Finally I should mention one more MySQL limitation which requires you to be extra careful working with large data sets. The assumption is that the users arent tech-savvy, and if you need 50,000 concurrent inserts per second, you will know how to configure the MySQL server. supposing im completely optimized. Thanks for contributing an answer to Stack Overflow! I'd advising re-thinking your requirements based on what you actually need to know. e1.evalid = e2.evalid It's much faster. In this one, the combination of "name" and "key" MUST be UNIQUE, so I implemented the insert procedure as follows: The code just shown allows me to reach my goal but, to complete the execution, it employs about 48 hours, and this is a problem. How do two equations multiply left by left equals right by right? statements with multiple VALUES lists The time required for inserting a row is determined by the Nice thanks. val column in this table has 10000 distinct value, so range 1..100 selects about 1% of the table. thread_cache = 32 How do I import an SQL file using the command line in MySQL? Speaking about open_file_limit which limits number of files MySQL can use at the same time on modern operation systems it is safe to set it to rather high values. How much index is fragmented ? This one contains about 200 Millions rows and its structure is as follows: (a little premise: I am not a database expert, so the code I've written could be based on wrong foundations. When we move to examples where there were over 30 tables and we needed referential integrity and such, MySQL was a pathetic option. 2. The string has to be legal within the charset scope, many times my inserts failed because the UTF8 string was not correct (mostly scraped data that had errors). read_rnd_buffer_size = 128M InnoDB doesnt 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. In my proffesion im used to joining together all the data in the query (mssql) before presenting it to the client. PRIMARY KEY (startingpoint,endingpoint) Well need to perform 30 million random row reads, which gives us 300,000 seconds with 100 rows/sec rate. To answer my own question I seemed to find a solution. The problem is not the data size; normalized data normally becomes smaller, but a dramatically increased number of index lookups could be random accesses. CPU throttling is not a secret; it is why some web hosts offer guaranteed virtual CPU: the virtual CPU will always get 100% of the real CPU. FROM tblquestions Q The transaction log is needed in case of a power outage or any kind of other failure. How do I import an SQL file using the command line in MySQL? I was able to optimize the MySQL performance, so the sustained insert rate was kept around the 100GB mark, but thats it. Answer depends on selectivity at large extent as well as if where clause is matched by index or full scan is performed. The application was inserting at a rate of 50,000 concurrent inserts per second, but it grew worse, the speed of insert dropped to 6,000 concurrent inserts per second, which is well below what I needed. sort_buffer_size = 32M What PHILOSOPHERS understand for intelligence? INNER JOIN tblanswersetsanswers_x ASAX USING (answersetid) Very good info! This article puzzles a bit. Check every index if its needed, and try to use as few as possible. A simple AFTER INSERT trigger takes about 7 second. Data retrieval, search, DSS, business intelligence applications which need to analyze a lot of rows run aggregates, etc., is when this problem is the most dramatic. With some systems connections that cant be reused, its essential to make sure that MySQL is configured to support enough connections. 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. PostgreSQL solved it for us. Anyone have any ideas on how I can make this faster? The world's most popular open source database, Download import pandas as pd # 1. Since i enabled them, i had no slow inserts any more. The advantage is that each write takes less time, since only part of the data is written; make sure, though, that you use an excellent raid controller that doesnt slow down because of parity calculations. Needless to say, the cost is double the usual cost of VPS. A foreign key is an index that is used to enforce data integrity this is a design used when doing database normalisation. Asking for help, clarification, or responding to other answers. query_cache_size=32M I have tried changing the flush method to O_DSYNC, but it didn't help. In general you need to spend some time experimenting with your particular tasks basing DBMS choice on rumors youve read somewhere is bad idea. What PHILOSOPHERS understand for intelligence? These other activity do not even need to actually start a transaction, and they don't even have to be read-read contention; you can also have write-write contention or a queue built up from heavy activity. Please feel free to send it to me to pz at mysql performance blog.com. NULL, 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. If the hashcode does not 'follow' the primary key, this checking could be random IO. The fact that Im not going to use it doesnt mean you shouldnt. The reason why is plain and simple - the more data we have, the more problems occur. Im not using an * in my actual statement MySQL is a relational database. LOAD DATA INFILE is a highly optimized, MySQL-specific statement that directly inserts data into a table from a CSV / TSV file. 1. http://tokutek.com/downloads/tokudb-performance-brief.pdf, Increase from innodb_log_file_size = 50M to Some people claim it reduced their performance; some claimed it improved it, but as I said in the beginning, it depends on your solution, so make sure to benchmark it. The query is getting slower and slower. Increasing the number of the pool is beneficial in case multiple connections perform heavy operations. The size of the table slows down the insertion of indexes by what changes are in 5.1 which change how the optimzer parses queries.. does running optimize table regularly help in these situtations? I think that this poor performance are caused by the fact that the script must check on a very large table (200 Millions rows) and for each insertion that the pair "name;key" is unique. I have a project I have to implement with open-source software. Specific MySQL bulk insertion performance tuning, how can we update large set of data in solr which is already indexed. Subscribe to our newsletter for updates on enterprise-grade open source software and tools to keep your business running better. An insert into a table with a clustered index that has no non-clustered indexes, without TABLOCK, having a high enough cardinality estimate (> ~1000 rows) Adding an index to a table, even if that table already has data. Less indexes faster inserts. Runing explain is good idea. 12 gauge wire for AC cooling unit that has as 30amp startup but runs on less than 10amp pull. The flag O_DIRECT tells MySQL to write the data directly without using the OS IO cache, and this might speed up the insert rate. MySQL default settings are very modest, and the server will not use more than 1GB of RAM. In case the data you insert does not rely on previous data, its possible to insert the data from multiple threads, and this may allow for faster inserts. Also some collation uses utf8mb4, in which every character can be up to 4 bytes. Does Chain Lightning deal damage to its original target first? query_cache_type=1 When loading a table from a text file, use LOAD DATA INFILE. In theory optimizer should know and select it automatically. MySQL optimizer calculates Logical I/O for index access and for table scan. http://forum.mysqlperformanceblog.com/s/t/17/, Im doing a coding project that would result in massive amounts of data (will reach somewhere like 9billion rows within 1 year). What sort of contractor retrofits kitchen exhaust ducts in the US? For RDS MySQL, you can consider using alternatives such as the following: AWS Database Migration Service (AWS DMS) - You can migrate data to Amazon Simple Storage Service (Amazon S3) using AWS DMS from RDS for MySQL database instance. Database solutions and resources for Financial Institutions. One could could call it trivial fast task, unfortunately I had I am surprised you managed to get it up to 100GB. LANGUAGE char(2) NOT NULL default EN, INNER JOIN tblanswersets ASets USING (answersetid) The rumors are Google is using MySQL for Adsense. AND e2.InstructorID = 1021338, GROUP BY Q.questioncatid, ASets.answersetname,A.answerID,A.answername,A.answervalue, SELECT DISTINCT spp.provider_profile_id, sp.provider_id, sp.business_name, spp.business_phone, spp.business_address1, spp.business_address2, spp.city, spp.region_id, spp.state_id, spp.rank_number, spp.zipcode, sp.sic1, sp.approved The problem started when I got to around 600,000 rows (table size: 290MB). my key_buffer is set to 1000M, but this problem already begins long before the memory is full. Stack Exchange network consists of 181 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. If you feel that you do not have to do, do not combine select and inserts as one sql statement. The index on (hashcode, active) has to be checked on each insert make sure no duplicate entries are inserted. Even if you look at 1% fr rows or less, a full table scan may be faster. 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