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  • SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28

    - by pinaldave
    It is very easy to say that you replace your hardware as that is not up to the mark. In reality, it is very difficult to implement. It is really hard to convince an infrastructure team to change any hardware because they are not performing at their best. I had a nightmare related to this issue in a deal with an infrastructure team as I suggested that they replace their faulty hardware. This is because they were initially not accepting the fact that it is the fault of their hardware. But it is really easy to say “Trust me, I am correct”, while it is equally important that you put some logical reasoning along with this statement. PAGEIOLATCH_XX is such a kind of those wait stats that we would directly like to blame on the underlying subsystem. Of course, most of the time, it is correct – the underlying subsystem is usually the problem. From Book On-Line: PAGEIOLATCH_DT Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Destroy mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_EX Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Exclusive mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_KP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Keep mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_SH Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Shared mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_UP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Update mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_XX Explanation: Simply put, this particular wait type occurs when any of the tasks is waiting for data from the disk to move to the buffer cache. ReducingPAGEIOLATCH_XX wait: Just like any other wait type, this is again a very challenging and interesting subject to resolve. Here are a few things you can experiment on: Improve your IO subsystem speed (read the first paragraph of this article, if you have not read it, I repeat that it is easy to say a step like this than to actually implement or do it). This type of wait stats can also happen due to memory pressure or any other memory issues. Putting aside the issue of a faulty IO subsystem, this wait type warrants proper analysis of the memory counters. If due to any reasons, the memory is not optimal and unable to receive the IO data. This situation can create this kind of wait type. Proper placing of files is very important. We should check file system for the proper placement of files – LDF and MDF on separate drive, TempDB on separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. It is very possible that there are no proper indexes on the system and there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can significantly reduce lots of CPU, Memory and IO (considering cover index has much lesser columns than cluster table and all other it depends conditions). You can refer to the two articles’ links below previously written by me that talk about how to optimize indexes. Create Missing Indexes Drop Unused Indexes Updating statistics can help the Query Optimizer to render optimal plan, which can only be either directly or indirectly. I have seen that updating statistics with full scan (again, if your database is huge and you cannot do this – never mind!) can provide optimal information to SQL Server optimizer leading to efficient plan. Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, 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 – PAGELATCH_DT, PAGELATCH_EX, PAGELATCH_KP, PAGELATCH_SH, PAGELATCH_UP – Wait Type – Day 12 of 28

    - by pinaldave
    This is another common wait type. However, I still frequently see people getting confused with PAGEIOLATCH_X and PAGELATCH_X wait types. Actually, there is a big difference between the two. PAGEIOLATCH is related to IO issues, while PAGELATCH is not related to IO issues but is oftentimes linked to a buffer issue. Before we delve deeper in this interesting topic, first let us understand what Latch is. Latches are internal SQL Server locks which can be described as very lightweight and short-term synchronization objects. Latches are not primarily to protect pages being read from disk into memory. It’s a synchronization object for any in-memory access to any portion of a log or data file.[Updated based on comment of Paul Randal] The difference between locks and latches is that locks seal all the involved resources throughout the duration of the transactions (and other processes will have no access to the object), whereas latches locks the resources during the time when the data is changed. This way, a latch is able to maintain the integrity of the data between storage engine and data cache. A latch is a short-living lock that is put on resources on buffer cache and in the physical disk when data is moved in either directions. As soon as the data is moved, the latch is released. Now, let us understand the wait stat type  related to latches. From Book On-Line: PAGELATCH_DT Occurs when a task is waiting on a latch for a buffer that is not in an I/O request. The latch request is in Destroy mode. PAGELATCH_EX Occurs when a task is waiting on a latch for a buffer that is not in an I/O request. The latch request is in Exclusive mode. PAGELATCH_KP Occurs when a task is waiting on a latch for a buffer that is not in an I/O request. The latch request is in Keep mode. PAGELATCH_SH Occurs when a task is waiting on a latch for a buffer that is not in an I/O request. The latch request is in Shared mode. PAGELATCH_UP Occurs when a task is waiting on a latch for a buffer that is not in an I/O request. The latch request is in Update mode. PAGELATCH_X Explanation: When there is a contention of access of the in-memory pages, this wait type shows up. It is quite possible that some of the pages in the memory are of very high demand. For the SQL Server to access them and put a latch on the pages, it will have to wait. This wait type is usually created at the same time. Additionally, it is commonly visible when the TempDB has higher contention as well. If there are indexes that are heavily used, contention can be created as well, leading to this wait type. Reducing PAGELATCH_X wait: The following counters are useful to understand the status of the PAGELATCH: Average Latch Wait Time (ms): The wait time for latch requests that have to wait. Latch Waits/sec: This is the number of latch requests that could not be granted immediately. Total Latch Wait Time (ms): This is the total latch wait time for latch requests in the last second. If there is TempDB contention, I suggest that you read the blog post of Robert Davis right away. He has written an excellent blog post regarding how to find out TempDB contention. The same blog post explains the terms in the allocation of GAM, SGAM and PFS. If there was a TempDB contention, Paul Randal explains the optimal settings for the TempDB in his misconceptions series. Trace Flag 1118 can be useful but use it very carefully. I totally understand that this blog post is not as clear as my other blog posts. I suggest if this wait stats is on one of your higher wait type. Do leave a comment or send me an email and I will get back to you with my solution for your situation. May the looking at all other wait stats and types together become effective as this wait type can help suggest proper bottleneck in your system. Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussions of Wait Stats in this blog are generic and vary from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Pinal Dave, PostADay, SQL, SQL Authority, 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 – LOGBUFFER – Wait Type – Day 18 of 28

    - by pinaldave
    At first, I was not planning to write about this wait type. The reason was simple- I have faced this only once in my lifetime so far maybe because it is one of the top 5 wait types. I am not sure if it is a common wait type or not, but in the samples I had it really looks rare to me. From Book On-Line: LOGBUFFER Occurs when a task is waiting for space in the log buffer to store a log record. Consistently high values may indicate that the log devices cannot keep up with the amount of log being generated by the server. LOGBUFFER Explanation: The book online definition of the LOGBUFFER seems to be very accurate. On the system where I faced this wait type, the log file (LDF) was put on the local disk, and the data files (MDF, NDF) were put on SanDrives. My client then was not familiar about how the file distribution was supposed to be. Once we moved the LDF to a faster drive, this wait type disappeared. Reducing LOGBUFFER wait: There are several suggestions to reduce this wait stats: Move Transaction Log to Separate Disk from mdf and other files. (Make sure your drive where your LDF is has no IO bottleneck issues). Avoid cursor-like coding methodology and frequent commit statements. Find the most-active file based on IO stall time, as shown in the script written over here. You can also use fn_virtualfilestats to find IO-related issues using the script mentioned over here. Check the IO-related counters (PhysicalDisk:Avg.Disk Queue Length, PhysicalDisk:Disk Read Bytes/sec and PhysicalDisk :Disk Write Bytes/sec) for additional details. Read about them over here. If you have noticed, my suggestions for reducing the LOGBUFFER is very similar to WRITELOG. Although the procedures on reducing them are alike, I am not suggesting that LOGBUFFER and WRITELOG are same wait types. From the definition of the two, you will find their difference. However, they are both related to LOG and both of them can severely degrade the performance. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Pinal Dave, PostADay, SQL, SQL Authority, 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 – CXPACKET – Parallelism – Usual Solution – Wait Type – Day 6 of 28

    - by pinaldave
    CXPACKET has to be most popular one of all wait stats. I have commonly seen this wait stat as one of the top 5 wait stats in most of the systems with more than one CPU. Books On-Line: Occurs when trying to synchronize the query processor exchange iterator. You may consider lowering the degree of parallelism if contention on this wait type becomes a problem. CXPACKET Explanation: When a parallel operation is created for SQL Query, there are multiple threads for a single query. Each query deals with a different set of the data (or rows). Due to some reasons, one or more of the threads lag behind, creating the CXPACKET Wait Stat. There is an organizer/coordinator thread (thread 0), which takes waits for all the threads to complete and gathers result together to present on the client’s side. The organizer thread has to wait for the all the threads to finish before it can move ahead. The Wait by this organizer thread for slow threads to complete is called CXPACKET wait. Note that not all the CXPACKET wait types are bad. You might experience a case when it totally makes sense. There might also be cases when this is unavoidable. If you remove this particular wait type for any query, then that query may run slower because the parallel operations are disabled for the query. Reducing CXPACKET wait: We cannot discuss about reducing the CXPACKET wait without talking about the server workload type. OLTP: On Pure OLTP system, where the transactions are smaller and queries are not long but very quick usually, set the “Maximum Degree of Parallelism” to 1 (one). This way it makes sure that the query never goes for parallelism and does not incur more engine overhead. EXEC sys.sp_configure N'cost threshold for parallelism', N'1' GO RECONFIGURE WITH OVERRIDE GO Data-warehousing / Reporting server: As queries will be running for long time, it is advised to set the “Maximum Degree of Parallelism” to 0 (zero). This way most of the queries will utilize the parallel processor, and long running queries get a boost in their performance due to multiple processors. EXEC sys.sp_configure N'cost threshold for parallelism', N'0' GO RECONFIGURE WITH OVERRIDE GO Mixed System (OLTP & OLAP): Here is the challenge. The right balance has to be found. I have taken a very simple approach. I set the “Maximum Degree of Parallelism” to 2, which means the query still uses parallelism but only on 2 CPUs. However, I keep the “Cost Threshold for Parallelism” very high. This way, not all the queries will qualify for parallelism but only the query with higher cost will go for parallelism. I have found this to work best for a system that has OLTP queries and also where the reporting server is set up. Here, I am setting ‘Cost Threshold for Parallelism’ to 25 values (which is just for illustration); you can choose any value, and you can find it out by experimenting with the system only. In the following script, I am setting the ‘Max Degree of Parallelism’ to 2, which indicates that the query that will have a higher cost (here, more than 25) will qualify for parallel query to run on 2 CPUs. This implies that regardless of the number of CPUs, the query will select any two CPUs to execute itself. EXEC sys.sp_configure N'cost threshold for parallelism', N'25' GO EXEC sys.sp_configure N'max degree of parallelism', N'2' GO RECONFIGURE WITH OVERRIDE GO Read all the post in the Wait Types and Queue series. Additionally a must read comment of Jonathan Kehayias. Note: The information presented here is from my experience and I no way claim it to be accurate. I suggest you all to read the online book for further clarification. All the discussion of Wait Stats over here is generic and it varies from system to system. It is recommended that you test this on the development server before implementing on the production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: DMV, Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Using BPEL Performance Statistics to Diagnose Performance Bottlenecks

    - by fip
    Tuning performance of Oracle SOA 11G applications could be challenging. Because SOA is a platform for you to build composite applications that connect many applications and "services", when the overall performance is slow, the bottlenecks could be anywhere in the system: the applications/services that SOA connects to, the infrastructure database, or the SOA server itself.How to quickly identify the bottleneck becomes crucial in tuning the overall performance. Fortunately, the BPEL engine in Oracle SOA 11G (and 10G, for that matter) collects BPEL Engine Performance Statistics, which show the latencies of low level BPEL engine activities. The BPEL engine performance statistics can make it a bit easier for you to identify the performance bottleneck. Although the BPEL engine performance statistics are always available, the access to and interpretation of them are somewhat obscure in the early and current (PS5) 11G versions. This blog attempts to offer instructions that help you to enable, retrieve and interpret the performance statistics, before the future versions provides a more pleasant user experience. Overview of BPEL Engine Performance Statistics  SOA BPEL has a feature of collecting some performance statistics and store them in memory. One MBean attribute, StatLastN, configures the size of the memory buffer to store the statistics. This memory buffer is a "moving window", in a way that old statistics will be flushed out by the new if the amount of data exceeds the buffer size. Since the buffer size is limited by StatLastN, impacts of statistics collection on performance is minimal. By default StatLastN=-1, which means no collection of performance data. Once the statistics are collected in the memory buffer, they can be retrieved via another MBean oracle.as.soainfra.bpel:Location=[Server Name],name=BPELEngine,type=BPELEngine.> My friend in Oracle SOA development wrote this simple 'bpelstat' web app that looks up and retrieves the performance data from the MBean and displays it in a human readable form. It does not have beautiful UI but it is fairly useful. Although in Oracle SOA 11.1.1.5 onwards the same statistics can be viewed via a more elegant UI under "request break down" at EM -> SOA Infrastructure -> Service Engines -> BPEL -> Statistics, some unsophisticated minds like mine may still prefer the simplicity of the 'bpelstat' JSP. One thing that simple JSP does do well is that you can save the page and send it to someone to further analyze Follows are the instructions of how to install and invoke the BPEL statistic JSP. My friend in SOA Development will soon blog about interpreting the statistics. Stay tuned. Step1: Enable BPEL Engine Statistics for Each SOA Servers via Enterprise Manager First st you need to set the StatLastN to some number as a way to enable the collection of BPEL Engine Performance Statistics EM Console -> soa-infra(Server Name) -> SOA Infrastructure -> SOA Administration -> BPEL Properties Click on "More BPEL Configuration Properties" Click on attribute "StatLastN", set its value to some integer number. Typically you want to set it 1000 or more. Step 2: Download and Deploy bpelstat.war File to Admin Server, Note: the WAR file contains a JSP that does NOT have any security restriction. You do NOT want to keep in your production server for a long time as it is a security hazard. Deactivate the war once you are done. Download the bpelstat.war to your local PC At WebLogic Console, Go to Deployments -> Install Click on the "upload your file(s)" Click the "Browse" button to upload the deployment to Admin Server Accept the uploaded file as the path, click next Check the default option "Install this deployment as an application" Check "AdminServer" as the target server Finish the rest of the deployment with default settings Console -> Deployments Check the box next to "bpelstat" application Click on the "Start" button. It will change the state of the app from "prepared" to "active" Step 3: Invoke the BPEL Statistic Tool The BPELStat tool merely call the MBean of BPEL server and collects and display the in-memory performance statics. You usually want to do that after some peak loads. Go to http://<admin-server-host>:<admin-server-port>/bpelstat Enter the correct admin hostname, port, username and password Enter the SOA Server Name from which you want to collect the performance statistics. For example, SOA_MS1, etc. Click Submit Keep doing the same for all SOA servers. Step 3: Interpret the BPEL Engine Statistics You will see a few categories of BPEL Statistics from the JSP Page. First it starts with the overall latency of BPEL processes, grouped by synchronous and asynchronous processes. Then it provides the further break down of the measurements through the life time of a BPEL request, which is called the "request break down". 1. Overall latency of BPEL processes The top of the page shows that the elapse time of executing the synchronous process TestSyncBPELProcess from the composite TestComposite averages at about 1543.21ms, while the elapse time of executing the asynchronous process TestAsyncBPELProcess from the composite TestComposite2 averages at about 1765.43ms. The maximum and minimum latency were also shown. Synchronous process statistics <statistics>     <stats key="default/TestComposite!2.0.2-ScopedJMSOSB*soa_bfba2527-a9ba-41a7-95c5-87e49c32f4ff/TestSyncBPELProcess" min="1234" max="4567" average="1543.21" count="1000">     </stats> </statistics> Asynchronous process statistics <statistics>     <stats key="default/TestComposite2!2.0.2-ScopedJMSOSB*soa_bfba2527-a9ba-41a7-95c5-87e49c32f4ff/TestAsyncBPELProcess" min="2234" max="3234" average="1765.43" count="1000">     </stats> </statistics> 2. Request break down Under the overall latency categorized by synchronous and asynchronous processes is the "Request breakdown". Organized by statistic keys, the Request breakdown gives finer grain performance statistics through the life time of the BPEL requests.It uses indention to show the hierarchy of the statistics. Request breakdown <statistics>     <stats key="eng-composite-request" min="0" max="0" average="0.0" count="0">         <stats key="eng-single-request" min="22" max="606" average="258.43" count="277">             <stats key="populate-context" min="0" max="0" average="0.0" count="248"> Please note that in SOA 11.1.1.6, the statistics under Request breakdown is aggregated together cross all the BPEL processes based on statistic keys. It does not differentiate between BPEL processes. If two BPEL processes happen to have the statistic that share same statistic key, the statistics from two BPEL processes will be aggregated together. Keep this in mind when we go through more details below. 2.1 BPEL process activity latencies A very useful measurement in the Request Breakdown is the performance statistics of the BPEL activities you put in your BPEL processes: Assign, Invoke, Receive, etc. The names of the measurement in the JSP page directly come from the names to assign to each BPEL activity. These measurements are under the statistic key "actual-perform" Example 1:  Follows is the measurement for BPEL activity "AssignInvokeCreditProvider_Input", which looks like the Assign activity in a BPEL process that assign an input variable before passing it to the invocation:                                <stats key="AssignInvokeCreditProvider_Input" min="1" max="8" average="1.9" count="153">                                     <stats key="sensor-send-activity-data" min="0" max="1" average="0.0" count="306">                                     </stats>                                     <stats key="sensor-send-variable-data" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="monitor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                 </stats> Note: because as previously mentioned that the statistics cross all BPEL processes are aggregated together based on statistic keys, if two BPEL processes happen to name their Invoke activity the same name, they will show up at one measurement (i.e. statistic key). Example 2: Follows is the measurement of BPEL activity called "InvokeCreditProvider". You can not only see that by average it takes 3.31ms to finish this call (pretty fast) but also you can see from the further break down that most of this 3.31 ms was spent on the "invoke-service".                                  <stats key="InvokeCreditProvider" min="1" max="13" average="3.31" count="153">                                     <stats key="initiate-correlation-set-again" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="invoke-service" min="1" max="13" average="3.08" count="153">                                         <stats key="prep-call" min="0" max="1" average="0.04" count="153">                                         </stats>                                     </stats>                                     <stats key="initiate-correlation-set" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="sensor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                     <stats key="sensor-send-variable-data" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="monitor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                     <stats key="update-audit-trail" min="0" max="2" average="0.03" count="153">                                     </stats>                                 </stats> 2.2 BPEL engine activity latency Another type of measurements under Request breakdown are the latencies of underlying system level engine activities. These activities are not directly tied to a particular BPEL process or process activity, but they are critical factors in the overall engine performance. These activities include the latency of saving asynchronous requests to database, and latency of process dehydration. My friend Malkit Bhasin is working on providing more information on interpreting the statistics on engine activities on his blog (https://blogs.oracle.com/malkit/). I will update this blog once the information becomes available. Update on 2012-10-02: My friend Malkit Bhasin has published the detail interpretation of the BPEL service engine statistics at his blog http://malkit.blogspot.com/2012/09/oracle-bpel-engine-soa-suite.html.

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  • SQL SERVER – 2000 – DBCC SQLPERF(waitstats) – Wait Type – Day 24 of 28

    - by pinaldave
    I have received many comments, email, suggestions and motivations for my current series of wait types and wait statistics. One of the questions which I keep on receiving almost every other day is whether all of the discussions I have presented so far are also applicable to SQL Server 2000. Additionally, I receive another question asking me if wait statistics matters in SQL Server 2000. If it is, then the asker wants to know how to measure wait types for SQL Server 2000. In SQL Server, you can run the following command to get a list of all the wait types: DBCC SQLPERF(waitstats) The query above will work in SQL Server 2005/2008/R2  because of backup compatibility. As you might have noticed, I have been discussing everything keeping SQL Server 2005+ in mind, but I have given little consideration on SQL Server 2000. However, I am pretty sure that most of the suggestions I have provided are applicable to SQL Server 2000. The wait types I have been discussing mostly exist in SQL Server 2000 as well. But the difference of the 2000 version is that it gets late recent releases, but it is worth it. Wait types are very essential to measure performance bottleneck. Because of this, I do not have to state that I am big fan of them just so I could identify performance bottleneck. Please read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, 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 – OLEDB – Link Server – Wait Type – Day 23 of 28

    - by pinaldave
    When I decided to start writing about this wait type, the very first question that came to my mind was, “What does ‘OLEDB’ stand for?” A quick search on Wikipedia tells me that OLEDB means Object Linking and Embedding Database. (How many of you knew this?) Anyway, I found it very interesting that this wait type was in one of the top 10 wait types in many of the systems I have come across in my performance tuning experience. Books On-Line: ????OLEDB occurs when SQL Server calls the SQL Server Native Client OLE DB Provider. This wait type is not used for synchronization. Instead, it indicates the duration of calls to the OLE DB provider. OLEDB Explanation: This wait type primarily happens when Link Server or Remove Query has been executed. The most common case wherein this wait type is visible is during the execution of Linked Server. When SQL Server is retrieving data from the remote server, it uses OLEDB API to retrieve the data. It is possible that the remote system is not quick enough or the connection between them is not fast enough, leading SQL Server to wait for the result’s return from the remote (or external) server. This is the time OLEDB wait type occurs. Reducing OLEDB wait: Check the Link Server configuration. Checking Disk-Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) At this point in time, I am not able to think of any more ways on reducing this wait type. Do you have any opinion about this subject? Please share it here and I will share your comment with the rest of the Community, and of course, with due credit unto you. Please read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – SOS_SCHEDULER_YIELD – Wait Type – Day 8 of 28

    - by pinaldave
    This is a very interesting wait type and quite often seen as one of the top wait types. Let us discuss this today. From Book On-Line: Occurs when a task voluntarily yields the scheduler for other tasks to execute. During this wait the task is waiting for its quantum to be renewed. SOS_SCHEDULER_YIELD Explanation: SQL Server has multiple threads, and the basic working methodology for SQL Server is that SQL Server does not let any “runnable” thread to starve. Now let us assume SQL Server OS is very busy running threads on all the scheduler. There are always new threads coming up which are ready to run (in other words, runnable). Thread management of the SQL Server is decided by SQL Server and not the operating system. SQL Server runs on non-preemptive mode most of the time, meaning the threads are co-operative and can let other threads to run from time to time by yielding itself. When any thread yields itself for another thread, it creates this wait. If there are more threads, it clearly indicates that the CPU is under pressure. You can fun the following DMV to see how many runnable task counts there are in your system. SELECT scheduler_id, current_tasks_count, runnable_tasks_count, work_queue_count, pending_disk_io_count FROM sys.dm_os_schedulers WHERE scheduler_id < 255 GO If you notice a two-digit number in runnable_tasks_count continuously for long time (not once in a while), you will know that there is CPU pressure. The two-digit number is usually considered as a bad thing; you can read the description of the above DMV over here. Additionally, there are several other counters (%Processor Time and other processor related counters), through which you can refer to so you can validate CPU pressure along with the method explained above. Reducing SOS_SCHEDULER_YIELD wait: This is the trickiest part of this procedure. As discussed, this particular wait type relates to CPU pressure. Increasing more CPU is the solution in simple terms; however, it is not easy to implement this solution. There are other things that you can consider when this wait type is very high. Here is the query where you can find the most expensive query related to CPU from the cache Note: The query that used lots of resources but is not cached will not be caught here. SELECT SUBSTRING(qt.TEXT, (qs.statement_start_offset/2)+1, ((CASE qs.statement_end_offset WHEN -1 THEN DATALENGTH(qt.TEXT) ELSE qs.statement_end_offset END - qs.statement_start_offset)/2)+1), qs.execution_count, qs.total_logical_reads, qs.last_logical_reads, qs.total_logical_writes, qs.last_logical_writes, qs.total_worker_time, qs.last_worker_time, qs.total_elapsed_time/1000000 total_elapsed_time_in_S, qs.last_elapsed_time/1000000 last_elapsed_time_in_S, qs.last_execution_time, qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) qt CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC -- CPU time You can find the most expensive queries that are utilizing lots of CPU (from the cache) and you can tune them accordingly. Moreover, you can find the longest running query and attempt to tune them if there is any processor offending code. Additionally, pay attention to total_worker_time because if that is also consistently higher, then  the CPU under too much pressure. You can also check perfmon counters of compilations as they tend to use good amount of CPU. Index rebuild is also a CPU intensive process but we should consider that main cause for this query because that is indeed needed on high transactions OLTP system utilized to reduce fragmentations. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, 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 – MSQL_XP – Wait Type – Day 20 of 28

    - by pinaldave
    In this blog post, I am going to discuss something from my field experience. While consultation, I have seen various wait typed, but one of my customers who has been using SQL Server for all his operations had an interesting issue with a particular wait type. Our customer had more than 100+ SQL Server instances running and the whole server had MSSQL_XP wait type as the most number of wait types. While running sp_who2 and other diagnosis queries, I could not immediately figure out what the issue was because the query with that kind of wait type was nowhere to be found. After a day of research, I was relieved that the solution was very easy to figure out. Let us continue discussing this wait type. From Book On-Line: ?MSQL_XP occurs when a task is waiting for an extended stored procedure to end. SQL Server uses this wait state to detect potential MARS application deadlocks. The wait stops when the extended stored procedure call ends. MSQL_XP Explanation: This wait type is created because of the extended stored procedure. Extended Stored Procedures are executed within SQL Server; however, SQL Server has no control over them. Unless you know what the code for the extended stored procedure is and what it is doing, it is impossible to understand why this wait type is coming up. Reducing MSQL_XP wait: As discussed, it is hard to understand the Extended Stored Procedure if the code for it is not available. In the scenario described at the beginning of this post, our client was using third-party backup tool. The third-party backup tool was using Extended Stored Procedure. After we learned that this wait type was coming from the extended stored procedure of the backup tool they were using, we contacted the tech team of its vendor. The vendor admitted that the code was not optimal at some places, and within that day they had provided the patch. Once the updated version was installed, the issue on this wait type disappeared. As viewed in the wait statistics of all the 100+ SQL Server, there was no more MSSQL_XP wait type found. In simpler terms, you must first identify which Extended Stored Procedure is creating the wait type of MSSQL_XP and see if you can get in touch with the creator of the SP so you can help them optimize the code. If you have encountered this MSSQL_XP wait type, I encourage all of you to write how you managed it. Please do not mention the name of the vendor in your comment as I will not approve it. The focus of this blog post is to understand the wait types; not talk about others. Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – CXPACKET – Parallelism – Advanced Solution – Wait Type – Day 7 of 28

    - by pinaldave
    Earlier we discussed about the what is the common solution to solve the issue with CXPACKET wait time. Today I am going to talk about few of the other suggestions which can help to reduce the CXPACKET wait. If you are going to suggest that I should focus on MAXDOP and COST THRESHOLD – I totally agree. I have covered them in details in yesterday’s blog post. Today we are going to discuss few other way CXPACKET can be reduced. Potential Reasons: If data is heavily skewed, there are chances that query optimizer may estimate the correct amount of the data leading to assign fewer thread to query. This can easily lead to uneven workload on threads and may create CXPAKCET wait. While retrieving the data one of the thread face IO, Memory or CPU bottleneck and have to wait to get those resources to execute its tasks, may create CXPACKET wait as well. Data which is retrieved is on different speed IO Subsystem. (This is not common and hardly possible but there are chances). Higher fragmentations in some area of the table can lead less data per page. This may lead to CXPACKET wait. As I said the reasons here mentioned are not the major cause of the CXPACKET wait but any kind of scenario can create the probable wait time. Best Practices to Reduce CXPACKET wait: Refer earlier article regarding MAXDOP and Cost Threshold. De-fragmentation of Index can help as more data can be obtained per page. (Assuming close to 100 fill-factor) If data is on multiple files which are on multiple similar speed physical drive, the CXPACKET wait may reduce. Keep the statistics updated, as this will give better estimate to query optimizer when assigning threads and dividing the data among available threads. Updating statistics can significantly improve the strength of the query optimizer to render proper execution plan. This may overall affect the parallelism process in positive way. Bad Practice: In one of the recent consultancy project, when I was called in I noticed that one of the ‘experienced’ DBA noticed higher CXPACKET wait and to reduce them, he has increased the worker threads. The reality was increasing worker thread has lead to many other issues. With more number of the threads, more amount of memory was used leading memory pressure. As there were more threads CPU scheduler faced higher ‘Context Switching’ leading further degrading performance. When I explained all these to ‘experienced’ DBA he suggested that now we should reduce the number of threads. Not really! Lower number of the threads may create heavy stalling for parallel queries. I suggest NOT to touch the setting of number of the threads when dealing with CXPACKET wait. Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and I no way claim it to be accurate. I suggest reading book on-line for further clarification. All the discussion of Wait Stats over here is generic and it varies by system to system. You are recommended to test this on development server before implementing to production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: DMV, Pinal Dave, PostADay, SQL, SQL Authority, 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 – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28

    - by pinaldave
    For any good system three things are vital: CPU, Memory and IO (disk). Among these three, IO is the most crucial factor of SQL Server. Looking at real-world cases, I do not see IT people upgrading CPU and Memory frequently. However, the disk is often upgraded for either improving the space, speed or throughput. Today we will look at another IO-related wait type. From Book On-Line: Occurs when a task is waiting for I/Os to finish. ASYNC_IO_COMPLETION Explanation: Any tasks are waiting for I/O to finish. If by any means your application that’s connected to SQL Server is processing the data very slowly, this type of wait can occur. Several long-running database operations like BACKUP, CREATE DATABASE, ALTER DATABASE or other operations can also create this wait type. Reducing ASYNC_IO_COMPLETION wait: When it is an issue related to IO, one should check for the following things associated to IO subsystem: Look at the programming and see if there is any application code which processes the data slowly (like inefficient loop, etc.). Note that it should be re-written to avoid this  wait type. Proper placing of the files is very important. We should check the file system for proper placement of the files – LDF and MDF on separate drive, TempDB on another separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is a higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. Check event log and error log for any errors or warnings related to IO. If you are using SAN (Storage Area Network), check the throughput of the SAN system as well as configuration of the HBA Queue Depth. In one of my recent projects, the SAN was performing really badly and so the SAN administrator did not accept it. After some investigations, he agreed to change the HBA Queue Depth on the development setup (test environment). As soon as we changed the HBA Queue Depth to quite a higher value, there was a sudden big improvement in the performance. It is very likely to happen that there are no proper indexes on the system and yet there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can effectively reduce lots of CPU, Memory and IO (considering cover index has lesser columns than cluster table and all other; it depends upon the situation). You can refer to the following two articles I wrote that talk about how to optimize indexes: Create Missing Indexes Drop Unused Indexes Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussions of Wait Stats in this blog are generic and vary from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • stats::reorder vs Hmisc::reorder

    - by learnr
    I am trying to get around the strange overlap of stats::reorder vs Hmisc::reorder. Without Hmisc loaded I get the result I want, i.e. an unordered factor: > with(InsectSprays, reorder(spray, count, median)) [1] A A A A A A A A A A A A B B B B B B B B B B B B C C C C C C C C C C C C D D [39] D D D D D D D D D D E E E E E E E E E E E E F F F F F F F F F F F F attr(,"scores") A B C D E F 14.0 16.5 1.5 5.0 3.0 15.0 Levels: C E D A F B Now after loading Hmisc the result is an ordered factor: > library(Hmisc) Loading required package: survival Loading required package: splines Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > with(InsectSprays, reorder(spray, count, median)) [1] A A A A A A A A A A A A B B B B B B B B B B B B C C C C C C C C C C C C D D [39] D D D D D D D D D D E E E E E E E E E E E E F F F F F F F F F F F F Levels: C < E < D < A < F < B In calling stats::reorder directly, I now for some reason get an ordered factor. > with(InsectSprays, stats::reorder(spray, count, median)) [1] A A A A A A A A A A A A B B B B B B B B B B B B C C C C C C C C C C C C D D [39] D D D D D D D D D D E E E E E E E E E E E E F F F F F F F F F F F F Levels: C < E < D < A < F < B Specifying, that I would need an unordered factor results in an error suggesting that stats::reorder is not used? > with(InsectSprays, stats::reorder(spray, count, median, order = FALSE)) Error in FUN(X[[1L]], ...) : unused argument(s) (order = FALSE) So the question really is how do I get an unordered factor with Hmisc loaded?

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  • SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28

    - by pinaldave
    Locking is a mechanism used by the SQL Server Database Engine to synchronize access by multiple users to the same piece of data, at the same time. In simpler words, it maintains the integrity of data by protecting (or preventing) access to the database object. From Book On-Line: LCK_M_BU Occurs when a task is waiting to acquire a Bulk Update (BU) lock. LCK_M_IS Occurs when a task is waiting to acquire an Intent Shared (IS) lock. LCK_M_IU Occurs when a task is waiting to acquire an Intent Update (IU) lock. LCK_M_IX Occurs when a task is waiting to acquire an Intent Exclusive (IX) lock. LCK_M_S Occurs when a task is waiting to acquire a Shared lock. LCK_M_SCH_M Occurs when a task is waiting to acquire a Schema Modify lock. LCK_M_SCH_S Occurs when a task is waiting to acquire a Schema Share lock. LCK_M_SIU Occurs when a task is waiting to acquire a Shared With Intent Update lock. LCK_M_SIX Occurs when a task is waiting to acquire a Shared With Intent Exclusive lock. LCK_M_U Occurs when a task is waiting to acquire an Update lock. LCK_M_UIX Occurs when a task is waiting to acquire an Update With Intent Exclusive lock. LCK_M_X Occurs when a task is waiting to acquire an Exclusive lock. LCK_M_XXX Explanation: I think the explanation of this wait type is the simplest. When any task is waiting to acquire lock on any resource, this particular wait type occurs. The common reason for the task to be waiting to put lock on the resource is that the resource is already locked and some other operations may be going on within it. This wait also indicates that resources are not available or are occupied at the moment due to some reasons. There is a good chance that the waiting queries start to time out if this wait type is very high. Client application may degrade the performance as well. You can use various methods to find blocking queries: EXEC sp_who2 SQL SERVER – Quickest Way to Identify Blocking Query and Resolution – Dirty Solution DMV – sys.dm_tran_locks DMV – sys.dm_os_waiting_tasks Reducing LCK_M_XXX wait: Check the Explicit Transactions. If transactions are very long, this wait type can start building up because of other waiting transactions. Keep the transactions small. Serialization Isolation can build up this wait type. If that is an acceptable isolation for your business, this wait type may be natural. The default isolation of SQL Server is ‘Read Committed’. One of my clients has changed their isolation to “Read Uncommitted”. I strongly discourage the use of this because this will probably lead to having lots of dirty data in the database. Identify blocking queries mentioned using various methods described above, and then optimize them. Partition can be one of the options to consider because this will allow transactions to execute concurrently on different partitions. If there are runaway queries, use timeout. (Please discuss this solution with your database architect first as timeout can work against you). Check if there is no memory and IO-related issue using the following counters: Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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

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

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  • SQLAuthority News – Community Tech Days – TechEd on The Road – Ahmedabad – June 11, 2011

    - by pinaldave
    TechEd on Road is back! In Ahmedabad June 11, 2011! Inviting all Professional Developers, Project Managers, Architects, IT Managers, IT Administrators and Implementers of Ahmedabad to be a part of Tech•Ed on the Road, on 11th June, 2011. We have put together the best sessions from Tech•Ed India 2011 for you in your city. Focal point will be technologies like Database and BI, Windows 7, ASP.NET. REGISTER HERE! Venue: Venue: Ahmedabad Management Association (AMA) Dr. Vikram Sarabhai Marg, University Area, Ahmedabad, Gujarat 380 015 Time: 9:30AM – 5:30PM The biggest attraction of the event is session HTML5 – Future of the Web by Harish Vaidyanathan. He is Evangelist Lead in Microsoft and hands on developer himself. I strongly urge all of you to attend his session to understand direction of the web and Microsoft’s take on the subject. I (Pinal Dave) will be presenting on the session of SQL Server Performance Tuning and Jacob Sebastian will be presenting on T-SQL Worst Practices. Do not miss this opportunity. Those who have attended in the past know that from last two years the venue is jam packed in first few minutes. Do come in early to get better seat and reserve your spot. We will have QUIZ during the event and we will have various gifts – Watches, USB Drives, T-Shirts and many more interesting gifts. Refer the agenda today and register right away. There will be no video recording so come and visit the event in person. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Best Practices, Database, DBA, MVP, Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Munin does not show Apache/mySQL stats in web view

    - by Chris
    I'm facing a very strange Problem. I just set up Munin on a fresh Ubuntu slice with a common LAMP Stack. Everything works great, except that Munin does just not show the Apache/mySQL stats in the web view. Everything else in the web view works great, Apache works, mySQL works. I even tried calling the plugins via console: sudo munin-run apache_accesses And it works fine. AFAIK Munin log files are not telling me any problems.. My only hint: when I run munin-run without sudo it gives me a "Permission denied" - could this be the problem?

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  • rsnapshot stats

    - by Obscur Moirage
    I'd like to retrieve the following stats from rsnapshot files synced added files modded files deleted files Is there a feature to retrieve these in rsnapshot, or is there another product that's able to do it? EDIT: As requested, I'll try to show that I'm not just asking what I want to do without any research. I wasn't able to locate any rsnapshot feature doing this. Maybe I'm searching in a wrong direction. So, I've built a not very pretty script, called each time before rsnapshot is ran. This Perl script stores each file MD5, in order to compare backup files structures between rsnapshot updates. I'm pretty sure it's worthless to show this code here. I think that keeping an eye on what change on a server, for example, is a useful feature. So, I'm asking. @pauska Most of the time, I'm trying to search for an answer myself, which is not the case here. Thanks

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  • SQL SERVER – PREEMPTIVE and Non-PREEMPTIVE – Wait Type – Day 19 of 28

    - by pinaldave
    In this blog post, we are going to talk about a very interesting subject. I often get questions related to SQL Server 2008 Book-Online about various Preemptive wait types. I got a few questions asking what these wait types are and how they could be interpreted. To get current wait types of the system, you can read this article and run the script: SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28. Before we continue understanding them, let us study first what PREEMPTIVE and Non-PREEMPTIVE waits in SQL Server mean. PREEMPTIVE: Simply put, this wait means non-cooperative. While SQL Server is executing a task, the Operating System (OS) interrupts it. This leads to SQL Server to involuntarily give up the execution for other higher priority tasks. This is not good for SQL Server as it is a particular external process which makes SQL Server to yield. This kind of wait can reduce the performance drastically and needs to be investigated properly. Non-PREEMPTIVE: In simple terms, this wait means cooperative. SQL Server manages the scheduling of the threads. When SQL Server manages the scheduling instead of the OS, it makes sure its own priority. In this case, SQL Server decides the priority and one thread yields to another thread voluntarily. In the earlier version of SQL Server, there was no preemptive wait types mentioned and the associated task status with them was marked as suspended. In SQL Server 2005, preemptive wait types were not listed as well, but their associated task status was marked as running. In SQL Server 2008, preemptive wait types are properly listed and their associated task status is also marked as running. Now, SQL Server is in Non-Preemptive mode by default and it works fine. When CLR, extended Stored Procedures and other external components run, they run in Preemptive mode, leading to the creation of these wait types. There are a wide variety of preemptive wait types. If you see consistent high value in the Preemptive wait types, I strongly suggest that you look into the wait type and try to know the root cause. If you are still not sure, you can send me an email or leave a comment about it and I will do my best to help you reduce this wait type. 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 Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28

    - by pinaldave
    Previously, we covered the DMV sys.dm_os_wait_stats, and also saw how it can be useful to identify the major resource bottleneck. However, at the same time, we discussed that this is only useful when we are looking at an instance-level picture. Quite often we want to know about the processes going in our server at the given instant. Here is the query for the same. This DMV is written taking the following into consideration: we want to analyze the queries that are currently running or which have recently ran and their plan is still in the cache. SELECT dm_ws.wait_duration_ms, dm_ws.wait_type, dm_es.status, dm_t.TEXT, dm_qp.query_plan, dm_ws.session_ID, dm_es.cpu_time, dm_es.memory_usage, dm_es.logical_reads, dm_es.total_elapsed_time, dm_es.program_name, DB_NAME(dm_r.database_id) DatabaseName, -- Optional columns dm_ws.blocking_session_id, dm_r.wait_resource, dm_es.login_name, dm_r.command, dm_r.last_wait_type FROM sys.dm_os_waiting_tasks dm_ws INNER JOIN sys.dm_exec_requests dm_r ON dm_ws.session_id = dm_r.session_id INNER JOIN sys.dm_exec_sessions dm_es ON dm_es.session_id = dm_r.session_id CROSS APPLY sys.dm_exec_sql_text (dm_r.sql_handle) dm_t CROSS APPLY sys.dm_exec_query_plan (dm_r.plan_handle) dm_qp WHERE dm_es.is_user_process = 1 GO You can change CROSS APPLY to OUTER APPLY if you want to see all the details which are omitted because of the plan cache. Let us analyze the result of the above query and see how it can be helpful to identify the query and the kind of wait type it creates. Click to Enlarage The above query will return various columns. There are various columns that provide very important details. e.g. wait_duration_ms – it indicates current wait for the query that executes at that point of time. wait_type – it indicates the current wait type for the query text – indicates the query text query_plan – when clicked on the same, it will display the query plans There are many other important information like CPU_time, memory_usage, and logical_reads, which can be read from the query as well. In future posts on this series, we will see how once identified wait type we can attempt to reduce the same. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: DMV, Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQLAuthority News – I am Presenting 2 Sessions at TechEd India

    - by pinaldave
    TechED is the event which I am always excited about. It is one of the largest technology in India. Microsoft Tech Ed India 2011 is the premier technical education and networking event for tech professionals interested in learning, connecting and exploring a broad set of current and soon-to-be released Microsoft technologies, tools, platforms and services. I am going to speak at the TechED on two very interesting and advanced subjects. Venue: The LaLiT Ashok Kumara Krupa High Grounds Bangalore – 560001, Karnataka, India Sessions Date: March 25, 2011 Understanding SQL Server Behavioral Pattern – SQL Server Extended Events Date and Time: March 25, 2011 12:00 PM to 01:00 PM History repeats itself! SQL Server 2008 has introduced a very powerful, yet very minimal reoccurring feature called Extended Events. This advanced session will teach experienced administrators’ capabilities that were not possible before. From T-SQL error to CPU bottleneck, error login to deadlocks –Extended Event can detect it for you. Understanding the pattern of events can prevent future mistakes. SQL Server Waits and Queues – Your Gateway to Perf. Troubleshooting Date and Time: March 25, 2011 04:15 PM to 05:15 PM Just like a horoscope, SQL Server Waits and Queues can reveal your past, explain your present and predict your future. SQL Server Performance Tuning uses the Waits and Queues as a proven method to identify the best opportunities to improve performance. A glance at Wait Types can tell where there is a bottleneck. Learn how to identify bottlenecks and potential resolutions in this fast paced, advanced performance tuning session. My session will be on the third day of the event and I am very sure that everybody will be in groove to learn new interesting subjects. I will have few give-away during and at the end of the session. I will not tell you what I will have but it will be for sure something you will love to have. Please make a point and reserve above time slots to attend my session. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology Tagged: SQL Extended Events

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  • iTunesConnect acces to download stats for my client

    - by Thierryb
    Hello, I've developed an app for a client and would like to give him an access to my iTunesConnect in order to access to the download stat for his application. The problem is that if I create a new user and set permission to only see reports, he will be able to get all stats... And I don't want to get stats manually each day. Do you have an idea ? Thanks

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  • SQL SERVER – Guest Post – Jacob Sebastian – Filestream – Wait Types – Wait Queues – Day 22 of 28

    - by pinaldave
    Jacob Sebastian is a SQL Server MVP, Author, Speaker and Trainer. Jacob is one of the top rated expert community. Jacob wrote the book The Art of XSD – SQL Server XML Schema Collections and wrote the XML Chapter in SQL Server 2008 Bible. See his Blog | Profile. He is currently researching on the subject of Filestream and have submitted this interesting article on the very subject. What is FILESTREAM? FILESTREAM is a new feature introduced in SQL Server 2008 which provides an efficient storage and management option for BLOB data. Many applications that deal with BLOB data today stores them in the file system and stores the path to the file in the relational tables. Storing BLOB data in the file system is more efficient that storing them in the database. However, this brings up a few disadvantages as well. When the BLOB data is stored in the file system, it is hard to ensure transactional consistency between the file system data and relational data. Some applications store the BLOB data within the database to overcome the limitations mentioned earlier. This approach ensures transactional consistency between the relational data and BLOB data, but is very bad in terms of performance. FILESTREAM combines the benefits of both approaches mentioned above without the disadvantages we examined. FILESTREAM stores the BLOB data in the file system (thus takes advantage of the IO Streaming capabilities of NTFS) and ensures transactional consistency between the BLOB data in the file system and the relational data in the database. For more information on the FILESTREAM feature, visit: http://beyondrelational.com/filestream/default.aspx FILESTREAM Wait Types Since this series is on the different SQL Server wait types, let us take a look at the various wait types that are related to the FILESTREAM feature. FS_FC_RWLOCK This wait type is generated by FILESTREAM Garbage Collector. This occurs when Garbage collection is disabled prior to a backup/restore operation or when a garbage collection cycle is being executed. FS_GARBAGE_COLLECTOR_SHUTDOWN This wait type occurs when during the cleanup process of a garbage collection cycle. It indicates that that garbage collector is waiting for the cleanup tasks to be completed. FS_HEADER_RWLOCK This wait type indicates that the process is waiting for obtaining access to the FILESTREAM header file for read or write operation. The FILESTREAM header is a disk file located in the FILESTREAM data container and is named “filestream.hdr”. FS_LOGTRUNC_RWLOCK This wait type indicates that the process is trying to perform a FILESTREAM log truncation related operation. It can be either a log truncate operation or to disable log truncation prior to a backup or restore operation. FSA_FORCE_OWN_XACT This wait type occurs when a FILESTREAM file I/O operation needs to bind to the associated transaction, but the transaction is currently owned by another session. FSAGENT This wait type occurs when a FILESTREAM file I/O operation is waiting for a FILESTREAM agent resource that is being used by another file I/O operation. FSTR_CONFIG_MUTEX This wait type occurs when there is a wait for another FILESTREAM feature reconfiguration to be completed. FSTR_CONFIG_RWLOCK This wait type occurs when there is a wait to serialize access to the FILESTREAM configuration parameters. Waits and Performance System waits has got a direct relationship with the overall performance. In most cases, when waits increase the performance degrades. SQL Server documentation does not say much about how we can reduce these waits. However, following the FILESTREAM best practices will help you to improve the overall performance and reduce the wait types to a good extend. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology Tagged: Filestream

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  • SQL SERVER – Speed Up! – Parallel Processes and Unparalleled Performance – TechEd 2012 India

    - by pinaldave
    TechEd India 2012 is just around the corner and I will be presenting there on two different session. SQL Server Performance Tuning is a very challenging subject that requires expertise in Database Administration and Database Development. I always have enjoyed talking about SQL Server Performance tuning subject. Just like doctors I like to call my every attempt to improve the performance of SQL Server queries and database server as a practice too. I have been working with SQL Server for more than 8 years and I believe that many of the performance tuning concept I have mastered. However, performance tuning is not a simple subject. However there are occasions when I feel stumped, there are occasional when I am not sure what should be the next step. When I face situation where I cannot figure things out easily, it makes me most happy because I clearly see this as a learning opportunity. I have been presenting in TechEd India for last three years. This is my fourth time opportunity to present a technical session on SQL Server. Just like every other year, I decided to present something different, something which I have spend years of learning. This time, I am going to present about parallel processes. It is widely believed that more the CPU will improve performance of the server. It is true in many cases. However, there are cases when limiting the CPU usages have improved overall health of the server. I will be presenting on the subject of Parallel Processes and its effects. I have spent more than a year working on this subject only. After working on various queries on multi-CPU systems I have personally learned few things. In coming TechEd session, I am going to share my experience with parallel processes and performance tuning. Session Details Title: Speed Up! – Parallel Processes and Unparalleled Performance (Add to Calendar) Abstract: “More CPU More Performance” – A  very common understanding is that usage of multiple CPUs can improve the performance of the query. To get maximum performance out of any query – one has to master various aspects of the parallel processes. In this deep dive session, we will explore this complex subject with a very simple interactive demo. An attendee will walk away with proper understanding of CX_PACKET wait types, MAXDOP, parallelism threshold and various other concepts. Date and Time: March 23, 2012, 12:15 to 13:15 Location: Hotel Lalit Ashok - Kumara Krupa High Grounds, Bengaluru – 560001, Karnataka, India. Add to Calendar Please submit your questions in the comments area and I will be for sure discussing them during my session. If I pick your question to discuss during my session, here is your gift I commit right now – SQL Server Interview Questions and Answers Book. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology Tagged: TechEd, TechEdIn

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  • SQL SERVER – Guest Post – Jonathan Kehayias – Wait Type – Day 16 of 28

    - by pinaldave
    Jonathan Kehayias (Blog | Twitter) is a MCITP Database Administrator and Developer, who got started in SQL Server in 2004 as a database developer and report writer in the natural gas industry. After spending two and a half years working in TSQL, in late 2006, he transitioned to the role of SQL Database Administrator. His primary passion is performance tuning, where he frequently rewrites queries for better performance and performs in depth analysis of index implementation and usage. Jonathan blogs regularly on SQLBlog, and was a coauthor of Professional SQL Server 2008 Internals and Troubleshooting. On a personal note, I think Jonathan is extremely positive person. In every conversation with him I have found that he is always eager to help and encourage. Every time he finds something needs to be approved, he has contacted me without hesitation and guided me to improve, change and learn. During all the time, he has not lost his focus to help larger community. I am honored that he has accepted to provide his views on complex subject of Wait Types and Queues. Currently I am reading his series on Extended Events. Here is the guest blog post by Jonathan: SQL Server troubleshooting is all about correlating related pieces of information together to indentify where exactly the root cause of a problem lies. In my daily work as a DBA, I generally get phone calls like, “So and so application is slow, what’s wrong with the SQL Server.” One of the funny things about the letters DBA is that they go so well with Default Blame Acceptor, and I really wish that I knew exactly who the first person was that pointed that out to me, because it really fits at times. A lot of times when I get this call, the problem isn’t related to SQL Server at all, but every now and then in my initial quick checks, something pops up that makes me start looking at things further. The SQL Server is slow, we see a number of tasks waiting on ASYNC_IO_COMPLETION, IO_COMPLETION, or PAGEIOLATCH_* waits in sys.dm_exec_requests and sys.dm_exec_waiting_tasks. These are also some of the highest wait types in sys.dm_os_wait_stats for the server, so it would appear that we have a disk I/O bottleneck on the machine. A quick check of sys.dm_io_virtual_file_stats() and tempdb shows a high write stall rate, while our user databases show high read stall rates on the data files. A quick check of some performance counters and Page Life Expectancy on the server is bouncing up and down in the 50-150 range, the Free Page counter consistently hits zero, and the Free List Stalls/sec counter keeps jumping over 10, but Buffer Cache Hit Ratio is 98-99%. Where exactly is the problem? In this case, which happens to be based on a real scenario I faced a few years back, the problem may not be a disk bottleneck at all; it may very well be a memory pressure issue on the server. A quick check of the system spec’s and it is a dual duo core server with 8GB RAM running SQL Server 2005 SP1 x64 on Windows Server 2003 R2 x64. Max Server memory is configured at 6GB and we think that this should be enough to handle the workload; or is it? This is a unique scenario because there are a couple of things happening inside of this system, and they all relate to what the root cause of the performance problem is on the system. If we were to query sys.dm_exec_query_stats for the TOP 10 queries, by max_physical_reads, max_logical_reads, and max_worker_time, we may be able to find some queries that were using excessive I/O and possibly CPU against the system in their worst single execution. We can also CROSS APPLY to sys.dm_exec_sql_text() and see the statement text, and also CROSS APPLY sys.dm_exec_query_plan() to get the execution plan stored in cache. Ok, quick check, the plans are pretty big, I see some large index seeks, that estimate 2.8GB of data movement between operators, but everything looks like it is optimized the best it can be. Nothing really stands out in the code, and the indexing looks correct, and I should have enough memory to handle this in cache, so it must be a disk I/O problem right? Not exactly! If we were to look at how much memory the plan cache is taking by querying sys.dm_os_memory_clerks for the CACHESTORE_SQLCP and CACHESTORE_OBJCP clerks we might be surprised at what we find. In SQL Server 2005 RTM and SP1, the plan cache was allowed to take up to 75% of the memory under 8GB. I’ll give you a second to go back and read that again. Yes, you read it correctly, it says 75% of the memory under 8GB, but you don’t have to take my word for it, you can validate this by reading Changes in Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2. In this scenario the application uses an entirely adhoc workload against SQL Server and this leads to plan cache bloat, and up to 4.5GB of our 6GB of memory for SQL can be consumed by the plan cache in SQL Server 2005 SP1. This in turn reduces the size of the buffer cache to just 1.5GB, causing our 2.8GB of data movement in this expensive plan to cause complete flushing of the buffer cache, not just once initially, but then another time during the queries execution, resulting in excessive physical I/O from disk. Keep in mind that this is not the only query executing at the time this occurs. Remember the output of sys.dm_io_virtual_file_stats() showed high read stalls on the data files for our user databases versus higher write stalls for tempdb? The memory pressure is also forcing heavier use of tempdb to handle sorting and hashing in the environment as well. The real clue here is the Memory counters for the instance; Page Life Expectancy, Free List Pages, and Free List Stalls/sec. The fact that Page Life Expectancy is fluctuating between 50 and 150 constantly is a sign that the buffer cache is experiencing constant churn of data, once every minute to two and a half minutes. If you add to the Page Life Expectancy counter, the consistent bottoming out of Free List Pages along with Free List Stalls/sec consistently spiking over 10, and you have the perfect memory pressure scenario. All of sudden it may not be that our disk subsystem is the problem, but is instead an innocent bystander and victim. Side Note: The Page Life Expectancy counter dropping briefly and then returning to normal operating values intermittently is not necessarily a sign that the server is under memory pressure. The Books Online and a number of other references will tell you that this counter should remain on average above 300 which is the time in seconds a page will remain in cache before being flushed or aged out. This number, which equates to just five minutes, is incredibly low for modern systems and most published documents pre-date the predominance of 64 bit computing and easy availability to larger amounts of memory in SQL Servers. As food for thought, consider that my personal laptop has more memory in it than most SQL Servers did at the time those numbers were posted. I would argue that today, a system churning the buffer cache every five minutes is in need of some serious tuning or a hardware upgrade. Back to our problem and its investigation: There are two things really wrong with this server; first the plan cache is excessively consuming memory and bloated in size and we need to look at that and second we need to evaluate upgrading the memory to accommodate the workload being performed. In the case of the server I was working on there were a lot of single use plans found in sys.dm_exec_cached_plans (where usecounts=1). Single use plans waste space in the plan cache, especially when they are adhoc plans for statements that had concatenated filter criteria that is not likely to reoccur with any frequency.  SQL Server 2005 doesn’t natively have a way to evict a single plan from cache like SQL Server 2008 does, but MVP Kalen Delaney, showed a hack to evict a single plan by creating a plan guide for the statement and then dropping that plan guide in her blog post Geek City: Clearing a Single Plan from Cache. We could put that hack in place in a job to automate cleaning out all the single use plans periodically, minimizing the size of the plan cache, but a better solution would be to fix the application so that it uses proper parameterized calls to the database. You didn’t write the app, and you can’t change its design? Ok, well you could try to force parameterization to occur by creating and keeping plan guides in place, or we can try forcing parameterization at the database level by using ALTER DATABASE <dbname> SET PARAMETERIZATION FORCED and that might help. If neither of these help, we could periodically dump the plan cache for that database, as discussed as being a problem in Kalen’s blog post referenced above; not an ideal scenario. The other option is to increase the memory on the server to 16GB or 32GB, if the hardware allows it, which will increase the size of the plan cache as well as the buffer cache. In SQL Server 2005 SP1, on a system with 16GB of memory, if we set max server memory to 14GB the plan cache could use at most 9GB  [(8GB*.75)+(6GB*.5)=(6+3)=9GB], leaving 5GB for the buffer cache.  If we went to 32GB of memory and set max server memory to 28GB, the plan cache could use at most 16GB [(8*.75)+(20*.5)=(6+10)=16GB], leaving 12GB for the buffer cache. Thankfully we have SQL Server 2005 Service Pack 2, 3, and 4 these days which include the changes in plan cache sizing discussed in the Changes to Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2 blog post. In real life, when I was troubleshooting this problem, I spent a week trying to chase down the cause of the disk I/O bottleneck with our Server Admin and SAN Admin, and there wasn’t much that could be done immediately there, so I finally asked if we could increase the memory on the server to 16GB, which did fix the problem. It wasn’t until I had this same problem occur on another system that I actually figured out how to really troubleshoot this down to the root cause.  I couldn’t believe the size of the plan cache on the server with 16GB of memory when I actually learned about this and went back to look at it. SQL Server is constantly telling a story to anyone that will listen. As the DBA, you have to sit back and listen to all that it’s telling you and then evaluate the big picture and how all the data you can gather from SQL about performance relate to each other. One of the greatest tools out there is actually a free in the form of Diagnostic Scripts for SQL Server 2005 and 2008, created by MVP Glenn Alan Berry. Glenn’s scripts collect a majority of the information that SQL has to offer for rapid troubleshooting of problems, and he includes a lot of notes about what the outputs of each individual query might be telling you. When I read Pinal’s blog post SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28, I noticed that he referenced Checking Memory Related Performance Counters in his post, but there was no real explanation about why checking memory counters is so important when looking at an I/O related wait type. I thought I’d chat with him briefly on Google Talk/Twitter DM and point this out, and offer a couple of other points I noted, so that he could add the information to his blog post if he found it useful.  Instead he asked that I write a guest blog for this. I am honored to be a guest blogger, and to be able to share this kind of information with the community. The information contained in this blog post is a glimpse at how I do troubleshooting almost every day of the week in my own environment. SQL Server provides us with a lot of information about how it is running, and where it may be having problems, it is up to us to play detective and find out how all that information comes together to tell us what’s really the problem. This blog post is written by Jonathan Kehayias (Blog | Twitter). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: MVP, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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