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. It is not currently Want to improve . Obviously, this gets expensive with huge databases, but you still want to have a good percentage of the db in RAM for good performance. Tnx. It however can’t make row retrieval which is done by index sequential one. Would be a great help to readers. Is this normal – for a delete involving 2 tables to take so long? The more indexes you have the faster SELECT statments are, but the slower INSERTS and DELETES. 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). Could I maybe disable some concurrency related checks (as I have exactly one process inserting into the table, which I could even stop when I want to read data)? 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.. You will probably find that the many smaller queries actually shorten the entire time it takes. So long as your inserts are fast, I wouldn’t worry about it. 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. Surely the whole point of using a relational database is predicated upon normalisation. 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. After this one is INSERTed I can easily INSERT 100.000 (in groups of 150) in less than 10 minutes. Normally MySQL is rather fast loading data in MyISAM table, but there is exception, which is when it can’t rebuild indexes by sort but builds them row by row instead. UPDATES: 200 3. 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. 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. Im working on a project which will need some tables with about 200-300 million rows. I finally now resorting to small snapshots approach. System: It’s now on a 2xDualcore Opteron with 4GB Ram/Debian/Apache2/MySQL4.1/PHP4/SATA Raid1) In near future I will have the Apache on a dedicated machine and the Mysql Server too (and the next step will be a Master/Slave server setup for the database). Obviously I would like to be able to process as many lists as possible and thus I would like to have the insertion process as fast as possible. Once you know which are the offending queries, you can start exploring what makes them slow. We’re using LAMP. 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. Thank you for taking an interest! Also have two myisam tables: One with 5 million records using 1.2 GB of You can significantly increase performance by using indexes. Increasing performance of bulk updates of large tables in MySQL Wednesday, November 6th, 2013 I recently had to perform some bulk updates on semi-large tables (3 to 7 million rows) in MySQL. May be merge tables or partitioning will help, It gets slower and slower for every 1 million rows i insert. Peter, Thanks. One could could call it trivial fast task, unfortunately I had unique key on varchar(128) as part of the schema. You can’t go away with ALTER TABLE DISABLE KEYS as it does not affect unique keys. She enjoys realizing seemingly impossible things. It scans 2,000,000 pictures, then, for each picture, it scans 20,000 albums. On the other hand, it is well known with customers like Google, Yahoo, LiveJournal, and Technorati, MySQL has installations with many billions of rows and delivers great performance. 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. For example, you can add an index on picture.album_id like this: Now if you run the query, the process no longer involves scanning the entire list of pictures. I run the following query, which takes 93 seconds ! My question is what my plan of attack should be to get the best insert performance? As you could see in the article in the test I’ve created range covering 1% of table was 6 times slower than full table scan… which means at about 0.2% table scan is preferable. QUESTION: 1) Why does MS SQL performs faster when they have the same specs though with different OS? Maybe I can rewrite the SQL, since it seems like MySQL handles ONE JOIN, but no way it handles TWO JOINS. 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. Everything is real real slow. Mysql ver. Processing in memory is so much faster and you have whole bunch of problems solved just doing so. Then run your code and any query above the specified threshold will be added to that file. So I guess a better question is, 30 million records, 1 million users with 30 records each You mentioned (and I have experienced) that a composite key starting with userid in Innodb is indeed very efficient and fast. Answer depends on selectivity at large extent as well as if where clause is matched by index or full scan is performed. It also simply does not have the data available – is given index (range) currently in memory or will it need to read it from the disk ? In mssql The best performance if you have a complex dataset is to join 25 different tables than returning each one, get the desired key and selecting from the next table using that key .. Consider using FULLTEXT index. Consider a table which has 100-byte rows. Here’s my query. Although the storage requirements for this is higher than a fixed-columns arrangement with the perpetually frustrating names like attribute1, the cost is small enough in the age of terabyte-sized hard-drives that it’s rarely an issue. Also do not forget to try it out for different constants – plans are not always the same. 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. 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. Try to fit data set you’re working with in memory – Processing in memory is so much faster and you have a whole bunch of problems solved just doing so. Each file we process is about 750MB in size, and we insert 7 of them nightly. We encountered the performance problem when we join two large tables. Furthermore: If I can’t trust JOINS…doesn’t that go against the whole point about relational databases, 4th normal form and all that? MERGE tables? Hi, Im working proffesionally with postgresql and mssql and at home im using mysql for my leasure projects .. I think you can give me some advise. . When you run a query that should extract many rows, then faster solution is to scan entire table. For example, if a table with 30 million records and a composite key on userID, Could one expect better performance by splitting into 30 tables of 1 million records each, or are composite keys that efficient? Thank you. But, never tried explaining a bit on it? 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. SPECS of SETUP A: OS: Windows XP Prof Memory: 512MB. I think the root of my issue is that the indexes don’t fit into RAM. 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. I had 40000 row in database when ever i fire this query in mysql its taking too much time to get data from database. the co-occurrence counts of item-pairs). 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. The large table has 2 indexes on it and totals 3 GB – more than the ram in the machine – this done on Ubuntu 10. 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. you could use your master for write queries like, update or insert and the slave for selects. It has exactly one table. @ankit: replications? Hi. We are at a loss here. How the Query Cache Operates. Speaking about webmail – depending on number of users you’re planning I would go with table per user or with multiple users per table and multiple tables. old_passwords=1 big-tables, [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid, – i have webmin installed, but when I change mysql vars and restart server, my configs are not applied, defautl mysql. This is because the indexes have to be rewritten everytime you make a change. How should I create table structure so I can do rankings for each user based on their average score? 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. There are many design and configuration alternatives to deliver you what you’re looking for. Execution time As discussed in Chapter 2 , the standard slow query logging feature in MySQL 5.0 and earlier has serious limitations, including lack … Great article. Integrity checks don’t work — try making a check on a column NOT NULL to include NOT EMPTY (i.e., no blank space can be entered, which as you know, is different from NULL). I guess it’s all about memory vs hard disk access. As you can see, using index hints can further increase the query speed. First, all the albums are scanned to find the ones that belong to the user. No problem. …a nested select. So feel free to post there and I also invite you to join our community, too. 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. You need a lot of work on your technical writing skills. I have a table with a unique key on two columns (STRING, URL). I could send the table structures and queries/ php cocde that tends to bog down. But for my mysql server I’m having performance issues, sÃ¥ my question remains, what is the best route, join and complex queries, or several simple queries. And update the current status on the blog itself. Obviously, the resulting table becomes large (example: approx. Any hope that this issue will be fixed any time soon? So, I want to count, how many lists contain both, item1 and item2, item1 and item3, etc. Set slow_query_log_file to the path where you want to save the file. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? Meanwhile the table has a size of 1,5Gb. Indexes end up becoming a liability when updating a table.. The following MySQL settings should be added to your my.cnf within [mysqld] / [mysqld_safe] to enable slow query - … applied, and my.cnf are not modified. I may add that this one table had 3 million rows, and growing pretty slowly given the insert rate. 4 million rows), the execution time is more or less 30 seconds. Is there something special about a delete that makes it MUCH MUCH slower than a select? To use it, open the my.cnf file and set the slow_query_log variable to "On." To answer my own question I seemed to find a solution. 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? Joins are used to compose the complex object which was previously normalized to several tables, or perform complex queries finding relationships between objects. I have tried adjusting the join_buffer_size (128M and 16M) but to no avail. Note: multiple drives do not really help a lot as we’re speaking about single thread/query here. This query takes about 45 minutes to execute (DELETE FROM Data WHERE Cat=’1021′ AND LastModified < ‘2007-08-31 15:48:00’). 4 Googlers are speaking there, as is Peter. The things you wrote here are kind of difficult for me to follow. 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. I have MYSQL database performance issue and I have updated the MYSQL Performance blog as below link. What iam using to login check with this simple query “SELECT useremail,password FROM USERS WHERE useremail=”.$_REQUEST[‘USER_EMAIL’].”AND password=” .$_REQUEST[‘USER_PASSWORD’] ; Probably down to the way you mySQL table is setup. ), which is what it’s intended, but INSERTing in them is a nightmare. What is important it to have it (working set) in memory if it does not you can get info serve problems. The ‘data’ attribute contents the binary fragments. I did not mentioned it in the article but there is IGNORE INDEX() hint to force full table scan. Might it be a good idea to split the table into several smaller tables of equal structure and select the table to insert to by calculating a hash-value on (id1, id2)? For example: This query joins 200000 rows with 80000 rows on UUID(). $_REQUEST[‘USER_PASSWORD’] = mysql_real_escape_string($_REQUEST[‘USER_PASSWORD’]); otherwise some little script kiddy is going to cause you an even bigger problem in the future. The queries that were taking less than 1 second some times ago are taking at least 20 to 30 seconds. The server layer, which contains the query optimizer, doesn’t store statistics on data and indexes. Here are some of the ways I know. Inserts are done on dupe key ignore, this takes hours on the large files, it barely keeps up with input files. I am having a problem with updating records in a table. I’m actually quite surprised. Whenever I run “SELECT COUNT(*) FROM MYTABLE WHERE status=1” it was tooking only miliseconds from a mysql interface (in 120.000 records). Peter, I have similar situation to the message system, only mine data set would be even bigger. I’ve read SHE-DBA’s blog on using MySQL as a data-warehousing platform and where it _can_ be used as such provided the design is good and the queries are optimised. Using SQL_BIG_RESULT helps to make it use sort instead. I do multifield select on indexed fields, and if row is found, I update the data, if not I insert new row). So give your Anaconda small pieces of meat than full deer all in once. 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). Joining from a view to any table hides all indexes except those on the joined to tables. Also, are there any suggestions about which storage engine to use? Wednesday, November 6th, 2013. I was hoping to see the machine either disk or CPU-bound to help troubleshoot what the problem is, but this is not the case. The question I have, is why is this happening, and if there is any kind of query I can preform in order to “focus” the DBMS “attention” to the particular table (in context), since SELECTing data is always faster then INSERTing it. I’m currently at design time, and at half the specified month period, and so far, the tables are about 10GB in size each (so far, 6 in total). There is no appreciable performance gain. 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. The problem is – unique keys are always rebuilt using key_cache, which means we’re down to some 100-200 rows/sec as soon as index becomes significantly larger than memory. For a table with several columns, to reduce memory requirements for queries that do not use the BLOB column, consider splitting the BLOB column into a separate table and referencing it with a join query when needed. Under such a heavy load the SELECT and inserts get slowed . This did not seem to help anything. Basically: we’ve moved to PostgreSQL, which is a real database and with version 8.x is fantastic with speed as well. Think of data as being names in an address book. “So you understand how much having data in memory changed things here is small example with numbers.” -OMG. In theory optimizer should know and select it automatically. The MySQL Query Cache. And if not, you might become upset and become one of those bloggers. Out I/O system offer around 60MB/sec but before this limit is reached the I/O system is flooded by very high amount on IOPS (we have observed around 1200 IOPS). Maybe the memory is full? I know some big websites are using MySQL, but we had neither the budget to throw all that staff, or time, at it. I simply put the search index in a separate table, of some 80 MB and the binary / blobs in another. Seems like we’re going in circles with these. This could be done by data partitioning (i.e. Each row record is approx. I expect performance of this to be in terms of seconds to minutes. The type of table it is — is it MYISAM or INNODB? Regarding how to estimate I would do some benchmarks and match them against what you would expect and what you’re looking for. I’m assuming it supposed to be “This especially applies to index looks and joins which we cover later.”. One tool that MySQL offers is the EXPLAIN keyword. Hello,pls suggest the solution for my problem. along with time when event happened. So if you’re dealing with large data sets and complex queries here are few tips. Red Hat and the Red Hat logo are trademarks of Red Hat, Inc., registered in the United States and other countries. We’ve got 20,000,000 bank loan records we query against all sorts of tables. Now the page loads quite slowly. Joins to smaller tables is OK but you might want to preload them to memory before join so there is no random IO needed to populate the caches. SETUP B: It was decided to use MYSql instead of MS SQL. (I’ve been struggling with this one for about a week now. The table has hundreds of millions of records. Does this look like a performance nightmare waiting to happen? Prefer full table scans to index accesses – For large data sets, full table scans are often faster than range scans and other types of index lookups. The select speed on InnoDB is painful and requires huge hardware and memory to be meaningful. I noticed that when there were few million records in both table, things got extremely sluggish. I wonder how I can optimize my table. Would duplicating data on inserts and updates be an option which would mean having two of the same table, one using InnoDB for main reading purposes and one for MyISAM for searching using Full text search and every time you do an update actually uipdate bith table etc. 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. id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE stat range dateline dateline 4 NULL 277483 Using where; Using temporary; Using filesort 1 SIMPLE iplist eq_ref PRIMARY PRIMARY 4 vb38.stat.ip_interval 1. Anyway… not the correct forum/blog. Get the highlights in your inbox every week. After that, the pictures are quickly located using the indexed album_id column. We will have to do this check in the application. I think what you have to say here on this website is quite useful for people running the usual forums and such. Let’s do some computations again. loaded into large tables, total mysql data size is 96 gig, the large tables are 2-6 gig. I m using php 5 and MySQL 4.1………. Of course, this is all RDMS for beginners, but, I guess you knew that. Sorry for the confusion, but this is what I was talking about also. Perhaps some process whereby you step through the larger table say 1000 records at a time? Yes my ommission. My strategy is to go through the lists one by one, and, for each list, insert the 50 * 49 / 2 pairs into a table with 3 columns (id1, id2, cnt) (where the pair id1, id2 forms the primary key) using INSERT … ON DUPLICATE KEY UPDATE cnt = cnt + 1. Subscribe now and we'll send you an update every Friday at 1pm ET. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. That somehow works better. 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. Adding the index really helped our reporting, BUT now the inserts are taking forever. Hardware is not an issue, that is to say I can get whatever hardware I need to do the job. CREATE TABLE user_attributes ( id INT PRIMARY KEY NOT NULL AUTO_INCREMENT, user_id INT NOT NULL, attribute_name VARCHAR(255) NOT NULL, attribute_value VARCHAR(255), UNIQUE INDEX index_user_attributes_name(user_id, attribute_name) ); This is the basic key-value store pattern where you can have many attributes per user. Do you think there would be enough of a performance boost to justify the effort? the time for retrieving records between 1-20000, 20000-40000, … is quite stable (about 5 seconds for each range). 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. The big sites such as Slashdot and so forth have to use massive clusters and replication. Most of your sentences don’t pass as “sentences”. We’ll need to perform 30 million random row reads, which gives us 300,000 seconds with 100 rows/sec rate. Missouri Raccoon Season, What To Order At Rasika, Southern Comfort And Orange Juice, Spicy Cabbage And Noodles Recipe, Arizona Desert Shrubs, How Does The Fed Print Money Reddit, Minimum Wage Australia After Tax, Pros And Cons Of Artificial Intelligence 2019, mysql query slow on large table" /> 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. It is not currently Want to improve . Obviously, this gets expensive with huge databases, but you still want to have a good percentage of the db in RAM for good performance. Tnx. It however can’t make row retrieval which is done by index sequential one. Would be a great help to readers. Is this normal – for a delete involving 2 tables to take so long? The more indexes you have the faster SELECT statments are, but the slower INSERTS and DELETES. 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). Could I maybe disable some concurrency related checks (as I have exactly one process inserting into the table, which I could even stop when I want to read data)? 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.. You will probably find that the many smaller queries actually shorten the entire time it takes. So long as your inserts are fast, I wouldn’t worry about it. 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. Surely the whole point of using a relational database is predicated upon normalisation. 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. After this one is INSERTed I can easily INSERT 100.000 (in groups of 150) in less than 10 minutes. Normally MySQL is rather fast loading data in MyISAM table, but there is exception, which is when it can’t rebuild indexes by sort but builds them row by row instead. UPDATES: 200 3. 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. 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. Im working on a project which will need some tables with about 200-300 million rows. I finally now resorting to small snapshots approach. System: It’s now on a 2xDualcore Opteron with 4GB Ram/Debian/Apache2/MySQL4.1/PHP4/SATA Raid1) In near future I will have the Apache on a dedicated machine and the Mysql Server too (and the next step will be a Master/Slave server setup for the database). Obviously I would like to be able to process as many lists as possible and thus I would like to have the insertion process as fast as possible. Once you know which are the offending queries, you can start exploring what makes them slow. We’re using LAMP. 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. Thank you for taking an interest! Also have two myisam tables: One with 5 million records using 1.2 GB of You can significantly increase performance by using indexes. Increasing performance of bulk updates of large tables in MySQL Wednesday, November 6th, 2013 I recently had to perform some bulk updates on semi-large tables (3 to 7 million rows) in MySQL. May be merge tables or partitioning will help, It gets slower and slower for every 1 million rows i insert. Peter, Thanks. One could could call it trivial fast task, unfortunately I had unique key on varchar(128) as part of the schema. You can’t go away with ALTER TABLE DISABLE KEYS as it does not affect unique keys. She enjoys realizing seemingly impossible things. It scans 2,000,000 pictures, then, for each picture, it scans 20,000 albums. On the other hand, it is well known with customers like Google, Yahoo, LiveJournal, and Technorati, MySQL has installations with many billions of rows and delivers great performance. 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. For example, you can add an index on picture.album_id like this: Now if you run the query, the process no longer involves scanning the entire list of pictures. I run the following query, which takes 93 seconds ! My question is what my plan of attack should be to get the best insert performance? As you could see in the article in the test I’ve created range covering 1% of table was 6 times slower than full table scan… which means at about 0.2% table scan is preferable. QUESTION: 1) Why does MS SQL performs faster when they have the same specs though with different OS? Maybe I can rewrite the SQL, since it seems like MySQL handles ONE JOIN, but no way it handles TWO JOINS. 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. Everything is real real slow. Mysql ver. Processing in memory is so much faster and you have whole bunch of problems solved just doing so. Then run your code and any query above the specified threshold will be added to that file. So I guess a better question is, 30 million records, 1 million users with 30 records each You mentioned (and I have experienced) that a composite key starting with userid in Innodb is indeed very efficient and fast. Answer depends on selectivity at large extent as well as if where clause is matched by index or full scan is performed. It also simply does not have the data available – is given index (range) currently in memory or will it need to read it from the disk ? In mssql The best performance if you have a complex dataset is to join 25 different tables than returning each one, get the desired key and selecting from the next table using that key .. Consider using FULLTEXT index. Consider a table which has 100-byte rows. Here’s my query. Although the storage requirements for this is higher than a fixed-columns arrangement with the perpetually frustrating names like attribute1, the cost is small enough in the age of terabyte-sized hard-drives that it’s rarely an issue. Also do not forget to try it out for different constants – plans are not always the same. 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. 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. Try to fit data set you’re working with in memory – Processing in memory is so much faster and you have a whole bunch of problems solved just doing so. Each file we process is about 750MB in size, and we insert 7 of them nightly. We encountered the performance problem when we join two large tables. Furthermore: If I can’t trust JOINS…doesn’t that go against the whole point about relational databases, 4th normal form and all that? MERGE tables? Hi, Im working proffesionally with postgresql and mssql and at home im using mysql for my leasure projects .. I think you can give me some advise. . When you run a query that should extract many rows, then faster solution is to scan entire table. For example, if a table with 30 million records and a composite key on userID, Could one expect better performance by splitting into 30 tables of 1 million records each, or are composite keys that efficient? Thank you. But, never tried explaining a bit on it? 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. SPECS of SETUP A: OS: Windows XP Prof Memory: 512MB. I think the root of my issue is that the indexes don’t fit into RAM. 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. I had 40000 row in database when ever i fire this query in mysql its taking too much time to get data from database. the co-occurrence counts of item-pairs). 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. The large table has 2 indexes on it and totals 3 GB – more than the ram in the machine – this done on Ubuntu 10. 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. you could use your master for write queries like, update or insert and the slave for selects. It has exactly one table. @ankit: replications? Hi. We are at a loss here. How the Query Cache Operates. Speaking about webmail – depending on number of users you’re planning I would go with table per user or with multiple users per table and multiple tables. old_passwords=1 big-tables, [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid, – i have webmin installed, but when I change mysql vars and restart server, my configs are not applied, defautl mysql. This is because the indexes have to be rewritten everytime you make a change. How should I create table structure so I can do rankings for each user based on their average score? 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. There are many design and configuration alternatives to deliver you what you’re looking for. Execution time As discussed in Chapter 2 , the standard slow query logging feature in MySQL 5.0 and earlier has serious limitations, including lack … Great article. Integrity checks don’t work — try making a check on a column NOT NULL to include NOT EMPTY (i.e., no blank space can be entered, which as you know, is different from NULL). I guess it’s all about memory vs hard disk access. As you can see, using index hints can further increase the query speed. First, all the albums are scanned to find the ones that belong to the user. No problem. …a nested select. So feel free to post there and I also invite you to join our community, too. 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. You need a lot of work on your technical writing skills. I have a table with a unique key on two columns (STRING, URL). I could send the table structures and queries/ php cocde that tends to bog down. But for my mysql server I’m having performance issues, sÃ¥ my question remains, what is the best route, join and complex queries, or several simple queries. And update the current status on the blog itself. Obviously, the resulting table becomes large (example: approx. Any hope that this issue will be fixed any time soon? So, I want to count, how many lists contain both, item1 and item2, item1 and item3, etc. Set slow_query_log_file to the path where you want to save the file. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? Meanwhile the table has a size of 1,5Gb. Indexes end up becoming a liability when updating a table.. The following MySQL settings should be added to your my.cnf within [mysqld] / [mysqld_safe] to enable slow query - … applied, and my.cnf are not modified. I may add that this one table had 3 million rows, and growing pretty slowly given the insert rate. 4 million rows), the execution time is more or less 30 seconds. Is there something special about a delete that makes it MUCH MUCH slower than a select? To use it, open the my.cnf file and set the slow_query_log variable to "On." To answer my own question I seemed to find a solution. 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? Joins are used to compose the complex object which was previously normalized to several tables, or perform complex queries finding relationships between objects. I have tried adjusting the join_buffer_size (128M and 16M) but to no avail. Note: multiple drives do not really help a lot as we’re speaking about single thread/query here. This query takes about 45 minutes to execute (DELETE FROM Data WHERE Cat=’1021′ AND LastModified < ‘2007-08-31 15:48:00’). 4 Googlers are speaking there, as is Peter. The things you wrote here are kind of difficult for me to follow. 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. I have MYSQL database performance issue and I have updated the MYSQL Performance blog as below link. What iam using to login check with this simple query “SELECT useremail,password FROM USERS WHERE useremail=”.$_REQUEST[‘USER_EMAIL’].”AND password=” .$_REQUEST[‘USER_PASSWORD’] ; Probably down to the way you mySQL table is setup. ), which is what it’s intended, but INSERTing in them is a nightmare. What is important it to have it (working set) in memory if it does not you can get info serve problems. The ‘data’ attribute contents the binary fragments. I did not mentioned it in the article but there is IGNORE INDEX() hint to force full table scan. Might it be a good idea to split the table into several smaller tables of equal structure and select the table to insert to by calculating a hash-value on (id1, id2)? For example: This query joins 200000 rows with 80000 rows on UUID(). $_REQUEST[‘USER_PASSWORD’] = mysql_real_escape_string($_REQUEST[‘USER_PASSWORD’]); otherwise some little script kiddy is going to cause you an even bigger problem in the future. The queries that were taking less than 1 second some times ago are taking at least 20 to 30 seconds. The server layer, which contains the query optimizer, doesn’t store statistics on data and indexes. Here are some of the ways I know. Inserts are done on dupe key ignore, this takes hours on the large files, it barely keeps up with input files. I am having a problem with updating records in a table. I’m actually quite surprised. Whenever I run “SELECT COUNT(*) FROM MYTABLE WHERE status=1” it was tooking only miliseconds from a mysql interface (in 120.000 records). Peter, I have similar situation to the message system, only mine data set would be even bigger. I’ve read SHE-DBA’s blog on using MySQL as a data-warehousing platform and where it _can_ be used as such provided the design is good and the queries are optimised. Using SQL_BIG_RESULT helps to make it use sort instead. I do multifield select on indexed fields, and if row is found, I update the data, if not I insert new row). So give your Anaconda small pieces of meat than full deer all in once. 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). Joining from a view to any table hides all indexes except those on the joined to tables. Also, are there any suggestions about which storage engine to use? Wednesday, November 6th, 2013. I was hoping to see the machine either disk or CPU-bound to help troubleshoot what the problem is, but this is not the case. The question I have, is why is this happening, and if there is any kind of query I can preform in order to “focus” the DBMS “attention” to the particular table (in context), since SELECTing data is always faster then INSERTing it. I’m currently at design time, and at half the specified month period, and so far, the tables are about 10GB in size each (so far, 6 in total). There is no appreciable performance gain. 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. The problem is – unique keys are always rebuilt using key_cache, which means we’re down to some 100-200 rows/sec as soon as index becomes significantly larger than memory. For a table with several columns, to reduce memory requirements for queries that do not use the BLOB column, consider splitting the BLOB column into a separate table and referencing it with a join query when needed. Under such a heavy load the SELECT and inserts get slowed . This did not seem to help anything. Basically: we’ve moved to PostgreSQL, which is a real database and with version 8.x is fantastic with speed as well. Think of data as being names in an address book. “So you understand how much having data in memory changed things here is small example with numbers.” -OMG. In theory optimizer should know and select it automatically. The MySQL Query Cache. And if not, you might become upset and become one of those bloggers. Out I/O system offer around 60MB/sec but before this limit is reached the I/O system is flooded by very high amount on IOPS (we have observed around 1200 IOPS). Maybe the memory is full? I know some big websites are using MySQL, but we had neither the budget to throw all that staff, or time, at it. I simply put the search index in a separate table, of some 80 MB and the binary / blobs in another. Seems like we’re going in circles with these. This could be done by data partitioning (i.e. Each row record is approx. I expect performance of this to be in terms of seconds to minutes. The type of table it is — is it MYISAM or INNODB? Regarding how to estimate I would do some benchmarks and match them against what you would expect and what you’re looking for. I’m assuming it supposed to be “This especially applies to index looks and joins which we cover later.”. One tool that MySQL offers is the EXPLAIN keyword. Hello,pls suggest the solution for my problem. along with time when event happened. So if you’re dealing with large data sets and complex queries here are few tips. Red Hat and the Red Hat logo are trademarks of Red Hat, Inc., registered in the United States and other countries. We’ve got 20,000,000 bank loan records we query against all sorts of tables. Now the page loads quite slowly. Joins to smaller tables is OK but you might want to preload them to memory before join so there is no random IO needed to populate the caches. SETUP B: It was decided to use MYSql instead of MS SQL. (I’ve been struggling with this one for about a week now. The table has hundreds of millions of records. Does this look like a performance nightmare waiting to happen? Prefer full table scans to index accesses – For large data sets, full table scans are often faster than range scans and other types of index lookups. The select speed on InnoDB is painful and requires huge hardware and memory to be meaningful. I noticed that when there were few million records in both table, things got extremely sluggish. I wonder how I can optimize my table. Would duplicating data on inserts and updates be an option which would mean having two of the same table, one using InnoDB for main reading purposes and one for MyISAM for searching using Full text search and every time you do an update actually uipdate bith table etc. 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. id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE stat range dateline dateline 4 NULL 277483 Using where; Using temporary; Using filesort 1 SIMPLE iplist eq_ref PRIMARY PRIMARY 4 vb38.stat.ip_interval 1. Anyway… not the correct forum/blog. Get the highlights in your inbox every week. After that, the pictures are quickly located using the indexed album_id column. We will have to do this check in the application. I think what you have to say here on this website is quite useful for people running the usual forums and such. Let’s do some computations again. loaded into large tables, total mysql data size is 96 gig, the large tables are 2-6 gig. I m using php 5 and MySQL 4.1………. Of course, this is all RDMS for beginners, but, I guess you knew that. Sorry for the confusion, but this is what I was talking about also. Perhaps some process whereby you step through the larger table say 1000 records at a time? Yes my ommission. My strategy is to go through the lists one by one, and, for each list, insert the 50 * 49 / 2 pairs into a table with 3 columns (id1, id2, cnt) (where the pair id1, id2 forms the primary key) using INSERT … ON DUPLICATE KEY UPDATE cnt = cnt + 1. Subscribe now and we'll send you an update every Friday at 1pm ET. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. That somehow works better. 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. Adding the index really helped our reporting, BUT now the inserts are taking forever. Hardware is not an issue, that is to say I can get whatever hardware I need to do the job. CREATE TABLE user_attributes ( id INT PRIMARY KEY NOT NULL AUTO_INCREMENT, user_id INT NOT NULL, attribute_name VARCHAR(255) NOT NULL, attribute_value VARCHAR(255), UNIQUE INDEX index_user_attributes_name(user_id, attribute_name) ); This is the basic key-value store pattern where you can have many attributes per user. Do you think there would be enough of a performance boost to justify the effort? the time for retrieving records between 1-20000, 20000-40000, … is quite stable (about 5 seconds for each range). 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. The big sites such as Slashdot and so forth have to use massive clusters and replication. Most of your sentences don’t pass as “sentences”. We’ll need to perform 30 million random row reads, which gives us 300,000 seconds with 100 rows/sec rate. Missouri Raccoon Season, What To Order At Rasika, Southern Comfort And Orange Juice, Spicy Cabbage And Noodles Recipe, Arizona Desert Shrubs, How Does The Fed Print Money Reddit, Minimum Wage Australia After Tax, Pros And Cons Of Artificial Intelligence 2019, mysql query slow on large table" />
mysql query slow on large table

or just when you have a large change in your data distribution in your table? We have aprox 14,000,000 records using over 16gigs storage. PostgreSQL solved it for us. >>Use multiple servers to host portions of data set, Where can I find out more about this comment? 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. Administrative statements include ALTER TABLE, ANALYZE TABLE, CHECK TABLE, CREATE INDEX, DROP INDEX, OPTIMIZE TABLE, and REPAIR TABLE. Yes that is the problem. “the good solution is to make sure your data fits in memory as good as possible”. [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. 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. How you obtained a masters degree is beyond me. i joined 6 tables and the result using explain is, Tables Result master 130000 Sorting, temporary… subrtable 1 overal records is 20 subtable2 100 overal records is 100 subtable3 1 – overal records is 13,0000 subtable4 1 – the overall records of this is more than 100 thousand records, running the query with subtable4 took 36 – 59 secs running the query without took 6 secs, i want to have at less 1 sec run per query. All it does is process these logs, and handle the occasional query we need to do when we run a report for someone, maybe once a week. But if I do Description: Joins of "large" data sets virtually take forever. I found that setting delay_key_write to 1 on the table stops this from happening. It should be named "MySQL for beginners", because this is really database 101 for DBA's. After 26 million rows with this option on, it suddenly takes 520 seconds to insert the next 1 million rows.. Any idea why? Let me show you something: # Query_time: 1 Lock_time: 0 Rows_sent: 1 Rows_examined: 150000 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; This query is fine. My website has about 1 million hits daily . in a manner that the table size remain in a good range for fast queries. You can either flip through all the pages, or you can pull on the right letter tab to quickly locate the name you need. Some indexes may be placed in a sorted way or pages placed in random places – this may affect index scan/range scan speed dramatically. >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. It is not currently Want to improve . Obviously, this gets expensive with huge databases, but you still want to have a good percentage of the db in RAM for good performance. Tnx. It however can’t make row retrieval which is done by index sequential one. Would be a great help to readers. Is this normal – for a delete involving 2 tables to take so long? The more indexes you have the faster SELECT statments are, but the slower INSERTS and DELETES. 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). Could I maybe disable some concurrency related checks (as I have exactly one process inserting into the table, which I could even stop when I want to read data)? 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.. You will probably find that the many smaller queries actually shorten the entire time it takes. So long as your inserts are fast, I wouldn’t worry about it. 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. Surely the whole point of using a relational database is predicated upon normalisation. 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. After this one is INSERTed I can easily INSERT 100.000 (in groups of 150) in less than 10 minutes. Normally MySQL is rather fast loading data in MyISAM table, but there is exception, which is when it can’t rebuild indexes by sort but builds them row by row instead. UPDATES: 200 3. 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. 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. Im working on a project which will need some tables with about 200-300 million rows. I finally now resorting to small snapshots approach. System: It’s now on a 2xDualcore Opteron with 4GB Ram/Debian/Apache2/MySQL4.1/PHP4/SATA Raid1) In near future I will have the Apache on a dedicated machine and the Mysql Server too (and the next step will be a Master/Slave server setup for the database). Obviously I would like to be able to process as many lists as possible and thus I would like to have the insertion process as fast as possible. Once you know which are the offending queries, you can start exploring what makes them slow. We’re using LAMP. 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. Thank you for taking an interest! Also have two myisam tables: One with 5 million records using 1.2 GB of You can significantly increase performance by using indexes. Increasing performance of bulk updates of large tables in MySQL Wednesday, November 6th, 2013 I recently had to perform some bulk updates on semi-large tables (3 to 7 million rows) in MySQL. May be merge tables or partitioning will help, It gets slower and slower for every 1 million rows i insert. Peter, Thanks. One could could call it trivial fast task, unfortunately I had unique key on varchar(128) as part of the schema. You can’t go away with ALTER TABLE DISABLE KEYS as it does not affect unique keys. She enjoys realizing seemingly impossible things. It scans 2,000,000 pictures, then, for each picture, it scans 20,000 albums. On the other hand, it is well known with customers like Google, Yahoo, LiveJournal, and Technorati, MySQL has installations with many billions of rows and delivers great performance. 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. For example, you can add an index on picture.album_id like this: Now if you run the query, the process no longer involves scanning the entire list of pictures. I run the following query, which takes 93 seconds ! My question is what my plan of attack should be to get the best insert performance? As you could see in the article in the test I’ve created range covering 1% of table was 6 times slower than full table scan… which means at about 0.2% table scan is preferable. QUESTION: 1) Why does MS SQL performs faster when they have the same specs though with different OS? Maybe I can rewrite the SQL, since it seems like MySQL handles ONE JOIN, but no way it handles TWO JOINS. 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. Everything is real real slow. Mysql ver. Processing in memory is so much faster and you have whole bunch of problems solved just doing so. Then run your code and any query above the specified threshold will be added to that file. So I guess a better question is, 30 million records, 1 million users with 30 records each You mentioned (and I have experienced) that a composite key starting with userid in Innodb is indeed very efficient and fast. Answer depends on selectivity at large extent as well as if where clause is matched by index or full scan is performed. It also simply does not have the data available – is given index (range) currently in memory or will it need to read it from the disk ? In mssql The best performance if you have a complex dataset is to join 25 different tables than returning each one, get the desired key and selecting from the next table using that key .. Consider using FULLTEXT index. Consider a table which has 100-byte rows. Here’s my query. Although the storage requirements for this is higher than a fixed-columns arrangement with the perpetually frustrating names like attribute1, the cost is small enough in the age of terabyte-sized hard-drives that it’s rarely an issue. Also do not forget to try it out for different constants – plans are not always the same. 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. 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. Try to fit data set you’re working with in memory – Processing in memory is so much faster and you have a whole bunch of problems solved just doing so. Each file we process is about 750MB in size, and we insert 7 of them nightly. We encountered the performance problem when we join two large tables. Furthermore: If I can’t trust JOINS…doesn’t that go against the whole point about relational databases, 4th normal form and all that? MERGE tables? Hi, Im working proffesionally with postgresql and mssql and at home im using mysql for my leasure projects .. I think you can give me some advise. . When you run a query that should extract many rows, then faster solution is to scan entire table. For example, if a table with 30 million records and a composite key on userID, Could one expect better performance by splitting into 30 tables of 1 million records each, or are composite keys that efficient? Thank you. But, never tried explaining a bit on it? 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. SPECS of SETUP A: OS: Windows XP Prof Memory: 512MB. I think the root of my issue is that the indexes don’t fit into RAM. 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. I had 40000 row in database when ever i fire this query in mysql its taking too much time to get data from database. the co-occurrence counts of item-pairs). 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. The large table has 2 indexes on it and totals 3 GB – more than the ram in the machine – this done on Ubuntu 10. 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. you could use your master for write queries like, update or insert and the slave for selects. It has exactly one table. @ankit: replications? Hi. We are at a loss here. How the Query Cache Operates. Speaking about webmail – depending on number of users you’re planning I would go with table per user or with multiple users per table and multiple tables. old_passwords=1 big-tables, [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid, – i have webmin installed, but when I change mysql vars and restart server, my configs are not applied, defautl mysql. This is because the indexes have to be rewritten everytime you make a change. How should I create table structure so I can do rankings for each user based on their average score? 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. There are many design and configuration alternatives to deliver you what you’re looking for. Execution time As discussed in Chapter 2 , the standard slow query logging feature in MySQL 5.0 and earlier has serious limitations, including lack … Great article. Integrity checks don’t work — try making a check on a column NOT NULL to include NOT EMPTY (i.e., no blank space can be entered, which as you know, is different from NULL). I guess it’s all about memory vs hard disk access. As you can see, using index hints can further increase the query speed. First, all the albums are scanned to find the ones that belong to the user. No problem. …a nested select. So feel free to post there and I also invite you to join our community, too. 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. You need a lot of work on your technical writing skills. I have a table with a unique key on two columns (STRING, URL). I could send the table structures and queries/ php cocde that tends to bog down. But for my mysql server I’m having performance issues, sÃ¥ my question remains, what is the best route, join and complex queries, or several simple queries. And update the current status on the blog itself. Obviously, the resulting table becomes large (example: approx. Any hope that this issue will be fixed any time soon? So, I want to count, how many lists contain both, item1 and item2, item1 and item3, etc. Set slow_query_log_file to the path where you want to save the file. – what parameters i need to insert manually in my.cnf for best performance & low disk usage? Meanwhile the table has a size of 1,5Gb. Indexes end up becoming a liability when updating a table.. The following MySQL settings should be added to your my.cnf within [mysqld] / [mysqld_safe] to enable slow query - … applied, and my.cnf are not modified. I may add that this one table had 3 million rows, and growing pretty slowly given the insert rate. 4 million rows), the execution time is more or less 30 seconds. Is there something special about a delete that makes it MUCH MUCH slower than a select? To use it, open the my.cnf file and set the slow_query_log variable to "On." To answer my own question I seemed to find a solution. 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? Joins are used to compose the complex object which was previously normalized to several tables, or perform complex queries finding relationships between objects. I have tried adjusting the join_buffer_size (128M and 16M) but to no avail. Note: multiple drives do not really help a lot as we’re speaking about single thread/query here. This query takes about 45 minutes to execute (DELETE FROM Data WHERE Cat=’1021′ AND LastModified < ‘2007-08-31 15:48:00’). 4 Googlers are speaking there, as is Peter. The things you wrote here are kind of difficult for me to follow. 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. I have MYSQL database performance issue and I have updated the MYSQL Performance blog as below link. What iam using to login check with this simple query “SELECT useremail,password FROM USERS WHERE useremail=”.$_REQUEST[‘USER_EMAIL’].”AND password=” .$_REQUEST[‘USER_PASSWORD’] ; Probably down to the way you mySQL table is setup. ), which is what it’s intended, but INSERTing in them is a nightmare. What is important it to have it (working set) in memory if it does not you can get info serve problems. The ‘data’ attribute contents the binary fragments. I did not mentioned it in the article but there is IGNORE INDEX() hint to force full table scan. Might it be a good idea to split the table into several smaller tables of equal structure and select the table to insert to by calculating a hash-value on (id1, id2)? For example: This query joins 200000 rows with 80000 rows on UUID(). $_REQUEST[‘USER_PASSWORD’] = mysql_real_escape_string($_REQUEST[‘USER_PASSWORD’]); otherwise some little script kiddy is going to cause you an even bigger problem in the future. The queries that were taking less than 1 second some times ago are taking at least 20 to 30 seconds. The server layer, which contains the query optimizer, doesn’t store statistics on data and indexes. Here are some of the ways I know. Inserts are done on dupe key ignore, this takes hours on the large files, it barely keeps up with input files. I am having a problem with updating records in a table. I’m actually quite surprised. Whenever I run “SELECT COUNT(*) FROM MYTABLE WHERE status=1” it was tooking only miliseconds from a mysql interface (in 120.000 records). Peter, I have similar situation to the message system, only mine data set would be even bigger. I’ve read SHE-DBA’s blog on using MySQL as a data-warehousing platform and where it _can_ be used as such provided the design is good and the queries are optimised. Using SQL_BIG_RESULT helps to make it use sort instead. I do multifield select on indexed fields, and if row is found, I update the data, if not I insert new row). So give your Anaconda small pieces of meat than full deer all in once. 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). Joining from a view to any table hides all indexes except those on the joined to tables. Also, are there any suggestions about which storage engine to use? Wednesday, November 6th, 2013. I was hoping to see the machine either disk or CPU-bound to help troubleshoot what the problem is, but this is not the case. The question I have, is why is this happening, and if there is any kind of query I can preform in order to “focus” the DBMS “attention” to the particular table (in context), since SELECTing data is always faster then INSERTing it. I’m currently at design time, and at half the specified month period, and so far, the tables are about 10GB in size each (so far, 6 in total). There is no appreciable performance gain. 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. The problem is – unique keys are always rebuilt using key_cache, which means we’re down to some 100-200 rows/sec as soon as index becomes significantly larger than memory. For a table with several columns, to reduce memory requirements for queries that do not use the BLOB column, consider splitting the BLOB column into a separate table and referencing it with a join query when needed. Under such a heavy load the SELECT and inserts get slowed . This did not seem to help anything. Basically: we’ve moved to PostgreSQL, which is a real database and with version 8.x is fantastic with speed as well. Think of data as being names in an address book. “So you understand how much having data in memory changed things here is small example with numbers.” -OMG. In theory optimizer should know and select it automatically. The MySQL Query Cache. And if not, you might become upset and become one of those bloggers. Out I/O system offer around 60MB/sec but before this limit is reached the I/O system is flooded by very high amount on IOPS (we have observed around 1200 IOPS). Maybe the memory is full? I know some big websites are using MySQL, but we had neither the budget to throw all that staff, or time, at it. I simply put the search index in a separate table, of some 80 MB and the binary / blobs in another. Seems like we’re going in circles with these. This could be done by data partitioning (i.e. Each row record is approx. I expect performance of this to be in terms of seconds to minutes. The type of table it is — is it MYISAM or INNODB? Regarding how to estimate I would do some benchmarks and match them against what you would expect and what you’re looking for. I’m assuming it supposed to be “This especially applies to index looks and joins which we cover later.”. One tool that MySQL offers is the EXPLAIN keyword. Hello,pls suggest the solution for my problem. along with time when event happened. So if you’re dealing with large data sets and complex queries here are few tips. Red Hat and the Red Hat logo are trademarks of Red Hat, Inc., registered in the United States and other countries. We’ve got 20,000,000 bank loan records we query against all sorts of tables. Now the page loads quite slowly. Joins to smaller tables is OK but you might want to preload them to memory before join so there is no random IO needed to populate the caches. SETUP B: It was decided to use MYSql instead of MS SQL. (I’ve been struggling with this one for about a week now. The table has hundreds of millions of records. Does this look like a performance nightmare waiting to happen? Prefer full table scans to index accesses – For large data sets, full table scans are often faster than range scans and other types of index lookups. The select speed on InnoDB is painful and requires huge hardware and memory to be meaningful. I noticed that when there were few million records in both table, things got extremely sluggish. I wonder how I can optimize my table. Would duplicating data on inserts and updates be an option which would mean having two of the same table, one using InnoDB for main reading purposes and one for MyISAM for searching using Full text search and every time you do an update actually uipdate bith table etc. 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. id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE stat range dateline dateline 4 NULL 277483 Using where; Using temporary; Using filesort 1 SIMPLE iplist eq_ref PRIMARY PRIMARY 4 vb38.stat.ip_interval 1. Anyway… not the correct forum/blog. Get the highlights in your inbox every week. After that, the pictures are quickly located using the indexed album_id column. We will have to do this check in the application. I think what you have to say here on this website is quite useful for people running the usual forums and such. Let’s do some computations again. loaded into large tables, total mysql data size is 96 gig, the large tables are 2-6 gig. I m using php 5 and MySQL 4.1………. Of course, this is all RDMS for beginners, but, I guess you knew that. Sorry for the confusion, but this is what I was talking about also. Perhaps some process whereby you step through the larger table say 1000 records at a time? Yes my ommission. My strategy is to go through the lists one by one, and, for each list, insert the 50 * 49 / 2 pairs into a table with 3 columns (id1, id2, cnt) (where the pair id1, id2 forms the primary key) using INSERT … ON DUPLICATE KEY UPDATE cnt = cnt + 1. Subscribe now and we'll send you an update every Friday at 1pm ET. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. That somehow works better. 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. Adding the index really helped our reporting, BUT now the inserts are taking forever. Hardware is not an issue, that is to say I can get whatever hardware I need to do the job. CREATE TABLE user_attributes ( id INT PRIMARY KEY NOT NULL AUTO_INCREMENT, user_id INT NOT NULL, attribute_name VARCHAR(255) NOT NULL, attribute_value VARCHAR(255), UNIQUE INDEX index_user_attributes_name(user_id, attribute_name) ); This is the basic key-value store pattern where you can have many attributes per user. Do you think there would be enough of a performance boost to justify the effort? the time for retrieving records between 1-20000, 20000-40000, … is quite stable (about 5 seconds for each range). 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. The big sites such as Slashdot and so forth have to use massive clusters and replication. Most of your sentences don’t pass as “sentences”. We’ll need to perform 30 million random row reads, which gives us 300,000 seconds with 100 rows/sec rate.

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mysql query slow on large table