow will end at END_SUCCESS, otherwise, the whole Process Flow will end at END_ERROR (in our case, ending at END_WARNING seldom happens). In the real world, we can add more complex and meaningful subsequent business logic. 2.  Or we can utilize complex conditions to work with different results of the User Defined activity. Previously, in our script, we only have this line: echo ${FROM_USER} is saying hello to ${TO_USER}! > /tmp/test.txt We can add more logic in it and return different values accordingly. echo ${FROM_USER} is saying hello to ${TO_USER}! > /tmp/test.txt if CONDITION_1 ; then ...... exit 0 fi if CONDITION_2 ; then ...... exit 2 fi if CONDITION_3 ; then ...... exit 3 fi After that we can leverage the result by checking RESULT_CODE in condition expression of those out-going transitions. Let's suppose that we have the Process Flow as the following graph (SUB_PROCESS_n stands for more different further processes): We can set complex condition for the transition from USER_DEFINED to SUB_PROCESS_1 like this: Other transitions can be set in the same way. Note that, in our shell script, we return 0, 2 and 3, but not 1. As in Linux system, if the shell script comes across a system error like IO error, the return value will be 1. We can explicitly handle such a return value. Summary Let's summarize what has been discussed in this article: How to create a Process Flow with a User Defined activity in it How to pass parameters from the prior activity to the User Defined activity and finally into the shell script How to write the shell script within Oracle Warehouse Builder How to do variable substitutions How to let the User Defined activity return different values and in what way can we leverage

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