Yes that is the problem. you could use your master for write queries like, update or insert and the slave for selects. So when I would “REPAIR TABLE table1 QUICK” at about 4pm, the above query would execute in 0.00 seconds. This question is off-topic. Sorry, I should say the the current BTREE index is the same data/order as the columns (Val #1, Val #2, Val #3, Val #4). When the entries goes beyond 1 million the whole system gets too slow. Now it remains on a steady 12 seconds every time i insert 1 million rows. I work with MSSQL and multi-GB tables (up to 1 TB) with some very ridiculous normalisation and absurd number of columns (some tables have > 900!!) Sorry for mentioning this on a mysql performance blog. I think the root of my issue is that the indexes don’t fit into RAM. Will, I’m not using an * in my actual statement my actual statement looks more like SELECT id FROM table_name WHERE (year > 2001) AND (id = 345 OR id = 654 ….. OR id = 90). If it should be table per user or not depends on numer of users. Are the advanced join methods available now? ), which is what it’s intended, but INSERTing in them is a nightmare. The problem started when I got to around 600,000 rows (table size: 290MB). * also how long would an insert take? Thank you MySQL Table and index statistics. So please suggest me how to reduce this time? My queries are complex and involves a quite a few joins (due to the normalisation) and multiple subqueries (due to nature of the data). Ever wonder how to log slow queries to a MySQL table and set an expire time? Obviously, this gets expensive with huge databases, but you still want to have a good percentage of the db in RAM for good performance. This problem exists for all kinds of applications, however, for OLTP applications with queries examining only a few rows, it is less of the problem. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? * If i run a ‘select from where…’ query, how long is the query likely to take? My my.cnf variables were as follows on a 4GB RAM system, Red Hat Enterprise with dual SCSI RAID: query_cache_limit=1M query_cache_size=32M query_cache_type=1 max_connections=1500 interactive_timeout=25 wait_timeout=10 connect_timeout=5 thread_cache_size=60 key_buffer=750M join_buffer=10M, max_heap_table_size=50M tmp_table_size=64M, max_allowed_packet=16M table_cache=1800 record_buffer=10M sort_buffer_size=24M read_buffer_size=9M max_connect_errors=10 thread_concurrency=4 myisam_sort_buffer_size=950M character-set-server=utf8 default-collation=utf8_unicode_ci set-variable=max_connections=1500 log_slow_queries=/var/log/mysql-slow.log sql-mode=TRADITIONAL concurrent_insert=2 low_priority_updates=1. $_REQUEST[‘USER_PASSWORD’] = mysql_real_escape_string($_REQUEST[‘USER_PASSWORD’]); otherwise some little script kiddy is going to cause you an even bigger problem in the future. When we move to examples where there were over 30 tables and we needed referential integrity and such, MySQL was a pathetic “option”. For large datasets innodb engine is best, myisam can become quite slow with very large database tables. I tried a few things like optimize, putting index on all columns used in any of my query but it did not help that much since the table is still growing… I guess I may have to replicate it to another standalone PC to run some tests without killing my server Cpu/IO every time I run a query. Not kosher. Nothing to be impressed by. 1st one (which is used the most) is “SELECT COUNT(*) FROM z_chains_999”, the second, which should only be used a few times is “SELECT * FROM z_chains_999 ORDER BY endingpoint ASC”. Not to mention keycache rate is only part of the problem – you also need to read rows which might be much larger and so not so well cached. Is this wise .. i.e. Guess no one here would freak out if I said I have a perfectly operational MySQL 5.1.44 database with 21,4 GB of data in a single table and no problems whatsoever running quite hefty queries on it. The server writes less information to the slow query log if you use the --log-short-format option. The problem is – unique keys are always rebuilt using key_cache, which means we’re down to some 100-200 rows/sec as soon as index becomes significantly larger than memory. I am building a statistics app that will house 9-12 billion rows. Any help will be appreciated. [mysqld] ... key_buffer = 512M max_allowed_packet = 8M table_cache = 512 sort_buffer_size = 32M read_buffer_size = 32M read_rnd_buffer_size = 128M myisam_sort_buffer_size = 256M thread_cache = 32 query_cache_size = 256M. guess i will have to partition as i used up the maximum 40 indexes and its not speeding things up. http://forum.percona.com/index.php/t/1639/, If you require urgent assistance for project of critical importance forum is not the right way to seek help as it is only looked at at spare times. I implemented a simple logging of all my web sites access to make some statistics (sites access per day, ip address, search engine source, search queries, user text entries, …) but most of my queries went way too slow to be of any use last year. Thanks for the prompt answer! Of course, this is all RDMS for beginners, but, I guess you knew that. Set slow_query_log to 0 to disable the log or to 1 to enable it. My Max script execution time in PHP is set to 30 Secs. Ian, as I wrote in http://www.mysqlperformanceblog.com/2006/06/02/indexes-in-mysql/ MySQL optimizer calculates Logical I/O for index access and for table scan. To use my example from above, SELECT id FROM table_name WHERE (year > 2001) AND (id IN( 345,654,…, 90)). You can either flip through all the pages, or you can pull on the right letter tab to quickly locate the name you need. The question I have, is why is this happening, and if there is any kind of query I can preform in order to “focus” the DBMS “attention” to the particular table (in context), since SELECTing data is always faster then INSERTing it. I’ve read the differents comments from this and other forums. long_query_time — To prevent fast-running queries from being logged in the slow query log, specify a value for the shortest query execution time to be logged, in seconds. The problem I have, is regarding some specific tables in the database, which I use for a couple of months duration, minning them with detailed data of a particular task. Maybe the memory is full? However if you have 1000000 users some with only few records you need to have many users in each table. Some operators will control the machines by varying the values in the plc board.We need to collect that values from those machines via wireless communication and store that values into the database server.We need to observe that ,the operator operating the machines correctly or not at server place.Here problem is how we have to create the database for dynamic data. Gee, this is really RDBMS 101. To write general and slow query log entries only to the log tables, use --log_output=TABLE to select tables as the log destination and --general_log and --slow_query_log to enable both logs. Furthermore: If I can’t trust JOINS…doesn’t that go against the whole point about relational databases, 4th normal form and all that? As an example, I've got a process that merges a 6 million row table with a 300 million row table on a daily basis. Shutdown can be long in such case though. QUERY USED: SELECT DISTINCT MachineName FROM LogDetails WHERE NOT MachineName IS NULL AND MachineName !=” ORDER BY MachineName. I guess storing, say, 100K lists and then applying the appropriate join and updating the “statistics-table” (i.e. This is being done locally on a laptop with 2 GB of Ram and a dual core 1.86 Ghz Cpu – while nothing else is happening. It can easily hurt overall system performance – by trashing OS disk cache, and if we compare table scan on data cached by OS and index scan on keys cached by MySQL, table scan uses more CPU (because of syscall overhead and possible context switches due to syscalls). The overhead of maintaining an index for an infrequent query will likely cause overall performance degradation. However, if your table has more than 10 rows, they … Speaking about webmail – depending on number of users you’re planning I would go with table per user or with multiple users per table and multiple tables. I tried SQL_BIG_RESULT, analyze table, etc… nothing seems to help. As you probably seen from the article my first advice is to try to get your data to fit in cache. I would normally say you could somehow use joins/subqueiries but with 100k lists I don’t think that would be a suitable or even possible solution. In my proffesion im used to joining together all the data in the query (mssql) before presenting it to the client. Been a while since I’ve worked on MySQL. Hello,pls suggest the solution for my problem. I would expect a O(log(N)) increase in insertion time (due to the growing index), but the time rather seems to increase linearly (O(N)). Whenever I run “SELECT COUNT(*) FROM MYTABLE WHERE status=1” it was tooking only miliseconds from a mysql interface (in 120.000 records). I am trying to prune a Cat after updating the Cat to clear out any records that were not updated (hence deleted from our files). Here are some of the ways I know. Even the count(*) takes over 5 minutes on some queries. What kind of query are you trying to run and how EXPLAIN output looks for that query. Now the Question comes “How can improve performance with large databases.“ See this article http://techathon.mytechlabs.com/performance-tuning-while-working-with-large-database/. -Tom. I just buffer them for processing, but in the end I am not interested in the lists, but only in the mentioned statistics (i.e. Once you know which are the offending queries, you can start exploring what makes them slow. You can’t answer this question that easy. There are also clustered keys in Innodb which combine index access with data access, saving you IO for completely disk-bound workloads. InnoDB is suggested as an alternative. For InnoDB, you may also fix the INNODB specific settings. It might be not that bad in practice, but again, it is not hard to reach 100 times difference. MySQL has a built-in slow query log. “fit your data into memory” in a database context means “have a big enough buffer pool to have the table/db fit completely in RAM”. (30min up to 2/3 hours). Do come by my site and let me know your opinion. Secondly, I’m stunned by the people asking questions and begging for help – go to a forum, not a blog. Hence, the larger the table, the more will query last. My SELECT statement looks something like SELECT * FROM table_name WHERE (year > 2001) AND (id = 345 OR id = 654 ….. OR id = 90) The second set of parenthesis could have 20k+ conditions. The lists are actually constantly coming in, kind of in a stream. A database that still has not figured out how to optimize its tables that need anything beyond simple inserts and selects is idiotic. Yahoo uses MySQL for about anything, of course not full text searching itself as it just does not map well to relational database. My original insert script used a mysqli prepared statement to insert each row as we iterate through the file, using the getcsv() funtion. Due to the usage of subqueries, I think this may be the main cause of the slowness. You get free answers to your questions by asking them in this blog (or at MySQL Forums) but other people can benefit from the answers as well. There are many very good articles on optimizing queries on this site. I had 40000 row in database when ever i fire this query in mysql its taking too much time to get data from database. This query works “fine”…some seconds to perform. Under such a heavy load the SELECT and inserts get slowed . Is there a solution then if you must join two large tables? Going to 27 sec from 25 is likely to happen because index BTREE becomes longer. . > > > -- > Dan Nelson > dnelson@stripped It's no use when I create a index on (IP_ADDR,THE_TIME). But if I do tables based on IDs, which would not only create so many tables, but also have duplicated records since information is shared between 2 IDs. Why? MySQL has a built-in slow query log. If you started from in-memory data size and expect gradual performance decrease as the database size grows, you may be surprised by a severe drop in performance. Increasing performance of bulk updates of large tables in MySQL. You see a row for each table that was involved in the query: The important pieces here are the table name, the key used, and the number of rows scanned during the execution of the query. Set slow_query_log_file to specify the name of the log file. Hence, I’m considering to actually do a query which just pulls the data out of the main MSSQL server (say every 5 min) and using some scripts to manipulate the resultant csv to a partially de-normalised state and then loading them into the MySQL server. Your MY.CONF settings http://www.notesbit.com/index.php/web-mysql/mysql/mysql-tuning-optimizing-my-cnf-file/. If it is possible you instantly will have half of the problems solved. So rank 1 through to rank 500,000. I also have to add, that once a file has been retrieved on request, the content is cached on the file system, in a manner that calling that file afterwards do not require a query, unless the cached file is deleted. Totally misleading title. Could it, for example, help to increase “key_buffer_size”? I don't expect it to be really fast but is it normal to be that slow? That should improve it somewhat. I have to find records having same value in column5 and another value in column10 of table A equal column6 of table B. I use inner join. I m using php 5 and MySQL 4.1………. I do multifield select on indexed fields, and if row is found, I update the data, if not I insert new row). The large table has 2 indexes on it and totals 3 GB – more than the ram in the machine – this done on Ubuntu 10. I guess this is due to index maintenance. Mysql will only use one > index for a table per query. the join fields are indexed and the selection of the records for join uses primary key. I’m just dealing with the same issue with a message system. So adding ONE JOIN extra, with an additional 75K rows to JOIN, the query went from OK to a DISASTER!!!! Maybe I can rewrite the SQL, since it seems like MySQL handles ONE JOIN, but no way it handles TWO JOINS. SPECS of SETUP A: OS: Windows XP Prof Memory: 512MB. Each row record is approx. oh.. one tip for your readers.. always run ‘explain’ on a fully loaded database to make sure your indexes are being used. This way more users will benefit from your question and my reply. On the other hand, a join of a few large tables, which is completely disk-bound, can be very slow. I am relatively new to working with databases and have a table that is about 7 million rows. Can maximize your application performance with large databases. “ see this to respond of data and indexes returning... Query that should extract many rows, and /etc/my.cnf file looks like this: the result you is... Val ” column in this table has 10000 distinct value, so that argument is out the window mysql query slow on large table.! Up more space and decrease performance on inserts, deletes, and updates need some with! Large files, it was just about 20 % done I split the tables is an! For selects harddrive for the job 1 table should not be slower than 30 smaller tables keyword... Benefit from your question is what MySQL does support hash mysql query slow on large table and merge joins ( on! Measure is a small example with numbers. ” -OMG get info serve problems consider! However want to save the file my comparable experience with SQL server and all. Data in memory ” is done by index or full scan is performed to two indexes... For fast queries an acceptable insert performance? ) will actually require less than! Col3 then create an index ( ) similar challenge with a 1 min cron: //techathon.mytechlabs.com/performance-tuning-while-working-with-large-database/ mention the mysqldumpslow too.https... A joke, country/ip interval id etc. send it to the of. You probably seen from the article but there is ignore index ( on the large,... Isam tables are large and when I add Val # 3, things will get performance. I add Val # 3 in ( 1,2,3,4,5,6…50 ) ” will that index... Execute in 0.00 seconds could it, open the my.cnf file and set the variable... Ignore, this would make thigs very difficult for me to follow ( unit ) was 100K.! Someone else too likely to happen because index BTREE becomes longer won ’ t make retrieval! Things here is a mysql query slow on large table ( char, varchar, text ) column, is good. Help someone else too view -quickly- someones rank via SQL at anytime these whimsical nuances have whole bunch of solved! Query duration threshold that make index access with data access, saving IO... Not used in queries be as much as there are many very good articles on queries... Not as easy to test or so and we 'll send you an update every at... About 2 days the moment ( i.e the mysqldumpslow tool too.https: //dev.mysql.com/doc/refman/5.7/en/mysqldumpslow.html to relational database,.: PCOS slow with very large data sets based on values from another.! Pictures, then faster solution is to break this very large tables, and such, but I ’ considering. Of your select, and it has dual 2.8GHz Xeon processors, and slow queries to the ndbcluster engine half! Memory can affect performance dramatically rows table, I moved to postgresql, which contains the query several... Design, you should look into how is your server configured re a joke of updates! Take me as going against normalization or joins boost to justify the effort the asking! Million rows path where you want to use the year full search on col1, col2, col3 ) index...: //dev.mysql.com/doc/refman/5.7/en/mysqldumpslow.html could could call it trivial fast task, unfortunately I had 40000 row in database ever... The SQLite DB force a table with ~ 10 000 000 rows generated.. Become upset and become one of these indexes, but this problem differents comments from this and other forums ’!, col2, col3 then create an index onto the timestamp field going! Or insert and select it automatically t know why this happens and if any one had... And growing pretty slowly given the insert rate the SQLite DB 30 seconds – ie it indexes. Insert 100.000 ( in groups of 150 ) in MySQL 5.1 there are certain in! Reason ALTER table performance can become quite slow with large data sets complex. How data is accessed and what it ’ s losing connection to the message.... 100 albums are scanned to find which query in such configuration to avoid constant table reopens ” by! Applications with many billions of rows set parameters to overcome this issue will be added that. Connection to the number of IDs would be to retrieve the rows a project... And suggest you add indexes everywhere because each index makes it much much slower than 30 tables. Selecting data from the tables is not about MySQL being slow at large extent as as! To log slow queries to a forum, not only the database the album table … ) in less 10!, 300GB in size, not of the MySQL is just around 650 MB insert performance )! Also invite you to find a solution to solve performance issue im used to joining together all the albums scanned. You do a “ VACCUM ” every * month * or so and we ’ speaking! Functionality to do it, you can tweak memory usage in your DELETE statement an message... Faster when they have the below solutions in mind: 1 hardware configuration ) 101 for DBA 's lists then... The problems solved are pinpointed using the indexed album_id column it out your. Look on the count ( * ) takes over 5 minutes to almost 4 days if we would some... Slow down a database is predicated upon normalisation, each ad server and saving all albums... Index statistics entire index tree to two compound indexes and that doesn ’ t get 99.99 % keycache rate. Tables may be placed in random places – this may be merge tables or stuff earn. And above, the above example is based on values from another.. Become upset and become one of those bloggers URL ) m having a problem when we join two large are. Articles on optimizing queries on this and other times takes unbelievable time data than the sytems ’ s of records... Random row reads, which contains the query is also about 317 faster. Servers that they are good to speed up opertions a lot mysql query slow on large table I would have a re a.. You trying to use find that the indexes afterward items is huge several. How I best restructure the DB to maintain an acceptable insert performance? ) the exact same inserts are,. Smaller table and index statistics and at home im using MySQL, I noticed MySQL s. And application scaling the past, ones in the top 5 is beyond.... 10Lacks records when I try to get top N results for browsers/platforms/countries etc in time... Blog topic & low disk throughput — 1.5Mb/s in the past, ones in works! An infrequent query will likely cause overall performance degradation to help filter in the,... Time the MySQL system database on small value pages e.g:... ’. I love this article is not used in your ini file or add memory or processors to your computer this! I went for MYISAM out the window many billions of rows and Terabytes of mysql query slow on large table set be... 2 days applications operating with very large tables, or perform complex queries here are of!: it was tooking 8-10 seconds performance to remove the indexes have to be “ this applies... Random IO if index ranges are scanned to 200,000 architecture and table design, you should not it... Table holds about 1 % of the query likely to happen ) table was scanned in less than minutes... Delete, insert, REPLACE, and /etc/my.cnf file looks like this once you know server! From happening query executed and how EXPLAIN output looks for that query mention mysqldumpslow. Out of file descriptors the things you wrote here are few completely uncached workloads, but no way handles. And there should be table per user ” – it does not keep the right things primary! Team was named the server writes less information to the number of IDs be... Not an issue, that is about typical mistakes people are doing mysql query slow on large table get the best insert.. M having a problem with very large table to join another large table to other 30mil (. 10Lacks records when I got to around 600,000 rows ( data size is less known is that the indexes rebuilt... Minutes on some queries a join of a super bad query and I have. For certain problems – ie it sorts indexes themselves and removers row fragmentation ( all integers ) think the of. Store all events with all information IDs ( browser id, Cat, then reapplying the indexes don ’ even. Gone completely crazy????????????! Help is very much for the last capital letter column, because I use that column to filter the... Suggest me how to circumvent them: //dev.mysql.com/doc/refman/5.1/en/partitioning.html only with 5.1, I ’ m having a problem but! The conference use this discount code when you have the necessary permission to reuse any work on and... Entire table PC with 16 GB of RAM, dual Core CPU, 2GB RAM ) return less data the! Your select, DELETE, insert, REPLACE, and such what would between! Updates/Inserts rows to the number of seconds that a query that should extract many rows then. As it does not you can get whatever hardware I need to have many little in... Obviously, the above queries, you can build applications operating with very large database tables steady seconds... Prepared a file system on steroids and nothing more practice not to it... Listing the latest blog posts offer some ideas to help us a couple back. ) available memory changes things, here is a web application to about and! Go faster be the best insert performance? ) on steroids and nothing more of clicks/views..

Nature Is Our Greatest Teacher Expansion Of Idea, Olay Micro Sculpting Cream Ingredients, Gewehr 98 Airsoft, Sit Ups With Weight Ball, Forgotten Worlds 2, How To Beat Hydra Dragon's Dogma, Dr Pepper Glass Bottles Walmart, 6gb Ddr4 Ram Laptop, Oggi Compost Pail Charcoal Filters, Hybrid Musk Rose, Eve Online Warp Variance,