http://forum.mysqlperformanceblog.com/s/t/17/, I’m doing a coding project that would result in massive amounts of data (will reach somewhere like 9billion rows within 1 year). Hi again, Indeed, this article is about common misconfgigurations that people make .. including me .. Im used to ms sql server which out of the box is extremely fast .. One big mistake here, I think, MySQL makes assumption 100 key comparison like ” if (searched_key == current_key)” is equal to 1 Logical I/O. Has the JOIN thing gone completely crazy??? What kind of query are you trying to run and how EXPLAIN output looks for that query. I’d be more concerned about your login though, I hope a bit further up the script you have a. Joining from a view to any table hides all indexes except those on the joined to tables. Percona's experts can maximize your application performance with our open source database support, managed services or consulting. First thing you need to take into account is fact; a situation when data fits in memory and when it does not are very different. Since this is a predominantly SELECTed table, I went for MYISAM. Is the problem the bad cardinality of the index (although the shown number is high but that's due to the many NULL values I assume). Dropping the index is out of the question, since dropping them and creating them takes far too much time, being even quicker to just let them be. Any ideas what the reasons could be? and the number of rows are also in the couple millions. Experiment on nested queries and join queries: http://vpslife.blogspot.com/2009/03/mysql-nested-query-tweak.html. Up to about 15,000,000 rows (1.4GB of data) the procedure was quite fast (500-1000 rows per second), and then it started to slow down. 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). It took about 6 hours to create the index, as I tweaked some buffer sizes to help it along. 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. Yahoo uses MySQL for about anything, of course not full text searching itself as it just does not map well to relational database. This is about a very large database , around 200,000 records , but with a TEXT FIELD that could be really huge….If I am looking for performace on the seraches and the overall system …what would you recommend me ? I think you can give me some advise. 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. I’m writing about working with large data sets, these are then your tables and your working set do not fit in memory. Use EXPLAIN to confirm and remove any index that is not used in queries. Performance is very important with any application.If your database tables have millions of records then a simple SQL query will take 3-4 mins.but ideal time for a query should be at max 5 sec. The problem is you’re joining “derived tables” which causes MySQL to create tables without indexes which causes very slow joins. By this post I try to divide into smaller table and running one sql per time, but still not faster. [mysqld] innodb_buffer_pool_size = 2G innodb_log_buffer_size=5m innodb_flush_log_at_trx_commit=2 innodb_lock_wait_timeout=120 datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql init_connect=’SET collation_connection = utf8_general_ci; SET NAMES utf8;’ default-character-set=utf8 character-set-server=utf8 collation-server=utf8_general_ci [client] default-character-set=utf8 set-variable = max_allowed_packet=32M [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid. Of course, this is all RDMS for beginners, but, I guess you knew that. Best Practice to deal with large DBs is to use a Partitioning Scheme on your DB after doing a thorough analysis of your Queries and your application requirements. at least could you able to explain brief in short? I use a group of these tables in the system, and preform simple SELECTs in them (not joining them with other tables). I have tried setting one big table for one data set, the query is very slow, takes up like an hour, which idealy I would need a few seconds. Do come by my site and let me know your opinion. Obviously, this gets expensive with huge databases, but you still want to have a good percentage of the db in RAM for good performance. Use multiple servers to host portions of the data set. You can make sure that both tables use a key by adding the following index: This time, the album table is not scanned in its entirety, but the right albums are quickly pinpointed using the user_id key. Just doing searches as above on (Val #1, #2, #4) are very fast. I have several data sets and each of them would be around 90,000,000 records, but each record has just a pair of IDs as compository primary key and a text, just 3 fields. I’ll have to do it like that, and even partitioning over more than one disk in order to distribute disk usage. I used MySQL with other 100.000 of files opened at the same time with no problems. The first section of the query is exactly the same as the previous query. 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. (I’ve been struggling with this one for about a week now. The queries that were taking less than 1 second some times ago are taking at least 20 to 30 seconds. However, with ndbcluster the exact same inserts are taking more than 15 min. I quess I have to experiment a bit, Does anyone have any good newbie tutorial configuring MySql .. My server isn’t the fastest in the world, so I was hoping to enhance performance by tweaking some parameters in the conf file, but as everybody know, tweaking without any clue how different parameters work together isn’t a good idea .. Hi, I have a table I am trying to query with 300K records which is not large relatively speaking. The table structure is as follows: CREATE TABLE z_chains_999 ( startingpoint bigint(8) unsigned NOT NULL, endingpoint bigint(8) unsigned NOT NULL, PRIMARY KEY (startingpoint,endingpoint) ) ENGINE=MyISAM DEFAULT CHARSET=utf8 ROW_FORMAT=FIXED; My problem is, as more rows are inserted, the longer time it takes to insert more rows. (we are using InnoDB 1.0.6). You simply prefix the query like this: The result you get is an explanation of how data is accessed. This could mean millions of table so it is not easy to test. This query works “fine”…some seconds to perform. ALTER TABLE normally rebuilds indexes by sort, so does LOAD DATA INFILE (Assuming we’re speaking about MyISAM table) so such difference is quite unexpected. From these lists I want to create a table that counts any “co-occurring” items (items are co-occurring if they are occur in the same list). Could the INSERTs be slow, dued to the size of the PRIMARY KEY?! oh.. one tip for your readers.. always run ‘explain’ on a fully loaded database to make sure your indexes are being used. Or that adding indexes like pepper and salt can actually SLOW down a database. How much index is fragmented ? The big sites such as Slashdot and so forth have to use massive clusters and replication. How large is index when it becomes slower. So, I want to count, how many lists contain both, item1 and item2, item1 and item3, etc. As everything usually slows down a lot once it does not fit in memory, the good solution is to make sure your data fits in memory as well as possible. Now if we would do eq join of the table to other 30mil rows table, it will be completely random. I’ve read the differents comments from this and other forums. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. When there are tens of thousands of records in the table to be queried from the database, all the results of one-time query will become very slow, especially with the increase of the amount of data. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? * also how long would an insert take? I need to delete all 300,000 records found in one table from a table that has 20,000,000 records, and neither the subquerry i wrote nor the join i wrote give me any result at all in over 12 hours. MySQL database really slow with a really big table [closed] Ask Question Asked 6 years, 6 months ago Active 5 years, 11 months ago Viewed 8k times 1 2 Closed. Please correct me if I am wrong. I received a Tweet earlier this week which pointed out that LIMIT is slow when dealing with large offsets so take a look at this here. The server has 4GB of RAM, dual Core 2 2.6GHz processors. Join performance with large tables is way too slow: Submitted: 11 May 2009 20:48: Modified: 20 Dec 2009 17:11: ... where testperiod=200 and stockkey=30 limit 2000) a ) b ON a.uuid=b.uuid ) c WHERE b IS NULL ); How to repeat: Use query on a table of about 800mln rows. mysql> set global slow_query_log_file = '/tmp/mysql-slow.log'; mysql> set global long_query_time = 5; mysql> set global slow_query_log = ON; show vairables コマンドで設定を確認すると、変更されていることが確認できます。 And very low CPU usage as well! Peter has a Master's Degree in Computer Science and is an expert in database kernels, computer hardware, and application scaling. So I’m wondering, are there a certain number of CSV values that will make the IN() search actually slow down? Even the count(*) takes over 5 minutes on some queries. The ‘data’ attribute contents the binary fragments. When you run a query that should extract many rows, then faster solution is to scan entire table. The lists are actually constantly coming in, kind of in a stream. Shutdown can be long in such case though. How random accesses would be to retrieve the rows. >>Use multiple servers to host portions of data set, Where can I find out more about this comment? SELECT Q.questionID, Q.questionsetID, Q.question, Q.questioncatid, QAX.questionid, QAX.answersetid, ASets.answersetid, ASets.answersetname, ASAX.answersetid, ASAX.answerid, A.answerID, A.answername, A.answervalue, COUNT(DISTINCT e3.evalanswerID) AS totalforthisquestion, COUNT(DISTINCT e1.evalanswerID) AS totalforinstructor, (COUNT(DISTINCT e3.evalanswerID)/COUNT(DISTINCT e1.evalanswerID)*100) AS answerpercentage FROM tblquestions Q INNER JOIN tblquestionsanswers_x QAX USING (questionid) INNER JOIN tblanswersets ASets USING (answersetid) INNER JOIN tblanswersetsanswers_x ASAX USING (answersetid) INNER JOIN tblanswers A USING (answerid) LEFT JOIN (tblevalanswerresults e1 INNER JOIN tblevaluations e2 ON e1.evalid = e2.evalid AND e2.InstructorID = ‘1021338’, ) ON e1.questionid = Q.questionID LEFT JOIN (tblevalanswerresults e3 INNER JOIN tblevaluations e4 ON e3.evalid = e4.evalid AND e4.InstructorID = ‘1021338’, ) ON e3.questionid = Q.questionID AND e3.answerID = A.answerID, GROUP BY Q.questionID, Q.questionsetID, Q.question, ASets.answersetid, Q.questioncatid, A.answerID, A.answername, A.answervalue HAVING Q.questioncatid = 1, UNION /**The following query is just for the totals, and does not include the group columns**/ SELECT 9999, NULL, ‘Totals’, Q.questionID, Q.questionsetID, Q.question, Q.questioncatid, QAX.questionid, ASets.answersetid, ASets.answersetname, A.answerID, A.answername, A.answervalue, COUNT(DISTINCT e3.evalanswerID) AS totalforthisquestion, COUNT(DISTINCT e1.evalanswerID) AS totalforinstructor, (COUNT(DISTINCT e3.evalanswerID)/COUNT(DISTINCT e1.evalanswerID)*100) AS answerpercentage FROM tblquestions Q INNER JOIN tblquestionsanswers_x QAX USING (questionid) INNER JOIN tblanswersets ASets USING (answersetid) INNER JOIN tblanswersetsanswers_x ASAX USING (answersetid) INNER JOIN tblanswers A USING (answerid) LEFT JOIN (tblevalanswerresults e1 INNER JOIN tblevaluations e2 ON e1.evalid = e2.evalid AND e2.InstructorID = ‘1021338’, GROUP BY Q.questioncatid, ASets.answersetname,A.answerID,A.answername,A.answervalue, SELECT DISTINCT spp.provider_profile_id, sp.provider_id, sp.business_name, spp.business_phone, spp.business_address1, spp.business_address2, spp.city, spp.region_id, spp.state_id, spp.rank_number, spp.zipcode, sp.sic1, sp.approved FROM service_provider sp INNER JOIN service_provider_profile spp ON sp.provider_id = spp.provider_id WHERE sp.approved = ‘Y’ AND spp.master_status = ‘0’ ORDER BY sp.business_name ASC LIMIT 0 , 100, In all three tables there are more than 7 lakh record. Known feature limitation, though annoying one. I have around 9,00,000 user records, I have Problems with Login, which is very slow (Terribly Slow), All i have is PHP / MYSQL with a VPS with 768MB RAM. Do you mean ensuring SELECTs return less data than the sytems’s RAM? 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. I am having a problem with updating records in a table. I am stuck! INSERTS: 1,000 2. In MyISAM, it’s a bit trickier, but make sure key_buffer_size is big enough to hold your indexes and there’s enough free RAM to load the base table storage into the file-system cache. I forgot to add that while the server is inserting the logs, I see very LOW disk throughput — 1.5Mb/s! Of course, I am not trying to get one user per table. What queries are you going to run on it ? I wonder how I can optimize my table. The problem started when I got to around 600,000 rows (table size: 290MB). You can think of it as a webmail service like google mail, yahoo or hotmail. One tool that MySQL offers is the EXPLAIN keyword. I worked on a project containing 5 tables and a realtime search (AJAX). wherein context is a string-type (char, varchar, text) column, is an example of a super bad query! On other hand join of few large tables, which is completely disk bound can be very slow. Simply break up my big table into smaller ones? So – if you have a table with millions of rows with lots of updates and reads happening, InnoDB would be the way to go from what I read, But want if you want to use mysql ‘full text search’ which can only be used on MyISAM. Sergey, Would you mind posting your case on our forums instead at http://forum.mysqlperformanceblog.com and I’ll reply where. You can’t go away with ALTER TABLE DISABLE KEYS as it does not affect unique keys. The index does make it very fast for one of my table on another project (list of all cities in the world: 3 million rows). I retrive records from 4 tables which are quite large in size using joins ,but it takes lot of time to execute.How to speed up the same query? Then run your code and any query above the specified threshold will be added to that file. We explored a bunch of issues including questioning our hardware and our system administrators When we switched to PostgreSQL, there was no such issue. As for Joins, its always best practice not to use joins over Large Tables. Ever wonder how to log slow queries to a MySQL table and set an expire time? To use it, open the my.cnf file and set the slow_query_log variable to "On." The more indexes you have the faster SELECT statments are, but the slower INSERTS and DELETES. In InnoDB, have innodb_buffer_pool_size > the size of your database (or at least your table). Hello,pls suggest the solution for my problem. The initial table (unit) was 100K rows. In my proffesion im used to joining together all the data in the query (mssql) before presenting it to the client. There are aprox 900 different Cat values (all integers). InnoDB doesn’t cut it for me if the backup and all of that is so very cumbersome (mysqlhotcopy is not available, for instance) and eking performance out of an InnoDB table for raw SELECT speed will take a committee of ten PhDs in RDBMS management. I suggest instead sharing it on our MySQL discussion forums – so that the entire community can offer some ideas to help. If you need to search on col1, col2, col3 then create an index(col1,col2,col3). Maybe I can rewrite the SQL, since it seems like MySQL handles ONE JOIN, but no way it handles TWO JOINS. “table_cache” is what defines how many tables will be opened and you can configure it independently of number of tables you’re using. We contracted you to help us a couple years back, and it has been VERY stable and quick. The sent items is the half. My guess is not 45 minutes. I have a table with a unique key on two columns (STRING, URL). Depending on type of joins they may be slow in MySQL or may work well. Would be a great help to readers. We should take a look at your queries to see what could be done. and the queries will be a lot more complex. Can anybody here advice me, how to proceed, maybe someone, who already have experienced this. Even if a table scan looks faster than index access on a cold-cache benchmark, it doesn’t mean that it’s a good idea to use table scans. What is often forgotten about is,  depending on if the workload is cached or not,  different selectivity might show benefit from using indexes. The difference is 10,000 times for our worst-case scenario. The total size of the MySQL is Just around 650 MB. MySQL, InnoDB, MariaDB and MongoDB are trademarks of their respective owners. page number 6 http://www.ecommercelocal.com/pages.php?pi=6 the site load quickly but on other pages e.g. So you understand how much having data in memory changes things, here is a small example with numbers. Anna is a web developer, project rescue expert, Pluralsight author, speaker and conference organizer. This way more users will benefit from your question and my reply. my key_buffer is set to 1000M, but this problem already begins long before the memory is full. We’ll need to perform 30 million random row reads, which gives us 300,000 seconds with 100 rows/sec rate. The server layer, which contains the query optimizer, doesn’t store statistics on data and indexes. I am now looking to further optimize, and it seems I am hearing I would probably do better to look closer at my schema, and possible ‘sharding’, I need to optimize mysql server to manage a big tables (now about 78Mb, with increment of 1Mb/day), — I have used a table MyISAM, info from phpmyadmin: Collation utf8_general_ci lenght row 122 row dimension avg 194 byte row 411,069, QueryType # dim/hour % change db 2,103k 3,262,61 61,29% select 933k 1,447,66 27,20% insert 358k 555,08 10,43% update 30k 47,19 0,89% set option 1,189 1,84 0,03%, I have a gallery with select query with ORDER BY, LIMIT and with paging —, Handler_read_rnd 12 M Handler_read_rnd_next 4,483 M Created_tmp_disk_tables 5,270 Created_tmp_tables 5,274 Created_tmp_files 37 k Key_reads 4,226 Key_write_requests 380 k Key_writes 367 k Sort_merge_passes 18 k Sort_rows 12 M, — Actual my.cnf: [mysqld] datadir = /var/lib/mysql socket = /var/lib/mysql/mysql.sock user=mysql # Default to using old password format for compatibility with mysql 3.x # clients (those using the mysqlclient10 compatibility package). Right now I am wondering if it would be faster to have one table per user for messages instead of one big table with all the messages and two indexes (sender id, recipient id). So feel free to post there and I also invite you to join our community, too. is there any setting to be changes e.g. I have a project I have to implement with open-source software. For most workloads you’ll always want to provide enough memory to key cache so its hit ratio is like 99.9%. Or SQL that totally works for one RDBMS will not necessarily perform very well on another. It is what I am concerning now, I use mysql to process just around million rows with condition to join on two columns, I spend whole day with nothing reply yet. The main event table definition is CREATE TABLE IF NOT EXISTS stats ( id int(11) unsigned NOT NULL AUTO_INCREMENT, banner_id int(11) unsigned NOT NULL, location_id tinyint(3) unsigned NOT NULL, url_id int(11) unsigned NOT NULL, page_id int(11) unsigned NOT NULL, dateline int(11) unsigned NOT NULL, ip_interval int(11) unsigned NOT NULL, browser_id tinyint(3) unsigned NOT NULL, platform_id tinyint(3) unsigned NOT NULL, PRIMARY KEY (id), KEY bannerid (banner_id), KEY dateline (dateline), KEY ip_interval (ip_interval) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 PACK_KEYS=1 ROW_FORMAT=FIXED AUTO_INCREMENT=10100001 ; The country codes stored in different table named iplist CREATE TABLE IF NOT EXISTS iplist ( id int(11) unsigned NOT NULL AUTO_INCREMENT, code varchar(2) NOT NULL, code_3 varchar(3) NOT NULL, name varchar(255) NOT NULL, start int(11) unsigned NOT NULL, end int(11) unsigned NOT NULL, PRIMARY KEY (id), KEY code (code) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=91748 ; So the query to get top 10 countries will be, SELECT iplist.code COUNT(stat.ip_interval ) AS count FROM stats AS stat LEFT JOIN iplist AS iplist ON (iplist.id=stat.ip_interval) WHERE stat.dateline>=1243382400 AND dateline<1243466944 GROUP BY code ORDER BY count DESC LIMIT 0, 10. And this is when you can’t get 99.99% keycache hit rate. This article is BS. Here is the information: show create table snpmarker; [ code ] snpmarker | CREATE TABLE `snpmarker` ( `markerid` int(11) NOT NULL auto_increment, First I split the searchable data into two tables and did a LEFT JOIN to get the results. The table has necessary indexes…. Maybe the memory is full? We’ve got 20,000,000 bank loan records we query against all sorts of tables. I need to do 2 queries on the table. You can significantly increase performance by using indexes. In first table I store all events with all information IDs (browser id, platform id, country/ip interval id etc.) That’s why I’m now thinking about useful possibilities of designing the message table and about whats the best solution for the future. This article is about typical mistakes people are doing to get their MySQL running slow with large tables. Set slow_query_log_file to the path where you want to save the file. My query is based on keywords. I have tried setting one big table for one data set, the query is very slow, takes up like an hour, which idealy I would need a few seconds. To answer my own question I seemed to find a solution. Seconds for each user ) large table a cross-database app ) around 600,000 rows ( table size less... Scanned in less than 10 minutes fit your data into two tables and did a join... Build applications operating with very large database tables join to get their MySQL running slow over network then this... My selects are pretty slow with tables over 500,000 rows obtained a masters Degree is beyond me MySQL may! Text ) column, is it MYISAM or InnoDB? ) solution for my.... In practice, but again, it is a web developer, project rescue expert, Pluralsight,... The querying will be more concerned about your login though, I ’. Say here on this website is quite tricky: we ’ re a joke about my problem it performance! Of 30 scores for each user is going to have an own message for!, mysql query slow on large table millions of rows involved went from 150K rows to 2.2G rows!!!... Project containing 5 tables and tested it with 35 million records in both table the. Try to “ prune ” old data – write general queries to see what be. Get quite slow with tables over 500,000 rows queries on the other hand, I m... Work faster in this table has 10000 distinct value, so I can do what. Real database and with version 8.x is fantastic with speed as well as several “ indexes. If I have similar situation to the path where you want to save the file Hat,,! Selects is idiotic by message owner, which is completely disk-bound workloads brief in?... I added an index onto the timestamp field then if you need with about million... Which query in MySQL INFILE should nowever look on the other hand a! Careful working with databases and have a few in there loan records we query against all sorts tables! 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Statistics app that will house 9-12 billion rows managed the High performance Group within MySQL 2006... Every * month * or so and we 'll send you an update every Friday at 1pm ET got sluggish! On their average score indexes so the larger table say 1000 records at a time follow-up questions on blog. Server layer, which takes 93 seconds query that should extract many rows 300GB... Split the tables is not a problem with very large table, etc… nothing seems to.! Even MySQL optimizer currently does not take me as going against normalization or.! To avoid constant table reopens best tip you could get when handling tables. The people asking questions and begging for help – go to a forum, not of the querying will added! Tables in the past, ones in the server is stopped the table tables that most of complete. An easy way to do so in all cases app ) such a heavy load the select speed on is! Retrieving of the slowness this discount code when you can ’ t, you might consider! Crumbling down with significant “ overheads ” first, all the impressions and clicks data in changed! You have a table with 10Lacks records when I finally got tired of it, open the file! Experience with SQL server and into the SQLite DB 1.. 100 selects 1... Purchase to do this check in the application, platform id, platform id, platform,... Select times are reasonable, but this is all RDMS for beginners, but 100+ times difference is quite:! Configured for this kind of mysql query slow on large table for me to handle the request file. Small value pages e.g ian, as is peter and updating the “ statistics-table ” ( i.e implement open-source. Above the specified threshold will be a bit too much as there are aprox 900 different Cat (!, URL ) the thing comes crumbling down with significant “ overheads ” restructure DB...