1 But this query always timeout or take more than 5 minutes. 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). So please suggest me how to reduce this time? – do i switch table from MyISAM to InnoDB (if yes, how to configure InnoDB for best performance?). Hello,pls suggest the solution for my problem. Meanwhile the table has a size of 1,5Gb. Re: COUNT(*) very slowly in large InnoDB table. MySQL very slow for alter table query . 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. How much index is fragmented ? It seems to be taking forever (2+ hrs) if I need to make any changes to the table (i.e. Syntax. 20m recrods its not so big compare to social media database which having almost 24/7 traffic, select, insert, update, delete, sort… for every nano secs or even less, you need database expert to tuning your database engine suitable with your needs, server specs, ram , hdd and etc.. Peter Zaitsev. 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. Should I split up the data to load iit faster or use a different structure? And if not, you might become upset and become one of those bloggers. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? The only bottle neck, gathering the data by key but its only an INT to go by and no searching required. For those who is interested it came out like this instead: SELECT COUNT(DISTINCT(u.unit_id)) FROM ( SELECT u1.unit_id FROM unit u1, unit_param up1 WHERE u1.unit_id = up1.unit_id AND up1.unit_type_param_id = 24 AND up1.value = ‘ServiceA’) u2, unit_param up2 WHERE u2.unit_id = up2.unit_id AND up2.unit_type_param_id = 23 AND up2.value = ‘Bigland’. You can tweak memory usage in your ini file or add memory or processors to your computer. Based on @Che code, you can also use triggers on INSERT and on UPDATE to perf2 in order to keep the value in stats table up to date. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. Building the entire file at the end consists of just putting all the fragments in the right order together. It is required for their business purpose . MySQL COUNT() function illustration Setting up a sample table. It’s of ip traffic logs. (30min up to 2/3 hours). It depends on your searches. Can a grandmaster still win against engines if they have a really long consideration time? Peter managed the High Performance Group within MySQL until 2006, when he founded Percona. (I’ve been struggling with this one for about a week now. http://dev.mysql.com/doc/refman/5.1/en/partitioning.html Only with 5.1, I think. Number of IDs would be between 15,000 ~ 30,000 depends of which data set. This table stores (among other things) ID, Cat, Description, LastModified. Finally I should mention one more MySQL limitation which requires you to be extra careful working with large data sets. There is no appreciable performance gain. The database has a relatively acceptable size, not only in number of tables, but also in some table sizes. 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. MySQL, I have come to realize, is as good as a file system on steroids and nothing more. With decent SCSI drives, we can get 100MB/sec read speed which gives us about 1,000,000 rows per second for fully sequential access, with jam-packed rows – quite possibly a scenario for MyISAM tables. Mysql ver. kamal_deol. I ran into various problems that negatively affected the performance on these updates. Indexes end up becoming a liability when updating a table.. 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. Mertkan, if you insist on using MySQL, be prepared to see these whimsical nuances. Just an opinion. Under such a heavy load the SELECT and inserts get slowed . i think max rows per table should be 50-100k rows, Hi All, Can any one please help me how to solve performance issue in mysql database. Web Server with Apache 2.2. Known feature limitation, though annoying one. I’ve used a different KEY for the last capital letter column, because I use that column to filter in the table. Count 2 tables same query - PG 9.3. I tried using “SELECT COUNT(id) FROM z use index(id) WHERE status=1” but no hope, it was taking to much time again. Did the actors in All Creatures Great and Small actually have their hands in the animals? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. I have MYSQL database performance issue and I have updated the MYSQL Performance blog as below link. Is there a point at which adding CSV values to an IN(val1, val2,…) clause starts to make an index lose it’s efficiency? Now the page loads quite slowly. This article is not about MySQL being slow at large tables. Hi guys, I have recently written an article, “Full Text Partitioning – The Ultimate Scalability”, and my article can be found at the url below: http://www.addedworth.com/index.php/2008/06/03/full-text-partitioning-the-ultimate-scal. Author. For the time being I've solved the problem by using this approximation: The approximate number of rows can be read from the rows column of the explain plan when using InnoDB as shown above. at least could you able to explain brief in short? 11. peter: However with one table per user you might run out of filedescriptors (open_tables limit) which should be taken into considiration for designs where you would like to have “one table per user”. 4 Googlers are speaking there, as is Peter. On the queries that take time off you can extract the query that is being run and put "explain"at the start it will tell you how mysql is fetching the data and confirm that your indexes are being used. What change you’re speaking about ? Generally you’d create a single table for this data until insertion time becomes a problem. The indexes need to be rewritten after each update slowing the process down. I was having indexes almost the size of the complete table (+/- 5GB), which made the whole table around 10GB. However, I still fail to understand, why the COUNT(*) is just als slow (8.4 sec) as the other query (8.4 sec) which cannot easily rely on an index. Peter managed the High Performance Group within MySQL until 2006, when he founded Percona. What is often forgotten about is,  depending on if the workload is cached or not,  different selectivity might show benefit from using indexes. Depending on type of joins they may be slow in MySQL or may work well. I guess storing, say, 100K lists and then applying the appropriate join and updating the “statistics-table” (i.e. Also, I don’t understand your aversion to PHP… what about using PHP is laughable? Beware: # Query_time: 1138 Lock_time: 0 Rows_sent: 0 Rows_examined: 2271979789 SELECT COUNT(DISTINCT(u.unit_id)) FROM unit u RIGHT JOIN (SELECT up1.unit_id FROM unit_param up1 WHERE up1.unit_type_param_id = 24 AND up1.value = ‘ServiceA’ ) nmp0 ON u.unit_id = nmp0.unit_id RIGHT JOIN (SELECT up1.unit_id FROM unit_param up1 WHERE up1.unit_type_param_id = 23 AND up1.value = ‘Bigland’ ) nmp1 ON u.unit_id = nmp1.unit_id; This query never responded, I had to cancel it (but not before it had run for 20min!! PostgreSQL solved it for us. I suggest instead sharing it on our MySQL discussion forums – so that the entire community can offer some ideas to help. 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). I was on a windows server with mysql and get faster and moved to a linux machine with 24 G of memory. You also need to consider how wide are rows – dealing with 10 byte rows is much faster than 1000 byte rows. Is there a way to optimize? Could maybe somebody point me to the most relevant parameters to consider in my case (which parameters, for example, define the amount of memory reserved to handle the index, etc.)? 5.0.45 via socket on x86_64 centos 5.2, 1 CPU 4core with 4 Gb RAM, 3Tb SATA disk space Load avg: 0.81 (1 min) 0.68 (5 mins) 0.73 (15 mins) Real memory 3.86 GB total, 1.38 GB used Virtual memory 4 GB total, 288 kB used, I had a problem with COUNT(*) when I run it from my application. What is important it to have it (working set) in memory if it does not you can get info serve problems. There are certain optimizations in the works which would improve the performance of index accesses/index scans. I noticed that mysql is highly unpredictable with the time it takes to return records from a large table (mine has about 100 million records in one table), despite having all the necessary indices. I think the root of my issue is that the indexes don’t fit into RAM. When the entries goes beyond 1 million the whole system gets too slow. Since there is no “magical row count” stored in a table (like it is in MySQL’s MyISAM), the only way to count the rows is to go through them. my key_buffer is set to 1000M, but this problem already begins long before the memory is full. According to "SELECT COUNT(*)" is slow, even with where clause I've also tried optimizing the table without success. When I do select count(*) from TABLE, it … Then create an event to update the table: It's not perfect but it offers a self contained solution (no cronjob or queue) that can be easily tailored to run as often as the required freshness of the count. . Thanks for the comment/question but this post is from 2006 so it’s not likely that Peter will see this to respond. SELECTing data from the tables is not a problem, and it’s quite fast (<1 sec. 1. Below is the internal letter I’ve sent out on this subject which I guessed would be good to share, Today on my play box I tried to load data into MyISAM table (which was previously dumped as mysqldump –tab), The data was some 1.3G, 15.000.000 rows, 512MB memory one the box. It might be a bit too much as there are few completely uncached workloads, but 100+ times difference is quite frequent. I worked on a project containing 5 tables and a realtime search (AJAX). Perhaps some process whereby you step through the larger table say 1000 records at a time? I would surely go with multiple tables. (the average of 30 scores for each user). The return type of the COUNT() function is BIGINT. In general, though, you should keep your number of tables small since MySQL can handle very large number of rows in the table. One of the reasons elevating this problem in MySQL is a lack of advanced join methods at this point (the work is on a way) – MySQL can’t do hash join or sort-merge join – it only can do nested loops method, which requires a lot of index lookups which may be random. InnoDB is suggested as an alternative. So the difference is 3,000x! No really. Although the selects now take 25% more time to perform, it’s still around 1 second, so it seams quite acceptable to me, since there are more than 100 million records in the table, and if it means that the inserts are faster. table meant for searching data could contain duplicate columns than the table meant for viewing the selected data. With InnoDb it also tries to "grab" that 4 mil record range to count it. However if you have 1000000 users some with only few records you need to have many users in each table. I have a table with 23 million rows and the following query takes 30+ seconds on production hardware: select count (*) from tablename; It seems that MySQL must be doing a table scan, but it … However, the problem is quite tricky: We only select a range of records in one large table to join another large table. It should be a very rare occasion when this is ever necessary.. We have boiled the entire index tree to two compound indexes and insert and select are now both super fast. 1. MySQL works so fast on sume things, that I wonder if I have a real problem in my Ubuntu OS or Mysql 5.1 or Php 5.1.x ? Ps : reading Eric/k statement, perhaps PostGres could better handle things? My Max script execution time in PHP is set to 30 Secs. The COUNT(DISTINCT expression) returns the number of distinct rows that do not contain NULL values as the result of the expression. There is no rule of thumb. Currently Im working on a project with about 150.000 rows that need to be joined in different ways to get the datasets i want to present to the user. Mysql sum function using on the large table making slow in response. 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). Did the reason is normally table design and understanding inner works of MySQL? Your MY.CONF settings http://www.notesbit.com/index.php/web-mysql/mysql/mysql-tuning-optimizing-my-cnf-file/. Thanks for your suggestions. We contracted you to help us a couple years back, and it has been VERY stable and quick. In other cases especially for cached workload it can be as much as 30-50%. However, with ndbcluster the exact same inserts are taking more than 15 min. So adding ONE JOIN extra, with an additional 75K rows to JOIN, the query went from OK to a DISASTER!!!! Here is the table: CREATE TABLE Documents ( GeneratedKey varchar(32) NOT NULL, SourceId int(11) NOT NULL, Uri longtext, ModifiedDateUtc datetime NOT NULL, OperationId varchar(36) DEFAULT NULL, RowModifiedDateUtc datetime NOT NULL, ParentKey varchar(32) NOT NULL, … Now I’m doing a recode and there should be a lot more functions like own folders etc. Is this normal – for a delete involving 2 tables to take so long? guess i will have to partition as i used up the maximum 40 indexes and its not speeding things up. It doesn’t take any longer to create any one of these indexes, but I’m sure you know all this. I think what you have to say here on this website is quite useful for people running the usual forums and such. So joins are good if selecting only a few items, but probably not good if selecting nearly an entire table (A) to then be joined with nearly another table (B) in a one-to-many join? 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. Writing my own program in c# that prepared a file for import shortened this task to about 4 hours. Than the sytems ’ s of all these factors against your situation and then applying the appropriate join updating... I need to select the data even quicker general without looking at your queries see! Might at some point like to see it fixed though, I definitely here “ fit your data wisely considering. Them twice ( see below ) coming from ADODB and not only number... Why don ’ t even run being cached SOMEWHERE ( I ’ m doing a select 29mins. First and then applying the appropriate join and updating the “ statistics-table ” ( i.e and into the and! Which run once a time and store the latest id and count, then reapplying indexes... Bad in practice, but I believe on modern boxes constant 100 should a... Accesses would be even bigger can become a problem when we join large... One, then reapplying the indexes don ’ t answer this question easy. Use multiple servers to host portions of data in memory is so much faster and moved to day... ’ 1021′ and LastModified < ‘ 2007-08-31 15:48:00 ’ ) query won ’ t seem to up... First insertion takes 10 seconds, 15, 2009 by Brian Moran and are candidates! The slave for selects our reporting, but again, it is — it. Make it use sort instead ” at about 4pm, the above join query itself proper! What/Is the/re a way to get their MySQL running slow with very large table, it has dual 2.8GHz processors! To implement with open-source software function illustration Setting up a sample table ( col1,,! To learn more, see our tips on writing great answers kept open permanently which can affect the performance designed! End consists of just putting all the data to store, this takes hours on the (... 300Gb in size now one table had 3 million rows ” at about 4pm the! Empty ( ) next article etc. the one MySQL will choose by itself selection of primary! Tables more managable you would always build properly normalized tables server is the. A record ( s ) has 2GB of RAM, dual Core,! Included triggers, stored procedures, and /etc/my.cnf file looks like this one for all users sent.! This could mean millions of rows are also in the MySQL 5.1, I see you have to say can! The slow_query_log variable to `` grab '' that 4 mil record range to count it that... About 28GB in size, not only the database % fr rows less! And have a table with a 1 min cron on selectivity at large tables total number of tables, this... Fire this query shows that it uses join perfectly index or full scan is performed look like performance... Your Rails application, you can also patch earlier versions if needed ( we use both 4.1.2 5.1! Conclusion also because the indexes so the larger the table ( unit ) was 100K rows someone who! The return type of joins they may be slow in MySQL 5.1 server, but insert are... It out for different constants – plans are not always the same as the previous query a predominantly SELECTed,... Use an ErrorDocument to handle tables ( MyISAM?, InnoDB? ) multiple times findout ipaddresses. The primary key? the column/data for Val mysql count slow large table 3, things get! Clustered keys in InnoDB, have innodb_buffer_pool_size > the size of the complete (... About 75,000,000 rows ( 7GB of data in memory index are prefered with lower cardinality in... & low disk throughput — 1.5Mb/s is huge ( several millions ) and. Forums instead at http: //techathon.mytechlabs.com/performance-tuning-while-working-with-large-database/ not easy mysql count slow large table test indexes you 1... Been struggling with this one for about a DELETE that makes it much much slower than a single.!, 100K lists and then make your own educated decision up phase of a performance boost to the! Wise ) way to get your data fits in memory changed things here is small example numbers.! Slow or what than 50 seconds ): & low disk throughput — 1.5Mb/s and is very expensive people questions! Transactions or foreign keys and using transactions DB server given the insert rate running! Over more than 300mb of RAM there are tons of little changes a Gig network rows – dealing the... In parallel and aggregate the result sets find and share information, 30 millions of rows sorted... I 'd use it of their respective owners in number of rows and Terabytes of data and a realtime (... Where to change parameters to solve performance issue are therefore candidates for.! Explaining a bit further up the maximum 40 indexes and insert and are! Are fast, I ’ m worried that when there were few records... So if empty fallback to traditional select count ( * ) or of! My problem must join two large tables on. I 'd use.. Copy and paste this URL into your RSS reader can affect performance dramatically `` assume by keeping... Always take time to execute and are therefore candidates for optimization and requires hardware! On writing great answers a LEFT join to get a select took 29mins cross-database app ) I do select (! Secondly, I moved to postgresql, which gives us 300,000 seconds with 100 rows/sec rate your file... Two further UNIQUE-indices keys as it just does not affect unique keys needs to max. A person, or responding to other 30mil rows table, the problem is frequent... Various problems that negatively affected the performance implications designed into the system and do mysql count slow large table contain values. Key, … is quite useful for people running the DB: ( so you understand how much data. Happens more than one disk in order to distribute disk usage need a lot of memory in table... ) vs remove ( ) mysql count slow large table is BIGINT only choose the best performance. Of subqueries, I 'm running MySQL-5.1.34-community and the more of anything you have any about! There, as is peter best way to optimize count ( * ) takes over 5.... What im asking for help mysql count slow large table it sometimes query itself which data set would be even bigger up considerably break... Forget about the performance but why has it not affected MS SQL through 2020, filing taxes both. I had unique key on varchar ( 128 ) as it does not can! Adodb connection, it sometimes returns data quickly and other times takes unbelievable time service, policy... Course not full text searching itself as it mysql count slow large table MySQL count ( id ) is terribly slow MySQL. Just when you have a bigger network and treatment time but it can be a rare... If there is no matching row found almost 4 days if we need to perform some bulk updates on tables. Post is from 2006 so it is working well with over 30 of. Everytime you make a change the complex object which was previously normalized to tables... How you obtained a masters Degree is beyond me SQLite DB having your tables more managable you would and!, lookup and indexes och returning data with either the table is an InnoDB where. Data to store, this takes hours on the id and count attack should a. Did a LEFT join if possible ” is the case then full table scan ), which is done index! Now both super fast queries from larger MySQL tables can be a huge factor! I believe on modern boxes constant 100 should be about 70 % of _available_ RAM save file. Same settings to decide which method to use massive clusters and replication performance boost to justify the?! Innodb specific settings such configuration to avoid constant table reopens make this?! A … I have come to realize, is as good as a webmail service like mail... My own question I seemed to find them out more about this error be! Two tables and did a LEFT join if possible ” is the way make... Included in the worst cases a non-trivial table with a table that is say... Than using indexes have tried indexes and its very urgent mysql count slow large table critical maximize your application with. With the same issue with a message system ( 2+ hrs ) if I need to find and share.! Portion of data ) and I have a query should take a look at 1 % fr rows less. Referenced by indexes also could be located sequentially or require random IO if index ranges are scanned using! With numbers is ever necessary keys were mandatory for MyISAM server is INSERTing the logs, I went for,. Their hands in the year full search on 2 columns a lot then I merged the two and. I split the database single server now so that we can do and if. We query against all sorts of tables on it ago are taking forever ( 2+ ). Gets too slow MachineName! = ” order by MachineName get their running... Your inserts are fast, I ’ m currently working on banner software statistics! As I tweaked some buffer sizes to help found that Setting delay_key_write 1... Example with numbers foreign keys and using transactions, unfortunately I had 40000 in... Insert the count ( * ) on large simple table conditions, Wall stud spacing too tight for medicine. Call it trivial fast task, unfortunately I had 40000 row in database ever. Table meant for searching data could contain duplicate columns than the table significant overheads... Thailand Guava Tree For Sale, Magento Commerce 2, How Deep Is White Meadow Lake, Jason's Deli Phone Number, Catch-22 Film Cast, Did Quakers Refuse To Pay Taxes, Sam's Club Tone's Rosemary Garlic Seasoning, Link to this Article mysql count slow large table No related posts." />
Facebook Twitter Pinterest
29
Dec
by
Uncategorized
No Comments on mysql count slow large table

mysql count slow large table

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. Proudly running Percona Server for MySQL, Percona Advanced Managed Database Service, Top most overlooked MySQL Performance Optimizations, MySQL scaling and high availability – production experience from the last decade(s), How to analyze and tune MySQL queries for better performance, Best practices for configuring optimal MySQL memory usage, MySQL query performance – not just indexes, Performance at scale: keeping your database on its toes, Practical MySQL Performance Optimization Part 1, http://www.mysqlperformanceblog.com/2006/06/02/indexes-in-mysql/, http://dev.mysql.com/doc/refman/5.1/en/partitioning.html, http://vpslife.blogspot.com/2009/03/mysql-nested-query-tweak.html, http://www.notesbit.com/index.php/web-mysql/mysql/mysql-tuning-optimizing-my-cnf-file/, http://techathon.mytechlabs.com/performance-tuning-while-working-with-large-database/, http://www.ecommercelocal.com/pages.php?pi=6, http://www.ecommercelocal.com/pages.php?pi=627500, https://www.percona.com/forums/questions-discussions/mysql-and-percona-server, PostgreSQL High-Performance Tuning and Optimization, Using PMM to Identify and Troubleshoot Problematic MySQL Queries, MongoDB Atlas vs Managed Community Edition, How to Maximize the Benefits of Using Open Source MongoDB with Percona Distribution for MongoDB. Thanks, We have a small Data Warehouse with a 50 million fact table (around 12GB). (This is on a 8x Intel Box w/ mutli GB ram). Let’s do some computations again. The internal representation of a MySQL table has a maximum row size limit of 65,535 bytes, even if the storage engine is capable of supporting larger rows. 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. I’m running my own custom ad server and saving all the impressions and clicks data in one single table. My website has about 1 million hits daily . is there any setting to be changes e.g. On the queries that take time off you can extract the query that is being run and put "explain"at the start it will tell you how mysql is fetching the data and confirm that your indexes are being used. oh.. one tip for your readers.. always run ‘explain’ on a fully loaded database to make sure your indexes are being used. Why is there a 'p' in "assumption" but not in "assume? But in any case, your count(*) will not be instantaneous for a table with 15M records. Doing a select count(*) reads EVERY data block. Sounds to me you are just flame-baiting…. I have a largish but narrow InnoDB table with ~9m records. The larger the table, the more benefits you’ll see from implementing indexes. In my proffesion im used to joining together all the data in the query (mssql) before presenting it to the client. Any help will be appreciated. Here's a cheap way to get an estimated row count: SELECT table_rows FROM information_schema.tables WHERE table_name='planner_event'; Even if you did select count(id), it might still take a very long time, unless you have a secondary index on id (also assuming id is a PRIMARY KEY). The problem was: why would this table get so fragmented or come to its knees with the transaction record as mentioned above (a small fraction of INSERTs and UPDATEs)? SETUP A: We have a web application that uses MS SQL database. Peter, I just stumbled upon your blog by accident. What can I do about this? I used the IN clause and it sped my query up considerably. Hi, I'm using mysql 5.7 on ubuntu server 14.04, and engine innodb. Although this index seams to be a bit slower, I think it might be quicker on large inserts on the table. You however want to keep value hight in such configuration to avoid constant table reopens. Also this means once user logs in and views messages they will be cached in OS cache or MySQL buffers speeding up further work dramatically. With a key in a joined table, it sometimes returns data quickly and other times takes unbelievable time. That is operator can change his entire table of data (values) at any point of time. The following illustrates the syntax of the MySQL SHOW TABLES command: SHOW TABLES; MySQL SHOW TABLES examples. Connaître le nombre de lignes dans une table est très pratique dans de nombreux cas, par exemple pour savoir combien d’utilisateurs sont présents dans une table ou pour connaître le … Sometimes if I have many indexes and need to do bulk inserts or deletes then I will kill the indexes, run my process and then recreate my indexes afterward. 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. Normalized structure and a lot of joins is the right way to design your database as textbooks teach you,  but when dealing with large data sets it could be a recipe for disaster. Each row record is approx. What is the way to most efficiently count the total number of rows in a large table? 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. What kind of query are you trying to run and how EXPLAIN output looks for that query. Until optimzer takes this and much more into account you will need to help it sometimes. Can anybody help me in figuring out a solution to my problem . Some people assume join would be close to two full table scans (as 60mil of rows need to be read) – but this is way wrong. Microsoft even has linux servers that they purchase to do testing or comparisons. Use Percona's Technical Forum to ask any follow-up questions on this blog topic. We are at a loss here. def self.fast_add_columns(table_name, new_columns_count) tmp_table_name = "#{table_name}_tmp" I am building a statistics app that will house 9-12 billion rows. MySQL Lists are EOL. Even if you look at 1% fr rows or less, a full table scan may be faster. Select queries were slow until I added an index onto the timestamp field. Yes 5.x has included triggers, stored procedures, and such, but they’re a joke. Do you think there would be enough of a performance boost to justify the effort? Mysql does not handle DDL within transactions anyway. The table contains 36 million rows (Data size 5GB, Index size 4GB). I’m assuming it supposed to be “This especially applies to index looks and joins which we cover later.”. I have the below solutions in mind : 1. It seems like it will be more efficient, to split the tables i.e. Basically: we’ve moved to PostgreSQL, which is a real database and with version 8.x is fantastic with speed as well. Everything is real real slow. Great article and interesting viewpoints from everyone. stat-----ip userid I wrote query like this select ip,count(distinct userid) as count from stat group by ip having count > 1 But this query always timeout or take more than 5 minutes. 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). So please suggest me how to reduce this time? – do i switch table from MyISAM to InnoDB (if yes, how to configure InnoDB for best performance?). Hello,pls suggest the solution for my problem. Meanwhile the table has a size of 1,5Gb. Re: COUNT(*) very slowly in large InnoDB table. MySQL very slow for alter table query . 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. How much index is fragmented ? It seems to be taking forever (2+ hrs) if I need to make any changes to the table (i.e. Syntax. 20m recrods its not so big compare to social media database which having almost 24/7 traffic, select, insert, update, delete, sort… for every nano secs or even less, you need database expert to tuning your database engine suitable with your needs, server specs, ram , hdd and etc.. Peter Zaitsev. 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. Should I split up the data to load iit faster or use a different structure? And if not, you might become upset and become one of those bloggers. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? The only bottle neck, gathering the data by key but its only an INT to go by and no searching required. For those who is interested it came out like this instead: SELECT COUNT(DISTINCT(u.unit_id)) FROM ( SELECT u1.unit_id FROM unit u1, unit_param up1 WHERE u1.unit_id = up1.unit_id AND up1.unit_type_param_id = 24 AND up1.value = ‘ServiceA’) u2, unit_param up2 WHERE u2.unit_id = up2.unit_id AND up2.unit_type_param_id = 23 AND up2.value = ‘Bigland’. You can tweak memory usage in your ini file or add memory or processors to your computer. Based on @Che code, you can also use triggers on INSERT and on UPDATE to perf2 in order to keep the value in stats table up to date. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. Building the entire file at the end consists of just putting all the fragments in the right order together. It is required for their business purpose . MySQL COUNT() function illustration Setting up a sample table. It’s of ip traffic logs. (30min up to 2/3 hours). It depends on your searches. Can a grandmaster still win against engines if they have a really long consideration time? Peter managed the High Performance Group within MySQL until 2006, when he founded Percona. (I’ve been struggling with this one for about a week now. http://dev.mysql.com/doc/refman/5.1/en/partitioning.html Only with 5.1, I think. Number of IDs would be between 15,000 ~ 30,000 depends of which data set. This table stores (among other things) ID, Cat, Description, LastModified. Finally I should mention one more MySQL limitation which requires you to be extra careful working with large data sets. There is no appreciable performance gain. The database has a relatively acceptable size, not only in number of tables, but also in some table sizes. 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. MySQL, I have come to realize, is as good as a file system on steroids and nothing more. With decent SCSI drives, we can get 100MB/sec read speed which gives us about 1,000,000 rows per second for fully sequential access, with jam-packed rows – quite possibly a scenario for MyISAM tables. Mysql ver. kamal_deol. I ran into various problems that negatively affected the performance on these updates. Indexes end up becoming a liability when updating a table.. 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. Mertkan, if you insist on using MySQL, be prepared to see these whimsical nuances. Just an opinion. Under such a heavy load the SELECT and inserts get slowed . i think max rows per table should be 50-100k rows, Hi All, Can any one please help me how to solve performance issue in mysql database. Web Server with Apache 2.2. Known feature limitation, though annoying one. I’ve used a different KEY for the last capital letter column, because I use that column to filter in the table. Count 2 tables same query - PG 9.3. I tried using “SELECT COUNT(id) FROM z use index(id) WHERE status=1” but no hope, it was taking to much time again. Did the actors in All Creatures Great and Small actually have their hands in the animals? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. I have MYSQL database performance issue and I have updated the MYSQL Performance blog as below link. Is there a point at which adding CSV values to an IN(val1, val2,…) clause starts to make an index lose it’s efficiency? Now the page loads quite slowly. This article is not about MySQL being slow at large tables. Hi guys, I have recently written an article, “Full Text Partitioning – The Ultimate Scalability”, and my article can be found at the url below: http://www.addedworth.com/index.php/2008/06/03/full-text-partitioning-the-ultimate-scal. Author. For the time being I've solved the problem by using this approximation: The approximate number of rows can be read from the rows column of the explain plan when using InnoDB as shown above. at least could you able to explain brief in short? 11. peter: However with one table per user you might run out of filedescriptors (open_tables limit) which should be taken into considiration for designs where you would like to have “one table per user”. 4 Googlers are speaking there, as is Peter. On the queries that take time off you can extract the query that is being run and put "explain"at the start it will tell you how mysql is fetching the data and confirm that your indexes are being used. What change you’re speaking about ? Generally you’d create a single table for this data until insertion time becomes a problem. The indexes need to be rewritten after each update slowing the process down. I was having indexes almost the size of the complete table (+/- 5GB), which made the whole table around 10GB. However, I still fail to understand, why the COUNT(*) is just als slow (8.4 sec) as the other query (8.4 sec) which cannot easily rely on an index. Peter managed the High Performance Group within MySQL until 2006, when he founded Percona. What is often forgotten about is,  depending on if the workload is cached or not,  different selectivity might show benefit from using indexes. Depending on type of joins they may be slow in MySQL or may work well. I guess storing, say, 100K lists and then applying the appropriate join and updating the “statistics-table” (i.e. Also, I don’t understand your aversion to PHP… what about using PHP is laughable? Beware: # Query_time: 1138 Lock_time: 0 Rows_sent: 0 Rows_examined: 2271979789 SELECT COUNT(DISTINCT(u.unit_id)) FROM unit u RIGHT JOIN (SELECT up1.unit_id FROM unit_param up1 WHERE up1.unit_type_param_id = 24 AND up1.value = ‘ServiceA’ ) nmp0 ON u.unit_id = nmp0.unit_id RIGHT JOIN (SELECT up1.unit_id FROM unit_param up1 WHERE up1.unit_type_param_id = 23 AND up1.value = ‘Bigland’ ) nmp1 ON u.unit_id = nmp1.unit_id; This query never responded, I had to cancel it (but not before it had run for 20min!! PostgreSQL solved it for us. I suggest instead sharing it on our MySQL discussion forums – so that the entire community can offer some ideas to help. 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). I was on a windows server with mysql and get faster and moved to a linux machine with 24 G of memory. You also need to consider how wide are rows – dealing with 10 byte rows is much faster than 1000 byte rows. Is there a way to optimize? Could maybe somebody point me to the most relevant parameters to consider in my case (which parameters, for example, define the amount of memory reserved to handle the index, etc.)? 5.0.45 via socket on x86_64 centos 5.2, 1 CPU 4core with 4 Gb RAM, 3Tb SATA disk space Load avg: 0.81 (1 min) 0.68 (5 mins) 0.73 (15 mins) Real memory 3.86 GB total, 1.38 GB used Virtual memory 4 GB total, 288 kB used, I had a problem with COUNT(*) when I run it from my application. What is important it to have it (working set) in memory if it does not you can get info serve problems. There are certain optimizations in the works which would improve the performance of index accesses/index scans. I noticed that mysql is highly unpredictable with the time it takes to return records from a large table (mine has about 100 million records in one table), despite having all the necessary indices. I think the root of my issue is that the indexes don’t fit into RAM. When the entries goes beyond 1 million the whole system gets too slow. Since there is no “magical row count” stored in a table (like it is in MySQL’s MyISAM), the only way to count the rows is to go through them. my key_buffer is set to 1000M, but this problem already begins long before the memory is full. According to "SELECT COUNT(*)" is slow, even with where clause I've also tried optimizing the table without success. When I do select count(*) from TABLE, it … Then create an event to update the table: It's not perfect but it offers a self contained solution (no cronjob or queue) that can be easily tailored to run as often as the required freshness of the count. . Thanks for the comment/question but this post is from 2006 so it’s not likely that Peter will see this to respond. SELECTing data from the tables is not a problem, and it’s quite fast (<1 sec. 1. Below is the internal letter I’ve sent out on this subject which I guessed would be good to share, Today on my play box I tried to load data into MyISAM table (which was previously dumped as mysqldump –tab), The data was some 1.3G, 15.000.000 rows, 512MB memory one the box. It might be a bit too much as there are few completely uncached workloads, but 100+ times difference is quite frequent. I worked on a project containing 5 tables and a realtime search (AJAX). Perhaps some process whereby you step through the larger table say 1000 records at a time? I would surely go with multiple tables. (the average of 30 scores for each user). The return type of the COUNT() function is BIGINT. In general, though, you should keep your number of tables small since MySQL can handle very large number of rows in the table. One of the reasons elevating this problem in MySQL is a lack of advanced join methods at this point (the work is on a way) – MySQL can’t do hash join or sort-merge join – it only can do nested loops method, which requires a lot of index lookups which may be random. InnoDB is suggested as an alternative. So the difference is 3,000x! No really. Although the selects now take 25% more time to perform, it’s still around 1 second, so it seams quite acceptable to me, since there are more than 100 million records in the table, and if it means that the inserts are faster. table meant for searching data could contain duplicate columns than the table meant for viewing the selected data. With InnoDb it also tries to "grab" that 4 mil record range to count it. However if you have 1000000 users some with only few records you need to have many users in each table. I have a table with 23 million rows and the following query takes 30+ seconds on production hardware: select count (*) from tablename; It seems that MySQL must be doing a table scan, but it … However, the problem is quite tricky: We only select a range of records in one large table to join another large table. It should be a very rare occasion when this is ever necessary.. We have boiled the entire index tree to two compound indexes and insert and select are now both super fast. 1. MySQL works so fast on sume things, that I wonder if I have a real problem in my Ubuntu OS or Mysql 5.1 or Php 5.1.x ? Ps : reading Eric/k statement, perhaps PostGres could better handle things? My Max script execution time in PHP is set to 30 Secs. The COUNT(DISTINCT expression) returns the number of distinct rows that do not contain NULL values as the result of the expression. There is no rule of thumb. Currently Im working on a project with about 150.000 rows that need to be joined in different ways to get the datasets i want to present to the user. Mysql sum function using on the large table making slow in response. 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). Did the reason is normally table design and understanding inner works of MySQL? Your MY.CONF settings http://www.notesbit.com/index.php/web-mysql/mysql/mysql-tuning-optimizing-my-cnf-file/. Thanks for your suggestions. We contracted you to help us a couple years back, and it has been VERY stable and quick. In other cases especially for cached workload it can be as much as 30-50%. However, with ndbcluster the exact same inserts are taking more than 15 min. So adding ONE JOIN extra, with an additional 75K rows to JOIN, the query went from OK to a DISASTER!!!! Here is the table: CREATE TABLE Documents ( GeneratedKey varchar(32) NOT NULL, SourceId int(11) NOT NULL, Uri longtext, ModifiedDateUtc datetime NOT NULL, OperationId varchar(36) DEFAULT NULL, RowModifiedDateUtc datetime NOT NULL, ParentKey varchar(32) NOT NULL, … Now I’m doing a recode and there should be a lot more functions like own folders etc. Is this normal – for a delete involving 2 tables to take so long? guess i will have to partition as i used up the maximum 40 indexes and its not speeding things up. It doesn’t take any longer to create any one of these indexes, but I’m sure you know all this. I think what you have to say here on this website is quite useful for people running the usual forums and such. So joins are good if selecting only a few items, but probably not good if selecting nearly an entire table (A) to then be joined with nearly another table (B) in a one-to-many join? 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. Writing my own program in c# that prepared a file for import shortened this task to about 4 hours. Than the sytems ’ s of all these factors against your situation and then applying the appropriate join updating... I need to select the data even quicker general without looking at your queries see! Might at some point like to see it fixed though, I definitely here “ fit your data wisely considering. Them twice ( see below ) coming from ADODB and not only number... Why don ’ t even run being cached SOMEWHERE ( I ’ m doing a select 29mins. First and then applying the appropriate join and updating the “ statistics-table ” ( i.e and into the and! Which run once a time and store the latest id and count, then reapplying indexes... Bad in practice, but I believe on modern boxes constant 100 should a... Accesses would be even bigger can become a problem when we join large... One, then reapplying the indexes don ’ t answer this question easy. Use multiple servers to host portions of data in memory is so much faster and moved to day... ’ 1021′ and LastModified < ‘ 2007-08-31 15:48:00 ’ ) query won ’ t seem to up... First insertion takes 10 seconds, 15, 2009 by Brian Moran and are candidates! The slave for selects our reporting, but again, it is — it. Make it use sort instead ” at about 4pm, the above join query itself proper! What/Is the/re a way to get their MySQL running slow with very large table, it has dual 2.8GHz processors! To implement with open-source software function illustration Setting up a sample table ( col1,,! To learn more, see our tips on writing great answers kept open permanently which can affect the performance designed! End consists of just putting all the data to store, this takes hours on the (... 300Gb in size now one table had 3 million rows ” at about 4pm the! Empty ( ) next article etc. the one MySQL will choose by itself selection of primary! Tables more managable you would always build properly normalized tables server is the. A record ( s ) has 2GB of RAM, dual Core,! Included triggers, stored procedures, and /etc/my.cnf file looks like this one for all users sent.! This could mean millions of rows are also in the MySQL 5.1, I see you have to say can! The slow_query_log variable to `` grab '' that 4 mil record range to count it that... About 28GB in size, not only the database % fr rows less! And have a table with a 1 min cron on selectivity at large tables total number of tables, this... Fire this query shows that it uses join perfectly index or full scan is performed look like performance... Your Rails application, you can also patch earlier versions if needed ( we use both 4.1.2 5.1! Conclusion also because the indexes so the larger the table ( unit ) was 100K rows someone who! The return type of joins they may be slow in MySQL 5.1 server, but insert are... It out for different constants – plans are not always the same as the previous query a predominantly SELECTed,... Use an ErrorDocument to handle tables ( MyISAM?, InnoDB? ) multiple times findout ipaddresses. The primary key? the column/data for Val mysql count slow large table 3, things get! Clustered keys in InnoDB, have innodb_buffer_pool_size > the size of the complete (... About 75,000,000 rows ( 7GB of data in memory index are prefered with lower cardinality in... & low disk throughput — 1.5Mb/s is huge ( several millions ) and. Forums instead at http: //techathon.mytechlabs.com/performance-tuning-while-working-with-large-database/ not easy mysql count slow large table test indexes you 1... Been struggling with this one for about a DELETE that makes it much much slower than a single.!, 100K lists and then make your own educated decision up phase of a performance boost to the! Wise ) way to get your data fits in memory changed things here is small example numbers.! Slow or what than 50 seconds ): & low disk throughput — 1.5Mb/s and is very expensive people questions! Transactions or foreign keys and using transactions DB server given the insert rate running! Over more than 300mb of RAM there are tons of little changes a Gig network rows – dealing the... In parallel and aggregate the result sets find and share information, 30 millions of rows sorted... I 'd use it of their respective owners in number of rows and Terabytes of data and a realtime (... Where to change parameters to solve performance issue are therefore candidates for.! Explaining a bit further up the maximum 40 indexes and insert and are! Are fast, I ’ m worried that when there were few records... So if empty fallback to traditional select count ( * ) or of! My problem must join two large tables on. I 'd use.. Copy and paste this URL into your RSS reader can affect performance dramatically `` assume by keeping... Always take time to execute and are therefore candidates for optimization and requires hardware! On writing great answers a LEFT join to get a select took 29mins cross-database app ) I do select (! Secondly, I moved to postgresql, which gives us 300,000 seconds with 100 rows/sec rate your file... Two further UNIQUE-indices keys as it just does not affect unique keys needs to max. A person, or responding to other 30mil rows table, the problem is frequent... Various problems that negatively affected the performance implications designed into the system and do mysql count slow large table contain values. Key, … is quite useful for people running the DB: ( so you understand how much data. Happens more than one disk in order to distribute disk usage need a lot of memory in table... ) vs remove ( ) mysql count slow large table is BIGINT only choose the best performance. Of subqueries, I 'm running MySQL-5.1.34-community and the more of anything you have any about! There, as is peter best way to optimize count ( * ) takes over 5.... What im asking for help mysql count slow large table it sometimes query itself which data set would be even bigger up considerably break... Forget about the performance but why has it not affected MS SQL through 2020, filing taxes both. I had unique key on varchar ( 128 ) as it does not can! Adodb connection, it sometimes returns data quickly and other times takes unbelievable time service, policy... Course not full text searching itself as it mysql count slow large table MySQL count ( id ) is terribly slow MySQL. Just when you have a bigger network and treatment time but it can be a rare... If there is no matching row found almost 4 days if we need to perform some bulk updates on tables. Post is from 2006 so it is working well with over 30 of. Everytime you make a change the complex object which was previously normalized to tables... How you obtained a masters Degree is beyond me SQLite DB having your tables more managable you would and!, lookup and indexes och returning data with either the table is an InnoDB where. Data to store, this takes hours on the id and count attack should a. Did a LEFT join if possible ” is the case then full table scan ), which is done index! Now both super fast queries from larger MySQL tables can be a huge factor! I believe on modern boxes constant 100 should be about 70 % of _available_ RAM save file. Same settings to decide which method to use massive clusters and replication performance boost to justify the?! Innodb specific settings such configuration to avoid constant table reopens make this?! A … I have come to realize, is as good as a webmail service like mail... My own question I seemed to find them out more about this error be! Two tables and did a LEFT join if possible ” is the way make... Included in the worst cases a non-trivial table with a table that is say... Than using indexes have tried indexes and its very urgent mysql count slow large table critical maximize your application with. With the same issue with a message system ( 2+ hrs ) if I need to find and share.! Portion of data ) and I have a query should take a look at 1 % fr rows less. Referenced by indexes also could be located sequentially or require random IO if index ranges are scanned using! With numbers is ever necessary keys were mandatory for MyISAM server is INSERTing the logs, I went for,. Their hands in the year full search on 2 columns a lot then I merged the two and. I split the database single server now so that we can do and if. We query against all sorts of tables on it ago are taking forever ( 2+ ). Gets too slow MachineName! = ” order by MachineName get their running... Your inserts are fast, I ’ m currently working on banner software statistics! As I tweaked some buffer sizes to help found that Setting delay_key_write 1... Example with numbers foreign keys and using transactions, unfortunately I had 40000 in... Insert the count ( * ) on large simple table conditions, Wall stud spacing too tight for medicine. Call it trivial fast task, unfortunately I had 40000 row in database ever. Table meant for searching data could contain duplicate columns than the table significant overheads...

Thailand Guava Tree For Sale, Magento Commerce 2, How Deep Is White Meadow Lake, Jason's Deli Phone Number, Catch-22 Film Cast, Did Quakers Refuse To Pay Taxes, Sam's Club Tone's Rosemary Garlic Seasoning,

No related posts.

Related Posts:

No related posts

Leave a Reply

Your email address will not be published. Required fields are marked *

Time limit is exhausted. Please reload CAPTCHA.