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  • GNU make: should -j equal number the number of CPU cores in a system?

    - by Johan
    Hi What is you experience with the make -j flag? There seem to be some controversial if the jobs are supposed to be equal to the numbers of cores, or if you can maximize the build by adding one extra job that can be cued up while the others "work". The question is if it is better to use -j4 or -j5? And have you seen (or done) any benchmarking that support one or the other? Thanks Johan

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  • Beginners php developer does using LiveDocx white Zend Framework is cpu resource eater ?

    - by user63898
    Hello all im beginner in the php world i need to build option in web application that can convert well defined structures into rtf/pdf from txt/html i found using this site search about LiveDocx php component that is dependent on Zend Framework now im not familiar white the php engine ( the parser ) so im asking you experts is it good solution to use this components ? or its just over head ?

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  • Can I spead out a long running stored proc accross multiple CPU's?

    - by Russ
    [Also on SuperUser - http://superuser.com/questions/116600/can-i-spead-out-a-long-running-stored-proc-accross-multiple-cpus] I have a stored procedure in SQL server the gets, and decrypts a block of data. ( Credit cards in this case. ) Most of the time, the performance is tolerable, but there are a couple customers where the process is painfully slow, taking literally 1 minute to complete. ( Well, 59377ms to return from SQL Server to be exact, but it can vary by a few hundred ms based on load ) When I watch the process, I see that SQL is only using a single proc to perform the whole process, and typically only proc 0. Is there a way I can change my stored proc so that SQL can multi-thread the process? Is it even feasible to cheat and to break the calls in half, ( top 50%, bottom 50% ), and spread the load, as a gross hack? ( just spit-balling here ) My stored proc: USE [Commerce] GO /****** Object: StoredProcedure [dbo].[GetAllCreditCardsByCustomerId] Script Date: 03/05/2010 11:50:14 ******/ SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO ALTER PROCEDURE [dbo].[GetAllCreditCardsByCustomerId] @companyId UNIQUEIDENTIFIER, @DecryptionKey NVARCHAR (MAX) AS SET NoCount ON DECLARE @cardId uniqueidentifier DECLARE @tmpdecryptedCardData VarChar(MAX); DECLARE @decryptedCardData VarChar(MAX); DECLARE @tmpTable as Table ( CardId uniqueidentifier, DecryptedCard NVarChar(Max) ) DECLARE creditCards CURSOR FAST_FORWARD READ_ONLY FOR Select cardId from CreditCards where companyId = @companyId and Active=1 order by addedBy desc --2 OPEN creditCards --3 FETCH creditCards INTO @cardId -- prime the cursor WHILE @@Fetch_Status = 0 BEGIN --OPEN creditCards DECLARE creditCardData CURSOR FAST_FORWARD READ_ONLY FOR select convert(nvarchar(max), DecryptByCert(Cert_Id('Oh-Nay-Nay'), EncryptedCard, @DecryptionKey)) FROM CreditCardData where cardid = @cardId order by valueOrder OPEN creditCardData FETCH creditCardData INTO @tmpdecryptedCardData -- prime the cursor WHILE @@Fetch_Status = 0 BEGIN print 'CreditCardData' print @tmpdecryptedCardData set @decryptedCardData = ISNULL(@decryptedCardData, '') + @tmpdecryptedCardData print '@decryptedCardData' print @decryptedCardData; FETCH NEXT FROM creditCardData INTO @tmpdecryptedCardData -- fetch next END CLOSE creditCardData DEALLOCATE creditCardData insert into @tmpTable (CardId, DecryptedCard) values ( @cardId, @decryptedCardData ) set @decryptedCardData = '' FETCH NEXT FROM creditCards INTO @cardId -- fetch next END select CardId, DecryptedCard FROM @tmpTable CLOSE creditCards DEALLOCATE creditCards

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  • Can I spread out a long running stored proc accross multiple CPU's?

    - by Russ
    [Also on SuperUser - http://superuser.com/questions/116600/can-i-spead-out-a-long-running-stored-proc-accross-multiple-cpus] I have a stored procedure in SQL server the gets, and decrypts a block of data. ( Credit cards in this case. ) Most of the time, the performance is tolerable, but there are a couple customers where the process is painfully slow, taking literally 1 minute to complete. ( Well, 59377ms to return from SQL Server to be exact, but it can vary by a few hundred ms based on load ) When I watch the process, I see that SQL is only using a single proc to perform the whole process, and typically only proc 0. Is there a way I can change my stored proc so that SQL can multi-thread the process? Is it even feasible to cheat and to break the calls in half, ( top 50%, bottom 50% ), and spread the load, as a gross hack? ( just spit-balling here ) My stored proc: USE [Commerce] GO /****** Object: StoredProcedure [dbo].[GetAllCreditCardsByCustomerId] Script Date: 03/05/2010 11:50:14 ******/ SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO ALTER PROCEDURE [dbo].[GetAllCreditCardsByCustomerId] @companyId UNIQUEIDENTIFIER, @DecryptionKey NVARCHAR (MAX) AS SET NoCount ON DECLARE @cardId uniqueidentifier DECLARE @tmpdecryptedCardData VarChar(MAX); DECLARE @decryptedCardData VarChar(MAX); DECLARE @tmpTable as Table ( CardId uniqueidentifier, DecryptedCard NVarChar(Max) ) DECLARE creditCards CURSOR FAST_FORWARD READ_ONLY FOR Select cardId from CreditCards where companyId = @companyId and Active=1 order by addedBy desc --2 OPEN creditCards --3 FETCH creditCards INTO @cardId -- prime the cursor WHILE @@Fetch_Status = 0 BEGIN --OPEN creditCards DECLARE creditCardData CURSOR FAST_FORWARD READ_ONLY FOR select convert(nvarchar(max), DecryptByCert(Cert_Id('Oh-Nay-Nay'), EncryptedCard, @DecryptionKey)) FROM CreditCardData where cardid = @cardId order by valueOrder OPEN creditCardData FETCH creditCardData INTO @tmpdecryptedCardData -- prime the cursor WHILE @@Fetch_Status = 0 BEGIN print 'CreditCardData' print @tmpdecryptedCardData set @decryptedCardData = ISNULL(@decryptedCardData, '') + @tmpdecryptedCardData print '@decryptedCardData' print @decryptedCardData; FETCH NEXT FROM creditCardData INTO @tmpdecryptedCardData -- fetch next END CLOSE creditCardData DEALLOCATE creditCardData insert into @tmpTable (CardId, DecryptedCard) values ( @cardId, @decryptedCardData ) set @decryptedCardData = '' FETCH NEXT FROM creditCards INTO @cardId -- fetch next END select CardId, DecryptedCard FROM @tmpTable CLOSE creditCards DEALLOCATE creditCards

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  • Can I spread out a long running stored proc accross multiple CPU's?

    - by Russ
    [Also on SuperUser - http://superuser.com/questions/116600/can-i-spead-out-a-long-running-stored-proc-accross-multiple-cpus] I have a stored procedure in SQL server the gets, and decrypts a block of data. ( Credit cards in this case. ) Most of the time, the performance is tolerable, but there are a couple customers where the process is painfully slow, taking literally 1 minute to complete. ( Well, 59377ms to return from SQL Server to be exact, but it can vary by a few hundred ms based on load ) When I watch the process, I see that SQL is only using a single proc to perform the whole process, and typically only proc 0. Is there a way I can change my stored proc so that SQL can multi-thread the process? Is it even feasible to cheat and to break the calls in half, ( top 50%, bottom 50% ), and spread the load, as a gross hack? ( just spit-balling here ) My stored proc: USE [Commerce] GO /****** Object: StoredProcedure [dbo].[GetAllCreditCardsByCustomerId] Script Date: 03/05/2010 11:50:14 ******/ SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO ALTER PROCEDURE [dbo].[GetAllCreditCardsByCustomerId] @companyId UNIQUEIDENTIFIER, @DecryptionKey NVARCHAR (MAX) AS SET NoCount ON DECLARE @cardId uniqueidentifier DECLARE @tmpdecryptedCardData VarChar(MAX); DECLARE @decryptedCardData VarChar(MAX); DECLARE @tmpTable as Table ( CardId uniqueidentifier, DecryptedCard NVarChar(Max) ) DECLARE creditCards CURSOR FAST_FORWARD READ_ONLY FOR Select cardId from CreditCards where companyId = @companyId and Active=1 order by addedBy desc --2 OPEN creditCards --3 FETCH creditCards INTO @cardId -- prime the cursor WHILE @@Fetch_Status = 0 BEGIN --OPEN creditCards DECLARE creditCardData CURSOR FAST_FORWARD READ_ONLY FOR select convert(nvarchar(max), DecryptByCert(Cert_Id('Oh-Nay-Nay'), EncryptedCard, @DecryptionKey)) FROM CreditCardData where cardid = @cardId order by valueOrder OPEN creditCardData FETCH creditCardData INTO @tmpdecryptedCardData -- prime the cursor WHILE @@Fetch_Status = 0 BEGIN print 'CreditCardData' print @tmpdecryptedCardData set @decryptedCardData = ISNULL(@decryptedCardData, '') + @tmpdecryptedCardData print '@decryptedCardData' print @decryptedCardData; FETCH NEXT FROM creditCardData INTO @tmpdecryptedCardData -- fetch next END CLOSE creditCardData DEALLOCATE creditCardData insert into @tmpTable (CardId, DecryptedCard) values ( @cardId, @decryptedCardData ) set @decryptedCardData = '' FETCH NEXT FROM creditCards INTO @cardId -- fetch next END select CardId, DecryptedCard FROM @tmpTable CLOSE creditCards DEALLOCATE creditCards

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  • iPhone: CPU power to do DSP/Fourier transform/frequency domain?

    - by mahboudz
    I want to analyze MIC audio on an ongoing basis (not just a snipper or prerecorded sample), and display frequency graph and filter out certain aspects of the audio. Is the iPhone powerful enough for that? I suspect the answer is a yes, given the Google and iPhone voice recognition, Shazaam and other music recognition apps, and guitar tuner apps out there. However, I don't know what limitations I'll have to deal with. Anyone play around with this area?

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  • Setting CPU target to x86 on .NET 2.0 project adds .NET 3.5 dependencies.

    - by AngryHacker
    I have a project in VS2008 that targets .NET 2.0 framework. It was original set to build for AnyCPU. I changed it to x86 and for whatever reason, VS adds the following lines to .csproj: <ItemGroup> <BootstrapperPackage Include="Microsoft.Net.Client.3.5"> <Visible>False</Visible> <ProductName>.NET Framework Client Profile</ProductName> <Install>false</Install> </BootstrapperPackage> ... ... <BootstrapperPackage Include="Microsoft.Net.Framework.3.5.SP1"> <Visible>False</Visible> <ProductName>.NET Framework 3.5 SP1</ProductName> <Install>false</Install> </BootstrapperPackage> </ItemGroup> Can someone explain as to why this is being added and whether I can safely remove it, as I still have to target the .NET 2.0 framework. Thanks.

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  • Why does Indy 10's echo server have high CPU usage when the client disconnects?

    - by Virtuo
    When I disconnect echo client like : EchoClient1.Disconnect; client disconnects fine... but EchoServer does NOT EVEN register client disconnection and it ends up with high process usage !?!? in every example and every doc it says that calling EchoClient.Disconnect is sufficient ! anyone, any idea ? (I am working in Win7, cloud that be a problem ?) Server code : procedure TForm2.EServerConnect(AContext: TIdContext); begin SrvMsg.Lines.Add('ECHO Client connected !'); end; procedure TForm2.EServerDisconnect(AContext: TIdContext); begin SrvMsg.Lines.Add('ECHO Client disconnected !'); end; problem is "TForm2.EServerDisconnect" never executes !?!?

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  • Fast inter-process (inter-threaded) communications IPC on large multi-cpu system.

    - by IPC
    What would be the fastest portable bi-directional communication mechanism for inter-process communication where threads from one application need to communicate to multiple threads in another application on the same computer, and the communicating threads can be on different physical CPUs). I assume that it would involve a shared memory and a circular buffer and shared synchronization mechanisms. But shared mutexes are very expensive (and there are limited number of them too) to synchronize when threads are running on different physical CPUs.

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  • Does the Java Memory Model (JSR-133) imply that entering a monitor flushes the CPU data cache(s)?

    - by Durandal
    There is something that bugs me with the Java memory model (if i even understand everything correctly). If there are two threads A and B, there are no guarantees that B will ever see a value written by A, unless both A and B synchronize on the same monitor. For any system architecture that guarantees cache coherency between threads, there is no problem. But if the architecture does not support cache coherency in hardware, this essentially means that whenever a thread enters a monitor, all memory changes made before must be commited to main memory, and the cache must be invalidated. And it needs to be the entire data cache, not just a few lines, since the monitor has no information which variables in memory it guards. But that would surely impact performance of any application that needs to synchronize frequently (especially things like job queues with short running jobs). So can Java work reasonably well on architectures without hardware cache-coherency? If not, why doesn't the memory model make stronger guarantees about visibility? Wouldn't it be more efficient if the language would require information what is guarded by a monitor? As i see it the memory model gives us the worst of both worlds, the absolute need to synchronize, even if cache coherency is guaranteed in hardware, and on the other hand bad performance on incoherent architectures (full cache flushes). So shouldn't it be more strict (require information what is guarded by a monitor) or more lose and restrict potential platforms to cache-coherent architectures? As it is now, it doesn't make too much sense to me. Can somebody clear up why this specific memory model was choosen? EDIT: My use of strict and lose was a bad choice in retrospect. I used "strict" for the case where less guarantees are made and "lose" for the opposite. To avoid confusion, its probably better to speak in terms of stronger or weaker guarantees.

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  • What's up with LDoms: Part 1 - Introduction & Basic Concepts

    - by Stefan Hinker
    LDoms - the correct name is Oracle VM Server for SPARC - have been around for quite a while now.  But to my surprise, I get more and more requests to explain how they work or to give advise on how to make good use of them.  This made me think that writing up a few articles discussing the different features would be a good idea.  Now - I don't intend to rewrite the LDoms Admin Guide or to copy and reformat the (hopefully) well known "Beginners Guide to LDoms" by Tony Shoumack from 2007.  Those documents are very recommendable - especially the Beginners Guide, although based on LDoms 1.0, is still a good place to begin with.  However, LDoms have come a long way since then, and I hope to contribute to their adoption by discussing how they work and what features there are today.  In this and the following posts, I will use the term "LDoms" as a common abbreviation for Oracle VM Server for SPARC, just because it's a lot shorter and easier to type (and presumably, read). So, just to get everyone on the same baseline, lets briefly discuss the basic concepts of virtualization with LDoms.  LDoms make use of a hypervisor as a layer of abstraction between real, physical hardware and virtual hardware.  This virtual hardware is then used to create a number of guest systems which each behave very similar to a system running on bare metal:  Each has its own OBP, each will install its own copy of the Solaris OS and each will see a certain amount of CPU, memory, disk and network resources available to it.  Unlike some other type 1 hypervisors running on x86 hardware, the SPARC hypervisor is embedded in the system firmware and makes use both of supporting functions in the sun4v SPARC instruction set as well as the overall CPU architecture to fulfill its function. The CMT architecture of the supporting CPUs (T1 through T4) provide a large number of cores and threads to the OS.  For example, the current T4 CPU has eight cores, each running 8 threads, for a total of 64 threads per socket.  To the OS, this looks like 64 CPUs.  The SPARC hypervisor, when creating guest systems, simply assigns a certain number of these threads exclusively to one guest, thus avoiding the overhead of having to schedule OS threads to CPUs, as do typical x86 hypervisors.  The hypervisor only assigns CPUs and then steps aside.  It is not involved in the actual work being dispatched from the OS to the CPU, all it does is maintain isolation between different guests. Likewise, memory is assigned exclusively to individual guests.  Here,  the hypervisor provides generic mappings between the physical hardware addresses and the guest's views on memory.  Again, the hypervisor is not involved in the actual memory access, it only maintains isolation between guests. During the inital setup of a system with LDoms, you start with one special domain, called the Control Domain.  Initially, this domain owns all the hardware available in the system, including all CPUs, all RAM and all IO resources.  If you'd be running the system un-virtualized, this would be what you'd be working with.  To allow for guests, you first resize this initial domain (also called a primary domain in LDoms speak), assigning it a small amount of CPU and memory.  This frees up most of the available CPU and memory resources for guest domains.  IO is a little more complex, but very straightforward.  When LDoms 1.0 first came out, the only way to provide IO to guest systems was to create virtual disk and network services and attach guests to these services.  In the meantime, several different ways to connect guest domains to IO have been developed, the most recent one being SR-IOV support for network devices released in version 2.2 of Oracle VM Server for SPARC. I will cover these more advanced features in detail later.  For now, lets have a short look at the initial way IO was virtualized in LDoms: For virtualized IO, you create two services, one "Virtual Disk Service" or vds, and one "Virtual Switch" or vswitch.  You can, of course, also create more of these, but that's more advanced than I want to cover in this introduction.  These IO services now connect real, physical IO resources like a disk LUN or a networt port to the virtual devices that are assigned to guest domains.  For disk IO, the normal case would be to connect a physical LUN (or some other storage option that I'll discuss later) to one specific guest.  That guest would be assigned a virtual disk, which would appear to be just like a real LUN to the guest, while the IO is actually routed through the virtual disk service down to the physical device.  For network, the vswitch acts very much like a real, physical ethernet switch - you connect one physical port to it for outside connectivity and define one or more connections per guest, just like you would plug cables between a real switch and a real system. For completeness, there is another service that provides console access to guest domains which mimics the behavior of serial terminal servers. The connections between the virtual devices on the guest's side and the virtual IO services in the primary domain are created by the hypervisor.  It uses so called "Logical Domain Channels" or LDCs to create point-to-point connections between all of these devices and services.  These LDCs work very similar to high speed serial connections and are configured automatically whenever the Control Domain adds or removes virtual IO. To see all this in action, now lets look at a first example.  I will start with a newly installed machine and configure the control domain so that it's ready to create guest systems. In a first step, after we've installed the software, let's start the virtual console service and downsize the primary domain.  root@sun # ldm list NAME STATE FLAGS CONS VCPU MEMORY UTIL UPTIME primary active -n-c-- UART 512 261632M 0.3% 2d 13h 58m root@sun # ldm add-vconscon port-range=5000-5100 \ primary-console primary root@sun # svcadm enable vntsd root@sun # svcs vntsd STATE STIME FMRI online 9:53:21 svc:/ldoms/vntsd:default root@sun # ldm set-vcpu 16 primary root@sun # ldm set-mau 1 primary root@sun # ldm start-reconf primary root@sun # ldm set-memory 7680m primary root@sun # ldm add-config initial root@sun # shutdown -y -g0 -i6 So what have I done: I've defined a range of ports (5000-5100) for the virtual network terminal service and then started that service.  The vnts will later provide console connections to guest systems, very much like serial NTS's do in the physical world. Next, I assigned 16 vCPUs (on this platform, a T3-4, that's two cores) to the primary domain, freeing the rest up for future guest systems.  I also assigned one MAU to this domain.  A MAU is a crypto unit in the T3 CPU.  These need to be explicitly assigned to domains, just like CPU or memory.  (This is no longer the case with T4 systems, where crypto is always available everywhere.) Before I reassigned the memory, I started what's called a "delayed reconfiguration" session.  That avoids actually doing the change right away, which would take a considerable amount of time in this case.  Instead, I'll need to reboot once I'm all done.  I've assigned 7680MB of RAM to the primary.  That's 8GB less the 512MB which the hypervisor uses for it's own private purposes.  You can, depending on your needs, work with less.  I'll spend a dedicated article on sizing, discussing the pros and cons in detail. Finally, just before the reboot, I saved my work on the ILOM, to make this configuration available after a powercycle of the box.  (It'll always be available after a simple reboot, but the ILOM needs to know the configuration of the hypervisor after a power-cycle, before the primary domain is booted.) Now, lets create a first disk service and a first virtual switch which is connected to the physical network device igb2. We will later use these to connect virtual disks and virtual network ports of our guest systems to real world storage and network. root@sun # ldm add-vds primary-vds root@sun # ldm add-vswitch net-dev=igb2 switch-primary primary You are free to choose whatever names you like for the virtual disk service and the virtual switch.  I strongly recommend that you choose names that make sense to you and describe the function of each service in the context of your implementation.  For the vswitch, for example, you could choose names like "admin-vswitch" or "production-network" etc. This already concludes the configuration of the control domain.  We've freed up considerable amounts of CPU and RAM for guest systems and created the necessary infrastructure - console, vts and vswitch - so that guests systems can actually interact with the outside world.  The system is now ready to create guests, which I'll describe in the next section. For further reading, here are some recommendable links: The LDoms 2.2 Admin Guide The "Beginners Guide to LDoms" The LDoms Information Center on MOS LDoms on OTN

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  • FairScheduling Conventions in Hadoop

    - by dan.mcclary
    While scheduling and resource allocation control has been present in Hadoop since 0.20, a lot of people haven't discovered or utilized it in their initial investigations of the Hadoop ecosystem. We could chalk this up to many things: Organizations are still determining what their dataflow and analysis workloads will comprise Small deployments under tests aren't likely to show the signs of strains that would send someone looking for resource allocation options The default scheduling options -- the FairScheduler and the CapacityScheduler -- are not placed in the most prominent position within the Hadoop documentation. However, for production deployments, it's wise to start with at least the foundations of scheduling in place so that you can tune the cluster as workloads emerge. To do that, we have to ask ourselves something about what the off-the-rack scheduling options are. We have some choices: The FairScheduler, which will work to ensure resource allocations are enforced on a per-job basis. The CapacityScheduler, which will ensure resource allocations are enforced on a per-queue basis. Writing your own implementation of the abstract class org.apache.hadoop.mapred.job.TaskScheduler is an option, but usually overkill. If you're going to have several concurrent users and leverage the more interactive aspects of the Hadoop environment (e.g. Pig and Hive scripting), the FairScheduler is definitely the way to go. In particular, we can do user-specific pools so that default users get their fair share, and specific users are given the resources their workloads require. To enable fair scheduling, we're going to need to do a couple of things. First, we need to tell the JobTracker that we want to use scheduling and where we're going to be defining our allocations. We do this by adding the following to the mapred-site.xml file in HADOOP_HOME/conf: <property> <name>mapred.jobtracker.taskScheduler</name> <value>org.apache.hadoop.mapred.FairScheduler</value> </property> <property> <name>mapred.fairscheduler.allocation.file</name> <value>/path/to/allocations.xml</value> </property> <property> <name>mapred.fairscheduler.poolnameproperty</name> <value>pool.name</value> </property> <property> <name>pool.name</name> <value>${user.name}</name> </property> What we've done here is simply tell the JobTracker that we'd like to task scheduling to use the FairScheduler class rather than a single FIFO queue. Moreover, we're going to be defining our resource pools and allocations in a file called allocations.xml For reference, the allocation file is read every 15s or so, which allows for tuning allocations without having to take down the JobTracker. Our allocation file is now going to look a little like this <?xml version="1.0"?> <allocations> <pool name="dan"> <minMaps>5</minMaps> <minReduces>5</minReduces> <maxMaps>25</maxMaps> <maxReduces>25</maxReduces> <minSharePreemptionTimeout>300</minSharePreemptionTimeout> </pool> <mapreduce.job.user.name="dan"> <maxRunningJobs>6</maxRunningJobs> </user> <userMaxJobsDefault>3</userMaxJobsDefault> <fairSharePreemptionTimeout>600</fairSharePreemptionTimeout> </allocations> In this case, I've explicitly set my username to have upper and lower bounds on the maps and reduces, and allotted myself double the number of running jobs. Now, if I run hive or pig jobs from either the console or via the Hue web interface, I'll be treated "fairly" by the JobTracker. There's a lot more tweaking that can be done to the allocations file, so it's best to dig down into the description and start trying out allocations that might fit your workload.

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  • List of Commonly Used Value Types in XNA Games

    - by Michael B. McLaughlin
    Most XNA programmers are concerned about generating garbage. More specifically about allocating GC-managed memory (GC stands for “garbage collector” and is both the name of the class that provides access to the garbage collector and an acronym for the garbage collector (as a concept) itself). Two of the major target platforms for XNA (Windows Phone 7 and Xbox 360) use variants of the .NET Compact Framework. On both variants, the GC runs under various circumstances (Windows Phone 7 and Xbox 360). Of concern to XNA programmers is the fact that it runs automatically after a fixed amount of GC-managed memory has been allocated (currently 1MB on both systems). Many beginning XNA programmers are unaware of what constitutes GC-managed memory, though. So here’s a quick overview. In .NET, there are two different “types” of types: value types and reference types. Only reference types are managed by the garbage collector. Value types are not managed by the garbage collector and are instead managed in other ways that are implementation dependent. For purposes of XNA programming, the important point is that they are not managed by the GC and thus do not, by themselves, increment that internal 1 MB allocation counter. (n.b. Structs are value types. If you have a struct that has a reference type as a member, then that reference type, when instantiated, will still be allocated in the GC-managed memory and will thus count against the 1 MB allocation counter. Putting it in a struct doesn’t change the fact that it gets allocated on the GC heap, but the struct itself is created outside of the GC’s purview). Both value types and reference types use the keyword ‘new’ to allocate a new instance of them. Sometimes this keyword is hidden by a method which creates new instances for you, e.g. XmlReader.Create. But the important thing to determine is whether or not you are dealing with a value types or a reference type. If it’s a value type, you can use the ‘new’ keyword to allocate new instances of that type without incrementing the GC allocation counter (except as above where it’s a struct with a reference type in it that is allocated by the constructor, but there are no .NET Framework or XNA Framework value types that do this so it would have to be a struct you created or that was in some third-party library you were using for that to even become an issue). The following is a list of most all of value types you are likely to use in a generic XNA game: AudioCategory (used with XACT; not available on WP7) AvatarExpression (Xbox 360 only, but exposed on Windows to ease Xbox development) bool BoundingBox BoundingSphere byte char Color DateTime decimal double any enum (System.Enum itself is a class, but all enums are value types such that there are no GC allocations for enums) float GamePadButtons GamePadCapabilities GamePadDPad GamePadState GamePadThumbSticks GamePadTriggers GestureSample int IntPtr (rarely but occasionally used in XNA) KeyboardState long Matrix MouseState nullable structs (anytime you see, e.g. int? something, that ‘?’ denotes a nullable struct, also called a nullable type) Plane Point Quaternion Ray Rectangle RenderTargetBinding sbyte (though I’ve never seen it used since most people would just use a short) short TimeSpan TouchCollection TouchLocation TouchPanelCapabilities uint ulong ushort Vector2 Vector3 Vector4 VertexBufferBinding VertexElement VertexPositionColor VertexPositionColorTexture VertexPositionNormalTexture VertexPositionTexture Viewport So there you have it. That’s not quite a complete list, mind you. For example: There are various structs in the .NET framework you might make use of. I left out everything from the Microsoft.Xna.Framework.Graphics.PackedVector namespace, since everything in there ventures into the realm of advanced XNA programming anyway (n.b. every single instantiable thing in that namespace is a struct and thus a value type; there are also two interfaces but interfaces cannot be instantiated at all and thus don’t figure in to this discussion). There are so many enums you’re likely to use (PlayerIndex, SpriteSortMode, SpriteEffects, SurfaceFormat, etc.) that including them would’ve flooded the list and reduced its utility. So I went with “any enum” and trust that you can figure out what the enums are (and it’s rare to use ‘new’ with an enum anyway). That list also doesn’t include any of the pre-defined static instances of some of the classes (e.g. BlendState.AlphaBlend, BlendState.Opaque, etc.) which are already allocated such that using them doesn’t cause any new allocations and therefore doesn’t increase that 1 MB counter. That list also has a few misleading things. VertexElement, VertexPositionColor, and all the other vertex types are structs. But you’re only likely to ever use them as an array (for use with VertexBuffer or DynamicVertexBuffer), and all arrays are reference types (even arrays of value types such as VertexPositionColor[ ] or int[ ]). * So that’s it for now. The note below may be a bit confusing (it deals with how the GC works and how arrays are managed in .NET). If so, you can probably safely ignore it for now but feel free to ask any questions regardless. * Arrays of value types (where the value type doesn’t contain any reference type members) are much faster for the GC to examine than arrays of reference types, so there is a definite benefit to using arrays of value types where it makes sense. But creating arrays of value types does cause the GC’s allocation counter to increase. Indeed, allocating a large array of a value type is one of the quickest ways to increment the allocation counter since a .NET array is a sequential block of memory. An array of reference types is just a sequential block of references (typically 4 bytes each) while an array of value types is a sequential block of instances of that type. So for an array of Vector3s it would be 12 bytes each since each float is 4 bytes and there are 3 in a Vector3; for an array of VertexPositionNormalTexture structs it would typically be 32 bytes each since it has two Vector3s and a Vector2. (Note that there are a few additional bytes taken up in the creation of an array, typically 12 but sometimes 16 or possibly even more, which depend on the implementation details of the array type on the particular platform the code is running on).

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  • Real tortoises keep it slow and steady. How about the backups?

    - by Maria Zakourdaev
      … Four tortoises were playing in the backyard when they decided they needed hibiscus flower snacks. They pooled their money and sent the smallest tortoise out to fetch the snacks. Two days passed and there was no sign of the tortoise. "You know, she is taking a lot of time", said one of the tortoises. A little voice from just out side the fence said, "If you are going to talk that way about me I won't go." Is it too much to request from the quite expensive 3rd party backup tool to be a way faster than the SQL server native backup? Or at least save a respectable amount of storage by producing a really smaller backup files?  By saying “really smaller”, I mean at least getting a file in half size. After Googling the internet in an attempt to understand what other “sql people” are using for database backups, I see that most people are using one of three tools which are the main players in SQL backup area:  LiteSpeed by Quest SQL Backup by Red Gate SQL Safe by Idera The feedbacks about those tools are truly emotional and happy. However, while reading the forums and blogs I have wondered, is it possible that many are accustomed to using the above tools since SQL 2000 and 2005.  This can easily be understood due to the fact that a 300GB database backup for instance, using regular a SQL 2005 backup statement would have run for about 3 hours and have produced ~150GB file (depending on the content, of course).  Then you take a 3rd party tool which performs the same backup in 30 minutes resulting in a 30GB file leaving you speechless, you run to management persuading them to buy it due to the fact that it is definitely worth the price. In addition to the increased speed and disk space savings you would also get backup file encryption and virtual restore -  features that are still missing from the SQL server. But in case you, as well as me, don’t need these additional features and only want a tool that performs a full backup MUCH faster AND produces a far smaller backup file (like the gain you observed back in SQL 2005 days) you will be quite disappointed. SQL Server backup compression feature has totally changed the market picture. Medium size database. Take a look at the table below, check out how my SQL server 2008 R2 compares to other tools when backing up a 300GB database. It appears that when talking about the backup speed, SQL 2008 R2 compresses and performs backup in similar overall times as all three other tools. 3rd party tools maximum compression level takes twice longer. Backup file gain is not that impressive, except the highest compression levels but the price that you pay is very high cpu load and much longer time. Only SQL Safe by Idera was quite fast with it’s maximum compression level but most of the run time have used 95% cpu on the server. Note that I have used two types of destination storage, SATA 11 disks and FC 53 disks and, obviously, on faster storage have got my backup ready in half time. Looking at the above results, should we spend money, bother with another layer of complexity and software middle-man for the medium sized databases? I’m definitely not going to do so.  Very large database As a next phase of this benchmark, I have moved to a 6 terabyte database which was actually my main backup target. Note, how multiple files usage enables the SQL Server backup operation to use parallel I/O and remarkably increases it’s speed, especially when the backup device is heavily striped. SQL Server supports a maximum of 64 backup devices for a single backup operation but the most speed is gained when using one file per CPU, in the case above 8 files for a 2 Quad CPU server. The impact of additional files is minimal.  However, SQLsafe doesn’t show any speed improvement between 4 files and 8 files. Of course, with such huge databases every half percent of the compression transforms into the noticeable numbers. Saving almost 470GB of space may turn the backup tool into quite valuable purchase. Still, the backup speed and high CPU are the variables that should be taken into the consideration. As for us, the backup speed is more critical than the storage and we cannot allow a production server to sustain 95% cpu for such a long time. Bottomline, 3rd party backup tool developers, we are waiting for some breakthrough release. There are a few unanswered questions, like the restore speed comparison between different tools and the impact of multiple backup files on restore operation. Stay tuned for the next benchmarks.    Benchmark server: SQL Server 2008 R2 sp1 2 Quad CPU Database location: NetApp FC 15K Aggregate 53 discs Backup statements: No matter how good that UI is, we need to run the backup tasks from inside of SQL Server Agent to make sure they are covered by our monitoring systems. I have used extended stored procedures (command line execution also is an option, I haven’t noticed any impact on the backup performance). SQL backup LiteSpeed SQL Backup SQL safe backup database <DBNAME> to disk= '\\<networkpath>\par1.bak' , disk= '\\<networkpath>\par2.bak', disk= '\\<networkpath>\par3.bak' with format, compression EXECUTE master.dbo.xp_backup_database @database = N'<DBName>', @backupname= N'<DBName> full backup', @desc = N'Test', @compressionlevel=8, @filename= N'\\<networkpath>\par1.bak', @filename= N'\\<networkpath>\par2.bak', @filename= N'\\<networkpath>\par3.bak', @init = 1 EXECUTE master.dbo.sqlbackup '-SQL "BACKUP DATABASE <DBNAME> TO DISK= ''\\<networkpath>\par1.sqb'', DISK= ''\\<networkpath>\par2.sqb'', DISK= ''\\<networkpath>\par3.sqb'' WITH DISKRETRYINTERVAL = 30, DISKRETRYCOUNT = 10, COMPRESSION = 4, INIT"' EXECUTE master.dbo.xp_ss_backup @database = 'UCMSDB', @filename = '\\<networkpath>\par1.bak', @backuptype = 'Full', @compressionlevel = 4, @backupfile = '\\<networkpath>\par2.bak', @backupfile = '\\<networkpath>\par3.bak' If you still insist on using 3rd party tools for the backups in your production environment with maximum compression level, you will definitely need to consider limiting cpu usage which will increase the backup operation time even more: RedGate : use THREADPRIORITY option ( values 0 – 6 ) LiteSpeed : use  @throttle ( percentage, like 70%) SQL safe :  the only thing I have found was @Threads option.   Yours, Maria

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  • SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Signal Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Signal Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Signal Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the Signalwait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the Signal wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the Signal wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Single Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Single Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Single Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Single Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the single wait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the single wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the single wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Diagnose PC Hardware Problems with an Ubuntu Live CD

    - by Trevor Bekolay
    So your PC randomly shuts down or gives you the blue screen of death, but you can’t figure out what’s wrong. The problem could be bad memory or hardware related, and thankfully the Ubuntu Live CD has some tools to help you figure it out. Test your RAM with memtest86+ RAM problems are difficult to diagnose—they can range from annoying program crashes, or crippling reboot loops. Even if you’re not having problems, when you install new RAM it’s a good idea to thoroughly test it. The Ubuntu Live CD includes a tool called Memtest86+ that will do just that—test your computer’s RAM! Unlike many of the Live CD tools that we’ve looked at so far, Memtest86+ has to be run outside of a graphical Ubuntu session. Fortunately, it only takes a few keystrokes. Note: If you used UNetbootin to create an Ubuntu flash drive, then memtest86+ will not be available. We recommend using the Universal USB Installer from Pendrivelinux instead (persistence is possible with Universal USB Installer, but not mandatory). Boot up your computer with a Ubuntu Live CD or USB drive. You will be greeted with this screen: Use the down arrow key to select the Test memory option and hit Enter. Memtest86+ will immediately start testing your RAM. If you suspect that a certain part of memory is the problem, you can select certain portions of memory by pressing “c” and changing that option. You can also select specific tests to run. However, the default settings of Memtest86+ will exhaustively test your memory, so we recommend leaving the settings alone. Memtest86+ will run a variety of tests that can take some time to complete, so start it running before you go to bed to give it adequate time. Test your CPU with cpuburn Random shutdowns – especially when doing computationally intensive tasks – can be a sign of a faulty CPU, power supply, or cooling system. A utility called cpuburn can help you determine if one of these pieces of hardware is the problem. Note: cpuburn is designed to stress test your computer – it will run it fast and cause the CPU to heat up, which may exacerbate small problems that otherwise would be minor. It is a powerful diagnostic tool, but should be used with caution. Boot up your computer with a Ubuntu Live CD or USB drive, and choose to run Ubuntu from the CD or USB drive. When the desktop environment loads up, open the Synaptic Package Manager by clicking on the System menu in the top-left of the screen, then selecting Administration, and then Synaptic Package Manager. Cpuburn is in the universe repository. To enable the universe repository, click on Settings in the menu at the top, and then Repositories. Add a checkmark in the box labeled “Community-maintained Open Source software (universe)”. Click close. In the main Synaptic window, click the Reload button. After the package list has reloaded and the search index has been rebuilt, enter “cpuburn” in the Quick search text box. Click the checkbox in the left column, and select Mark for Installation. Click the Apply button near the top of the window. As cpuburn installs, it will caution you about the possible dangers of its use. Assuming you wish to take the risk (and if your computer is randomly restarting constantly, it’s probably worth it), open a terminal window by clicking on the Applications menu in the top-left of the screen and then selection Applications > Terminal. Cpuburn includes a number of tools to test different types of CPUs. If your CPU is more than six years old, see the full list; for modern AMD CPUs, use the terminal command burnK7 and for modern Intel processors, use the terminal command burnP6 Our processor is an Intel, so we ran burnP6. Once it started up, it immediately pushed the CPU up to 99.7% total usage, according to the Linux utility “top”. If your computer is having a CPU, power supply, or cooling problem, then your computer is likely to shutdown within ten or fifteen minutes. Because of the strain this program puts on your computer, we don’t recommend leaving it running overnight – if there’s a problem, it should crop up relatively quickly. Cpuburn’s tools, including burnP6, have no interface; once they start running, they will start driving your CPU until you stop them. To stop a program like burnP6, press Ctrl+C in the terminal window that is running the program. Conclusion The Ubuntu Live CD provides two great testing tools to diagnose a tricky computer problem, or to stress test a new computer. While they are advanced tools that should be used with caution, they’re extremely useful and easy enough that anyone can use them. Similar Articles Productive Geek Tips Reset Your Ubuntu Password Easily from the Live CDCreate a Persistent Bootable Ubuntu USB Flash DriveAdding extra Repositories on UbuntuHow to Share folders with your Ubuntu Virtual Machine (guest)Building a New Computer – Part 3: Setting it Up TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Have Fun Editing Photo Editing with Citrify Outlook Connector Upgrade Error Gadfly is a cool Twitter/Silverlight app Enable DreamScene in Windows 7 Microsoft’s “How Do I ?” Videos Home Networks – How do they look like & the problems they cause

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  • SQL SERVER – SSMS: Top Object and Batch Execution Statistics Reports

    - by Pinal Dave
    The month of June till mid of July has been the fever of sports. First, it was Wimbledon Tennis and then the Soccer fever was all over. There is a huge number of fan followers and it is great to see the level at which people sometimes worship these sports. Being an Indian, I cannot forget to mention the India tour of England later part of July. Following these sports and as the events unfold to the finals, there are a number of ways the statisticians can slice and dice the numbers. Cue from soccer I can surely say there is a team performance against another team and then there is individual member fairs against a particular opponent. Such statistics give us a fair idea to how a team in the past or in the recent past has fared against each other, head-to-head stats during World cup and during other neutral venue games. All these statistics are just pointers. In reality, they don’t reflect the calibre of the current team because the individuals who performed in each of these games are totally different (Typical example being the Brazil Vs Germany semi-final match in FIFA 2014). So at times these numbers are misleading. It is worth investigating and get the next level information. Similar to these statistics, SQL Server Management studio is also equipped with a number of reports like a) Object Execution Statistics report and b) Batch Execution Statistics reports. As discussed in the example, the team scorecard is like the Batch Execution statistics and individual stats is like Object Level statistics. The analogy can be taken only this far, trust me there is no correlation between SQL Server functioning and playing sports – It is like I think about diet all the time except while I am eating. Performance – Batch Execution Statistics Let us view the first report which can be invoked from Server Node -> Reports -> Standard Reports -> Performance – Batch Execution Statistics. Most of the values that are displayed in this report come from the DMVs sys.dm_exec_query_stats and sys.dm_exec_sql_text(sql_handle). This report contains 3 distinctive sections as outline below.   Section 1: This is a graphical bar graph representation of Average CPU Time, Average Logical reads and Average Logical Writes for individual batches. The Batch numbers are indicative and the details of individual batch is available in section 3 (detailed below). Section 2: This represents a Pie chart of all the batches by Total CPU Time (%) and Total Logical IO (%) by batches. This graphical representation tells us which batch consumed the highest CPU and IO since the server started, provided plan is available in the cache. Section 3: This is the section where we can find the SQL statements associated with each of the batch Numbers. This also gives us the details of Average CPU / Average Logical Reads and Average Logical Writes in the system for the given batch with object details. Expanding the rows, I will also get the # Executions and # Plans Generated for each of the queries. Performance – Object Execution Statistics The second report worth a look is Object Execution statistics. This is a similar report as the previous but turned on its head by SQL Server Objects. The report has 3 areas to look as above. Section 1 gives the Average CPU, Average IO bar charts for specific objects. The section 2 is a graphical representation of Total CPU by objects and Total Logical IO by objects. The final section details the various objects in detail with the Avg. CPU, IO and other details which are self-explanatory. At a high-level both the reports are based on queries on two DMVs (sys.dm_exec_query_stats and sys.dm_exec_sql_text) and it builds values based on calculations using columns in them: SELECT * FROM    sys.dm_exec_query_stats s1 CROSS APPLY sys.dm_exec_sql_text(sql_handle) AS s2 WHERE   s2.objectid IS NOT NULL AND DB_NAME(s2.dbid) IS NOT NULL ORDER BY  s1.sql_handle; This is one of the simplest form of reports and in future blogs we will look at more complex reports. I truly hope that these reports can give DBAs and developers a hint about what is the possible performance tuning area. As a closing point I must emphasize that all above reports pick up data from the plan cache. If a particular query has consumed a lot of resources earlier, but plan is not available in the cache, none of the above reports would show that bad query. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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