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Why does insert to table slow down MySQL?
Inserting to a table that has an index will degrade performance because MySQL has to calculate the index on every insert. In case there are multiple indexes, they will impact insert performance even more. Check every index if it’s needed, and try to use as few as possible.
How to optimize MySQL for faster inserts?
Some optimizations don’t need any special tools, because the time difference will be significant. For example, when we switched between using single inserts to multiple inserts during data import, it took one task a few hours, and the other task didn’t complete within 24 hours.
Why does MySQL support 50, 000 concurrent inserts per second?
The reason for that is that MySQL comes pre-configured to support web servers on VPS or modest servers. The assumption is that the users aren’t tech-savvy, and if you need 50,000 concurrent inserts per second, you will know how to configure the MySQL server.
What kind of storage engine does MySQL use?
MySQL supports two storage engines: MyISAM and InnoDB table type. This article will focus only on optimizing InnoDB for optimizing insert speed. (because MyISAM table allows for full table locking, it’s a different topic altogether) MariaDB and Percona MySQL supports TukoDB as well; this will not be covered as well.
How can I speed up MySQL insert rate?
Using file system compression. Some filesystems support compression (like ZFS ), which means that storing MySQL data on compressed partitions may speed the insert rate. The reason is that if the data compresses well, there will be less data to write, which can speed up the insert rate.
Which is the fastest way to improve MySQL performance?
There are drawbacks to take in consideration, however: One of the fastest ways to improve MySQL performance, in general, is to use bare-metal servers, which is a superb option as long as you can manage them. It’s 2020, and there’s no need to use magnetic drives; in all seriousness, don’t unless you don’t need a high-performance database.
Why is MySQL full text query so slow?
My theory is that ft_min_word_len is longer than “2” on your system (default is 4) so the “word” ’96’ is not actually making it into the full-text index… so you’re doing a full table scan or at least you’re having to find all of the rows containing ‘hannover’ in the index and then discarding the rows not matching the final criteria.
Which is faster to query fulltext or subquery?
Fulltext indexes index tokens very well. Consequently, exact strings that contains multiple tokens should take longer to process. The only way to find hannover 96 faster is to use a subquery.