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  • how do you manage application performance reviews

    - by CoolBeans
    I have been trying to figure out ways to effectively do performance reviews before an install happens for all releases done by our team. Do you usually make this a part of code review process or do you handle it as a separate review task? FYI - we do not have a dedicated performance testing team. It is up to the developers to make sure the app performs well. The apps I am referring to are web applications.

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  • Tap into MySQL's Amazing Performance Results with the Performance Tuning Course

    - by Antoinette O'Sullivan
    Want to leverage the high-speed load utilities, distinctive memory caches, full text indexes, and other performance-enhancing mechanisms that MySQL offers to fuel today's critical business systems. The authentic MySQL Performance Tuning course, in 4 days, teaches you to evaluate the MySQL architecture, learn to use the tools, configure the database for performance, tune application and SQL code, tune the server, examine the storage engines, assess the application architecture, and learn general tuning concepts. You can take this course in one the following three ways: Training-on-Demand: Access the streaming video, instructor delivery of this course from your own desk, at your own pace. Book time for hands-on practice when it suits you. Live-Virtual Class: Take this instructor-led class live from your own desk. With 700 events on the schedule you are sure to find a time and date to suit you! In-Class: Travel to a classroom to take this class. A sample of events on the schedule are as follows.  Location  Date  Delivery Language  Hamburg, Germany  22 October 2012  German  Prague, Czech Republic  1 October 2012  Czech  Warsaw, Poland  3 December 2012  Polish  London, England  19 November 2012  English  Rome, Italy  23 October 2012  Italian Lisbon, Portugal  6 November 2012  European Portugese  Aix en Provence, France  4 September 2012   French  Strasbourg, France 16 October 2012   French  Nieuwegein, Netherlands 26 November 2012   Dutch  Madrid, Spain 17 December 2012   Spanish  Mechelen, Belgium  1 October 2012  English  Riga, Latvia  10 December 2012  Latvian  Petaling Jaya, Malaysia  10 September 2012 English   Edmonton, Canada 10 December 2012   English  Vancouver, Canada 10 December 2012   English  Ottawa, Canada 26 November 2012   English  Toronto, Canada 26 November 2012   English  Montreal, Canada 26 November 2012   English  Mexico City, Mexico 10 September 2012   Spanish  Sao Paolo, Brazil 26 November 2012  Brazilian Portugese   Tokyo, Japan 19 November 2012   Japanese  Tokyo, Japan  19 November 2012  Japanese For further information on this class, or to register your interest in additional events, go to the Oracle University Portal: http://oracle.com/education/mysql

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  • SQLAuthority News – Three Posts on Reporting – T-SQL Tuesday #005

    - by pinaldave
    If you are following my blog, you already know that I am more of “T-SQL and Performance Tuning” type of person. I do have a good understanding of Business Intelligence suit and I also do certain training sessions on the same subject. When I was writing the blog post for T-SQL Tuesday #005 – Reporting, I realized that I have written a post that clearly explains how to generate reports using SQL Server Management Studio. Here is a quick recap on how one can use SSMS and out-of-the-box reports which can help many developers. Please note that they can be resource-intensive as well, so please use SSMS carefully. SQL SERVER – Generate Report for Index Physical Statistics – SSMS SQL SERVER – Out of the Box – Activity and Performance Reports from SSSMS SQL SERVER – Configure Management Data Collection in Quick Steps – T-SQL Tuesday #005 Junior developers and DBA can use these reports right away and can also start learning and exploring most database performance issues with the help of Sr. DBAs. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Reporting, SQL Reports

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  • SQL SERVER – What is Fill Factor and What is the Best Value for Fill Factor

    - by pinaldave
    Working in performance tuning area, one has to know about Index and Index Maintenance. For any Index the most important property is Fill Factor. Fill factor is the value that determines the percentage of space on each leaf-level page to be filled with data. In an SQL Server, the smallest unit is a page, which is made of  Page with size 8K. Every page can store one or more rows based on the size of the row. The default value of the Fill Factor is 100, which is same as value 0. The default Fill Factor (100 or 0) will allow the SQL Server to fill the leaf-level pages of an index with the maximum numbers of the rows it can fit. There will be no or very little empty space left in the page, when the fill factor is 100. I have written following two article about Fill Factor. What is Fill factor? – Index, Fill Factor and Performance – Part 1 What is the best value for the Fill Factor? – Index, Fill Factor and Performance – Part 2 I strongly encourage read them and provide your feedback. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – 2008 – Unused Index Script – Download

    - by pinaldave
    Download Missing Index Script with Unused Index Script Performance Tuning is quite interesting and Index plays a vital role in it. A proper index can improve the performance and a bad index can hamper the performance. Here is the script from my script bank which I use to identify unused indexes on any database. Please note, if you should not drop all the unused indexes this script suggest. This is just for guidance. You should not create more than 5-10 indexes per table. Additionally, this script sometime does not give accurate information so use your common sense. Any way, the scripts is good starting point. You should pay attention to User Scan, User Lookup and User Update when you are going to drop index. The generic understanding is if this values are all high and User Seek is low, the index needs tuning. The index drop script is also provided in the last column. Download Missing Index Script with Unused Index Script -- Unused Index Script -- Original Author: Pinal Dave (C) 2011 SELECT TOP 25 o.name AS ObjectName , i.name AS IndexName , i.index_id AS IndexID , dm_ius.user_seeks AS UserSeek , dm_ius.user_scans AS UserScans , dm_ius.user_lookups AS UserLookups , dm_ius.user_updates AS UserUpdates , p.TableRows , 'DROP INDEX ' + QUOTENAME(i.name) + ' ON ' + QUOTENAME(s.name) + '.' + QUOTENAME(OBJECT_NAME(dm_ius.OBJECT_ID)) AS 'drop statement' FROM sys.dm_db_index_usage_stats dm_ius INNER JOIN sys.indexes i ON i.index_id = dm_ius.index_id AND dm_ius.OBJECT_ID = i.OBJECT_ID INNER JOIN sys.objects o ON dm_ius.OBJECT_ID = o.OBJECT_ID INNER JOIN sys.schemas s ON o.schema_id = s.schema_id INNER JOIN (SELECT SUM(p.rows) TableRows, p.index_id, p.OBJECT_ID FROM sys.partitions p GROUP BY p.index_id, p.OBJECT_ID) p ON p.index_id = dm_ius.index_id AND dm_ius.OBJECT_ID = p.OBJECT_ID WHERE OBJECTPROPERTY(dm_ius.OBJECT_ID,'IsUserTable') = 1 AND dm_ius.database_id = DB_ID() AND i.type_desc = 'nonclustered' AND i.is_primary_key = 0 AND i.is_unique_constraint = 0 ORDER BY (dm_ius.user_seeks + dm_ius.user_scans + dm_ius.user_lookups) ASC GO Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Download, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – SQL Server Performance: Indexing Basics – SQL in Sixty Seconds #006 – Video

    - by pinaldave
    A DBA’s role is critical, because a production environment has to run 24×7, hence maintenance, trouble shooting, and quick resolutions are the need of the hour.  The first baby step into any performance tuning exercise in SQL Server involves creating, analyzing, and maintaining indexes. Though we have learnt indexing concepts from our college days, indexing implementation inside SQL Server can vary.  Understanding this behavior and designing our applications appropriately will make sure the application is performed to its highest potential. Vinod Kumar and myself we often thought about this and realized that practical understanding of the indexes is very important. One can not master every single aspects of the index. However there are some minimum expertise one should gain if performance is one of the concern. More on Indexes: SQL Index SQL Performance I encourage you to submit your ideas for SQL in Sixty Seconds. We will try to accommodate as many as we can. Here is the interview of Vinod Kumar by myself. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Video

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  • Graphics performance of 945GME

    - by l0b0
    Edit: Since setting Appearance - Visual Effects up to a stunning "Normal", I now get ~35 FPS in glxgears right after login, with nothing else running :( I'm getting terrible graphics performance in NeverWinter Nights (native with SoU+HotU+CEP2) on my Eee PC 1005HAB. Even with all graphics settings (including the "advanced" ones) at minimum I get about 2-10 FPS, depending on the scene. Firefox is really sluggish as well - Changing tabs often takes a second, scrolling is laggy, and typing this I notice the delay between pressing keys and seeing the text on screen. The rest of the OS is running OK, although general performance seems to be even worse than my old Eee PC 900. glxgears gives about 60 FPS, which is apparently as it should be (synchronized with the monitor refresh rate). Bugs like Launchpad #252094 and the instructions for Reverting the Jaunty Xorg intel driver to 2.4 are old enough that I'm afraid following the instructions would render the system unusable. Are there any tips for improving graphics performance on this system that are still relevant for 10.10? $ uname -a Linux l0b0eee 2.6.35-28-generic #49-Ubuntu SMP Tue Mar 1 14:40:58 UTC 2011 i686 GNU/Linux $ lspci -nn | grep VGA 00:02.0 VGA compatible controller [0300]: Intel Corporation Mobile 945GME Express Integrated Graphics Controller [8086:27ae] (rev 03) $ glxinfo name of display: :0.0 display: :0 screen: 0 direct rendering: Yes server glx vendor string: SGI server glx version string: 1.4 ...

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  • Bad 3D Performance in Ubuntu 12.04

    - by Pandem
    I already posted a question before but I didn't really get any advice/help. I'll be a bit more brief/general in hope it'll help. I have an MSI HD 7850 with the Catalyst 12.4 drivers installed. I've found that I'm having bad 3D performance for some reason but I'm not entirely sure what. I suspect it may just that the graphics card is new and AMD just need to work on their drivers but it would be nice to get advice and narrow the problem down so that I can be sure rather than wait for driver updates that may not even help. I ran gxlgears to give some general idea of how bad the performance is. At default size it is averaging around 2000 FPS. The command glxinfo confirms the renderer is using AMD Radeon HD 7800 Series with OpenGL version 4.2. Edits below: As asked for others: lspci -v output is here. fglrxinfo output is here xvinfo output is here glxinfo | grep rendering says yes for direct rendering. These confirmed that everything was configured correctly. Within Unity and Gnome Classic: glxgears had an FPS of around 2000 FPS fgl_glxgears had an FPS of around 544 FPS Within LDXE: glxgears had an FPS of around 4600 FPS fgl_glxgears had an FPS of around 1600 FPS In the end it was discovered that Compiz was causing a large performance decrease and solution was simply to change window manager for the time being. Thanks to TechZilla for all his help!

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  • MERGE Bug with Filtered Indexes

    - by Paul White
    A MERGE statement can fail, and incorrectly report a unique key violation when: The target table uses a unique filtered index; and No key column of the filtered index is updated; and A column from the filtering condition is updated; and Transient key violations are possible Example Tables Say we have two tables, one that is the target of a MERGE statement, and another that contains updates to be applied to the target.  The target table contains three columns, an integer primary key, a single character alternate key, and a status code column.  A filtered unique index exists on the alternate key, but is only enforced where the status code is ‘a’: CREATE TABLE #Target ( pk integer NOT NULL, ak character(1) NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) );   CREATE UNIQUE INDEX uq1 ON #Target (ak) INCLUDE (status_code) WHERE status_code = 'a'; The changes table contains just an integer primary key (to identify the target row to change) and the new status code: CREATE TABLE #Changes ( pk integer NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) ); Sample Data The sample data for the example is: INSERT #Target (pk, ak, status_code) VALUES (1, 'A', 'a'), (2, 'B', 'a'), (3, 'C', 'a'), (4, 'A', 'd');   INSERT #Changes (pk, status_code) VALUES (1, 'd'), (4, 'a');          Target                     Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ a           ¦    ¦  1 ¦ d           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ d           ¦ +-----------------------+ The target table’s alternate key (ak) column is unique, for rows where status_code = ‘a’.  Applying the changes to the target will change row 1 from status ‘a’ to status ‘d’, and row 4 from status ‘d’ to status ‘a’.  The result of applying all the changes will still satisfy the filtered unique index, because the ‘A’ in row 1 will be deleted from the index and the ‘A’ in row 4 will be added. Merge Test One Let’s now execute a MERGE statement to apply the changes: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; The MERGE changes the two target rows as expected.  The updated target table now contains: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦ <—changed from ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦ <—changed from ‘d’ +-----------------------+ Merge Test Two Now let’s repopulate the changes table to reverse the updates we just performed: TRUNCATE TABLE #Changes;   INSERT #Changes (pk, status_code) VALUES (1, 'a'), (4, 'd'); This will change row 1 back to status ‘a’ and row 4 back to status ‘d’.  As a reminder, the current state of the tables is:          Target                        Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ d           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ a           ¦ +-----------------------+ We execute the same MERGE statement: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; However this time we receive the following message: Msg 2601, Level 14, State 1, Line 1 Cannot insert duplicate key row in object 'dbo.#Target' with unique index 'uq1'. The duplicate key value is (A). The statement has been terminated. Applying the changes using UPDATE Let’s now rewrite the MERGE to use UPDATE instead: UPDATE t SET status_code = c.status_code FROM #Target AS t JOIN #Changes AS c ON t.pk = c.pk WHERE c.status_code <> t.status_code; This query succeeds where the MERGE failed.  The two rows are updated as expected: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ a           ¦ <—changed back to ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ d           ¦ <—changed back to ‘d’ +-----------------------+ What went wrong with the MERGE? In this test, the MERGE query execution happens to apply the changes in the order of the ‘pk’ column. In test one, this was not a problem: row 1 is removed from the unique filtered index by changing status_code from ‘a’ to ‘d’ before row 4 is added.  At no point does the table contain two rows where ak = ‘A’ and status_code = ‘a’. In test two, however, the first change was to change row 1 from status ‘d’ to status ‘a’.  This change means there would be two rows in the filtered unique index where ak = ‘A’ (both row 1 and row 4 meet the index filtering criteria ‘status_code = a’). The storage engine does not allow the query processor to violate a unique key (unless IGNORE_DUP_KEY is ON, but that is a different story, and doesn’t apply to MERGE in any case).  This strict rule applies regardless of the fact that if all changes were applied, there would be no unique key violation (row 4 would eventually be changed from ‘a’ to ‘d’, removing it from the filtered unique index, and resolving the key violation). Why it went wrong The query optimizer usually detects when this sort of temporary uniqueness violation could occur, and builds a plan that avoids the issue.  I wrote about this a couple of years ago in my post Beware Sneaky Reads with Unique Indexes (you can read more about the details on pages 495-497 of Microsoft SQL Server 2008 Internals or in Craig Freedman’s blog post on maintaining unique indexes).  To summarize though, the optimizer introduces Split, Filter, Sort, and Collapse operators into the query plan to: Split each row update into delete followed by an inserts Filter out rows that would not change the index (due to the filter on the index, or a non-updating update) Sort the resulting stream by index key, with deletes before inserts Collapse delete/insert pairs on the same index key back into an update The effect of all this is that only net changes are applied to an index (as one or more insert, update, and/or delete operations).  In this case, the net effect is a single update of the filtered unique index: changing the row for ak = ‘A’ from pk = 4 to pk = 1.  In case that is less than 100% clear, let’s look at the operation in test two again:          Target                     Changes                   Result +-----------------------+    +------------------+    +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦    ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦    ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ d           ¦    ¦  1 ¦ A  ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦    ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+    ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦                            ¦  4 ¦ A  ¦ d           ¦ +-----------------------+                            +-----------------------+ From the filtered index’s point of view (filtered for status_code = ‘a’ and shown in nonclustered index key order) the overall effect of the query is:   Before           After +---------+    +---------+ ¦ pk ¦ ak ¦    ¦ pk ¦ ak ¦ ¦----+----¦    ¦----+----¦ ¦  4 ¦ A  ¦    ¦  1 ¦ A  ¦ ¦  2 ¦ B  ¦    ¦  2 ¦ B  ¦ ¦  3 ¦ C  ¦    ¦  3 ¦ C  ¦ +---------+    +---------+ The single net change there is a change of pk from 4 to 1 for the nonclustered index entry ak = ‘A’.  This is the magic performed by the split, sort, and collapse.  Notice in particular how the original changes to the index key (on the ‘ak’ column) have been transformed into an update of a non-key column (pk is included in the nonclustered index).  By not updating any nonclustered index keys, we are guaranteed to avoid transient key violations. The Execution Plans The estimated MERGE execution plan that produces the incorrect key-violation error looks like this (click to enlarge in a new window): The successful UPDATE execution plan is (click to enlarge in a new window): The MERGE execution plan is a narrow (per-row) update.  The single Clustered Index Merge operator maintains both the clustered index and the filtered nonclustered index.  The UPDATE plan is a wide (per-index) update.  The clustered index is maintained first, then the Split, Filter, Sort, Collapse sequence is applied before the nonclustered index is separately maintained. There is always a wide update plan for any query that modifies the database. The narrow form is a performance optimization where the number of rows is expected to be relatively small, and is not available for all operations.  One of the operations that should disallow a narrow plan is maintaining a unique index where intermediate key violations could occur. Workarounds The MERGE can be made to work (producing a wide update plan with split, sort, and collapse) by: Adding all columns referenced in the filtered index’s WHERE clause to the index key (INCLUDE is not sufficient); or Executing the query with trace flag 8790 set e.g. OPTION (QUERYTRACEON 8790). Undocumented trace flag 8790 forces a wide update plan for any data-changing query (remember that a wide update plan is always possible).  Either change will produce a successfully-executing wide update plan for the MERGE that failed previously. Conclusion The optimizer fails to spot the possibility of transient unique key violations with MERGE under the conditions listed at the start of this post.  It incorrectly chooses a narrow plan for the MERGE, which cannot provide the protection of a split/sort/collapse sequence for the nonclustered index maintenance. The MERGE plan may fail at execution time depending on the order in which rows are processed, and the distribution of data in the database.  Worse, a previously solid MERGE query may suddenly start to fail unpredictably if a filtered unique index is added to the merge target table at any point. Connect bug filed here Tests performed on SQL Server 2012 SP1 CUI (build 11.0.3321) x64 Developer Edition © 2012 Paul White – All Rights Reserved Twitter: @SQL_Kiwi Email: [email protected]

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  • DNS Query.log - Multiple query’s for ripe.net

    - by Christopher Wilson
    Currently I run a DNS server (bind9) that handles queries from clients over the internet lately I have noticed hundreds of queries from all different address's that look like this (Server IP removed) client 216.59.33.210#53: query: ripe.net IN ANY +ED (0.0.0.0) client 216.59.33.204#53: query: ripe.net IN ANY +ED (0.0.0.0) client 208.64.127.5#53: query: ripe.net IN ANY +ED (0.0.0.0) client 184.107.255.202#53: query: ripe.net IN ANY +ED (0.0.0.0) client 208.64.127.5#53: query: ripe.net IN ANY +ED (0.0.0.0) client 208.64.127.5#53: query: ripe.net IN ANY +ED (0.0.0.0) client 205.204.65.83#53: query: ripe.net IN ANY +ED (0.0.0.0) client 69.162.110.106#53: query: ripe.net IN ANY +ED (0.0.0.0) client 216.59.33.210#53: query: ripe.net IN ANY +ED (0.0.0.0) client 69.162.110.106#53: query: ripe.net IN ANY +ED (0.0.0.0) client 216.59.33.204#53: query: ripe.net IN ANY +ED (0.0.0.0) client 208.64.127.5#53: query: ripe.net IN ANY +ED (0.0.0.0) Can someone please explain why there are so many clients querying for ripe.net ?

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  • Understanding MySQL Query Caches and when to implement it?

    - by Jeff
    On our current MySQL server query cache is enabled. Qchache_hits: 31913 Qchache_inserts: 50959 Qchache_lowmem_prunes: 9320 Qchache_not_chached: 209320 Qchache_queries_in_chace: 986 com_update: 0 com_delete: 0 I do not fully understand the Query cache - I am reading about it currently and trying to understand it. Our database holds inventory data, customer data, employee data, sales data and so forth. The query is very rarely run more than once. The possibility of a query being run twice is viewing a specific sales information twice. But basically everything in our system changes constantly. It is always being updated, deleted, insterted and off the top of my head I can't picture users running the same query twice within a week. Do I even need to have the query cache enabled? I am guessing that the inserts means 51k entries have been added, but only 986 of those are being stored? Would an idea be to refresh the cache, and watch it for a week and check how many of the queries in cached are accessed maybe on a weekly basis to see if it is actually returning any benefits? Any help/guidance on this is appreciated, thanks

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  • SQL query performance optimization (TimesTen)

    - by Sergey Mikhanov
    Hi community, I need some help with TimesTen DB query optimization. I made some measures with Java profiler and found the code section that takes most of the time (this code section executes the SQL query). What is strange that this query becomes expensive only for some specific input data. Here’s the example. We have two tables that we are querying, one represents the objects we want to fetch (T_PROFILEGROUP), another represents the many-to-many link from some other table (T_PROFILECONTEXT_PROFILEGROUPS). We are not querying linked table. These are the queries that I executed with DB profiler running (they are the same except for the ID): Command> select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; < 1169655247309537280 > < 1169655249792565248 > < 1464837997699399681 > 3 rows found. Command> select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1466585677823868928; < 1169655247309537280 > 1 row found. This is what I have in the profiler: 12:14:31.147 1 SQL 2L 6C 10825P Preparing: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272 12:14:31.147 2 SQL 4L 6C 10825P sbSqlCmdCompile ()(E): (Found already compiled version: refCount:01, bucket:47) cmdType:100, cmdNum:1146695. 12:14:31.147 3 SQL 4L 6C 10825P Opening: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; 12:14:31.147 4 SQL 4L 6C 10825P Fetching: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; 12:14:31.148 5 SQL 4L 6C 10825P Fetching: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; 12:14:31.148 6 SQL 4L 6C 10825P Fetching: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; 12:14:31.228 7 SQL 4L 6C 10825P Fetching: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; 12:14:31.228 8 SQL 4L 6C 10825P Closing: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1464837998949302272; 12:14:35.243 9 SQL 2L 6C 10825P Preparing: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1466585677823868928 12:14:35.243 10 SQL 4L 6C 10825P sbSqlCmdCompile ()(E): (Found already compiled version: refCount:01, bucket:44) cmdType:100, cmdNum:1146697. 12:14:35.243 11 SQL 4L 6C 10825P Opening: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1466585677823868928; 12:14:35.243 12 SQL 4L 6C 10825P Fetching: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1466585677823868928; 12:14:35.243 13 SQL 4L 6C 10825P Fetching: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1466585677823868928; 12:14:35.243 14 SQL 4L 6C 10825P Closing: select G.M_ID from T_PROFILECONTEXT_PROFILEGROUPS CG, T_PROFILEGROUP G where CG.M_ID_EID = G.M_ID and CG.M_ID_OID = 1466585677823868928; It’s clear that the first query took almost 100ms, while the second was executed instantly. It’s not about queries precompilation (the first one is precompiled too, as same queries happened earlier). We have DB indices for all columns used here: T_PROFILEGROUP.M_ID, T_PROFILECONTEXT_PROFILEGROUPS.M_ID_OID and T_PROFILECONTEXT_PROFILEGROUPS.M_ID_EID. My questions are: Why querying the same set of tables yields such a different performance for different parameters? Which indices are involved here? Is there any way to improve this simple query and/or the DB to make it faster? UPDATE: to give the feeling of size: Command> select count(*) from T_PROFILEGROUP; < 183840 > 1 row found. Command> select count(*) from T_PROFILECONTEXT_PROFILEGROUPS; < 2279104 > 1 row found.

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  • Increase application performance

    - by Prayos
    I'm writing a program for a company that will generate a daily report for them. All of the data that they use for this report is stored in a local SQLite database. For this report, the utilize pretty much every bit of the information in the database. So currently, when I query the datbase, I retrieve everything, and store the information in lists. Here's what I've got: using (var dataReader = _connection.Select(query)) { if (dataReader.HasRows) { while (dataReader.Read()) { _date.Add(Convert.ToDateTime(dataReader["date"])); _measured.Add(Convert.ToDouble(dataReader["measured_dist"])); _bit.Add(Convert.ToDouble(dataReader["bit_loc"])); _psi.Add(Convert.ToDouble(dataReader["pump_press"])); _time.Add(Convert.ToDateTime(dataReader["timestamp"])); _fob.Add(Convert.ToDouble(dataReader["force_on_bit"])); _torque.Add(Convert.ToDouble(dataReader["torque"])); _rpm.Add(Convert.ToDouble(dataReader["rpm"])); _pumpOneSpm.Add(Convert.ToDouble(dataReader["pump_1_strokes_pm"])); _pumpTwoSpm.Add(Convert.ToDouble(dataReader["pump_2_strokes_pm"])); _pullForce.Add(Convert.ToDouble(dataReader["pull_force"])); _gpm.Add(Convert.ToDouble(dataReader["flow"])); } } } I then utilize these lists for the calculations. Obviously, the more information that is in this database, the longer the initial query will take. I'm curious if there is a way to increase the performance of the query at all? Thanks for any and all help. EDIT One of the report rows is called Daily Drilling Hours. For this calculation, I use this method: // Retrieves the timestamps where measured depth == bit depth and PSI >= 50 public double CalculateDailyProjectDrillingHours(DateTime date) { var dailyTimeStamps = _time.Where((t, i) => _date[i].Equals(date) && _measured[i].Equals(_bit[i]) && _psi[i] >= 50).ToList(); return _dailyDrillingHours = Convert.ToDouble(Math.Round(TimeCalculations(dailyTimeStamps).TotalHours, 2, MidpointRounding.AwayFromZero)); } // Checks that the interval is less than 10, then adds the interval to the total time private static TimeSpan TimeCalculations(IList<DateTime> timeStamps) { var interval = new TimeSpan(0, 0, 10); var totalTime = new TimeSpan(); TimeSpan timeDifference; for (var j = 0; j < timeStamps.Count - 1; j++) { if (timeStamps[j + 1].Subtract(timeStamps[j]) <= interval) { timeDifference = timeStamps[j + 1].Subtract(timeStamps[j]); totalTime = totalTime.Add(timeDifference); } } return totalTime; }

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  • Monitoring disk performance with MRTG

    - by Ghostrider
    I use MRTG to monitor vital stats on my servers like disk space, CPU load, memory usage, temperatures etc. It all works fine and well for parameters that don't change rapidly. By running small VB script I can also get any Performance Counter. However these scripts are called by MRTG every 5 minutes while performance counters like physical disk idle time return a snapshot value from previous few seconds so a lot or data is missed. Surely I could write a service that would poll all required counters in background and store average values somewhere on disk where MRTG would pick them up. However before I do so I would like to find out if there is some ready solution that would allow me to get average value of some counter for the last 5 minutes as opposed to immediate snapshot.

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  • Performance analysis strategies

    - by Bernd
    I am assigned to a performance-tuning-debugging-troubleshooting task. Scenario: a multi-application environment running on several networked machines using databases. OS is Unix, DB is Oracle. Business logic is implemented across applications using synchronous/asynchronous communication. Applications are multi-user with several hundred call center users at peak time. User interfaces are web-based. Applications are third party, I can get access to developers and source code. I only have the production system and a functional test environment, no load test environment. Problem: bad performance! I need fast results. Management is going crazy. I got symptom examples like these: user interface actions taking minutes to complete. Seaching for a customer usually takes 6 seconds but an immediate subsequent search with same parameters may take 6 minutes. What would be your strategy for finding root causes?

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  • Testing performance of queries in mysl

    - by Unreason
    I am trying to setup a script that would test performance of queries on a development mysql server. Here are more details: I have root access I am the only user accessing the server Mostly interested in InnoDB performance The queries I am optimizing are mostly search queries (SELECT ... LIKE '%xy%') What I want to do is to create reliable testing environment for measuring the speed of a single query, free from dependencies on other variables. Till now I have been using SQL_NO_CACHE, but sometimes the results of such tests also show caching behaviour - taking much longer to execute on the first run and taking less time on subsequent runs. If someone can explain this behaviour in full detail I might stick to using SQL_NO_CACHE; I do believe that it might be due to file system cache and/or caching of indexes used to execute the query, as this post explains. It is not clear to me when Buffer Pool and Key Buffer get invalidated or how they might interfere with testing. So, short of restarting mysql server, how would you recommend to setup an environment that would be reliable in determining if one query performs better then the other?

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  • Best way to handle MySQL date for performance with thousands of users

    - by bitLost
    I am currently part of a team designing a site that will potentially have thousands of users who will be doing a number of date related searches. During the design phase we have been trying to determine which makes more sense for performance optimization. Should we store the datetime field as a mysql datetime. Or should be break it up into a number of fields (year, month, day, hour, minute, ...) The question is with a large data set and a potentially large set of users, would we gain performance wise breaking the datetime into multiple fields and saving on relying on mysql date functions? Or is mysql already optimized for this?

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  • SQL SERVER – Four Posts on Removing the Bookmark Lookup – Key Lookup

    - by pinaldave
    In recent times I have observed that not many people have proper understanding of what is bookmark lookup or key lookup. Increasing numbers of the questions tells me that this is something developers are encountering every single day but have no idea how to deal with it. I have previously written three articles on this subject. I want to point all of you looking for further information on the same post. SQL SERVER – Query Optimization – Remove Bookmark Lookup – Remove RID Lookup – Remove Key Lookup SQL SERVER – Query Optimization – Remove Bookmark Lookup – Remove RID Lookup – Remove Key Lookup – Part 2 SQL SERVER – Query Optimization – Remove Bookmark Lookup – Remove RID Lookup – Remove Key Lookup – Part 3 SQL SERVER – Interesting Observation – Execution Plan and Results of Aggregate Concatenation Queries In one of my recent class we had in depth conversation about what are the alternative of creating covering indexes to remove the bookmark lookup. I really want to this question open to all of you and see what community thinks about the same. Is there any other way then creating covering index or included index to remove his expensive keylookup? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Backup and Restore, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLAuthority News, SQLServer, T SQL, Technology

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  • SQLAuthority News – Download Whitepaper – Understanding and Controlling Parallel Query Processing in SQL Server

    - by pinaldave
    My recently article SQL SERVER – Reducing CXPACKET Wait Stats for High Transactional Database has received many good comments regarding MAXDOP 1 and MAXDOP 0. I really enjoyed reading the comments as the comments are received from industry leaders and gurus. I was further researching on the subject and I end up on following white paper written by Microsoft. Understanding and Controlling Parallel Query Processing in SQL Server Data warehousing and general reporting applications tend to be CPU intensive because they need to read and process a large number of rows. To facilitate quick data processing for queries that touch a large amount of data, Microsoft SQL Server exploits the power of multiple logical processors to provide parallel query processing operations such as parallel scans. Through extensive testing, we have learned that, for most large queries that are executed in a parallel fashion, SQL Server can deliver linear or nearly linear response time speedup as the number of logical processors increases. However, some queries in high parallelism scenarios perform suboptimally. There are also some parallelism issues that can occur in a multi-user parallel query workload. This white paper describes parallel performance problems you might encounter when you run such queries and workloads, and it explains why these issues occur. In addition, it presents how data warehouse developers can detect these issues, and how they can work around them or mitigate them. To review the document, please download the Understanding and Controlling Parallel Query Processing in SQL Server Word document. Note: Above abstract has been taken from here. The real question is what does the parallel queries has made life of DBA much simpler or is it looked at with potential issue related to degradation of the performance? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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  • Practical Performance Monitoring and Tuning Event

    - by Andrew Kelly
      For any of you who may be interested or know of someone in the market for a performance Monitoring and Tuning class I have just the ticket for you. It’s a 3 day event that will be held in Atlanta Ga. on January 25th to the 27th 2011. For those of you that know me or have been to my sessions you realize I like to provide more than just classroom theory and like to teach real world and above all practical methodology when it comes to performance in SQL Server. This class covers all the essentials...(read more)

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • How to achieve best performance in DirectX 9.0 while rendering on multiple monitors

    - by Vibhore Tanwer
    I am new to DirectX, and trying to learn best practice. Please suggest what are the best practices for rendering on multiple monitors different things at the same time? how can I boost performance of application? I have gone through this article http://msdn.microsoft.com/en-us/library/windows/desktop/bb147263%28v=vs.85%29.aspx . I am making use of some pixel shaders to achieve some effects. At most 4 effect(4 shader effects) can be applied at same time. What are the best practices to achieve best performance with DirectX 9.0. I read somewhere that DirectX 11 provides support for parallel rendering, but I am not able to get any working sample for DirectX 11.0. Please help me with this, Any help would be of great value. Thanks

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  • Will JVisualVM degrade application performance?

    - by rocky
    I have doubts in JVisual VM profiler tool related to performance. I have requirement to implement a JVM Monitoring tool for my enterpise java application. I have gone through some profiling tools in market but all them are having some kind of agent file which we need include in server startup. I have a fear that these client agent will degrade my application performance will more. So I have decided to JVisual VM because this profiler tool comes with JDK itself but before implementing JVisualVM, does anybody faces any issues with JVisualVM profiler tool? As well as, is this safe if I implement in application?

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  • SQL SERVER – Quiz and Video – Introduction to Hierarchical Query using a Recursive CTE

    - by pinaldave
    This blog post is inspired from SQL Queries Joes 2 Pros: SQL Query Techniques For Microsoft SQL Server 2008 – SQL Exam Prep Series 70-433 – Volume 2.[Amazon] | [Flipkart] | [Kindle] | [IndiaPlaza] This is follow up blog post of my earlier blog post on the same subject - SQL SERVER – Introduction to Hierarchical Query using a Recursive CTE – A Primer. In the article we discussed various basics terminology of the CTE. The article further covers following important concepts of common table expression. What is a Common Table Expression (CTE) Building a Recursive CTE Identify the Anchor and Recursive Query Add the Anchor and Recursive query to a CTE Add an expression to track hierarchical level Add a self-referencing INNER JOIN statement Above six are the most important concepts related to CTE and SQL Server.  There are many more things one has to learn but without beginners fundamentals one can’t learn the advanced  concepts. Let us have small quiz and check how many of you get the fundamentals right. Quiz 1) You have an employee table with the following data. EmpID FirstName LastName MgrID 1 David Kennson 11 2 Eric Bender 11 3 Lisa Kendall 4 4 David Lonning 11 5 John Marshbank 4 6 James Newton 3 7 Sally Smith NULL You need to write a recursive CTE that shows the EmpID, FirstName, LastName, MgrID, and employee level. The CEO should be listed at Level 1. All people who work for the CEO will be listed at Level 2. All of the people who work for those people will be listed at Level 3. Which CTE code will achieve this result? WITH EmpList AS (SELECT Boss.EmpID, Boss.FName, Boss.LName, Boss.MgrID, 1 AS Lvl FROM Employee AS Boss WHERE Boss.MgrID IS NULL UNION ALL SELECT E.EmpID, E.FirstName, E.LastName, E.MgrID, EmpList.Lvl + 1 FROM Employee AS E INNER JOIN EmpList ON E.MgrID = EmpList.EmpID) SELECT * FROM EmpList WITH EmpListAS (SELECT EmpID, FirstName, LastName, MgrID, 1 as Lvl FROM Employee WHERE MgrID IS NULL UNION ALL SELECT EmpID, FirstName, LastName, MgrID, 2 as Lvl ) SELECT * FROM BossList WITH EmpList AS (SELECT EmpID, FirstName, LastName, MgrID, 1 as Lvl FROM Employee WHERE MgrID is NOT NULL UNION SELECT EmpID, FirstName, LastName, MgrID, BossList.Lvl + 1 FROM Employee INNER JOIN EmpList BossList ON Employee.MgrID = BossList.EmpID) SELECT * FROM EmpList 2) You have a table named Employee. The EmployeeID of each employee’s manager is in the ManagerID column. You need to write a recursive query that produces a list of employees and their manager. The query must also include the employee’s level in the hierarchy. You write the following code segment: WITH EmployeeList (EmployeeID, FullName, ManagerName, Level) AS ( –PICK ANSWER CODE HERE ) SELECT EmployeeID, FullName, ” AS [ManagerID], 1 AS [Level] FROM Employee WHERE ManagerID IS NULL UNION ALL SELECT emp.EmployeeID, emp.FullName mgr.FullName, 1 + 1 AS [Level] FROM Employee emp JOIN Employee mgr ON emp.ManagerID = mgr.EmployeeId SELECT EmployeeID, FullName, ” AS [ManagerID], 1 AS [Level] FROM Employee WHERE ManagerID IS NULL UNION ALL SELECT emp.EmployeeID, emp.FullName, mgr.FullName, mgr.Level + 1 FROM EmployeeList mgr JOIN Employee emp ON emp.ManagerID = mgr.EmployeeId Now make sure that you write down all the answers on the piece of paper. Watch following video and read earlier article over here. If you want to change the answer you still have chance. Solution 1) 1 2) 2 Now compare let us check the answers and compare your answers to following answers. I am very confident you will get them correct. Available at USA: Amazon India: Flipkart | IndiaPlaza Volume: 1, 2, 3, 4, 5 Please leave your feedback in the comment area for the quiz and video. Did you know all the answers of the quiz? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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