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  • SQL Server Training in the UK–SSIS, MDX, Admin, MDS, Internals

    - by simonsabin
    If you are looking for SQL Server training they there is no better place to start than a new company Technitrain Its been setup by a fellow MVP and SQLBits Organiser Chris Webb. Why this company rather than any others? Training based on real world experience by the best in the business. The key to Technitrain’s model is not to cram the shelves high with courses and get some average Joe trainers to deliver them. Technitrain bring in world renowned experts in their fields to deliver courses written...(read more)

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  • Just when you thought it was safe..........

    - by GrumpyOldDBA
    One of my duties is to handle software releases to our Production system, as is my want I always run my eye down any schema changes, this new object stood out for a number of reasons. I may add this to my interview questions: SET ANSI_NULLS ON SET QUOTED_IDENTIFIER ON GO IF NOT EXISTS ( SELECT 1 FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_SCHEMA= 'dbo' AND TABLE_NAME= 'MSPaymentForExtraction' ) BEGIN CREATE TABLE [dbo].[MSPaymentForExtraction]([MSPaymentID] [ int ] NOT NULL IDENTITY...(read more)

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  • OBIEE 11.1.1 - How to enable HTTP compression and caching in Oracle iPlanet Web Server

    - by Ahmed Awan
    1. To implement HTTP compression / caching, install and configure Oracle iPlanet Web Server 7.0.x for the bi_serverN Managed Servers (refer to document http://docs.oracle.com/cd/E23943_01/web.1111/e16435/iplanet.htm) 2. On the Oracle iPlanet Web Server machine, open the file Administrator's Configuration (obj.conf) for editing. (Guidelines for modifying the obj.conf file is available at http://download.oracle.com/docs/cd/E19146-01/821-1827/821-1827.pdf) 3. Add the following lines in obj.conf file inside <Object name="default"> . </Object> and restart the Oracle iPlanet Web Server machine: #HTTP Caching <If $path =~ '^(.*)\.(jpg|jpeg|gif|png|css|js)$'> ObjectType fn="set-variable" insert-srvhdrs="Expires:$(httpdate($time + 864000))" </If>   <If $path =~ '^(.*)\.(jpg|jpeg|gif|png|css|js)$'> PathCheck fn="set-cache-control" control="public,max-age=864000" </If>   #HTTP Compression   Output fn="insert-filter" filter="http-compression" vary="false" compression-level="9" fragment_size="8096"

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  • EPM Planning 11.1.2 - MassGridStatistics

    - by Keith Rosenthal
    A utility is available for Oracle Hyperion Planning that determines web form load times.  This utility, MassGridStatistics, opens all web forms within the Planning application.  After the forms are opened, an html page will appear showing the form options, suppression, number of row column and page members, and load times.  Any form having a load time longer than one second could potentially have scalability issues in a multi-user environment and should be considered for re-design.  Adding suppression (especially block suppression) and reducing the number of rows and columns are potential fixes that will reduce load times. The MassGridStatistics utility is located in a .7z file called MassGridStatistics.7z.  Extract the file using 7-Zip.  A readme file is provided listing the installation instructions and the steps to run the utility. MassGridStatistics is included with the 11.1.2.1.101 patch set and will also be in all future releases starting with 11.1.2.2.  For earlier Planning releases, an SR will be necessary to have Support provide the utility.

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  • HPCM 11.1.2.2.x - HPCM Standard Costing Generating >99 Calc Scipts

    - by Jane Story
    HPCM Standard Profitability calculation scripts are named based on a documented naming convention. From 11.1.2.2.x, the script name = a script suffix (1 letter) + POV identifier (3 digits) + Stage Order Number (1 digit) + “_” + index (2 digits) (please see documentation for more information (http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_admin/apes01.html). This naming convention results in the name being 8 characters in length i.e. the maximum number of characters permitted calculation script names in non-unicode Essbase BSO databases. The index in the name will indicate the number of scripts per stage. In the vast majority of cases, the number of scripts generated per stage will be significantly less than 100 and therefore, there will be no issue. However, in some cases, the number of scripts generated can exceed 99. It is unusual for an application to generate more than 99 calculation scripts for one stage. This may indicate that explicit assignments are being extensively used. An assessment should be made of the design to see if assignment rules can be used instead. Assignment rules will reduce the need for so many calculation script lines which will reduce the requirement for such a large number of calculation scripts. In cases where the scripts generates exceeds 100, the length of the name of the 100th calculation script is different from the 99th as the calculation script name changes from being 8 characters long and becomes 9 characters long (e.g. A6811_100 rather than A6811_99). A name of 9 characters is not permitted in non Unicode applications. It is “too long”. When this occurs, an error will show in the hpcm.log as “Error processing calculation scripts” and “Unexpected error in business logic “. Further down the log, it is possible to see that this is “Caused by: Error copying object “ and “Caused by: com.essbase.api.base.EssException: Cannot put olap file object ... object name_[<calc script name> e.g. A6811_100] too long for non-unicode mode application”. The error file will give the name of the calculation script which is causing the issue. In my example, this is A6811_100 and you can see this is 9 characters in length. It is not possible to increase the number of characters allowed in a calculation script name. However, it is possible to increase the size of each calculation script. The default for an HPCM application, set in the preferences, is set to 4mb. If the size of each calculation script is larger, the number of scripts generated will reduce and, therefore, less than 100 scripts will be generated which means that the name of the calculation script will remain 8 characters long. To increase the size of the generated calculation scripts for an application, in the HPM_APPLICATION_PREFERENCE table for the application, find the row where HPM_PREFERENCE_NAME_ID=20. The default value in this row is 4194304. This can be increased e.g. 7340032 will increase this to 7mb. Please restart the profitability service after making the change.

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  • EXALYTICS - If Oracle BI Server Does Not Fail Over to the TimesTen Instance

    - by Ahmed Awan
    If the BI Server does not fail over to the second TimesTen instance on the scaled-out node, then ensure that the logical table source (LTS) for the repository has mapped both TimesTen physical data sources. This mapping ensures that at the logical table source level, a mapping exists to both TimesTen instances. If one TimesTen instance is not available, then failover logic for the BI Server at the DSN level tries to connect to the other TimesTen instance. Reference: http://docs.oracle.com/cd/E23943_01/bi.1111/e24706/toc.htm

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  • Essbase BSO Data Fragmentation

    - by Ann Donahue
    Essbase BSO Data Fragmentation Data fragmentation naturally occurs in Essbase Block Storage (BSO) databases where there are a lot of end user data updates, incremental data loads, many lock and send, and/or many calculations executed.  If an Essbase database starts to experience performance slow-downs, this is an indication that there may be too much fragmentation.  See Chapter 54 Improving Essbase Performance in the Essbase DBA Guide for more details on measuring and eliminating fragmentation: http://docs.oracle.com/cd/E17236_01/epm.1112/esb_dbag/daprcset.html Fragmentation is likely to occur in the following situations: Read/write databases that users are constantly updating data Databases that execute calculations around the clock Databases that frequently update and recalculate dense members Data loads that are poorly designed Databases that contain a significant number of Dynamic Calc and Store members Databases that use an isolation level of uncommitted access with commit block set to zero There are two types of data block fragmentation Free space tracking, which is measured using the Average Fragmentation Quotient statistic. Block order on disk, which is measured using the Average Cluster Ratio statistic. Average Fragmentation Quotient The Average Fragmentation Quotient ratio measures free space in a given database.  As you update and calculate data, empty spaces occur when a block can no longer fit in its original space and will either append at the end of the file or fit in another empty space that is large enough.  These empty spaces take up space in the .PAG files.  The higher the number the more empty spaces you have, therefore, the bigger the .PAG file and the longer it takes to traverse through the .PAG file to get to a particular record.  An Average Fragmentation Quotient value of 3.174765 means the database is 3% fragmented with free space. Average Cluster Ratio Average Cluster Ratio describes the order the blocks actually exist in the database. An Average Cluster Ratio number of 1 means all the blocks are ordered in the correct sequence in the order of the Outline.  As you load data and calculate data blocks, the sequence can start to be out of order.  This is because when you write to a block it may not be able to place back in the exact same spot in the database that it existed before.  The lower this number the more out of order it becomes and the more it affects performance.  An Average Cluster Ratio value of 1 means no fragmentation.  Any value lower than 1 i.e. 0.01032828 means the data blocks are getting further out of order from the outline order. Eliminating Data Block Fragmentation Both types of data block fragmentation can be removed by doing a dense restructure or export/clear/import of the data.  There are two types of dense restructure: 1. Implicit Restructures Implicit dense restructure happens when outline changes are done using EAS Outline Editor or Dimension Build. Essbase restructures create new .PAG files restructuring the data blocks in the .PAG files. When Essbase restructures the data blocks, it regenerates the index automatically so that index entries point to the new data blocks. Empty blocks are NOT removed with implicit restructures. 2. Explicit Restructures Explicit dense restructure happens when a manual initiation of the database restructure is executed. An explicit dense restructure is a full restructure which comprises of a dense restructure as outlined above plus the removal of empty blocks Empty Blocks vs. Fragmentation The existence of empty blocks is not considered fragmentation.  Empty blocks can be created through calc scripts or formulas.  An empty block will add to an existing database block count and will be included in the block counts of the database properties.  There are no statistics for empty blocks.  The only way to determine if empty blocks exist in an Essbase database is to record your current block count, export the entire database, clear the database then import the exported data.  If the block count decreased, the difference is the number of empty blocks that had existed in the database.

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  • Scream if you want to go faster

    - by simonsabin
    My session for 24hrs of pass on High Performance functions will be starting at 11:00 GMT thats migdnight for folks in the UK. To attend follow this link https://www.livemeeting.com/cc/8000181573/join?id=N5Q8S7&role=attend&pw=d2%28_KmN3r The rest of the sessions can be found here http://www.sqlpass.org/24hours/2010/Sessions/ChronologicalOrder.aspx So far the sessions have been great so no pressure :( See you there in 4.5 hrs...(read more)

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  • EPM 11.1.2.1 - Smartview client and HFM office provider

    - by user809526
    If your connection to the smartview provider is very slow, because the login part takes a long time (user directory slowness, ...), consider adding on the desktop side a Windows parameter: HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\InternetSettings\ ReceiveTimeout 300000 to avoid being prompted over and over again for username/password This is an addition to the support doc id: "Smart View 11.1.2.1 Keeps Prompting For Username And Password For Financial Management Provider [ID 1353294.1]"

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  • Why is MySQL table_cache full but never used

    - by Jeremy Clarke
    I have been using the tuning-primer.sh script to tune my my.cnf settings. I have most things working well but the part about TABLE CACHE makes no sense: TABLE CACHE Current table_cache value = 900 tables. You have a total of 0 tables You have 900 open tables. Current table_cache hit rate is 1% , while 100% of your table cache is in use. You should probably increase your table_cache When I do SHOW STATUS; I get the following table-related numbers: Open_tables = 900 Opened_tables = 0 It seems like something is going wrong. I have some extra memory I could use on increasing the table_cache size, but my sense is that the 900 tables already available aren't doing anything, and increasing it will just waste more energy. Why might this be happening? Are there other settings that could cause all my table_cache slots to be used even though there are no hits to them? I have 150 max connections and probably no more than 4 tables per join, FWIW. Here is the tuner script output for temp tables, which I've also been tuning: TEMP TABLES Current max_heap_table_size = 90 M Current tmp_table_size = 90 M Of 11032358 temp tables, 40% were created on disk Perhaps you should increase your tmp_table_size and/or max_heap_table_size to reduce the number of disk-based temporary tables. Note! BLOB and TEXT columns are not allow in memory tables. If you are using these columns raising these values might not impact your ratio of on disk temp tables.

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  • SQLAuthority News – Great Time Spent at Great Indian Developers Summit 2014

    - by Pinal Dave
    The Great Indian Developer Conference (GIDS) is one of the most popular annual event held in Bangalore. This year GIDS is scheduled on April 22, 25. I will be presented total four sessions at this event and each session is very different from each other. Here are the details of four of my sessions, which I presented there. Pluralsight Shades This event was a great event and I had fantastic fun presenting a technology over here. I was indeed very excited that along with me, I had many of my friends presenting at the event as well. I want to thank all of you to attend my session and having standing room every single time. I have already sent resources in my newsletter. You can sign up for the newsletter over here. Indexing is an Art I was amazed with the crowd present in the sessions at GIDS. There was a great interest in the subject of SQL Server and Performance Tuning. Audience at GIDS I believe event like such provides a great platform to meet and share knowledge. Pinal at Pluralsight Booth Here are the abstract of the sessions which I had presented. They were recorded so at some point in time they will be available, but if you want the content of all the courses immediately, I suggest you check out my video courses on the same subject on Pluralsight. Indexes, the Unsung Hero Relevant Pluralsight Course Slow Running Queries are the most common problem that developers face while working with SQL Server. While it is easy to blame SQL Server for unsatisfactory performance, the issue often persists with the way queries have been written, and how Indexes has been set up. The session will focus on the ways of identifying problems that slow down SQL Server, and Indexing tricks to fix them. Developers will walk out with scripts and knowledge that can be applied to their servers, immediately post the session. Indexes are the most crucial objects of the database. They are the first stop for any DBA and Developer when it is about performance tuning. There is a good side as well evil side to indexes. To master the art of performance tuning one has to understand the fundamentals of indexes and the best practices associated with the same. We will cover various aspects of Indexing such as Duplicate Index, Redundant Index, Missing Index as well as best practices around Indexes. SQL Server Performance Troubleshooting: Ancient Problems and Modern Solutions Relevant Pluralsight Course Many believe Performance Tuning and Troubleshooting is an art which has been lost in time. However, truth is that art has evolved with time and there are more tools and techniques to overcome ancient troublesome scenarios. There are three major resources that when bottlenecked creates performance problems: CPU, IO, and Memory. In this session we will focus on High CPU scenarios detection and their resolutions. If time permits we will cover other performance related tips and tricks. At the end of this session, attendees will have a clear idea as well as action items regarding what to do when facing any of the above resource intensive scenarios. Developers will walk out with scripts and knowledge that can be applied to their servers, immediately post the session. To master the art of performance tuning one has to understand the fundamentals of performance, tuning and the best practices associated with the same. We will discuss about performance tuning in this session with the help of Demos. Pinal Dave at GIDS MySQL Performance Tuning – Unexplored Territory Relevant Pluralsight Course Performance is one of the most essential aspects of any application. Everyone wants their server to perform optimally and at the best efficiency. However, not many people talk about MySQL and Performance Tuning as it is an extremely unexplored territory. In this session, we will talk about how we can tune MySQL Performance. We will also try and cover other performance related tips and tricks. At the end of this session, attendees will not only have a clear idea, but also carry home action items regarding what to do when facing any of the above resource intensive scenarios. Developers will walk out with scripts and knowledge that can be applied to their servers, immediately post the session. To master the art of performance tuning one has to understand the fundamentals of performance, tuning and the best practices associated with the same. You will also witness some impressive performance tuning demos in this session. Hidden Secrets and Gems of SQL Server We Bet You Never Knew Relevant Pluralsight Course SQL Trio Session! It really amazes us every time when someone says SQL Server is an easy tool to handle and work with. Microsoft has done an amazing work in making working with complex relational database a breeze for developers and administrators alike. Though it looks like child’s play for some, the realities are far away from this notion. The basics and fundamentals though are simple and uniform across databases, the behavior and understanding the nuts and bolts of SQL Server is something we need to master over a period of time. With a collective experience of more than 30+ years amongst the speakers on databases, we will try to take a unique tour of various aspects of SQL Server and bring to you life lessons learnt from working with SQL Server. We will share some of the trade secrets of performance, configuration, new features, tuning, behaviors, T-SQL practices, common pitfalls, productivity tips on tools and more. This is a highly demo filled session for practical use if you are a SQL Server developer or an Administrator. The speakers will be able to stump you and give you answers on almost everything inside the Relational database called SQL Server. I personally attended the session of Vinod Kumar, Balmukund Lakhani, Abhishek Kumar and my favorite Govind Kanshi. Summary If you have missed this event here are two action items 1) Sign up for Resource Newsletter 2) Watch my video courses on Pluralsight Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, SQLAuthority News, T SQL Tagged: GIDS

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  • SQL SERVER – A Funny Cartoon on Index

    - by pinaldave
    Performance Tuning has been my favorite subject and I have done it for many years now. Today I will list one of the most common conversation about Index I have heard in my life. Every single time, I am at consultation for performance tuning I hear following conversation among various team members. I want to ask you, does this kind of conversation happens in your organization? Any way, If you think Index solves all of your performance problem I think it is not true. There are many other reason one has to consider along with Indexes. For example I consider following various topic one need to understand for performance tuning. ?Logical Query Processing ?Efficient Join Techniques ?Query Tuning Considerations ?Avoiding Common Performance Tuning Issues Statistics and Best Practices ?TempDB Tuning ?Hardware Planning ?Understanding Query Processor ?Using SQL Server 2005 and 2008 Updated Feature Sets ?CPU, Memory, I/O Bottleneck Index Tuning (of course) ?Many more… Well, I have written this blog thinking I will keep this blog post a bit easy and not load up. I will in future discuss about other performance tuning concepts. Let me know what do you think about the cartoon I made. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Humor, SQL Index, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Which will give more free RAM to linux?

    - by Linda Thomas
    Trying to avoid some issues so I've been trying to learn vm. in kernel tuning but still a little confused even after googling. The lower background_ratio is the sooner the flushes? the lower dirty_ratio is the less dirty ram that is kept, right vm.dirty_ratio = 20 vm.dirty_background_ratio = 1 or vm.dirty_ratio = 60 vm.dirty_background_ratio = 20 or vm.dirty_ratio = 20 vm.dirty_background_ratio = 10 or vm.dirty_ratio = 20 vm.dirty_background_ratio = 5

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  • MySQL Memory usage

    - by Rob Stevenson-Leggett
    Our MySQL server seems to be using a lot of memory. I've tried looking for slow queries and queries with no index and have halved the peak CPU usage and Apache memory usage but the MySQL memory stays constantly at 2.2GB (~51% of available memory on the server). Here's the graph from Plesk. Running top in the SSH window shows the same figures. Does anyone have any ideas on why the memory usage is constant like this and not peaks and troughs with usage of the app? Here's the output of the MySQL Tuning Primer script: -- MYSQL PERFORMANCE TUNING PRIMER -- - By: Matthew Montgomery - MySQL Version 5.0.77-log x86_64 Uptime = 1 days 14 hrs 4 min 21 sec Avg. qps = 22 Total Questions = 3059456 Threads Connected = 13 Warning: Server has not been running for at least 48hrs. It may not be safe to use these recommendations To find out more information on how each of these runtime variables effects performance visit: http://dev.mysql.com/doc/refman/5.0/en/server-system-variables.html Visit http://www.mysql.com/products/enterprise/advisors.html for info about MySQL's Enterprise Monitoring and Advisory Service SLOW QUERIES The slow query log is enabled. Current long_query_time = 1 sec. You have 6 out of 3059477 that take longer than 1 sec. to complete Your long_query_time seems to be fine BINARY UPDATE LOG The binary update log is NOT enabled. You will not be able to do point in time recovery See http://dev.mysql.com/doc/refman/5.0/en/point-in-time-recovery.html WORKER THREADS Current thread_cache_size = 0 Current threads_cached = 0 Current threads_per_sec = 2 Historic threads_per_sec = 0 Threads created per/sec are overrunning threads cached You should raise thread_cache_size MAX CONNECTIONS Current max_connections = 100 Current threads_connected = 14 Historic max_used_connections = 20 The number of used connections is 20% of the configured maximum. Your max_connections variable seems to be fine. INNODB STATUS Current InnoDB index space = 6 M Current InnoDB data space = 18 M Current InnoDB buffer pool free = 0 % Current innodb_buffer_pool_size = 8 M Depending on how much space your innodb indexes take up it may be safe to increase this value to up to 2 / 3 of total system memory MEMORY USAGE Max Memory Ever Allocated : 2.07 G Configured Max Per-thread Buffers : 274 M Configured Max Global Buffers : 2.01 G Configured Max Memory Limit : 2.28 G Physical Memory : 3.84 G Max memory limit seem to be within acceptable norms KEY BUFFER Current MyISAM index space = 4 M Current key_buffer_size = 7 M Key cache miss rate is 1 : 40 Key buffer free ratio = 81 % Your key_buffer_size seems to be fine QUERY CACHE Query cache is supported but not enabled Perhaps you should set the query_cache_size SORT OPERATIONS Current sort_buffer_size = 2 M Current read_rnd_buffer_size = 256 K Sort buffer seems to be fine JOINS Current join_buffer_size = 132.00 K You have had 16 queries where a join could not use an index properly You should enable "log-queries-not-using-indexes" Then look for non indexed joins in the slow query log. If you are unable to optimize your queries you may want to increase your join_buffer_size to accommodate larger joins in one pass. Note! This script will still suggest raising the join_buffer_size when ANY joins not using indexes are found. OPEN FILES LIMIT Current open_files_limit = 1024 files The open_files_limit should typically be set to at least 2x-3x that of table_cache if you have heavy MyISAM usage. Your open_files_limit value seems to be fine TABLE CACHE Current table_cache value = 64 tables You have a total of 426 tables You have 64 open tables. Current table_cache hit rate is 1% , while 100% of your table cache is in use You should probably increase your table_cache TEMP TABLES Current max_heap_table_size = 16 M Current tmp_table_size = 32 M Of 15134 temp tables, 9% were created on disk Effective in-memory tmp_table_size is limited to max_heap_table_size. Created disk tmp tables ratio seems fine TABLE SCANS Current read_buffer_size = 128 K Current table scan ratio = 2915 : 1 read_buffer_size seems to be fine TABLE LOCKING Current Lock Wait ratio = 1 : 142213 Your table locking seems to be fine The app is a facebook game with about 50-100 concurrent users. Thanks, Rob

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  • 4096 and 8192 block size read slower than write? by using lsi 9361-8i RAID10

    - by Min Hong Tan
    is it possible that 1024 and 2048 block size read speed is faster than 4096 and 8192 block? I'm using lsi 9361-8i with RAID 10 , with 8 x Kingston E50 250G. result: 1024 = Write: 2,251 MB/s Read: 2,625 MB/s 2048 = Write: 2,141 MB/s Read: 3,672 MB/s 4096 = Write: 2,147 MB/s Read: 231 MB/s 8192 = Write: 2,147 MB/s Read: 442 MB/s is there any possible? and below is the reading when i simply want to test out the RAID 10 function and disaster test by taking out one of the 250G harddisk. the result is different like below: Result: 1024 = Write: 825 MB/s Read: 1,139 MB/s 2048 = Write: 797 MB/s Read: 1,312 MB/s 4096 = Write: 911 MB/s Read: 1,342 MB/s 8192 = Write: 786 MB/s Read: 1,204 MB/s and the result for 4096 and 8192block are different? can any one explain to me is it normal? or I need to do some tuning/configuration? will it affect my host linux performance?

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  • How can I see if apache is overloaded and dropping or not accepting connections?

    - by cat pants
    Basically I just want to see if apache is handling a current level of high traffic or if I need to tune it to handle more connections. (I have found plenty of information on the actual tuning, so no help needed there) I know it has been dropping or not accepting connections earlier today, but not seeing anything in the error logs. Is the expected behavior to throw a 503 in the error log if apache cannot accept more connections? If so, what error logging level do I need in order to see these? What is the correct terminology: dropping connections or not accepting connections? MPM is prefork, OS is Linux, apache version is 2.2.15.

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  • Alternative or succesor to GDBM

    - by Anon Guy
    We a have a GDBM key-value database as the backend to a load-balanced web-facing application that is in implemented in C++. The data served by the application has grown very large, so our admins have moved the GDBM files from "local" storage (on the webservers, or very close by) to a large, shared, remote, NFS-mounted filesystem. This has affected performance. Our performance tests (in a test environment) show page load times jumping from hundreds of milliseconds (for local disk) to several seconds (over NFS, local network), and sometimes getting as high as 30 seconds. I believe a large part of the problem is that the application makes lots of random reads from the GDBM files, and that these are slow over NFS, and this will be even worse in production (where the front-end and back-end have even more network hardware between them) and as our database gets even bigger. While this is not a critical application, I would like to improve performance, and have some resources available, including the application developer time and Unix admins. My main constraint is time only have the resources for a few weeks. As I see it, my options are: Improve NFS performance by tuning parameters. My instinct is we wont get much out of this, but I have been wrong before, and I don't really know very much about NFS tuning. Move to a different key-value database, such as memcachedb or Tokyo Cabinet. Replace NFS with some other protocol (iSCSI has been mentioned, but i am not familiar with it). How should I approach this problem?

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  • How to tune down the Hyperic built-in postgresql database for a small setup

    - by Svish
    We are testing out Hyperic 4.5.1 in a quite small environment for now. Currently there are just 1-5 agents and there probably won't be any more than 10-15. When I run ps ax there are 20(!) postgres processes running. For a small setup like this, that can't be necessary, can it? I'm a software developer and don't have much experience with setting up servers and such though, so don't really know. Either way, what settings are appropriate for a small Hyperic setup like this? Current, default and untouched configuration file, hqdb/data/postgresql.conf: # ----------------------------- # PostgreSQL configuration file # ----------------------------- # # This file consists of lines of the form: # # name = value # # (The '=' is optional.) White space may be used. Comments are introduced # with '#' anywhere on a line. The complete list of option names and # allowed values can be found in the PostgreSQL documentation. The # commented-out settings shown in this file represent the default values. # # Please note that re-commenting a setting is NOT sufficient to revert it # to the default value, unless you restart the server. # # Any option can also be given as a command line switch to the server, # e.g., 'postgres -c log_connections=on'. Some options can be changed at # run-time with the 'SET' SQL command. # # This file is read on server startup and when the server receives a # SIGHUP. If you edit the file on a running system, you have to SIGHUP the # server for the changes to take effect, or use "pg_ctl reload". Some # settings, which are marked below, require a server shutdown and restart # to take effect. # # Memory units: kB = kilobytes MB = megabytes GB = gigabytes # Time units: ms = milliseconds s = seconds min = minutes h = hours d = days #--------------------------------------------------------------------------- # FILE LOCATIONS #--------------------------------------------------------------------------- # The default values of these variables are driven from the -D command line # switch or PGDATA environment variable, represented here as ConfigDir. #data_directory = 'ConfigDir' # use data in another directory # (change requires restart) #hba_file = 'ConfigDir/pg_hba.conf' # host-based authentication file # (change requires restart) #ident_file = 'ConfigDir/pg_ident.conf' # ident configuration file # (change requires restart) # If external_pid_file is not explicitly set, no extra PID file is written. #external_pid_file = '(none)' # write an extra PID file # (change requires restart) #--------------------------------------------------------------------------- # CONNECTIONS AND AUTHENTICATION #--------------------------------------------------------------------------- # - Connection Settings - #listen_addresses = 'localhost' # what IP address(es) to listen on; # comma-separated list of addresses; # defaults to 'localhost', '*' = all # (change requires restart) port = 9432 # (change requires restart) max_connections = 100 # (change requires restart) # Note: increasing max_connections costs ~400 bytes of shared memory per # connection slot, plus lock space (see max_locks_per_transaction). You # might also need to raise shared_buffers to support more connections. #superuser_reserved_connections = 3 # (change requires restart) #unix_socket_directory = '' # (change requires restart) #unix_socket_group = '' # (change requires restart) #unix_socket_permissions = 0777 # octal # (change requires restart) #bonjour_name = '' # defaults to the computer name # (change requires restart) # - Security & Authentication - #authentication_timeout = 1min # 1s-600s #ssl = off # (change requires restart) #password_encryption = on #db_user_namespace = off # Kerberos #krb_server_keyfile = '' # (change requires restart) #krb_srvname = 'postgres' # (change requires restart) #krb_server_hostname = '' # empty string matches any keytab entry # (change requires restart) #krb_caseins_users = off # (change requires restart) # - TCP Keepalives - # see 'man 7 tcp' for details #tcp_keepalives_idle = 0 # TCP_KEEPIDLE, in seconds; # 0 selects the system default #tcp_keepalives_interval = 0 # TCP_KEEPINTVL, in seconds; # 0 selects the system default #tcp_keepalives_count = 0 # TCP_KEEPCNT; # 0 selects the system default #--------------------------------------------------------------------------- # RESOURCE USAGE (except WAL) #--------------------------------------------------------------------------- # - Memory - shared_buffers = 64MB # min 128kB or max_connections*16kB # (change requires restart) #temp_buffers = 8MB # min 800kB #max_prepared_transactions = 5 # can be 0 or more # (change requires restart) # Note: increasing max_prepared_transactions costs ~600 bytes of shared memory # per transaction slot, plus lock space (see max_locks_per_transaction). work_mem = 2MB # min 64kB maintenance_work_mem = 32MB # min 1MB #max_stack_depth = 2MB # min 100kB # - Free Space Map - max_fsm_pages = 204800 # min max_fsm_relations*16, 6 bytes each # (change requires restart) #max_fsm_relations = 1000 # min 100, ~70 bytes each # (change requires restart) # - Kernel Resource Usage - #max_files_per_process = 1000 # min 25 # (change requires restart) #shared_preload_libraries = '' # (change requires restart) # - Cost-Based Vacuum Delay - #vacuum_cost_delay = 0 # 0-1000 milliseconds #vacuum_cost_page_hit = 1 # 0-10000 credits #vacuum_cost_page_miss = 10 # 0-10000 credits #vacuum_cost_page_dirty = 20 # 0-10000 credits #vacuum_cost_limit = 200 # 0-10000 credits # - Background writer - #bgwriter_delay = 200ms # 10-10000ms between rounds #bgwriter_lru_percent = 1.0 # 0-100% of LRU buffers scanned/round #bgwriter_lru_maxpages = 5 # 0-1000 buffers max written/round #bgwriter_all_percent = 0.333 # 0-100% of all buffers scanned/round #bgwriter_all_maxpages = 5 # 0-1000 buffers max written/round #--------------------------------------------------------------------------- # WRITE AHEAD LOG #--------------------------------------------------------------------------- # - Settings - fsync = on # turns forced synchronization on or off #wal_sync_method = fsync # the default is the first option # supported by the operating system: # open_datasync # fdatasync # fsync # fsync_writethrough # open_sync #full_page_writes = on # recover from partial page writes #wal_buffers = 64kB # min 32kB # (change requires restart) commit_delay = 100000 # range 0-100000, in microseconds #commit_siblings = 5 # range 1-1000 # - Checkpoints - checkpoint_segments = 10 # in logfile segments, min 1, 16MB each #checkpoint_timeout = 5min # range 30s-1h #checkpoint_warning = 30s # 0 is off # - Archiving - #archive_command = '' # command to use to archive a logfile segment #archive_timeout = 0 # force a logfile segment switch after this # many seconds; 0 is off #--------------------------------------------------------------------------- # QUERY TUNING #--------------------------------------------------------------------------- # - Planner Method Configuration - #enable_bitmapscan = on #enable_hashagg = on #enable_hashjoin = on #enable_indexscan = on #enable_mergejoin = on #enable_nestloop = on #enable_seqscan = on #enable_sort = on #enable_tidscan = on # - Planner Cost Constants - #seq_page_cost = 1.0 # measured on an arbitrary scale #random_page_cost = 4.0 # same scale as above #cpu_tuple_cost = 0.01 # same scale as above #cpu_index_tuple_cost = 0.005 # same scale as above #cpu_operator_cost = 0.0025 # same scale as above #effective_cache_size = 128MB # - Genetic Query Optimizer - #geqo = on #geqo_threshold = 12 #geqo_effort = 5 # range 1-10 #geqo_pool_size = 0 # selects default based on effort #geqo_generations = 0 # selects default based on effort #geqo_selection_bias = 2.0 # range 1.5-2.0 # - Other Planner Options - #default_statistics_target = 10 # range 1-1000 #constraint_exclusion = off #from_collapse_limit = 8 #join_collapse_limit = 8 # 1 disables collapsing of explicit # JOINs #--------------------------------------------------------------------------- # ERROR REPORTING AND LOGGING #--------------------------------------------------------------------------- # - Where to Log - log_destination = 'stderr' # Valid values are combinations of # stderr, syslog and eventlog, # depending on platform. # This is used when logging to stderr: redirect_stderr = on # Enable capturing of stderr into log # files # (change requires restart) # These are only used if redirect_stderr is on: log_directory = '../../logs' # Directory where log files are written # Can be absolute or relative to PGDATA log_filename = 'hqdb-%Y-%m-%d.log' # Log file name pattern. # Can include strftime() escapes #log_truncate_on_rotation = off # If on, any existing log file of the same # name as the new log file will be # truncated rather than appended to. But # such truncation only occurs on # time-driven rotation, not on restarts # or size-driven rotation. Default is # off, meaning append to existing files # in all cases. log_rotation_age = 1d # Automatic rotation of logfiles will # happen after that time. 0 to # disable. #log_rotation_size = 10MB # Automatic rotation of logfiles will # happen after that much log # output. 0 to disable. # These are relevant when logging to syslog: #syslog_facility = 'LOCAL0' #syslog_ident = 'postgres' # - When to Log - #client_min_messages = notice # Values, in order of decreasing detail: # debug5 # debug4 # debug3 # debug2 # debug1 # log # notice # warning # error #log_min_messages = notice # Values, in order of decreasing detail: # debug5 # debug4 # debug3 # debug2 # debug1 # info # notice # warning # error # log # fatal # panic #log_error_verbosity = default # terse, default, or verbose messages #log_min_error_statement = error # Values in order of increasing severity: # debug5 # debug4 # debug3 # debug2 # debug1 # info # notice # warning # error # fatal # panic (effectively off) log_min_duration_statement = 10000 # -1 is disabled, 0 logs all statements # and their durations. #silent_mode = off # DO NOT USE without syslog or # redirect_stderr # (change requires restart) # - What to Log - #debug_print_parse = off #debug_print_rewritten = off #debug_print_plan = off #debug_pretty_print = off #log_connections = off #log_disconnections = off #log_duration = off #log_line_prefix = '' # Special values: # %u = user name # %d = database name # %r = remote host and port # %h = remote host # %p = PID # %t = timestamp (no milliseconds) # %m = timestamp with milliseconds # %i = command tag # %c = session id # %l = session line number # %s = session start timestamp # %x = transaction id # %q = stop here in non-session # processes # %% = '%' # e.g. '<%u%%%d> ' #log_statement = 'none' # none, ddl, mod, all #log_hostname = off #--------------------------------------------------------------------------- # RUNTIME STATISTICS #--------------------------------------------------------------------------- # - Query/Index Statistics Collector - #stats_command_string = on #update_process_title = on stats_start_collector = on # needed for block or row stats # (change requires restart) stats_block_level = on stats_row_level = on stats_reset_on_server_start = off # (change requires restart) # - Statistics Monitoring - #log_parser_stats = off #log_planner_stats = off #log_executor_stats = off #log_statement_stats = off #--------------------------------------------------------------------------- # AUTOVACUUM PARAMETERS #--------------------------------------------------------------------------- #autovacuum = off # enable autovacuum subprocess? # 'on' requires stats_start_collector # and stats_row_level to also be on #autovacuum_naptime = 1min # time between autovacuum runs #autovacuum_vacuum_threshold = 500 # min # of tuple updates before # vacuum #autovacuum_analyze_threshold = 250 # min # of tuple updates before # analyze #autovacuum_vacuum_scale_factor = 0.2 # fraction of rel size before # vacuum #autovacuum_analyze_scale_factor = 0.1 # fraction of rel size before # analyze #autovacuum_freeze_max_age = 200000000 # maximum XID age before forced vacuum # (change requires restart) #autovacuum_vacuum_cost_delay = -1 # default vacuum cost delay for # autovacuum, -1 means use # vacuum_cost_delay #autovacuum_vacuum_cost_limit = -1 # default vacuum cost limit for # autovacuum, -1 means use # vacuum_cost_limit #--------------------------------------------------------------------------- # CLIENT CONNECTION DEFAULTS #--------------------------------------------------------------------------- # - Statement Behavior - #search_path = '"$user",public' # schema names #default_tablespace = '' # a tablespace name, '' uses # the default #check_function_bodies = on #default_transaction_isolation = 'read committed' #default_transaction_read_only = off #statement_timeout = 0 # 0 is disabled #vacuum_freeze_min_age = 100000000 # - Locale and Formatting - datestyle = 'iso, mdy' #timezone = unknown # actually, defaults to TZ # environment setting #timezone_abbreviations = 'Default' # select the set of available timezone # abbreviations. Currently, there are # Default # Australia # India # However you can also create your own # file in share/timezonesets/. #extra_float_digits = 0 # min -15, max 2 #client_encoding = sql_ascii # actually, defaults to database # encoding # These settings are initialized by initdb -- they might be changed lc_messages = 'C' # locale for system error message # strings lc_monetary = 'C' # locale for monetary formatting lc_numeric = 'C' # locale for number formatting lc_time = 'C' # locale for time formatting # - Other Defaults - #explain_pretty_print = on #dynamic_library_path = '$libdir' #local_preload_libraries = '' #--------------------------------------------------------------------------- # LOCK MANAGEMENT #--------------------------------------------------------------------------- #deadlock_timeout = 1s #max_locks_per_transaction = 64 # min 10 # (change requires restart) # Note: each lock table slot uses ~270 bytes of shared memory, and there are # max_locks_per_transaction * (max_connections + max_prepared_transactions) # lock table slots. #--------------------------------------------------------------------------- # VERSION/PLATFORM COMPATIBILITY #--------------------------------------------------------------------------- # - Previous Postgres Versions - #add_missing_from = off #array_nulls = on #backslash_quote = safe_encoding # on, off, or safe_encoding #default_with_oids = off #escape_string_warning = on #standard_conforming_strings = off #regex_flavor = advanced # advanced, extended, or basic #sql_inheritance = on # - Other Platforms & Clients - #transform_null_equals = off #--------------------------------------------------------------------------- # CUSTOMIZED OPTIONS #--------------------------------------------------------------------------- #custom_variable_classes = '' # list of custom variable class names SELECT * FROM pg_stat_activity; datid | datname | procpid | usesysid | usename | current_query | waiting | query_start | backend_start | client_addr | client_port -------+---------+---------+----------+---------+---------------------------------+---------+-------------------------------+-------------------------------+-------------+------------- 16384 | hqdb | 3267 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.036781+01 | 2011-02-08 15:51:20.02413+01 | 127.0.0.1 | 47892 16384 | hqdb | 3268 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.050994+01 | 2011-02-08 15:51:20.047393+01 | 127.0.0.1 | 47893 16384 | hqdb | 3269 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.056661+01 | 2011-02-08 15:51:20.053201+01 | 127.0.0.1 | 47894 16384 | hqdb | 3271 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.062351+01 | 2011-02-08 15:51:20.058822+01 | 127.0.0.1 | 47895 16384 | hqdb | 3272 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.068328+01 | 2011-02-08 15:51:20.064517+01 | 127.0.0.1 | 47896 16384 | hqdb | 3273 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.07444+01 | 2011-02-08 15:51:20.070755+01 | 127.0.0.1 | 47897 16384 | hqdb | 3274 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.080941+01 | 2011-02-08 15:51:20.076983+01 | 127.0.0.1 | 47898 16384 | hqdb | 3275 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.08741+01 | 2011-02-08 15:51:20.083697+01 | 127.0.0.1 | 47899 16384 | hqdb | 3276 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.093597+01 | 2011-02-08 15:51:20.089977+01 | 127.0.0.1 | 47900 16384 | hqdb | 3277 | 10 | hqadmin | <IDLE> in transaction | f | 2011-02-08 15:51:20.133974+01 | 2011-02-08 15:51:20.096149+01 | 127.0.0.1 | 47901 16384 | hqdb | 3308 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:49:27.402197+01 | 2011-02-08 15:51:29.826321+01 | 127.0.0.1 | 47902 16384 | hqdb | 3309 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.572395+01 | 2011-02-08 15:51:29.865243+01 | 127.0.0.1 | 47903 16384 | hqdb | 3310 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.586273+01 | 2011-02-08 15:51:29.874346+01 | 127.0.0.1 | 47904 16384 | hqdb | 3311 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:10:03.024088+01 | 2011-02-08 15:51:29.883598+01 | 127.0.0.1 | 47905 16384 | hqdb | 3312 | 10 | hqadmin | <IDLE> in transaction | f | 2011-02-08 15:51:35.804457+01 | 2011-02-08 15:51:29.892925+01 | 127.0.0.1 | 47906 16384 | hqdb | 3418 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.580207+01 | 2011-02-08 15:51:55.56911+01 | 127.0.0.1 | 47910 16384 | hqdb | 3419 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.59781+01 | 2011-02-08 15:51:55.588609+01 | 127.0.0.1 | 47911 16384 | hqdb | 3422 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:10:02.668836+01 | 2011-02-08 15:51:55.603076+01 | 127.0.0.1 | 47914 16384 | hqdb | 3421 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.770427+01 | 2011-02-08 15:51:55.603086+01 | 127.0.0.1 | 47913 16384 | hqdb | 3420 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.680785+01 | 2011-02-08 15:51:55.637058+01 | 127.0.0.1 | 47912 16384 | hqdb | 18233 | 10 | hqadmin | SELECT * FROM pg_stat_activity; | f | 2011-02-09 10:49:29.688949+01 | 2011-02-09 10:48:13.031475+01 | | -1 (21 rows)

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  • SQLAuthority News – Microsoft Whitepaper – AlwaysOn Solution Guide: Offloading Read-Only Workloads to Secondary Replicas

    - by pinaldave
    SQL Server 2012 has many interesting features but the most talked feature is AlwaysOn. Performance tuning is always a hot topic. I see lots of need of the same and lots of business around it. However, many times when people talk about performance tuning they think of it as a either query tuning, performance tuning, or server tuning. All are valid points, but performance tuning expert usually understands the business workload and business logic before making suggestions. For example, if performance tuning expert analysis workload and realize that there are plenty of reports as well read only queries on the server they can for sure consider alternate options for the same. If read only data is not required real time or it can accept the data which is delayed a bit it makes sense to divide the workload. A secondary replica of the original data which can serve all the read only queries and report is a good idea in most of the cases where there is plenty of workload which is not dependent on the real time data. SQL Server 2012 has introduced the feature of AlwaysOn which can very well fit in this scenario and provide a solution in Read-Only Workloads. Microsoft has recently announced a white paper which is based on absolutely the same subject. I recommend it to read for every SQL Enthusiast who is are going to implement a solution to offload read-only workloads to secondary replicas. Download white paper AlwaysOn Solution Guide: Offloading Read-Only Workloads to Secondary Replicas Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: AlwaysOn

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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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  • SQL Overlapping and Multi-Column Indexes

    - by durilai
    I am attempting to tune some stored procedures and have a question on indexes. I have used the tuning advisor and they recommended two indexes, both for the same table. The issue is one index is for one column and the other is for multiple columns, of which it includes the same column from the first. My question is why and what is the difference? CREATE NONCLUSTERED INDEX [_dta_index_Table1_5_2079723603__K23_K17_K13_K12_K2_K10_K22_K14_K19_K20_K9_K11_5_6_7_15_18] ON [dbo].[Table1] ( [EfctvEndDate] ASC, [StuLangCodeKey] ASC, [StuBirCntryCodeKey] ASC, [StuBirStOrProvncCodeKey] ASC, [StuKey] ASC, [GndrCodeKey] ASC, [EfctvStartDate] ASC, [StuHspncEnctyIndctr] ASC, [StuEnctyMsngIndctr] ASC, [StuRaceMsngIndctr] ASC, [StuBirDate] ASC, [StuBirCityName] ASC ) INCLUDE ( [StuFstNameLgl], [StuLastOrSrnmLgl], [StuMdlNameLgl], [StuIneligSnorImgrntIndctr], [StuExpctdGrdtngClYear] ) WITH (SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF) ON [PRIMARY] go CREATE NONCLUSTERED INDEX [_dta_index_Table1_5_2079723603__K23] ON [dbo].[Table1] ( [EfctvEndDate] ASC )WITH (SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF) ON [PRIMARY]

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  • nginx-tornado-django request timeout

    - by Xie
    We are using nginx-tornado-django to provide web services. That is, no web page frontend. The nginx server serves as a load-balancer. The server has 8 cores, so we launched 8 tornado-django processes on every server. Memcached is also deployed to gain better performance. The requests per day is about 1 million per server. We use MySQL as backend DB. The code is tested and correct. Our profiling shows that normally every request are processed within 100ms. The problem is, we find that about 10 percent of the requests suffers from time-out issue. Many requests didn't even reach tornado. I really don't have much experience on tuning of nginx/tornado/MySQL. Right now I don't have a clue on what is going wrong. Any advise is appreiciated.

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  • I'm asked to tune a long starting app into a short time period

    - by Jason
    Hi, I'm asked to shorten the startup period of a long starting app, however I have also to obligate to my managers to the amount of time i will reduce the startup - something like 10-20 seconds. As i'm new in my company I said I can obligate with timeframe of months (its a big server and I'm new and i plan to do lazy load + performance tuning). that answer was not accepted I was required to do some kind of a cache to hold important data in another server and then when my server starts up it would reach all its data from that cache - I find it a kind of a workaround and i don't really like it. do you like it? what do you think I should do? any suggestions? PS when i profiled the app i saw many small issues that make the startup long (like 2 minutes) it would not be a short process to fix all and to make lazy load. Any kind of suggestions would help. language - java. Thanks

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  • Python: Time a code segment for testing performance (with timeit)

    - by Mestika
    Hi, I've a python script which works just as it should but I need to write the time for the execution. I've gooled that I should use timeit but I can't seem to get it to work. My Python script looks like this: import sys import getopt import timeit import random import os import re import ibm_db import time from string import maketrans myfile = open("results_update.txt", "a") for r in range(100): rannumber = random.randint(0, 100) update = "update TABLE set val = %i where MyCount >= '2010' and MyCount < '2012' and number = '250'" % rannumber #print rannumber conn = ibm_db.pconnect("dsn=myDB","usrname","secretPWD") for r in range(5): print "Run %s\n" % r ibm_db.execute(query_stmt) query_stmt = ibm_db.prepare(conn, update) myfile.close() ibm_db.close(conn) What I need it the time it takes the execution of the query and written to the file "results_update.txt". The purpose is to test an update statement for my database with different indexes and tuning mechanisms. Sincerely Mestika

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