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  • Bad Performance With Games Under Wine in Ubuntu 12.04

    - by Pandem
    I'm somewhat new to Linux. I've dabbled with it before but never more than just experimentation in a VM or dual boot where I almost always reverted back to Windows soon after (more due to a lack of commitment than a dislike for the OS). Anyway my problem is that in the two games (Guild Wars and Team Fortress 2) I've tried so far I get fairly bad performance. Despite both games having a "Platinum" rating I've still been forced to run both in DirectX 8, otherwise they either crash, have texture defects or the UI is missing. By "bad performance" I mean sub-30 FPS where there are some players and regular large framerate drops with video settings on low. Currently in my mind I believe the performance issues are just a problem with the drivers because my graphics card is a AMD 7850 which is virtually brand new and probably not properly supported yet but I'm unsure and would appreciate advice or tips to improve things. I have Ubuntu 12.04 installed and I am usually logged in a Gnome Classic session. I have installed AMD's proprietary drivers (Catalyst version 12.4) and have Wine 1.4 installed. I have used Winetricks to install DX9/DX10 dlls and other things.

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  • Oracle ZFSSA Hybrid Storage Pool Demo

    - by Darius Zanganeh
    The ZFS Hybrid Storage Pool (HSP) has been around since the ZFSSA first launched.  It is one of the main contributors to the high performance we see on the Oracle ZFSSA both in benchmarks as well as many production environments.  Below is a short video I made to show at a high level just how impactful this HSP pool is on storage performance.  We squeeze a ton of performance out of our drives with our unique use of cache, write optimized ssd and read optimized ssd.  Many have written and blogged about this technology, here it is in action. Demo of the Oracle ZFSSA Hybrid Storage Pool and how it speeds up workloads.

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  • "Optimal" game loop for 2D side-scroller

    - by MrDatabase
    Is it possible to describe an "optimal" (in terms of performance) layout for a 2D side-scroller's game loop? In this context the "game loop" takes user input, updates the states of game objects and draws the game objects. For example having a GameObject base class with a deep inheritance hierarchy could be good for maintenance... you can do something like the following: foreach(GameObject g in gameObjects) g.update(); However I think this approach can create performance issues. On the other hand all game objects' data and functions could be global. Which would be a maintenance headache but might be closer to an optimally performing game loop. Any thoughts? I'm interested in practical applications of near optimal game loop structure... even if I get a maintenance headache in exchange for great performance.

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  • What criteria would I use SQL Stream Insight vs TPL Dataflow [closed]

    - by makerofthings7
    There is an add-in to the Task Parallel Library (TPL) called TPL Dataflow that allows a variety of data processing scenarios. It seems that there are some parallels to the SQL Stream Insight product, however since SQL's Stream Insight has some interesting licensing around it, and it has a better performance depending on what license I get... I found myself asking myself should I use TPL Dataflow and not have any licensing issues, and possibly better performance. Can anyone tell me if performance is a valid criteria for comparing SQL Stream Insight vs TPL Dataflow? What other criteria should I be looking at when comparing the two?

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  • Can a call to WaitHandle.SignalAndWait be ignored for performance profiling purposes?

    - by Dan Tao
    I just downloaded the trial version of ANTS Performance Profiler from Red Gate and am investigating some of my team's code. Immediately I notice that there's a particular section of code that ANTS is reporting as eating up to 99% CPU time. I am completely unfamiliar with ANTS or performance profiling in general (that is, aside from self-profiling using what I'm sure are extremely crude and frowned-upon methods such as double timeToComplete = (endTime - startTime).TotalSeconds), so I'm still fiddling around with the application and figuring out how it's used. But I did call the developer responsible for the code in question and his immediate reaction was "Yeah, that doesn't surprise me that it says that; but that code calls SignalAndWait [which I could see for myself, thanks to ANTS], which doesn't use any CPU, it just sits there waiting for something to do." He advised me to simply ignore that code and look for anything ELSE I could find. My question: is it true that SignalAndWait requires NO CPU overhead (and if so, how is this possible?), and is it reasonable that a performance profiler would view it as taking up 99% CPU time? I find this particularly curious because, if it's at 99%, that would suggest that our application is often idle, wouldn't it? And yet its performance has become rather sluggish lately. Like I said, I really am just a beginner when it comes to this tool, and I don't know anything about the WaitHandle class. So ANY information to help me to understand what's going on here would be appreciated.

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  • What is the performance impact of CSS's universal selector?

    - by Bungle
    I'm trying to find some simple client-side performance tweaks in a page that receives millions of monthly pageviews. One concern that I have is the use of the CSS universal selector (*). As an example, consider a very simple HTML document like the following: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <title>Example</title> <style type="text/css"> * { margin: 0; padding: 0; } </head> <body> <h1>This is a heading</h1> <p>This is a paragraph of text.</p> </body> </html> The universal selector will apply the above declaration to the body, h1 and p elements, since those are the only ones in the document. In general, would I see better performance from a rule such as: body, h1, p { margin: 0; padding: 0; } Or would this have exactly the same net effect? Essentially, what I'm asking is if these rules are effectively equivalent in this case, or if the universal selector has to perform more unnecessary work that I may not be aware of. I realize that the performance impact in this example may be very small, but I'm hoping to learn something that may lead to more significant performance improvements in real-world situations. Thanks for any help!

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  • Is there a IDE/compiler PC benchmark I can use to compare my PCs performance?

    - by RickL
    I'm looking for a benchmark (and results on other PCs) which would give me an idea of the development performance gain I could get by upgrading my PC, also the benchmark could be used to justify the upgrade to my boss. I use Visual Studio 2008 for my development, so I'd like to get an idea of by what factor the build times would be improved, and also it would be good if the benchmark could incorporate IDE performance (i.e. when editing, using intellisense, opening code files etc) into its result. I currently have an AMD 3800x2, with 2GB RAM on Vista 32. For example, I'd like to know what kind of performance gain I'd see in Visual Studio 2008 with a Q6600, 4GB RAM on Vista 64. And also with other processors, and other RAM sizes... also see whether hard disk performance is a big factor. EDIT: I mentioned Vista 64 because I'm aware that Vista 32 can only use 3GB RAM maximum. So I'd presume that wanting to use more RAM would require Vista 64, but perhaps it could still be slower overall there is a large overhead in using the 32 bit VS 2008 on 64 bit OS.

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  • Performance of stored proc when updating columns selectively based on parameters?

    - by kprobst
    I'm trying to figure out if this is relatively well-performing T-SQL (this is SQL Server 2008). I need to create a stored procedure that updates a table. The proc accepts as many parameters as there are columns in the table, and with the exception of the PK column, they all default to NULL. The body of the procedure looks like this: CREATE PROCEDURE proc_repo_update @object_id bigint ,@object_name varchar(50) = NULL ,@object_type char(2) = NULL ,@object_weight int = NULL ,@owner_id int = NULL -- ...etc AS BEGIN update object_repo set object_name = ISNULL(@object_name, object_name) ,object_type = ISNULL(@object_type, object_type) ,object_weight = ISNULL(@object_weight, object_weight) ,owner_id = ISNULL(@owner_id, owner_id) -- ...etc where object_id = @object_id return @@ROWCOUNT END So basically: Update a column only if its corresponding parameter was provided, and leave the rest alone. This works well enough, but as the ISNULL call will return the value of the column if the received parameter was null, will SQL Server optimize this somehow? This might be a performance bottleneck on the application where the table might be updated heavily (insertion will be uncommon so the performance there is not a problem). So I'm trying to figure out what's the best way to do this. Is there a way to condition the column expressions with something like CASE WHEN or something? The table will be indexed up the wazoo as well for read performance. Is this the best approach? My alternative at this point is to create the UPDATE expression in code (e.g. inline SQL) and execute it against the server. This would solve my doubts about performance, but I'd rather leave this in a stored proc if possible.

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  • Filtering SQLAlchemy query on attribute_mapped_collection field of relationship

    - by bsa
    I have two classes, Tag and Hardware, defined with a simple parent-child relationship (see the full definition at the end). Now I want to filter a query on Tag using the version field in Hardware through an attribute_mapped_collection, eg: def get_tags(order_code=None, hardware_filters=None): session = Session() query = session.query(Tag) if order_code: query = query.filter(Tag.order_code == order_code) if hardware_filters: for k, v in hardware_filters.iteritems(): query = query.filter(getattr(Tag.hardware, k).version == v) return query.all() But I get: AttributeError: Neither 'InstrumentedAttribute' object nor 'Comparator' object associated with Tag.hardware has an attribute 'baseband The same thing happens if I strip it back by hard-coding the attribute, eg: query.filter(Tag.hardware.baseband.version == v) I can do it this way: query = query.filter(Tag.hardware.any(artefact=k, version=v)) But why can't I filter directly through the attribute? Class definitions class Tag(Base): __tablename__ = 'tag' tag_id = Column(Integer, primary_key=True) order_code = Column(String, nullable=False) version = Column(String, nullable=False) status = Column(String, nullable=False) comments = Column(String) hardware = relationship( "Hardware", backref="tag", collection_class=attribute_mapped_collection('artefact'), ) __table_args__ = ( UniqueConstraint('order_code', 'version'), ) class Hardware(Base): __tablename__ = 'hardware' hardware_id = Column(Integer, primary_key=True) tag_id = Column(String, ForeignKey('tag.tag_id')) product_id = Column(String, nullable=True) artefact = Column(String, nullable=False) version = Column(String, nullable=False)

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  • Please recommend tools for PC, browser, home network performance problems?

    - by mobibob
    My client is experiencing some odd response behavior in their browser for the past few days. Classic, "nothing has changed" so I am starting at ground zero. Browsing a website will timeout or take a ridiculous time to load -- other times, the same site and query is immediately responsive. Once a connection is established, video streams are uninterrupted. The home network hosts a website, but it is not experiencing any activity in Apache's 'access.log' I am using speedtest.net to check if the ISP through the internet is 'OK' -- which looks typical (average +/-). I have to suspect the home network is beaconing or something very abnormal, but I don't know where to start.

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  • Recent improvements in Console Performance

    - by loren.konkus
    Recently, the WebLogic Server development and support organizations have worked with a number of customers to quantify and improve the performance of the Administration Console in large, distributed configurations where there is significant latency in the communications between the administration server and managed servers. These improvements fall into two categories: Constraining the amount of time that the Console stalls waiting for communication Reducing and streamlining the amount of data required for an update A few releases ago, we added support for a configurable domain-wide mbean "Invocation Timeout" value on the Console's configuration: general, advanced section for a domain. The default value for this setting is 0, which means wait indefinitely and was chosen for compatibility with the behavior of previous releases. This configuration setting applies to all mbean communications between the admin server and managed servers, and is the first line of defense against being blocked by a stalled or completely overloaded managed server. Each site should choose an appropriate timeout value for their environment and network latency. In the next release of WebLogic Server, we've added an additional console preference, "Management Operation Timeout", to the Console's shared preference page. This setting further constrains how long certain console pages will wait for slowly responding servers before returning partial results. While not all Console pages support this yet, key pages such as the Servers Configuration and Control table pages and the Deployments Control pages have been updated to support this. For example, if a user requests a Servers Table page and a Management Operation Timeout occurs, the table is displayed with both local configuration and remote runtime information from the responding managed servers and only local configuration information for servers that did not yet respond. This means that a troublesome managed server does not impede your ability to manage your domain using the Console. To support these changes, these Console pages have been re-written to use the Work Management feature of WebLogic Server to interact with each server or deployment concurrently, which further improves the responsiveness of these pages. The basic algorithm for these pages is: For each configuration mbean (ie, Servers) populate rows with configuration attributes from the fast, local mbean server Find a WorkManager For each server, Create a Work instance to obtain runtime mbean attributes for the server Schedule Work instance in the WorkManager Call WorkManager.waitForAll to wait WorkItems to finish, constrained by Management Operation Timeout For each WorkItem, if the runtime information obtained was not complete, add a message indicating which server has incomplete data Display collected data in table In addition to these changes to constrain how long the console waits for communication, a number of other changes have been made to reduce the amount and scope of managed server interactions for key pages. For example, in previous releases the Deployments Control table looked at the status of a deployment on every managed server, even those servers that the deployment was not currently targeted on. (This was done to handle an edge case where a deployment's target configuration was changed while it remained running on previously targeted servers.) We decided supporting that edge case did not warrant the performance impact for all, and instead only look at the status of a deployment on the servers it is targeted to. Comprehensive status continues to be available if a user clicks on the 'status' field for a deployment. Finally, changes have been made to the System Status portlet to reduce its impact on Console page display times. Obtaining health information for this display requires several mbean interactions with managed servers. In previous releases, this mbean interaction occurred with every display, and any delay or impediment in these interactions was reflected in the display time for every page. To reduce this impact, we've made several changes in this portlet: Using Work Management to obtain health concurrently Applying the operation timeout configuration to constrain how long we will wait Caching health information to reduce the cost during rapid navigation from page to page and only obtaining new health information if the previous information is over 30 seconds old. Eliminating heath collection if this portlet is minimized. Together, these Console changes have resulted in significant performance improvements for the customers with large configurations and high latency that we have worked with during their development, and some lesser performance improvements for those with small configurations and very fast networks. These changes will be included in the 11g Rel 1 patch set 2 (10.3.3.0) release of WebLogic Server.

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  • How do I find the cause for a huge difference in performance between two identical Ubuntu servers?

    - by the.duckman
    I am running two Dell R410 servers in the same rack of a data center. Both have the same hardware configuration, run Ubuntu 10.4, have the same packages installed and run the same Java web servers. No other load. One of them is 20-30% faster than the other, very consistently. I used dstat to figure out, if there are more context switches, IO, swapping or anything, but I see no reason for the difference. With the same workload, (no swapping, virtually no IO), the cpu usage and load is higher on one server. So the difference appears to be mainly CPU bound, but while a simple cpu benchmark using sysbench (with all other load turned off) did yield a difference, it was only 6%. So maybe it is not only CPU but also memory performance. I tried to figure out if the BIOS settings differ in some parameter, did a dump using dmidecode, but that yielded no difference. I compared /proc/cpuinfo, no difference. I compared the output of cpufreq-info, no difference. I am lost. What can I do, to figure out, what is going on?

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  • Windows 7 host with Ubuntu Guest and a performance hit, memory locks?

    - by Cyrylski
    I have a brand new Lenovo T510 with Core i5 and 4GB of RAM with Windows 7 on it. I Installed Ubuntu 10.10 in a Virtualbox. For some reason system gets really slow on this setup which makes me really angry. There's a video card shared with full 3D support enabled and 1GB of RAM allocated for the Ubuntu machine. It may sound stupid, but WHY is the whole memory consumed in an instant when I run Virtualbox? I struggled for like 10 minutes restraining myself from a brutal reset, and now everything runs smooth but memory "in use" in Resource Monitor is 3GB flat with only Chrome running. I'm new to Windows 7, but I'm really disappointed with performance at this point... I used to work in a different environment with much slower hardware and there was no such problem (WinXP over Ubuntu, 1GB out of 2GB allocated for WinXP guest on intel GMA). This is, until I clogged RAM totally there. But I was capable of running Chrome, Firefox and Apache server on a 1GB RAM in Ubuntu there and Photoshop CS4 on Windows XP and it worked. In this case I can't go beyond setting up Ubuntu properly. I bet I'm doing something wrong.

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  • Save object states in .data or attr - Performance vs CSS?

    - by Neysor
    In response to my answer yesterday about rotating an Image, Jamund told me to use .data() instead of .attr() First I thought that he is right, but then I thought about a bigger context... Is it always better to use .data() instead of .attr()? I looked in some other posts like what-is-better-data-or-attr or jquery-data-vs-attrdata The answers were not satisfactory for me... So I moved on and edited the example by adding CSS. I thought it might be useful to make a different Style on each image if it rotates. My style was the following: .rp[data-rotate="0"] { border:10px solid #FF0000; } .rp[data-rotate="90"] { border:10px solid #00FF00; } .rp[data-rotate="180"] { border:10px solid #0000FF; } .rp[data-rotate="270"] { border:10px solid #00FF00; } Because design and coding are often separated, it could be a nice feature to handle this in CSS instead of adding this functionality into JavaScript. Also in my case the data-rotate is like a special state which the image currently has. So in my opinion it make sense to represent it within the DOM. I also thought this could be a case where it is much better to save with .attr() then with .data(). Never mentioned before in one of the posts I read. But then i thought about performance. Which function is faster? I built my own test following: <!DOCTYPE HTML> <html> <head> <title>test</title> <script type="text/javascript" src="http://ajax.googleapis.com/ajax/libs/jquery/1.7.1/jquery.min.js"></script> <script type="text/javascript"> function runfirst(dobj,dname){ console.log("runfirst "+dname); console.time(dname+"-attr"); for(i=0;i<10000;i++){ dobj.attr("data-test","a"+i); } console.timeEnd(dname+"-attr"); console.time(dname+"-data"); for(i=0;i<10000;i++){ dobj.data("data-test","a"+i); } console.timeEnd(dname+"-data"); } function runlast(dobj,dname){ console.log("runlast "+dname); console.time(dname+"-data"); for(i=0;i<10000;i++){ dobj.data("data-test","a"+i); } console.timeEnd(dname+"-data"); console.time(dname+"-attr"); for(i=0;i<10000;i++){ dobj.attr("data-test","a"+i); } console.timeEnd(dname+"-attr"); } $().ready(function() { runfirst($("#rp4"),"#rp4"); runfirst($("#rp3"),"#rp3"); runlast($("#rp2"),"#rp2"); runlast($("#rp1"),"#rp1"); }); </script> </head> <body> <div id="rp1">Testdiv 1</div> <div id="rp2" data-test="1">Testdiv 2</div> <div id="rp3">Testdiv 3</div> <div id="rp4" data-test="1">Testdiv 4</div> </body> </html> It should also show if there is a difference with a predefined data-test or not. One result was this: runfirst #rp4 #rp4-attr: 515ms #rp4-data: 268ms runfirst #rp3 #rp3-attr: 505ms #rp3-data: 264ms runlast #rp2 #rp2-data: 260ms #rp2-attr: 521ms runlast #rp1 #rp1-data: 284ms #rp1-attr: 525ms So the .attr() function did always need more time than the .data() function. This is an argument for .data() I thought. Because performance is always an argument! Then I wanted to post my results here with some questions, and in the act of writing I compared with the questions Stack Overflow showed me (similar titles) And true enough, there was one interesting post about performance I read it and run their example. And now I am confused! This test showed that .data() is slower then .attr() !?!! Why is that so? First I thought it is because of a different jQuery library so I edited it and saved the new one. But the result wasn't changing... So now my questions to you: Why are there some differences in the performance in these two examples? Would you prefer to use data- HTML5 attributes instead of data, if it represents a state? Although it wouldn't be needed at the time of coding? Why - Why not? Now depending on the performance: Would performance be an argument for you using .attr() instead of data, if it shows that .attr() is better? Although data is meant to be used for .data()? UPDATE 1: I did see that without overhead .data() is much faster. Misinterpreted the data :) But I'm more interested in my second question. :) Would you prefer to use data- HTML5 attributes instead of data, if it represents a state? Although it wouldn't be needed at the time of coding? Why - Why not? Are there some other reasons you can think of, to use .attr() and not .data()? e.g. interoperability? because .data() is jquery style and HTML Attributes can be read by all... UPDATE 2: As we see from T.J Crowder's speed test in his answer attr is much faster then data! which is again confusing me :) But please! Performance is an argument, but not the highest! So give answers to my other questions please too!

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  • SQL Server Prefetch and Query Performance

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

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  • 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 – Error: Fix – Msg 208 – Invalid object name ‘dbo.backupset’ – Invalid object name ‘dbo.backupfile’

    - by pinaldave
    Just a day before I got a very interesting email. Here is the email (modified a bit to make it relevant to this blog post). “Pinal, We are facing a very strange issue. One of our query  related to backup files and backup set has stopped working suddenly in SSMS. It works fine in application where we have and in the stored procedure but when we have it in our SSMS it gives following error. Msg 208, Level 16, State 1, Line 1 Invalid object name ‘dbo.backupfile’. Here are our queries which we are trying to execute. SELECT name, database_name, backup_size, TYPE, compatibility_level, backup_set_id FROM dbo.backupset; SELECT logical_name, backup_size, file_type FROM dbo.backupfile; This query gives us details related to backupset and backup files when the backup was taken.” When I receive this kind of email, usually I have no answers directly. The claim that it works in stored procedure and in application but not in SSMS gives me no real data. I have requested him to very first check following two things: If he is connected to correct server? His answer was yes. If he has enough permissions? His answer was he was logged in as an admin. This means there was something more to it and I requested him to send me a screenshot of the his SSMS. He promptly sends that to me and as soon as I receive the screen shot I knew what was going on. Before I say anything take a look at the screenshot yourself and see if you can figure out why his queries are not working in SSMS. Just to make your life a bit easy, I have already given a hint in the image. The answer is very simple, the context of the database is master database. To execute above two queries the context of the database has to be msdb. Tables backupset and backupfile belong to the database msdb only. Here are two workaround or solution to above problem: 1) Change context to MSDB Above two queries when they will run as following they will not error out and will give the accurate desired result. USE msdb GO SELECT name, database_name, backup_size, TYPE, compatibility_level, backup_set_id FROM dbo.backupset; SELECT logical_name, backup_size, file_type FROM dbo.backupfile; 2) Prefix the query with msdb There are cases above script used in stored procedure or part of big query, it is not possible to change the context of the whole query to any specific database. Use three part naming convention and prefix them with msdb. SELECT name, database_name, backup_size, TYPE, compatibility_level, backup_set_id FROM msdb.dbo.backupset; SELECT logical_name, backup_size, file_type FROM msdb.dbo.backupfile; Very simple solution but sometime keeps people wondering for an answer. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Error Messages, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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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 – Data Pages in Buffer Pool – Data Stored in Memory Cache

    - by pinaldave
    This will drop all the clean buffers so we will be able to start again from there. Now, run the following script and check the execution plan of the query. Have you ever wondered what types of data are there in your cache? During SQL Server Trainings, I am usually asked if there is any way one can know how much data in a table is stored in the memory cache? The more detailed question I usually get is if there are multiple indexes on table (and used in a query), were the data of the single table stored multiple times in the memory cache or only for a single time? Here is a query you can run to figure out what kind of data is stored in the cache. USE AdventureWorks GO SELECT COUNT(*) AS cached_pages_count, name AS BaseTableName, IndexName, IndexTypeDesc FROM sys.dm_os_buffer_descriptors AS bd INNER JOIN ( SELECT s_obj.name, s_obj.index_id, s_obj.allocation_unit_id, s_obj.OBJECT_ID, i.name IndexName, i.type_desc IndexTypeDesc FROM ( SELECT OBJECT_NAME(OBJECT_ID) AS name, index_id ,allocation_unit_id, OBJECT_ID FROM sys.allocation_units AS au INNER JOIN sys.partitions AS p ON au.container_id = p.hobt_id AND (au.type = 1 OR au.type = 3) UNION ALL SELECT OBJECT_NAME(OBJECT_ID) AS name, index_id, allocation_unit_id, OBJECT_ID FROM sys.allocation_units AS au INNER JOIN sys.partitions AS p ON au.container_id = p.partition_id AND au.type = 2 ) AS s_obj LEFT JOIN sys.indexes i ON i.index_id = s_obj.index_id AND i.OBJECT_ID = s_obj.OBJECT_ID ) AS obj ON bd.allocation_unit_id = obj.allocation_unit_id WHERE database_id = DB_ID() GROUP BY name, index_id, IndexName, IndexTypeDesc ORDER BY cached_pages_count DESC; GO Now let us run the query above and observe the output of the same. We can see in the above query that there are four columns. Cached_Pages_Count lists the pages cached in the memory. BaseTableName lists the original base table from which data pages are cached. IndexName lists the name of the index from which pages are cached. IndexTypeDesc lists the type of index. Now, let us do one more experience here. Please note that you should not run this test on a production server as it can extremely reduce the performance of the database. DBCC DROPCLEANBUFFERS This will drop all the clean buffers and we will be able to start again from there. Now run following script and check the execution plan for the same. USE AdventureWorks GO SELECT UnitPrice, ModifiedDate FROM Sales.SalesOrderDetail WHERE SalesOrderDetailID BETWEEN 1 AND 100 GO The execution plans contain the usage of two different indexes. Now, let us run the script that checks the pages cached in SQL Server. It will give us the following output. It is clear from the Resultset that when more than one index is used, datapages related to both or all of the indexes are stored in Memory Cache separately. Let me know what you think of this article. I had a great pleasure while writing this article because I was able to write on this subject, which I like the most. In the next article, we will exactly see what data are cached and those that are not cached, using a few undocumented commands. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: DMV, Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL DMV

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  • SQLAuthority News – Community Service and Public Speaking Engagements

    - by pinaldave
    Today is the last day of the year and I was going over my memories for year 2010. Almost all of them are good and I feel for sure better person in terms of knowledge, nature and overall human being. Looking back at the year, it is very satisfying as I was able to go out in public and help community out at various capacity. Thought, most of the time my contribution was as speaker, many times, I have reached out and helped organized event and worked at any capacity to get the event out. I have taken parts in many TechEds, PASS events, Virtual Tech Days, Various Community Events around the Globe and my contribution is not limited to my country only. Overall – I feel good to be part of this wonderful and supportive community. SQLAuthority News – A Successful Community TechDays at Ahmedabad – December 11, 2010 SQLAuthority News – A Successful Performance Tuning Seminar at Pune – Dec 4-5, 2010 SQL SERVER – A Successful Performance Tuning Seminar – Hyderabad – Nov 27-28, 2010 – Next Pune SQLAuthority News – SQLPASS Nov 8-11, 2010-Seattle – An Alternative Look at Experience SQLAuthority News – Statistics and Best Practices – Virtual Tech Days – Nov 22, 2010 SQLAuthority News – SQL Server Performance Optimizations Seminar – Grand Success – Colombo, Sri Lanka – Oct 4 – 5, 2010 SQL SERVER – Visiting Alma Mater – Delivering Session on Database Performance and Career – Nirma Institute of Technology SQLAuthority News – Feedback Received for Virtual Tech Days Sessions on Spatial Database SQLAuthority News – Community Tech Days, Ahmedabad – July 24, 2010 SQLAuthority News – SQL Data Camp, Chennai, July 17, 2010 – A Huge Success SQLAuthority News – 2 Sessions at TechInsight 2010 – June 29 – July 1, 2010 SQLAuthority News – Author Visit – SQL Server 2008 R2 Launch SQLAuthority News – Professional Development and Community SQLAuthority News – TechEd India – April 12-14, 2010 Bangalore – An Unforgettable Experience – An Opportunity of A Lifetime SQLAuthority News – Speaking Sessions at TechEd India – 3 Sessions – 1 Panel Discussion SQLAuthority News – Meeting with Allen Bailochan Tuladhar – An Unlimited Experience SQLAuthority News – Author Visit Review – TechMela Nepal – March 29-30, 2010 SQLAuthority News – Excellent Event – TechEd Sri Lanka – Feb 8, 2010 SQLAuthority News – Hyderabad Techies February Fever Feb 11, 2010 – Indexing for Performance SQLAuthority News – MUGH – Microsoft User Group Hyderabad – Feb 2, 2010 Session Review SQLAuthority News – Ahmedabad Community Tech Days – Jan 30, 2010 – Huge Success For earlier year’s contribution you can check my webpage over here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Book Review, SQLAuthority News, T SQL, Technology

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  • Speeding up procedural texture generation

    - by FalconNL
    Recently I've begun working on a game that takes place in a procedurally generated solar system. After a bit of a learning curve (having neither worked with Scala, OpenGL 2 ES or Libgdx before), I have a basic tech demo going where you spin around a single procedurally textured planet: The problem I'm running into is the performance of the texture generation. A quick overview of what I'm doing: a planet is a cube that has been deformed to a sphere. To each side, a n x n (e.g. 256 x 256) texture is applied, which are bundled in one 8n x n texture that is sent to the fragment shader. The last two spaces are not used, they're only there to make sure the width is a power of 2. The texture is currently generated on the CPU, using the updated 2012 version of the simplex noise algorithm linked to in the paper 'Simplex noise demystified'. The scene I'm using to test the algorithm contains two spheres: the planet and the background. Both use a greyscale texture consisting of six octaves of 3D simplex noise, so for example if we choose 128x128 as the texture size there are 128 x 128 x 6 x 2 x 6 = about 1.2 million calls to the noise function. The closest you will get to the planet is about what's shown in the screenshot and since the game's target resolution is 1280x720 that means I'd prefer to use 512x512 textures. Combine that with the fact the actual textures will of course be more complicated than basic noise (There will be a day and night texture, blended in the fragment shader based on sunlight, and a specular mask. I need noise for continents, terrain color variation, clouds, city lights, etc.) and we're looking at something like 512 x 512 x 6 x 3 x 15 = 70 million noise calls for the planet alone. In the final game, there will be activities when traveling between planets, so a wait of 5 or 10 seconds, possibly 20, would be acceptable since I can calculate the texture in the background while traveling, though obviously the faster the better. Getting back to our test scene, performance on my PC isn't too terrible, though still too slow considering the final result is going to be about 60 times worse: 128x128 : 0.1s 256x256 : 0.4s 512x512 : 1.7s This is after I moved all performance-critical code to Java, since trying to do so in Scala was a lot worse. Running this on my phone (a Samsung Galaxy S3), however, produces a more problematic result: 128x128 : 2s 256x256 : 7s 512x512 : 29s Already far too long, and that's not even factoring in the fact that it'll be minutes instead of seconds in the final version. Clearly something needs to be done. Personally, I see a few potential avenues, though I'm not particularly keen on any of them yet: Don't precalculate the textures, but let the fragment shader calculate everything. Probably not feasible, because at one point I had the background as a fullscreen quad with a pixel shader and I got about 1 fps on my phone. Use the GPU to render the texture once, store it and use the stored texture from then on. Upside: might be faster than doing it on the CPU since the GPU is supposed to be faster at floating point calculations. Downside: effects that cannot (easily) be expressed as functions of simplex noise (e.g. gas planet vortices, moon craters, etc.) are a lot more difficult to code in GLSL than in Scala/Java. Calculate a large amount of noise textures and ship them with the application. I'd like to avoid this if at all possible. Lower the resolution. Buys me a 4x performance gain, which isn't really enough plus I lose a lot of quality. Find a faster noise algorithm. If anyone has one I'm all ears, but simplex is already supposed to be faster than perlin. Adopt a pixel art style, allowing for lower resolution textures and fewer noise octaves. While I originally envisioned the game in this style, I've come to prefer the realistic approach. I'm doing something wrong and the performance should already be one or two orders of magnitude better. If this is the case, please let me know. If anyone has any suggestions, tips, workarounds, or other comments regarding this problem I'd love to hear them.

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  • Why do I see a large performance hit with DRBD?

    - by BHS
    I see a much larger performance hit with DRBD than their user manual says I should get. I'm using DRBD 8.3.7 (Fedora 13 RPMs). I've setup a DRBD test and measured throughput of disk and network without DRBD: dd if=/dev/zero of=/data.tmp bs=512M count=1 oflag=direct 536870912 bytes (537 MB) copied, 4.62985 s, 116 MB/s / is a logical volume on the disk I'm testing with, mounted without DRBD iperf: [ 4] 0.0-10.0 sec 1.10 GBytes 941 Mbits/sec According to Throughput overhead expectations, the bottleneck would be whichever is slower, the network or the disk and DRBD should have an overhead of 3%. In my case network and I/O seem to be pretty evenly matched. It sounds like I should be able to get around 100 MB/s. So, with the raw drbd device, I get dd if=/dev/zero of=/dev/drbd2 bs=512M count=1 oflag=direct 536870912 bytes (537 MB) copied, 6.61362 s, 81.2 MB/s which is slower than I would expect. Then, once I format the device with ext4, I get dd if=/dev/zero of=/mnt/data.tmp bs=512M count=1 oflag=direct 536870912 bytes (537 MB) copied, 9.60918 s, 55.9 MB/s This doesn't seem right. There must be some other factor playing into this that I'm not aware of. global_common.conf global { usage-count yes; } common { protocol C; } syncer { al-extents 1801; rate 33M; } data_mirror.res resource data_mirror { device /dev/drbd1; disk /dev/sdb1; meta-disk internal; on cluster1 { address 192.168.33.10:7789; } on cluster2 { address 192.168.33.12:7789; } } For the hardware I have two identical machines: 6 GB RAM Quad core AMD Phenom 3.2Ghz Motherboard SATA controller 7200 RPM 64MB cache 1TB WD drive The network is 1Gb connected via a switch. I know that a direct connection is recommended, but could it make this much of a difference? Edited I just tried monitoring the bandwidth used to try to see what's happening. I used ibmonitor and measured average bandwidth while I ran the dd test 10 times. I got: avg ~450Mbits writing to ext4 avg ~800Mbits writing to raw device It looks like with ext4, drbd is using about half the bandwidth it uses with the raw device so there's a bottleneck that is not the network.

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