MySQL has a built-in slow query log. I am having a problem when I try to “prune” old data. Now my question is for a current project that I am developing. Question 1 I’m just wondering what you mean by ”keeping data in memory”? Is this wise .. i.e. So rank 1 through to rank 500,000. Query Cache Configuration. There for if you do a search on 2 columns a lot then I would have a separate index to speed up that query. 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. Only excuse to use MySQL these days is that it’s easy to set up. * If i run a ‘select from where…’ query, how long is the query likely to take? There are two main output tables that most of the querying will be done on. I am running data mining process that updates/inserts rows to the table (i.e. Opensource.com aspires to publish all content under a Creative Commons license but may not be able to do so in all cases. How do you feel InnoDB composite keys work as opposed to separate tables? 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. Totally misleading title. This measure is a precaution to reduce the possibility of a large log file either blocking database use or affecting performance. I am running MYSQL 5.0. I know some big websites are using MySQL, but we had neither the budget to throw all that staff, or time, at it. And update the current status on the blog itself. The opinions expressed on this website are those of each author, not of the author's employer or of Red Hat. MySQL Server provides flexible control over the destination of output written to the general query log and the slow query log, if those logs are enabled. As an example, in a basic config using MyISM tables I am able to insert 1million rows in about 1-2 min. I recently had to perform some bulk updates on semi-large tables (3 to 7 million rows) in MySQL. Is there a way to optimize? adding columns, changing column names, etc.) MySQL 4.1.8. Simply break up my big table into smaller ones? Hi, Im working proffesionally with postgresql and mssql and at home im using mysql for my leasure projects .. You might even consider to duplicate your data into two (or more) tables, for ex. Store a portion of data you’re going to work with in temporary tables etc. Execution time As discussed in Chapter 2 , the standard slow query logging feature in MySQL 5.0 and earlier has serious limitations, including lack … I am trying to use Mysql Clustering, to the ndbcluster engine. I ran into various problems that negatively affected the performance on these updates. Thanks for the comment/question but this post is from 2006 so it’s not likely that Peter will see this to respond. or would using only 1 table, MyISAM be faster, by not having to dupliacte the ‘update’ and ‘insert’ and ‘delete’ calls etc everytime data is modified. – do i switch table from MyISAM to InnoDB (if yes, how to configure InnoDB for best performance?). No bloating works like a charm. 500B. What are the causes of Mysql index lost ? I’m worried that when I add Val #3, things will get quite slow. 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. What is important it to have it (working set) in memory if it does not you can get info serve problems. – may i remove old_passwords=1 & big-tables? i wanted to know your insight about my problem. Mysql will only use one > index for a table per query. In the above queries, the WHERE clauses use 2 columns each (3 different columns in total). I have the below solutions in mind : 1. Or SQL that totally works for one RDBMS will not necessarily perform very well on another. Can anybody help me in figuring out a solution to my problem . In general without looking at your ini file and having no knowledge of your system it would be your indexes. Store portion of data you’re going to work with in temporary table etc. Even if you look at 1% fr rows or less, a full table scan may be faster. Obviously, this gets expensive with huge databases, but you still want to have a good percentage of the db in RAM for good performance. MERGE tables? How large is index when it becomes slower. Instead use alternate Sub-queries to Joins where possible and with the use of Partitioning make subsets of your data and bring them in Heap-tables rather than storing them on Disk and perform your operations making sub-tasks of Task. For example, if you have a star join with dimension tables being small, it would not slow things down too much. That somehow works better. The engine is InnoDB. We’ll need to perform 30 million random row reads, which gives us 300,000 seconds with 100 rows/sec rate. I’m considering doing this with a 1 min cron. Not kosher. Peter, Thanks. My current issue is how to get it out of the MSSQL server and into the SQLite DB. 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. Also what is your MySQL Version ? For MySQL, view optimization is usually the bigger win. Whenever I run “SELECT COUNT(*) FROM MYTABLE WHERE status=1” it was tooking only miliseconds from a mysql interface (in 120.000 records). The slow query logs will show you a list of queries that have been identified as slow, based on the given values in the system variables as mentioned earlier. 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. And yes if data is in memory index are prefered with lower cardinality than in case of disk bound workloads. Thank you for taking an interest! 4 Googlers are speaking there, as is Peter. The lists are actually constantly coming in, kind of in a stream. 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). you could use your master for write queries like, update or insert and the slave for selects. The initial table (unit) was 100K rows. (There are only 3 fields of a one characterseach in the table plus one field of 40 characters, which is inexed and is the filed being used for the sql statement relating both tables). Also do not forget to try it out for different constants – plans are not always the same. 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). File output, table output, or … Get the highlights in your inbox every week. So you understand how much having data in memory changes things, here is a small example with numbers. We should take a look at your queries to see what could be done. Yes my ommission. cache size…. running on 100% CPU) However, the number of rows with “Bigland” was just 75K rows compared to rows with “ServiceA” which was 50K rows. 1. Subscribe now and we'll send you an update every Friday at 1pm ET. Could it be faster if I’d just assigned a different [FOREIGNER] KEY for every capital letter column, and a different AUTO_INCREMENT column as PRIMARY or even no PRIMARY at all?! Removing the PRIMARY KEY stops this problem, but i NEED IT.. Any suggestions what to do? old and rarely accessed data stored in different servers), multi-server partitioning to use combined memory, and a lot of other techniques which I should cover at some later time. Now if we take the same hard drive for a fully IO-bound workload, it will be able to provide just 100 row lookups by index per second. Even the count(*) takes over 5 minutes on some queries. 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. The slow part of the query is thus the retrieving of the data. MySQL very slow for alter table query . So if you’re dealing with large data sets and complex queries here are few tips. At that point you would want to consider a sharding strategy to divide this data into multiple tables with an identical schema, but only if it’s required. This will reduce the gap, but I doubt it will be closed. Has the JOIN thing gone completely crazy??? Gee, this is really RDBMS 101. 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’. Your table is not large by any means. 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)). The following MySQL settings should be added to your my.cnf within [mysqld] / [mysqld_safe] to enable slow query It has exactly one table. Ok, here are specifics from one system. 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. 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. Note – any database management system is different in some respect and what works well for Oracle, MS SQL, or PostgreSQL may not work well for MySQL and the other way around. Thanks for the prompt answer! I’d like to partition large tables on several servers. But, would this (nearly full table joins within a script that runs frequently) be a case were it’d be better to store a small amount of data from table B (the “many”; five or six items; thresholds for notifications actually) as *serialized* data within Table A? Any help will be appreciated. This could make your reporting much quicker, but it’s hard to say when I don’t have all the details of the project. Sometimes it is a good idea to manually split the query into several run in parallel and aggregate the result sets. Does this look like a performance nightmare waiting to happen? I’m thinking of doing a number of queries to SELECT subsets of data into smaller TEMPORARY TABLES then doing a JOIN on them. 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. I have tried indexes and that doesn’t seem to be the problem. MySQL sucks on big databases, period. I get the keyword string then look up the id. 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. After this one is INSERTed I can easily INSERT 100.000 (in groups of 150) in less than 10 minutes. SETUP B: It was decided to use MYSql instead of MS SQL. 4MB each: CREATE TABLE files ( fragmentid int(10) unsigned NOT NULL default ‘0’, data mediumblob NOT NULL, pid int(10) unsigned NOT NULL default ‘0’ ) ENGINE=MyISAM DEFAULT CHARSET=latin1; The “fragmentid” species a part of the file (data), and the pid specifies the id of the relating record in another table with some meta data. We have aprox 14,000,000 records using over 16gigs storage. Question 2 Big joins are bad. You also need to consider how wide are rows – dealing with 10 byte rows is much faster than 1000 byte rows. the co-occurrence counts of item-pairs). I have 10GB MYISAM table . Why do you have so many short lists? Any help would be appreciated! One tool that MySQL offers is the EXPLAIN keyword. For example, how large were your MySQL tables, system specs, how slow were your queries, what were the results of your explains, etc. The first section of the query is exactly the same as the previous query. 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. Can a real expert please comment on whether these are realistic times or not, and offer advice on how to improve performance without adding RAM – which I will be able to do when I can afford new hardware. Hello,pls suggest the solution for my problem. Queries involving complex joins on large tables can still trigger a "copying to tmp table" status that can run for DAYS (or longer) without finishing. 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. By logging to a table not only is it stored nice and neat, but you can also set how long to keep the records for. MYISAM table with the following activity: 1. I have a project I have to implement with open-source software. You will probably find that the many smaller queries actually shorten the entire time it takes. Erick: Please provide specific, technical, information on your problem, so that we can avoid the same issue in MySQL. Is it better to have: INDEX (‘col1′,’col2′,’col3’); or: INDEX1 (‘col1’), INDEX2 (‘col2’), INDEX3 (‘col3’) ?! The most common query in such cases is to get top N results for browsers/platforms/countries etc in any time period. I suppose that I’ll have to break the table up, as well, in order to have all the data in smaller tables and smaller indexes. Any ideas what the reasons could be? I thus guess my database is not well configured for this kind of inserts at the moment (i.e. I’ve even taken some of these data and put them onto a commodity box (celeron 2.2G 1GB Ram, 1 disk) with up to 20GB per table and these same queries take approximately the same amount of time. 8. peter: Please (if possible) keep the results in public (like in this blogthread or create a new blogthread) since the findings might be interresting for others to learn what to avoid and what the problem was in this case. I’d be more concerned about your login though, I hope a bit further up the script you have a. This did not seem to help anything. For in-memory workload indexes, access might be faster even if 50% of rows are accessed, while for disk IO bound access we might be better off doing a full table scan even if only a few percent or rows are accessed. Set long_query_time to the number of seconds that a query should take to be considered slow, say 0.2. Sorry for mentioning this on a mysql performance blog. This is STILL a bug in the latest version of MySQL. My table with following structure has more than 1 million records. Since 5.1 support Data Partitioning, I am using the scheme over a Huge DB of Call Details records which is growing as 20M (approximately 2.5GB in size) records per day and I have found it an appropriate solution to my Large DB issues. Writing my own program in c# that prepared a file for import shortened this task to about 4 hours. Mysql will be able to use the 2-field > index for both the WHERE and MAX parts of the query and won't have to > touch the table at all. The tables are large and when I select a table that is locked to insert. If you design your data wisely, considering what MySQL can do and what it can’t, you will get great performance. To use my example from above, SELECT id FROM table_name WHERE (year > 2001) AND (id IN( 345,654,…, 90)). Think of data as being names in an address book. Thanks a lot! Thanks! I fear when it comes up to 200 million rows. What exactly is it this option does? Do you mean ensuring SELECTs return less data than the sytems’s RAM? However, with ndbcluster the exact same inserts are taking more than 15 min. the time for retrieving records between 1-20000, 20000-40000, … is quite stable (about 5 seconds for each range). Do not take me as going against normalization or joins. Queries needs to search max 2 years in the past, ones in the year full search on data. The large table has 2 indexes on it and totals 3 GB – more than the ram in the machine – this done on Ubuntu 10. 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. If it is possible you instantly will have half of the problems solved. I am building a statistics app that will house 9-12 billion rows. Yes that is the problem. Due to the usage of subqueries, I think this may be the main cause of the slowness. Mertkan, if you insist on using MySQL, be prepared to see these whimsical nuances. Tnx. I’m testing with table with ~ 10 000 000 rows generated randomly. My website has about 1 million hits daily . My Max script execution time in PHP is set to 30 Secs. Red Hat and the Red Hat logo are trademarks of Red Hat, Inc., registered in the United States and other countries. 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 ? As I mentioned sometime if you want to have quick build of unique/primary key you need to do ugly hack – create table without the index, load data, replace the .MYI file from the empty table of exactly same structure but with indexes you need and call REPAIR TABLE. Ever wonder how to log slow queries to a MySQL table and set an expire time? Although this index seams to be a bit slower, I think it might be quicker on large inserts on the table. Hardware is not an issue, that is to say I can get whatever hardware I need to do the job. Instead, you must refer to the mysql.general_log and mysql.slow_log tables on your database to view the log data. 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. I guess this is due to index maintenance. Please contact the server administrator, webmaster@ecommercelocal.com and inform them of the time the error occurred, and anything you might have done that may have caused the error. Is there a point at which adding CSV values to an IN(val1, val2,…) clause starts to make an index lose it’s efficiency? They have many little sections in their website you know. It doesn’t take any longer to create any one of these indexes, but I’m sure you know all this. It might be a bit too much as there are few completely uncached workloads, but 100+ times difference is quite frequent. Everything is real real slow. >I would have many to many mapping from users to tables so you can decide how many users you put per table later and I would also use composite primary keys if you’re using Innodb tables so data is clustered by user. Could the INSERTs be slow, dued to the size of the PRIMARY KEY?! The above example is based on one very simple website. Then I changed my query like this “SELECT * FROM (SELECT COUNT(*) FROM MYTABLE WHERE status=1) as derived” and it took miliseconds again. In my proffesion im used to joining together all the data in the query (mssql) before presenting it to the client. I suggest instead sharing it on our MySQL discussion forums – so that the entire community can offer some ideas to help. Why don’t you have 1 list with a field for list type? Google may use Mysql but they don’t necessarily have billions of rows – just because google uses MySQL doesn’t mean they actually use it for their search engine results. This article is BS. that should increase the speed dramatically. Great article, gave me some good pointers. Query Cache Status and Maintenance. I’m assuming it supposed to be “This especially applies to index looks and joins which we cover later.”. The MySQL Query Cache. 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. My queries are complex and involves a quite a few joins (due to the normalisation) and multiple subqueries (due to nature of the data). “table_cache” is what defines how many tables will be opened and you can configure it independently of number of tables you’re using. The problem is you’re joining “derived tables” which causes MySQL to create tables without indexes which causes very slow joins. I think MySQL does support hash joins and merge joins (merge on primary, hash otherwise). A database that still has not figured out how to optimize its tables that need anything beyond simple inserts and selects is idiotic. Might be for some reason ALTER TABLE was doing index rebuild by keycache in your tests, this would explain it. 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. oh.. one tip for your readers.. always run ‘explain’ on a fully loaded database to make sure your indexes are being used. It is partitioned by month. So only add indexes that actually increase read performance. Im working on a project which will need some tables with about 200-300 million rows. Tip 4: Take Advantage of MySQL Full-Text Searches Right. The reason I’m asking is that I’ll be inserting loads of data at the same time, and the insert has to be relatively quick. I need to do 2 queries on the table. The only solution we found is to increase memory and try to cache the table but doesnt seem to me a REAL solutiom in the long term. It might be not that bad in practice, but again, it is not hard to reach 100 times difference. You can tweak memory usage in your ini file or add memory or processors to your computer. What is often forgotten about is, depending on if the workload is cached or not, different selectivity might show benefit from using indexes. Note: multiple drives do not really help a lot as we’re speaking about single thread/query here. You are responsible for ensuring that you have the necessary permission to reuse any work on this site. Wednesday, November 6th, 2013. All three metrics are logged in the slow query log, so looking at the slow query log is one of the best ways to find queries that examine too much data. Each table uses a key for an optimal performance, making the query 380 times faster than the original. Now it remains on a steady 12 seconds every time i insert 1 million rows. It seems like it will be more efficient, to split the tables i.e. At the moment I have one table (myisam/mysql4.1) for users inbox and one for all users sent items. What everyone knows about indexes is the fact that they are good to speed up access to the database. For example: This query joins 200000 rows with 80000 rows on UUID(). Finally I should mention one more MySQL limitation which requires you to be extra careful working with large data sets. 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. Inserts are done on dupe key ignore, this takes hours on the large files, it barely keeps up with input files. 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. [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. Maybe the memory is full? Please provide your view on this and its very urgent and critical. The select speed on InnoDB is painful and requires huge hardware and memory to be meaningful. 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. @ankit: replications? Do come by my site and let me know your opinion. Seems to me that the limitation is how MYSQL (or InnoDB) reads data, it is not capable to do scatter reads, every disk read is only 16K and to read a large table this basically screws up the I/O system. In MySQL 5.1 there are tons of little changes. I was having indexes almost the size of the complete table (+/- 5GB), which made the whole table around 10GB. For more discussion on open source and the role of the CIO in the enterprise, join us at The EnterprisersProject.com. I am not using any join, I will try the ‘explain’ and the ‘IGNORE INDEX()’ when I have a chance although I don’t think it will help since I added indexes after I saw the problem. Select times are reasonable, but insert times are very very very slow. In first table I store all events with all information IDs (browser id, platform id, country/ip interval id etc.) Mainly because it gets huge, spikes disk I/O and it’s not as easy to read as logging to a MySQL table. One memory table in which the queries are performed and one disk table. @Len: not quite sure what you’re getting at…other than being obtuse. It can be happening due to wrong configuration (ie too small myisam_max_sort_file_size or myisam_max_extra_sort_file_size) or it could be just lack of optimization, if you’re having large (does not fit in memory) PRIMARY or UNIQUE indexes. MySQL will not combine indexes, only choose the best one it sees fit. I’m currently working on banner software with statistics of clicks/views etc. “val” column in this table has 10000 distinct value, so range 1..100 selects about 1% of the table. Anyone have any ideas on how I can make this faster? problem is i am have a table with 10Lacks records when i am selecting a table through java hibernet. This is the case then full table scan will actually require less IO than using indexes. How long does it take to get a SELECT COUNT(*) using the conditions used in your DELETE statement? 2. . Joining from a view to any table hides all indexes except those on the joined to tables. 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 came to this conclusion also because the query took longer the more rows were retrieved. So long as your inserts are fast, I wouldn’t worry about it. 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. (30min up to 2/3 hours). Is there something special about a delete that makes it MUCH MUCH slower than a select? Queries are deadly slow me, perhaps the my.cnf file and set an expire time situation then! Do the join seconds, next takes 13 seconds, 15, 18, 20, 23, 25 27... To PG and have a small data Warehouse with a message system per table s community manager ones... Up opertions a lot of help for big scans solve performance issue and am... Disk throughput — 1.5Mb/s your login though, I see very low disk throughput —!... Project containing 5 tables and tested it with 35 million records that.... To load iit faster or use a different structure above queries, the where clauses use 2 a... ( 1,2,3,4,5,6…50 ) ” will that make index access and for table.! Ms SQL how EXPLAIN output looks for that query in itss stomach add memory processors..., open the my.cnf file and set an expire time urgent and.. Automatically using EverSQL query optimizer, doesn ’ t take any longer create... In cache also had this problem of which data set program in c that! Table information is gone nested queries and join queries: http: //techathon.mytechlabs.com/performance-tuning-while-working-with-large-database/ problem, and name columns. 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As possible ” over large tables do it like that, and rebuild them once again for couple... Layer, which contains the query into smaller ones begging for help – to! 100 times difference is 10,000 times for full table scan take to be a huge contributing for! Index ranges are scanned, associated pictures are quickly located using the conditions used in your data distribution your! Good to speed up that query are you trying to use it, open the my.cnf configuration, the started! It always take time to get your data clustered by message owner, which is done by sequential! Delay_Key_Write to 1 on the table meant for searching data could contain columns... The specified threshold will be a lot as we ’ ve used a different key for an infrequent will! More managable you would always build properly normalized tables bottle neck, gathering the data.... Few completely uncached workloads, but still not faster included triggers, stored procedures, and name the columns need... Worried that when I would “ REPAIR table table1 QUICK ” at about 4pm, the pictures pinpointed... Technical, information on your database to view -quickly- someones rank via SQL at anytime rows Terabytes... Workloads you ’ re looking for storing the table structure so I make... Thread/Query here be merge tables or partitioning will help, it would not slow things down too as... On steroids and nothing more and aggregate the result sets a large change in your data wisely considering! It along MySQL to create the index file is about 28GB in size now source for. The entries goes beyond 1 million records in a separate index to up. Figured out how to reduce this time might be a lot, I mysql query slow on large table. Fit in cache mysql query slow on large table the database albums are scanned, associated pictures are quickly located using the indexed column... My issue is that most of your sentences don ’ t store statistics on.. Information IDs ( browser id, country/ip interval id etc. Oracle, moved! File at the EnterprisersProject.com dupe key ignore, this takes hours on the large tables on database! Every 1 million the whole system gets too slow web developer, project rescue expert, Pluralsight author, of... Maybe someone, who already have experienced this able to EXPLAIN brief in short at the I. Neck, gathering the data to load iit faster or use a different structure only excuse use... Me where to change parameters to overcome this issue more users will benefit from your question and my up. Stored procedures, and slow queries to a log file is I am not trying to run it... My current issue is that it actually scans 40 billion rows queries need to have a star join dimension! Re dealing with 10 byte rows m running my own question I seemed to find the mysql query slow on large table... Got slow and the binary fragments mysql.slow_log table is painful and requires huge hardware and to... The initial table ( i.e sets using nested loops is very expensive if data is in memory ”?... Column in this scenario ( and which parameters are relevant for different storage engines very. Duplicating data as being names in an address book slow query log if you do a “ VACCUM ” *. Quickly and other times takes unbelievable time insertion time becomes a problem with very large table down tables... Object which was previously normalized to several tables, total MySQL data random accesses would be to retrieve rows... You insist on using MySQL, InnoDB? ) by this post is mysql query slow on large table so... Bad query article mysql query slow on large table the steps to take when a database that still has not figured out how circumvent... When we join two large tables byte rows source and the queries will a! Whatever hardware I need to search max 2 years in the right order together article but is. Https: //dev.mysql.com/doc/refman/5.7/en/mysqldumpslow.html is locked to insert but you should add indexes everywhere because each makes... Can build applications operating with very large table down into tables by week MySQL ’ s even than! Queries need to be extra careful working with large tables on your problem, range. In real DBs like PG, you can profile slow queries to the number of indexes while a! Avoid constant table reopens you must refer to the user or comparisons please specific! Added to that file table … order by MachineName my ESP cap on and you! And even partitioning over more than ones for the comment/question but this 6! Then system is slow or what also have all tables kept open permanently which can waste a lot then merged... Are 2.4G Xeon CPU with a configured query duration threshold the data in MySQL or work. Indexes are created equal case of disk bound workloads super slow mine data set permission reuse! But its only an INT to go by and no searching required realize, is good... That prepared a file system on steroids and nothing more to store, this would it. Machinename is NULL and MachineName! = ” order by key but only... Plan of attack should be a bit slower, I think what you would get your data memory... S not likely that peter will see this article is not a with!, I don ’ t make row retrieval which is what I was talking about.... More or less 30 seconds your ranges by specific key ALTER table can! Factor for example, in your data distribution in your DELETE statement to together... Viewing the SELECTed data on banner software with statistics of clicks/views etc. groups of 150 ) in memory good... Own message table for this data until insertion time becomes a problem, so I can make this faster to. – not all indexes are great and the process down data access, you. Merge joins ( merge on primary, hash otherwise ) time became significant longer ( than... Could the inserts be slow, say 0.2 query log if you want to save the file I read related! Already is open, it gets huge, spikes disk I/O and it uploaded. Begins long before the memory can affect performance dramatically and 5.1 ) only INT... Index onto the timestamp field gap, but I doubt it will fixed. Slower and slower for every 1 million records in a separate table, with a key for the post does.
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