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• Poor performance after reinstalling to a USB drive

  - by anonymous

  I am currently running Ubuntu 11.10 off of a SanDisk 16GB USB. I installed it using a Live USB with the following partition configuration: 6GB Primary /dos FAT32 5GB Logical / ext4 5GB Logical /home ext4 I don't have a hard disk, and don't see myself getting one anytime soon. I rely solely on this 16GB, and two other 4GB USBs, one of which I used as the LiveUSB. I bring the USBs around, and even use the install at work. I previously used an install that used a swap file. It functioned fine for the most part, save for a few slow moments, but I came across this post, and it got me thinking about my USB's life, so I reinstalled with the current config. My problem now is that it is slower. Applications like Firefox would hang more often. In my previous setup (the automatically partitioned setup), Firefox would start hanging if I was running an unzip or install task on the same partition as /. Now however, it would hang if I had another window open i.e. the system settings window. My guess is that it may have something to do with the swap file or the install being on a Logical partition rather than a Primary partition, but I don't know. Any insight as to why it has slowed down?

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• SQL Server Prefetch and Query Performance

  Prefetching can make a surprising difference to SQL Server query execution times where there is a high incidence of waiting for disk i/o operations, but the benefits come at a cost. Mostly, the Query Optimizer gets it right, but occasionally there are queries that would benefit from tuning. Get smart with SQL Backup ProGet faster, smaller backups with integrated verification.Quickly and easily DBCC CHECKDB your backups. Learn more.

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• Better performance in App Engine with new Lisp language Clojure

  This post is part of the Who's @ Google I/O , a series of blog posts that give a closer look at developers who'll be speaking or demoing...

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• Redefining Search Engine Optimization - Prefer Pay For Performance SEO Over SEO Packages

  There are a lot of business owners who opt for search engine optimization in hope to benefit through this online marketing channel. Most of them sign up with companies offering them fixed SEO packages which is great however it is probably the biggest mistake they are making. Research has shown that in most SEO campaigns you are overpaying because at least for the first few months there is hardly any traffic.

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• Startup Improves SSD Cloud Performance

  Panzura's Application Cloud Controller will eliminate latency for SSD drives used in a cloud storage environment.

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• Performance compare of using List opposing to Array

  Benchmark both List and string[]

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• Pay For Performance of Your SEO Experts

  Search Engine Optimization, or SEO as it is popularly known the world over, is now amply discussed topic. What is SEO, is it useful, how is it useful, what are the advantages of SEO, how SEO is done, who does the SEO, what sources are required for SEO, what not to do in SEO - all these questions about SEO have been discussed in detail and supposedly detailed answers have been obtained about each of them.

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• Getting friendly with jQuery (added performance tips)

  Learning jQuery the fun and easy way (hopefully).

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• Java vs. C++: The Performance Showdown

  It's time to settle this once and for all: For memory allocation, looping, and floating-point operation, does Java or C++ perform better?

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• Java vs. C++: The Performance Showdown

  It's time to settle this once and for all: For memory allocation, looping, and floating-point operation, does Java or C++ perform better?

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• SQL SERVER – Update Statistics are Sampled By Default

  - by pinaldave

  After reading my earlier post SQL SERVER – Create Primary Key with Specific Name when Creating Table on Statistics, I have received another question by a blog reader. The question is as follows: Question: Are the statistics sampled by default? Answer: Yes. The sampling rate can be specified by the user and it can be anywhere between a very low value to 100%. Let us do a small experiment to verify if the auto update on statistics is left on. Also, let’s examine a very large table that is created and statistics by default- whether the statistics are sampled or not. USE [AdventureWorks] GO -- Create Table CREATE TABLE [dbo].[StatsTest]( [ID] [int] IDENTITY(1,1) NOT NULL, [FirstName] [varchar](100) NULL, [LastName] [varchar](100) NULL, [City] [varchar](100) NULL, CONSTRAINT [PK_StatsTest] PRIMARY KEY CLUSTERED ([ID] ASC) ) ON [PRIMARY] GO -- Insert 1 Million Rows INSERT INTO [dbo].[StatsTest] (FirstName,LastName,City) SELECT TOP 1000000 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Update the statistics UPDATE STATISTICS [dbo].[StatsTest] GO -- Shows the statistics DBCC SHOW_STATISTICS ("StatsTest"PK_StatsTest) GO -- Clean up DROP TABLE [dbo].[StatsTest] GO Now let us observe the result of the DBCC SHOW_STATISTICS. The result shows that Resultset is for sure sampling for a large dataset. The percentage of sampling is based on data distribution as well as the kind of data in the table. Before dropping the table, let us check first the size of the table. The size of the table is 35 MB. Now, let us run the above code with lesser number of the rows. USE [AdventureWorks] GO -- Create Table CREATE TABLE [dbo].[StatsTest]( [ID] [int] IDENTITY(1,1) NOT NULL, [FirstName] [varchar](100) NULL, [LastName] [varchar](100) NULL, [City] [varchar](100) NULL, CONSTRAINT [PK_StatsTest] PRIMARY KEY CLUSTERED ([ID] ASC) ) ON [PRIMARY] GO -- Insert 1 Hundred Thousand Rows INSERT INTO [dbo].[StatsTest] (FirstName,LastName,City) SELECT TOP 100000 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Update the statistics UPDATE STATISTICS [dbo].[StatsTest] GO -- Shows the statistics DBCC SHOW_STATISTICS ("StatsTest"PK_StatsTest) GO -- Clean up DROP TABLE [dbo].[StatsTest] GO You can see that Rows Sampled is just the same as Rows of the table. In this case, the sample rate is 100%. Before dropping the table, let us also check the size of the table. The size of the table is less than 4 MB. Let us compare the Result set just for a valid reference. Test 1: Total Rows: 1000000, Rows Sampled: 255420, Size of the Table: 35.516 MB Test 2: Total Rows: 100000, Rows Sampled: 100000, Size of the Table: 3.555 MB The reason behind the sample in the Test1 is that the data space is larger than 8 MB, and therefore it uses more than 1024 data pages. If the data space is smaller than 8 MB and uses less than 1024 data pages, then the sampling does not happen. Sampling aids in reducing excessive data scan; however, sometimes it reduces the accuracy of the data as well. Please note that this is just a sample test and there is no way it can be claimed as a benchmark test. The result can be dissimilar on different machines. There are lots of other information can be included when talking about this subject. I will write detail post covering all the subject very soon. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics

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• Time to stop using &ldquo;Execute Package Task&rdquo;&ndash; a way to execute package in SSIS catalog taking advantage of the new project deployment model ,and the logging and reporting feature

  - by Kevin Shyr

  I set out to find a way to dynamically call package in SSIS 2012.  The following are 2 excellent blogs I found; I used them heavily.  The code below has some addition to parameter types and message types, but was made essentially derived entirely from the blogs. http://sqlblog.com/blogs/jamie_thomson/archive/2011/07/16/ssis-logging-in-denali.aspx http://www.ssistalk.com/2012/07/24/quick-tip-run-ssis-2012-packages-synchronously-and-other-execution-options/   The code: Every package will be called by a PackageController package.  The packageController is initialized with some information on which package to run and what information to pass in.   The following is the stored procedure called from the “Execute SQL Task”.  Here is the highlight of the stored procedure It takes in packageName, project name, and folder name (folder in SSIS project deployment to SSIS catalog) The stored procedure sets the package variables of the upcoming package execution Execute package in SSIS Catalog Get the status of the execution.  Also, if exists, get the error message’s message_id and store them in the management database. Return value to “Execute SQL Task” to manage failure properly CREATE PROCEDURE [AUDIT].[LaunchPackageExecutionInSSISCatalog]        @PackageName NVARCHAR(255)        , @ProjectFolder NVARCHAR(255)        , @ProjectName NVARCHAR(255)        , @AuditKey INT        , @DisableNotification BIT        , @PackageExecutionLogID INT AS BEGIN TRY        DECLARE @execution_id BIGINT = 0;        -- Create a package execution        EXEC [SSISDB].[catalog].[create_execution]                     @package_name=@PackageName,                     @execution_id=@execution_id OUTPUT,                     @folder_name=@ProjectFolder,                     @project_name=@ProjectName,                     @use32bitruntime=False;          UPDATE [AUDIT].[PackageInstanceExecutionLog] WITH(ROWLOCK)        SET [SSISCatalogExecutionID] = @execution_id        WHERE [PackageInstanceExecutionLogID] = @PackageExecutionLogID          -- this is to set the execution synchronized so that I can check the result in the end        EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=50,                     @parameter_name=N'SYNCHRONIZED',                     @parameter_value=1; -- true          /********************************************************         ********************************************************              Section: setting parameters                     Source table:  SSISDB.internal.object_parameters              object_type list:                     20: project level variables                     30: package level variables                     50: execution parameter         ********************************************************         ********************************************************/        EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=30,                     @parameter_name=N'FromParent_AuditKey',                     @parameter_value=@AuditKey; -- true          EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=30,                     @parameter_name=N'FromParent_DisableNotification',                     @parameter_value=@DisableNotification; -- true          EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=30,                     @parameter_name=N'FromParent_PackageInstanceExecutionID',                     @parameter_value=@PackageExecutionLogID; -- true        /********************************************************         ********************************************************              Section: setting variables END         ********************************************************         ********************************************************/            /* This section is carried over from example code           I don't see a reason to change them yet        */        -- Set our package parameters        EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=50,                     @parameter_name=N'DUMP_ON_EVENT',                     @parameter_value=1; -- true          EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=50,                     @parameter_name=N'DUMP_EVENT_CODE',                     @parameter_value=N'0x80040E4D;0x80004005';          EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=50,                     @parameter_name=N'LOGGING_LEVEL',                     @parameter_value= 1; -- Basic          EXEC [SSISDB].[catalog].[set_execution_parameter_value]                     @execution_id,                      @object_type=50,                     @parameter_name=N'DUMP_ON_ERROR',                     @parameter_value=1; -- true                              /********************************************************         ********************************************************              Section: EXECUTING         ********************************************************         ********************************************************/        EXEC [SSISDB].[catalog].[start_execution]                     @execution_id;        /********************************************************         ********************************************************              Section: EXECUTING END         ********************************************************         ********************************************************/            /********************************************************         ********************************************************              Section: checking execution result                     Source table:  [SSISDB].[catalog].[executions]              status:                     1: created                     2: running                     3: cancelled                     4: failed                     5: pending                     6: ended unexpectedly                     7: succeeded                     8: stopping                     9: completed         ********************************************************         ********************************************************/        if EXISTS(SELECT TOP 1 1                            FROM [SSISDB].[catalog].[executions] WITH(NOLOCK)                            WHERE [execution_id] = @execution_id                                  AND [status] NOT IN (2, 7, 9)) BEGIN                /********************************************************               ********************************************************                     Section: logging error messages                            Source table:  [SSISDB].[internal].[operation_messages]                     message type:                            10:  OnPreValidate                             20:  OnPostValidate                             30:  OnPreExecute                             40:  OnPostExecute                             60:  OnProgress                             70:  OnInformation                             90:  Diagnostic                             110:  OnWarning                            120:  OnError                            130:  Failure                            140:  DiagnosticEx                             200:  Custom events                             400:  OnPipeline                     message source type:                            10:  Messages logged by the entry APIs (e.g. T-SQL, CLR Stored procedures)                             20:  Messages logged by the external process used to run package (ISServerExec)                             30:  Messages logged by the package-level objects                             40:  Messages logged by tasks in the control flow                             50:  Messages logged by containers (For, ForEach, Sequence) in the control flow                             60:  Messages logged by the Data Flow Task                                    ********************************************************               ********************************************************/                INSERT INTO AUDIT.PackageInstanceExecutionOperationErrorLink                     SELECT @PackageExecutionLogID                                  ,[operation_message_id]                            FROM [SSISDB].[internal].[operation_messages] WITH(NOLOCK)                            WHERE operation_id = @execution_id                                  AND message_type IN (120, 130)                           EXEC [AUDIT].[FailPackageInstanceExecution] @PackageExecutionLogID, 'SSISDB Internal operation_messages found'                GOTO ReturnTrueAsErrorFlag                /********************************************************               ********************************************************                     Section: checking messages END               ********************************************************               ********************************************************/                /* This part is not really working, so now using rowcount to pass status              --DECLARE @PackageErrorMessage NVARCHAR(4000)              --SET @PackageErrorMessage = @PackageName + 'failed with executionID: ' + CONVERT(VARCHAR(20), @execution_id)                --RAISERROR (@PackageErrorMessage -- Message text.              --     , 18 -- Severity,              --     , 1 -- State,              --     , N'check table AUDIT.PackageInstanceExecutionErrorMessages' -- First argument.              --     );              */        END        ELSE BEGIN              GOTO ReturnFalseAsErrorFlagToSignalSuccess        END        /********************************************************         ********************************************************              Section: checking execution result END         ********************************************************         ********************************************************/ END TRY BEGIN CATCH        DECLARE @SSISCatalogCallError NVARCHAR(MAX)        SELECT @SSISCatalogCallError = ERROR_MESSAGE()          EXEC [AUDIT].[FailPackageInstanceExecution] @PackageExecutionLogID, @SSISCatalogCallError          GOTO ReturnTrueAsErrorFlag END CATCH;     /********************************************************  ********************************************************    Section: end result  ********************************************************  ********************************************************/ ReturnTrueAsErrorFlag:        SELECT CONVERT(BIT, 1) AS PackageExecutionErrorExists ReturnFalseAsErrorFlagToSignalSuccess:        SELECT CONVERT(BIT, 0) AS PackageExecutionErrorExists   GO

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• SQL SERVER – Puzzle – Statistics are not Updated but are Created Once

  - by pinaldave

  After having excellent response to my quiz – Why SELECT * throws an error but SELECT COUNT(*) does not?I have decided to ask another puzzling question to all of you. I am running this test on SQL Server 2008 R2. Here is the quick scenario about my setup. Create Table Insert 1000 Records Check the Statistics Now insert 10 times more 10,000 indexes Check the Statistics – it will be NOT updated Note: Auto Update Statistics and Auto Create Statistics for database is TRUE Expected Result – Statistics should be updated – SQL SERVER – When are Statistics Updated – What triggers Statistics to Update Now the question is why the statistics are not updated? The common answer is – we can update the statistics ourselves using UPDATE STATISTICS TableName WITH FULLSCAN, ALL However, the solution I am looking is where statistics should be updated automatically based on algorithm mentioned here. Now the solution is to ____________________. Vinod Kumar is not allowed to take participate over here as he is the one who has helped me to build this puzzle. I will publish the solution on next week. Please leave a comment and if your comment consist valid answer, I will publish with due credit. Here is the script to reproduce the scenario which I mentioned. -- Execution Plans Difference -- Create Sample Database CREATE DATABASE SampleDB GO USE SampleDB GO -- Create Table CREATE TABLE ExecTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Insert One Thousand Records -- INSERT 1 INSERT INTO ExecTable (ID,FirstName,LastName,City) SELECT TOP 1000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%20 = 1 THEN 'New York' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 5 THEN 'San Marino' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 3 THEN 'Los Angeles' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 7 THEN 'La Cinega' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 13 THEN 'San Diego' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 17 THEN 'Las Vegas' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Display statistics of the table - none listed sp_helpstats N'ExecTable', 'ALL' GO -- Select Statement SELECT FirstName, LastName, City FROM ExecTable WHERE City  = 'New York' GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Replace your Statistics over here -- NOTE: Replace your _WA_Sys with stats from above query DBCC SHOW_STATISTICS('ExecTable', _WA_Sys_00000004_7D78A4E7); GO -------------------------------------------------------------- -- Round 2 -- Insert Ten Thousand Records -- INSERT 2 INSERT INTO ExecTable (ID,FirstName,LastName,City) SELECT TOP 10000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%20 = 1 THEN 'New York' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 5 THEN 'San Marino' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 3 THEN 'Los Angeles' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 7 THEN 'La Cinega' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 13 THEN 'San Diego' WHEN  ROW_NUMBER() OVER (ORDER BY a.name)%20 = 17 THEN 'Las Vegas' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Select Statement SELECT FirstName, LastName, City FROM ExecTable WHERE City  = 'New York' GO -- Display statistics of the table sp_helpstats N'ExecTable', 'ALL' GO -- Replace your Statistics over here -- NOTE: Replace your _WA_Sys with stats from above query DBCC SHOW_STATISTICS('ExecTable', _WA_Sys_00000004_7D78A4E7); GO -- You will notice that Statistics are still updated with 1000 rows -- Clean up Database DROP TABLE ExecTable GO USE MASTER GO ALTER DATABASE SampleDB SET SINGLE_USER WITH ROLLBACK IMMEDIATE; GO DROP DATABASE SampleDB GO Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics, Statistics

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• SQL SERVER – How to Ignore Columnstore Index Usage in Query

  - by pinaldave

  Earlier I wrote about SQL SERVER – Fundamentals of Columnstore Index and very first question I received in email was as following. “We are using SQL Server 2012 CTP3 and so far so good. In our data warehouse solution we have created 1 non-clustered columnstore index on our large fact table. We have very unique situation but your article did not cover it. We are running few queries on our fact table which is working very efficiently but there is one query which earlier was running very fine but after creating this non-clustered columnstore index this query is running very slow. We dropped the columnstore index and suddenly this one query is running fast but other queries which were benefited by this columnstore index it is running slow. Any workaround in this situation?” In summary the question in simple words “How can we ignore using columnstore index in selective queries?” Very interesting question – you can use I can understand there may be the cases when columnstore index is not ideal and needs to be ignored the same. You can use the query hint IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX to ignore the columnstore index. SQL Server Engine will use any other index which is best after ignoring the columnstore index. Here is the quick script to prove the same. We will first create sample database and then create columnstore index on the same. Once columnstore index is created we will write simple query. This query will use columnstore index. We will then show the usage of the query hint. USE AdventureWorks GO -- Create New Table CREATE TABLE [dbo].[MySalesOrderDetail]( [SalesOrderID] [int] NOT NULL, [SalesOrderDetailID] [int] NOT NULL, [CarrierTrackingNumber] [nvarchar](25) NULL, [OrderQty] [smallint] NOT NULL, [ProductID] [int] NOT NULL, [SpecialOfferID] [int] NOT NULL, [UnitPrice] [money] NOT NULL, [UnitPriceDiscount] [money] NOT NULL, [LineTotal] [numeric](38, 6) NOT NULL, [rowguid] [uniqueidentifier] NOT NULL, [ModifiedDate] [datetime] NOT NULL ) ON [PRIMARY] GO -- Create clustered index CREATE CLUSTERED INDEX [CL_MySalesOrderDetail] ON [dbo].[MySalesOrderDetail] ( [SalesOrderDetailID]) GO -- Create Sample Data Table -- WARNING: This Query may run upto 2-10 minutes based on your systems resources INSERT INTO [dbo].[MySalesOrderDetail] SELECT S1.* FROM Sales.SalesOrderDetail S1 GO 100 -- Create ColumnStore Index CREATE NONCLUSTERED COLUMNSTORE INDEX [IX_MySalesOrderDetail_ColumnStore] ON [MySalesOrderDetail] (UnitPrice, OrderQty, ProductID) GO Now we have created columnstore index so if we run following query it will use for sure the same index. -- Select Table with regular Index SELECT ProductID, SUM(UnitPrice) SumUnitPrice, AVG(UnitPrice) AvgUnitPrice, SUM(OrderQty) SumOrderQty, AVG(OrderQty) AvgOrderQty FROM [dbo].[MySalesOrderDetail] GROUP BY ProductID ORDER BY ProductID GO We can specify Query Hint IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX as described in following query and it will not use columnstore index. -- Select Table with regular Index SELECT ProductID, SUM(UnitPrice) SumUnitPrice, AVG(UnitPrice) AvgUnitPrice, SUM(OrderQty) SumOrderQty, AVG(OrderQty) AvgOrderQty FROM [dbo].[MySalesOrderDetail] GROUP BY ProductID ORDER BY ProductID OPTION (IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX) GO Let us clean up the database. -- Cleanup DROP INDEX [IX_MySalesOrderDetail_ColumnStore] ON [dbo].[MySalesOrderDetail] GO TRUNCATE TABLE dbo.MySalesOrderDetail GO DROP TABLE dbo.MySalesOrderDetail GO Again, make sure that you use hint sparingly and understanding the proper implication of the same. Make sure that you test it with and without hint and select the best option after review of your administrator. Here is the question for you – have you started to use SQL Server 2012 for your validation and development (not on production)? It will be interesting to know the answer. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• What’s the Difference Between Succession Management and Talent Reviews?

  - by HCM-Oracle

  By Marcie Van Houten Is there a difference or are they pieces of one holistic strategic talent process? And can you have one without the other?  First, let me give a quick definition of each.  Succession planning (or management) is about creating succession slates or talent pools in support of a critical job or position or sets thereof. And then using those plans to help mitigate risk and plan talent needs for the organization.  Talent reviews (known by other names often) are sets of meetings where managers and executives come together to review, discuss and often heatedly debate the merits and potential of their employees, and then place and sometimes calibrate that talent on a performance to potential matrix.  These are some of the most strategic conversations happening in conference rooms across the globe. I speak with a lot of organizations about their practices in this area and the answers to these questions are as varied and nuanced as there are organizations thinking about them.  Some are passionate about their talent review processes and have a very evolved and thoughtful approach.  They really know their people, where their talent is, and the opportunities they plan to offer them.  And to them that is their succession process.  They may never create a slate of named candidates for a job or assign employees to formal talent pools.   On the flip side there are other organizations that create slates and slates and often multiple talent pools to support their strategic positions.  Through these, they are able to mitigate the risk associated with having a key player leave their organization.  And for them, that is their succession process.  Some will start from the lower levels of their organization and roll up their succession plans, while other organizations only cover their top 200 executives and key positions with plans.  And then there are organizations that leverage some of all of these.  Ultimately, the goals are to increase employee engagement, reduce talent-related risk, ensure the right talent is aligned to the strategic initiatives and to drive business value.  The approaches are as unique as the organizations they represent and the business opportunities they are looking to seize upon.   And that's ok.  It's great in fact. Because one thing that is common is the recognition that the need to know your people and align your top talent to the future needs of the organization is mission critical. Sure, there are a set of commonly recognized best practices and guiding principles for all of this.  There is no one right or perfect answer.  And that is what makes this all so much darn fun.  With Talent Review and Succession Management from Oracle HCM Cloud, we’ve blended the ability to support your strategic talent review conversations with both succession plans and talent pools allowing for one very seamless and interactive process. So whether you create a lot of succession plans, only focus on talent pools, have a robust talent review process, or all of the above, Oracle has you covered. I’m looking forward to spending time with our customers at the upcoming OHUG Global Conference 2014 happening June 9-13 in Las Vegas.  It’s an opportunity for me to talk to customers about their business and how they are doing strategic talent processes like talent reviews and succession.  I hope to see you there. Marcie Van Houten brings over 20 years of management consulting, information systems and human capital management experience to her role as director of product strategy at Oracle. Ms. Van Houten has spent the past several years at Oracle working closely with customers to help drive the direction of the company's talent and succession management applications. Additionally, she spent nine years at PeopleSoft as Director of Information Systems leading human capital management implementation projects. Marcie Van Houten lives in Walnut Creek, California, and holds a MBA from Southern Methodist University in Dallas, Texas.  You can follow her on Twitter: @MarcieVH

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• SQL Server IO handling mechanism can be severely affected by high CPU usage

  - by sqlworkshops

  Are you using SSD or SAN / NAS based storage solution and sporadically observe SQL Server experiencing high IO wait times or from time to time your DAS / HDD becomes very slow according to SQL Server statistics? Read on… I need your help to up vote my connect item – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage. Instead of taking few seconds, queries could take minutes/hours to complete when CPU is busy.In SQL Server when a query / request needs to read data that is not in data cache or when the request has to write to disk, like transaction log records, the request / task will queue up the IO operation and wait for it to complete (task in suspended state, this wait time is the resource wait time). When the IO operation is complete, the task will be queued to run on the CPU. If the CPU is busy executing other tasks, this task will wait (task in runnable state) until other tasks in the queue either complete or get suspended due to waits or exhaust their quantum of 4ms (this is the signal wait time, which along with resource wait time will increase the overall wait time). When the CPU becomes free, the task will finally be run on the CPU (task in running state).The signal wait time can be up to 4ms per runnable task, this is by design. So if a CPU has 5 runnable tasks in the queue, then this query after the resource becomes available might wait up to a maximum of 5 X 4ms = 20ms in the runnable state (normally less as other tasks might not use the full quantum).In case the CPU usage is high, let’s say many CPU intensive queries are running on the instance, there is a possibility that the IO operations that are completed at the Hardware and Operating System level are not yet processed by SQL Server, keeping the task in the resource wait state for longer than necessary. In case of an SSD, the IO operation might even complete in less than a millisecond, but it might take SQL Server 100s of milliseconds, for instance, to process the completed IO operation. For example, let’s say you have a user inserting 500 rows in individual transactions. When the transaction log is on an SSD or battery backed up controller that has write cache enabled, all of these inserts will complete in 100 to 200ms. With a CPU intensive parallel query executing across all CPU cores, the same inserts might take minutes to complete. WRITELOG wait time will be very high in this case (both under sys.dm_io_virtual_file_stats and sys.dm_os_wait_stats). In addition you will notice a large number of WAITELOG waits since log records are written by LOG WRITER and hence very high signal_wait_time_ms leading to more query delays. However, Performance Monitor Counter, PhysicalDisk, Avg. Disk sec/Write will report very low latency times.Such delayed IO handling also occurs to read operations with artificially very high PAGEIOLATCH_SH wait time (with number of PAGEIOLATCH_SH waits remaining the same). This problem will manifest more and more as customers start using SSD based storage for SQL Server, since they drive the CPU usage to the limits with faster IOs. We have a few workarounds for specific scenarios, but we think Microsoft should resolve this issue at the product level. We have a connect item open – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage - (with example scripts) to reproduce this behavior, please up vote the item so the issue will be addressed by the SQL Server product team soon.Thanks for your help and best regards,Ramesh MeyyappanHome: www.sqlworkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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• Simple OpenGL program major slow down at high resolution

  - by Grieverheart

  I have created a small OpenGL 3.3 (Core) program using freeglut. The whole geometry is two boxes and one plane with some textures. I can move around like in an FPS and that's it. The problem is I face a big slow down of fps when I make my window large (i.e. above 1920x1080). I have monitors GPU usage when in full-screen and it shows GPU load of nearly 100% and Memory Controller load of ~85%. When at 600x600, these numbers are at about 45%, my CPU is also at full load. I use deferred rendering at the moment but even when forward rendering, the slow down was nearly as severe. I can't imagine my GPU is not powerful enough for something this simple when I play many games at 1080p (I have a GeForce GT 120M btw). Below are my shaders, First Pass #VS #version 330 core uniform mat4 ModelViewMatrix; uniform mat3 NormalMatrix; uniform mat4 MVPMatrix; uniform float scale; layout(location = 0) in vec3 in_Position; layout(location = 1) in vec3 in_Normal; layout(location = 2) in vec2 in_TexCoord; smooth out vec3 pass_Normal; smooth out vec3 pass_Position; smooth out vec2 TexCoord; void main(void){ pass_Position = (ModelViewMatrix * vec4(scale * in_Position, 1.0)).xyz; pass_Normal = NormalMatrix * in_Normal; TexCoord = in_TexCoord; gl_Position = MVPMatrix * vec4(scale * in_Position, 1.0); } #FS #version 330 core uniform sampler2D inSampler; smooth in vec3 pass_Normal; smooth in vec3 pass_Position; smooth in vec2 TexCoord; layout(location = 0) out vec3 outPosition; layout(location = 1) out vec3 outDiffuse; layout(location = 2) out vec3 outNormal; void main(void){ outPosition = pass_Position; outDiffuse = texture(inSampler, TexCoord).xyz; outNormal = pass_Normal; } Second Pass #VS #version 330 core uniform float scale; layout(location = 0) in vec3 in_Position; void main(void){ gl_Position = mat4(1.0) * vec4(scale * in_Position, 1.0); } #FS #version 330 core struct Light{ vec3 direction; }; uniform ivec2 ScreenSize; uniform Light light; uniform sampler2D PositionMap; uniform sampler2D ColorMap; uniform sampler2D NormalMap; out vec4 out_Color; vec2 CalcTexCoord(void){ return gl_FragCoord.xy / ScreenSize; } vec4 CalcLight(vec3 position, vec3 normal){ vec4 DiffuseColor = vec4(0.0); vec4 SpecularColor = vec4(0.0); vec3 light_Direction = -normalize(light.direction); float diffuse = max(0.0, dot(normal, light_Direction)); if(diffuse 0.0){ DiffuseColor = diffuse * vec4(1.0); vec3 camera_Direction = normalize(-position); vec3 half_vector = normalize(camera_Direction + light_Direction); float specular = max(0.0, dot(normal, half_vector)); float fspecular = pow(specular, 128.0); SpecularColor = fspecular * vec4(1.0); } return DiffuseColor + SpecularColor + vec4(0.1); } void main(void){ vec2 TexCoord = CalcTexCoord(); vec3 Position = texture(PositionMap, TexCoord).xyz; vec3 Color = texture(ColorMap, TexCoord).xyz; vec3 Normal = normalize(texture(NormalMap, TexCoord).xyz); out_Color = vec4(Color, 1.0) * CalcLight(Position, Normal); } Is it normal for the GPU to be used that much under the described circumstances? Is it due to poor performance of freeglut? I understand that the problem could be specific to my code, but I can't paste the whole code here, if you need more info, please tell me.

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• Reducing Deadlocks - not a DBA issue ?

  - by steveh99999

   As a DBA, I'm involved on an almost daily basis troubleshooting 'SQL Server' performance issues. Often, this troubleshooting soon veers away from a 'its a SQL Server issue' to instead become a wider application/database design/coding issue.One common perception with SQL Server is that deadlocking is an application design issue - and is fixed by recoding...  I see this reinforced by MCP-type questions/scenarios where the answer to prevent deadlocking is simply to change the order in code in which tables are accessed....Whilst this is correct, I do think this has led to a situation where many 'operational' or 'production support' DBAs, when faced with a deadlock, are happy to throw the issue over to developers without analysing the issue further....A couple of 'war stories' on deadlocks which I think are interesting :- Case One , I had an issue recently on a third-party application that I support on SQL 2008.  This particular third-party application has an unusual support agreement where the customer is allowed to change the index design on the third-party provided database.  However, we are not allowed to alter application code or modify table structure..This third-party application is also known to encounter occasional deadlocks – indeed, I have documentation from the vendor that up to 50 deadlocks per day is not unusual !So, as a DBA I have to support an application which in my opinion has too many deadlocks - but, I cannot influence the design of the tables or stored procedures for the application. This should be the classic - blame the third-party developers scenario, and hope this issue gets addressed in a future application release - ie we could wait years for this to be resolved and implemented in our production environment...But, as DBAs  can change the index layout, is there anything I could do still to reduce the deadlocks in the application ?I initially used SQL traceflag 1222 to write deadlock detection output to the SQL Errorlog – using this I was able to identify one table heavily involved in the deadlocks.When I examined the table definition, I was surprised to see it was a heap – ie no clustered index existed on the table.Using SQL profiler to see locking behaviour and plan for the query involved in the deadlock, I was able to confirm a table scan was being performed.By creating an appropriate clustered index - it was possible to produce a more efficient plan and locking behaviour.So, less locks, held for less time = less possibility of deadlocks. I'm still unhappy about the overall number of deadlocks on this system - but that's something to be discussed further with the vendor.Case Two,  a system which hadn't changed for months suddenly started seeing deadlocks on a regular basis. I love the 'nothing's changed' scenario, as it gives me the opportunity to appear wise and say 'nothings changed on this system, except the data'.. This particular deadlock occurred on a table which had been growing rapidly. By using DBCC SHOW_STATISTICS - the DBA team were able to see that the deadlocks seemed to be occurring shortly after auto-update stats had regenerated the table statistics using it's default sampling behaviour.As a quick fix, we were able to schedule a nightly UPDATE STATISTICS WITH FULLSCAN on the table involved in the deadlock - thus, greatly reducing the potential for stats to be updated via auto_update_stats, consequently reducing the potential for a bad plan to be generated based on an unrepresentative sample of the data. This reduced the possibility of a deadlock occurring.  Not a perfect solution by any means, but quick, easy to implement, and needed no application code changes. This fix gave us some 'breathing space'  to properly fix the code during the next scheduled application release.   The moral of this post - don't dismiss deadlocks as issues that can only be fixed by developers...

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• A* algorithm very slow

  - by Amaranth

  I have an programming a RTS game (I use XNA with C#). The pathfinding is working fine, except that when it has a lot of node to search in, there is a lag period of one or two seconds, it happens mainly when there is no path to the target destination, since it that situation there is more nodes to explore. I have the same problem when the path is shorter but selected more than 3 units (can't take the same path since the selected units can be in different part of the map). private List<NodeInfo> FindPath(Unit u, NodeInfo start, NodeInfo end) { Map map = GameInfo.GetInstance().GameMap; _nearestToTarget = start; start.MoveCost = 0; Vector2 endPosition = map.getTileByPos(end.X, end.Y).Position; //getTileByPos simply gets the tile in a 2D array with the X and Y indexes start.EstimatedRemainingCost = (int)(endPosition - map.getTileByPos(start.X, start.Y).Position).Length(); start.Parent = null; List<NodeInfo> openedNodes = new List<NodeInfo>(); ; List<NodeInfo> closedNodes = new List<NodeInfo>(); Point[] movements = GetMovements(u.UnitType); openedNodes.Add(start); while (!closedNodes.Contains(end) && openedNodes.Count > 0) { //Loop in nodes to find lowest cost NodeInfo currentNode = FindLowestCostOpenedNode(openedNodes); openedNodes.Remove(currentNode); closedNodes.Add(currentNode); Vector2 previousMouvement; if (currentNode.Parent == null) { previousMouvement = ConvertRotationToDirectionVector(u.Rotation); } else { previousMouvement = map.getTileByPos(currentNode.X, currentNode.Y).Position - map.getTileByPos(currentNode.Parent.X, currentNode.Parent.Y).Position; previousMouvement.Normalize(); } //For each neighbor foreach (Point movement in movements) { Point exploredGridPos = new Point(currentNode.X + movement.X, currentNode.Y + movement.Y); //Checks if valid move and checks if not if closed nodes list if (ValidNavigableNode(u.UnitType, new Point(currentNode.X, currentNode.Y), exploredGridPos) && !closedNodes.Contains(_gridMap[exploredGridPos.Y, exploredGridPos.X])) { NodeInfo exploredNode = _gridMap[exploredGridPos.Y, exploredGridPos.X]; Tile.TileType exploredTerrain = map.getTileByPos(exploredGridPos.X, exploredGridPos.Y).TerrainType; if(openedNodes.Contains(exploredNode)) { int newCost = currentNode.MoveCost + GetMoveCost(previousMouvement, movement, exploredTerrain); if (newCost < exploredNode.MoveCost) { exploredNode.Parent = currentNode; exploredNode.MoveCost = newCost; //Find nearest tile to the target (in case doesn't find path to target) //Only compares the node to the current nearest FindNearest(exploredNode); } } else { exploredNode.Parent = currentNode; exploredNode.MoveCost = currentNode.MoveCost + GetMoveCost(previousMouvement, movement, exploredTerrain); Vector2 exploredNodeWorldPos = map.getTileByPos(exploredGridPos.X, exploredGridPos.Y).Position; exploredNode.EstimatedRemainingCost = (int)(endPosition - exploredNodeWorldPos).Length(); //Find nearest tile to the target (in case doesn't find path to target) //Only compares the node to the current nearest FindNearest(exploredNode); openedNodes.Add(exploredNode); } } } } return closedNodes; } After that, I simply check if the end node is contained in the returned nodes. If so, I add the end node and each parent until I reach the start. If not, I add the nearestToTarget and each parent until I reach the start. I added a condition before calling FindPath so that only one unit can call a find path each frame (60 frame per second), but it makes no difference. I thought maybe I could solve this by allowing the find path to run in background while the game continues to run correctly, even if it takes a few frame (it is currently sequential sonce it is called in the update() of the unit if there's a target location but no path), but I don't really know how... I also though about sorting my opened nodes list by cost so I don't have to loop them, but I don't know if that would have an effect on the performance... Would there be other solutions? P.S. In the code, when I get the Move Cost, I check if the unit has to turn to perform the move, and the terrain type, nothing hard to do.

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• Very uneven CPU utilization with SQL Server 2012 on 2 processor computer with 16 cores / processor

  - by cooplarsh

  After installing SQL Server Enterprise 2012 with the Server + Cal license model, on a computer with 2 processors each with 16 cores (and no hyperthreading involved) and putting the server under extremely heavy load the 16 cores on the first processor were very underutilized, the first 4 cores on the 2nd CPU were heavily utilized, and the last 12 cores were not used at all (because of the 20 core limit for this sql server version). Total CPU utilization was displaying as around 25%. Unfortunately, the server suffered from extremely poor performance even though if the tasks were evenly distributed across the 20 cores it wouldn't have been anywhere near as bad. The Windows Server was running on a VMWare virtual image under ESX Server, but all of the CPU was allocated to the windows server. We tried changing affinity settings (e.g., allocating most cores to CPU and the others to I/O), but that didn't help solve the performance problems. Upgrading the product edition to SQL Server Enterprise Core 2012 not only allowed the SQL Server to utilize the 12 previously unused cores on the 2nd processor, but it also resulted in a much more even distribution of tasks across all of the processors. To get through the backlog of requests cpU utilization jumped to around 90%, and then came down to around 33% once it was caught up, but performance improved dramatically since we failed over to the newly updated version And the performance issues went away. I was wondering if anyone knows what might cause SQL Server to unevenly distribute the load, relying almost exclusively on the first 4 cores of the 2nd processor that had 12 cores idle, and allocate only a few tasks to each of the 16 cores on the first processor. Also, is there any way we could have more evenly distributed the load across the 20 cores that were being used without the product edition upgrade? The flip side of that question is what did the product upgrade do that caused SQL Server to start evenly distributing the load across all of the cores that it recognized? Thanks to any insight to answer these questions and/or links that might help me better understand how to make sense of what was happenings.

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• Linux - real-world hardware RAID controller tuning (scsi and cciss)

  - by ewwhite

  Most of the Linux systems I manage feature hardware RAID controllers (mostly HP Smart Array). They're all running RHEL or CentOS. I'm looking for real-world tunables to help optimize performance for setups that incorporate hardware RAID controllers with SAS disks (Smart Array, Perc, LSI, etc.) and battery-backed or flash-backed cache. Assume RAID 1+0 and multiple spindles (4+ disks). I spend a considerable amount of time tuning Linux network settings for low-latency and financial trading applications. But many of those options are well-documented (changing send/receive buffers, modifying TCP window settings, etc.). What are engineers doing on the storage side? Historically, I've made changes to the I/O scheduling elevator, recently opting for the deadline and noop schedulers to improve performance within my applications. As RHEL versions have progressed, I've also noticed that the compiled-in defaults for SCSI and CCISS block devices have changed as well. This has had an impact on the recommended storage subsystem settings over time. However, it's been awhile since I've seen any clear recommendations. And I know that the OS defaults aren't optimal. For example, it seems that the default read-ahead buffer of 128kb is extremely small for a deployment on server-class hardware. The following articles explore the performance impact of changing read-ahead cache and nr_requests values on the block queues. http://zackreed.me/articles/54-hp-smart-array-p410-controller-tuning http://www.overclock.net/t/515068/tuning-a-hp-smart-array-p400-with-linux-why-tuning-really-matters http://yoshinorimatsunobu.blogspot.com/2009/04/linux-io-scheduler-queue-size-and.html For example, these are suggested changes for an HP Smart Array RAID controller: echo "noop" > /sys/block/cciss\!c0d0/queue/scheduler blockdev --setra 65536 /dev/cciss/c0d0 echo 512 > /sys/block/cciss\!c0d0/queue/nr_requests echo 2048 > /sys/block/cciss\!c0d0/queue/read_ahead_kb What else can be reliably tuned to improve storage performance? I'm specifically looking for sysctl and sysfs options in production scenarios.

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• Why is only one Excel spreadsheet crippled, but others are fine?

  - by Dallas

  I have an inherited spreadsheet that I really don't want to rebuild at the moment. It's a simple small workbook that is small (< 200 rows that don't even reach to AA) and does nothing more than calculate some totals within the same worksheets. No macros, no external data sources, nothing beyond basic formatting of dates, numbers and strings. I see importing data from CSV/text has created many many workbook connections over time, but even if I delete them all (there were hundreds) it makes no difference in performance. Even clicking to simply change focus from cell to cell takes 10+ seconds, adorned by the spinning cursor and (Not Responding) appending to the title bar and the application locking up. The program seems to "recover" every time, but efficiency of editing this file is obviously seriously handicapped. All other files seem fine in Excel, and other programs have no apparent performance issues. I see Excel is chewing up CPU but I'm not sure how to narrow down what process or service is "clashing" with Excel. I tried the same file on other computers and performance is fine. If I turn off all start-up services and run only Excel, performance is restored... until I start using other programs and then it bogs down again. At this point, I would entertain almost any idea, theory or suggestion that helps pinpoint, solve or work around the issue.

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• disk write cache buffer and separate power supply

  - by HugoRune

  Windows has a setting to turn off the write-cache buffer (see image) Turn off Windows write-cache buffer flushing on the device To prevent data loss, do not select this check box unless the device has a separate power supply that allows the device to flush its buffer in case of power failure. Is it feasible and economical to get such a "separate power supply" for the internal sata drives of a non-server PC? Under what name is such a power supply sold? I know that there are UPS devices that can be connected to external drives,but what is required to be able to switch this setting safely on for an internal disk? The setting has different descriptions in different version of windows Windows XP: Enable write caching on the disk This setting enables write caching in Windows to improve disk performance, but a power outage or equipment failure might result in data loss or corruption. Windows Server 2003: Enable write caching on the disk Recommended only for disks with a backup power supply. This setting further improves disk performance, but it also increases the risk of data loss if the disk loses power. Windows Vista: Enable advanced performance Recommended only for disks with a backup power supply. This setting further improves disk performance, but it also increases the risk of data loss if the disk loses power. Windows 7 and 8: Turn off Windows write-cache buffer flushing on the device To prevent data loss, do not select this check box unless the device has a separate power supply that allows the device to flush its buffer in case of power failure. This article by Raymond Chen has some more detailed information about what the setting does.

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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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