Mohan Testing
- 1. Use EXPLAIN to profile the query execution plan Use Slow Query Log (always have it on!) Don’t use DISTINCT when you have or could use GROUP BY Use proper data partitions 1. For Cluster. Start thinking about Cluster *before* you need them Insert performance 1. Batch INSERT and REPLACE 2. Use LOAD DATA instead of INSERT LIMITm,n may not be as fast as it sounds Don’t use ORDER BY RAND() if you have > ~2K records Use SQL_NO_CACHE when you are SELECTing frequently updated data or large sets of data avoid wildcards at the start of LIKE queries avoid correlated subqueries and in select and where clause (try to avoid in) configparams -- no calculated comparisons -- isolate indexed columns innodb_flush_commit=0 can help slave lag ORDER BY and LIMIT work best with equalities and covered indexes isolate workloads don’t let administrative work interfere with customer performance. (ie backups) use optimistic locking, not pessimistic locking. try to use shared lock, not exclusive lock. share mode vs. FOR UPDATE use row-level instead of table-level locking for OLTP workloads Know your storage engines and what performs best for your needs, know that different ones exist. 1. use MERGE tables ARCHIVE tables for logs Optimize for data types, use consistent data types. Use PROCEDURE ANALYSE() to help determine if you need less separate text/blobs from metadata, don’t put text/blobs in results if you don’t need them if you can, compress text/blobs compress static data don’t back up static data as often derived tables (subqueries in the FROM clause) can be useful for retrieving BLOBs w/out sorting them. (self-join can speed up a query if 1st part finds the IDs and use it to fetch the rest) enable and increase the query and buffer caches if appropriate ALTER TABLE…ORDER BY can take chronological data and re-order it by a different field InnoDB ALWAYS keeps the primary key as part of each index, so do not make the primary key very large, be careful of redundant columns in an index, and this can make the query faster
- 2. Do not duplicate indexes Utilize different storage engines on master/slave ie, if you need fulltext indexing on a table. BLACKHOLE engine and replication is much faster than FEDERATED tables for things like logs. Design sane query schemas. don’t be afraid of table joins, often they are faster than denormalization Don’t use boolean flags Use a clever key and ORDER BY instead of MAX Keep the database host as clean as possible. Do you really need a windowing system on that server? Utilize the strengths of the OS Hire a MySQL ™ Certified DBA Know that there are many consulting companies out there that can help, as well as MySQL’s Professional Services. Config variables & tips: 1. use one of the supplied config files 2. key_buffer, unix cache (leave some RAM free), per-connection variables, innodb memory variables 3. be aware of global vs. per-connection variables 4. check SHOW STATUS and SHOW VARIABLES (GLOBAL|SESSION in 5.0 and up) 5. be aware of swapping esp. with Linux, “swappiness” (bypass OS filecache for innodb data files, innodb_flush_method=O_DIRECT if possible (this is also OS specific)) 6. defragment tables, rebuild indexes, do table maintenance 7. If you use innodb_flush_txn_commit=1, use a battery-backed hardware cache write controller 8. more RAM is good so faster disk speed 9. use 64-bit architectures Know when to split a complex query and join smaller ones Debugging sucks, testing rocks! Delete small amounts at a time if you can Archive old data -- don’t be a pack-rat! 2 common engines for this are ARCHIVE tables and MERGE tables use INET_ATON and INET_NTOA for IP addresses, not char or varchar make it a habit to REVERSE() email addresses, so you can easily search domains --skip-name-resolve increasemyisam_sort_buffer_size to optimize large inserts (this is a per-connection variable) look up memory tuning parameter for on-insert caching increase temp table size in a data warehousing environment (default is 32Mb) so it doesn’t write to disk (also constrained by max_heap_table_size, default 16Mb) Normalize first, and denormalize where appropriate. Databases are not spreadsheets, even though Access really really looks like one. Then again, Access isn’t a real database In 5.1 BOOL/BIT NOT NULL type is 1 bit, in previous versions it’s 1 byte.
- 3. A NULL data type can take more room to store than NOT NULL Choose appropriate character sets & collations -- UTF16 will store each character in 2 bytes, whether it needs it or not, latin1 is faster than UTF8. make similar queries consistent so cache is used Don’t use deprecated features Use Triggers wisely Run in SQL_MODE=STRICT to help identify warnings Turning OR on multiple index fields (<5.0) into UNION may speed things up (with LIMIT), after 5.0 the index_merge should pick stuff up. /tmpdir on battery-backed write cache consider battery-backed RAM for innodblogfiles usemin_rows and max_rows to specify approximate data size so space can be pre- allocated and reference points can be calculated. as your data grows, indexing may change (cardinality and selectivity change). Structuring may want to change. Make your schema as modular as your code. Make your code able to scale. Plan and embrace change, and get developers to do the same. pare down cron scripts create a test environment try out a few schemas and storage engines in your test environment before picking one. Use HASH indexing for indexing across columns with similar data prefixes Usemyisam_pack_keys for int data Don’t use COUNT * on Innodb tables for every search, do it a few times and/or summary tables, or if you need it for the total # of rows, use SQL_CALC_FOUND_ROWS and SELECT FOUND_ROWS() use --safe-updates for client Redundant data is redundant Use INSERT … ON DUPLICATE KEY update (INSERT IGNORE) to avoid having to SELECT usegroupwise maximum instead of subqueries be able to change your schema without ruining functionality of your code source control schema and config files for LVM innodb backups, restore to a different instance of MySQL so Innodb can roll forward usemulti_query if appropriate to reduce round-trips partition appropriately partition your database when you have real data segregate tables/databases that benefit from different configuration variables