Top 84 MySQL Performance Tips

MySQL is a widely used and fast SQL database server. It is a client/server implementation that consists of a server daemon (mysqld) and many different client programs/libraries.

You can check the same tips from here.Here is very useful tips for all mysql DBA’s,Developers these tips are noted from MySQL Camp 2006 suggested by mysql community experts.

  1. Kaj (Most Excellent Obvious Facilitator) Index stuff.
  2. Ronald Don’t Index Everything
  3. Use benchmarking
  4. Minimize traffic by fetching only what you need.
    1. Paging/chunked data retrieval to limit
    2. Don’t use SELECT *
    3. Be wary of lots of small quick queries if a longer query can be more efficient
  5. Use EXPLAIN to profile the query execution plan
  6. Use Slow Query Log (always have it on!)
  7. Don’t use DISTINCT when you have or could use GROUP BY
  8. Use proper data partitions
    1. For Cluster. Start thinking about Cluster *before* you need them
  9. Insert performance
    1. Batch INSERT and REPLACE
    2. Use LOAD DATA instead of INSERT
  10. LIMIT m,n may not be as fast as it sounds
  11. Don’t use ORDER BY RAND() if you have > ~2K records
  12. Use SQL_NO_CACHE when you are SELECTing frequently updated data or large sets of data
  13. avoid wildcards at the start of LIKE queries
  14. avoid correlated subqueries and in select and where clause (try to avoid in)
  15. config params —
  16. no calculated comparisons — isolate indexed columns
  17. innodb_flush_commit=0 can help slave lag
  18. ORDER BY and LIMIT work best with equalities and covered indexes
  19. isolate workloads don’t let administrative work interfere with customer performance. (ie backups)
  20. use optimistic locking, not pessimistic locking. try to use shared lock, not exclusive lock. share mode vs. FOR UPDATE
  21. use row-level instead of table-level locking for OLTP workloads
  22. Know your storage engines and what performs best for your needs, know that different ones exist.
    1. use MERGE tables ARCHIVE tables for logs
  23. Optimize for data types, use consistent data types. Use PROCEDURE ANALYSE() to help determine if you need less
  24. separate text/blobs from metadata, don’t put text/blobs in results if you don’t need them
  25. if you can, compress text/blobs
  26. compress static data
  27. don’t back up static data as often
  28. 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)
  29. enable and increase the query and buffer caches if appropriate
  30. ALTER TABLE…ORDER BY can take chronological data and re-order it by a different field
  31. 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
  32. Do not duplicate indexes
  33. Utilize different storage engines on master/slave ie, if you need fulltext indexing on a table.
  34. BLACKHOLE engine and replication is much faster than FEDERATED tables for things like logs.
  35. Design sane query schemas. don’t be afraid of table joins, often they are faster than denormalization
  36. Don’t use boolean flags
  37. Use a clever key and ORDER BY instead of MAX
  38. Keep the database host as clean as possible. Do you really need a windowing system on that server?
  39. Utilize the strengths of the OS
  40. Hire a MySQL ™ Certified DBA
  41. Know that there are many consulting companies out there that can help, as well as MySQL’s Professional Services.
  42. 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
  43. Know when to split a complex query and join smaller ones
  44. Debugging sucks, testing rocks!
  45. Delete small amounts at a time if you can
  46. Archive old data — don’t be a pack-rat! 2 common engines for this are ARCHIVE tables and MERGE tables
  47. use INET_ATON and INET_NTOA for IP addresses, not char or varchar
  48. make it a habit to REVERSE() email addresses, so you can easily search domains
  49. –skip-name-resolve
  50. increase myisam_sort_buffer_size to optimize large inserts (this is a per-connection variable)
  51. look up memory tuning parameter for on-insert caching
  52. 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)
  53. Normalize first, and denormalize where appropriate.
  54. Databases are not spreadsheets, even though Access really really looks like one. Then again, Access isn’t a real database
  55. In 5.1 BOOL/BIT NOT NULL type is 1 bit, in previous versions it’s 1 byte.
  56. A NULL data type can take more room to store than NOT NULL
  57. Choose appropriate character sets & collations — UTF16 will store each character in 2 bytes, whether it needs it or not, latin1 is faster than UTF8.
  58. make similar queries consistent so cache is used
  59. Have good SQL query standards
  60. Don’t use deprecated features
  61. Use Triggers wisely
  62. Run in SQL_MODE=STRICT to help identify warnings
  63. 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.
  64. /tmp dir on battery-backed write cache
  65. consider battery-backed RAM for innodb logfiles
  66. use min_rows and max_rows to specify approximate data size so space can be pre-allocated and reference points can be calculated.
  67. 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.
  68. pare down cron scripts
  69. create a test environment
  70. try out a few schemas and storage engines in your test environment before picking one.
  71. Use HASH indexing for indexing across columns with similar data prefixes
  72. Use myisam_pack_keys for int data
  73. 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()
  74. use –safe-updates for client
  75. Redundant data is redundant
  76. Use INSERT … ON DUPLICATE KEY update (INSERT IGNORE) to avoid having to SELECT
  77. use groupwise maximum instead of subqueries
  78. be able to change your schema without ruining functionality of your code
  79. source control schema and config files
  80. for LVM innodb backups, restore to a different instance of MySQL so Innodb can roll forward
  81. use multi_query if appropriate to reduce round-trips
  82. partition appropriately
  83. partition your database when you have real data
  84. segregate tables/databases that benefit from different configuration variables

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    10 thoughts on “Top 84 MySQL Performance Tips

    1. Thanks for a good list. Here are a few more tips:

      -Use as short indexes as possible. Use smallint if you don’t need a whole int. When indexing hex data (eg md5 hash), you can store it as two BIGINTs.
      -Delete data that you don’t need. Tables will grow, so monitor table sizes regularly. Use partitioning (or archive, or merge tables as mentioned above).
      -Use SHOW PROFILES to get more details than EXPLAIN
      -Monitor the heaviest queries, for example using Jet Profiler for MySQL

    2. “37. Use a clever key and ORDER BY instead of MAX”

      what is a ‘clever key’?

      is this just a column with a ‘1’ to flag the max?

    3. Hands down, the best way to improve MySQL performance is PHP data caching. What I normally do is cache the data results from a MySQL query into a table called ‘cache’ that establishes a primary key associated with that specific data. If a user accesses that data, and the cache time hasn’t expired, I grab the data from the cache which is easily 2000 faster. (primary key lookups are a cinch)

    4. Other tips:
      – think about persistent connections
      – use the right MySQL connector (e.g. PHP’s mysqli is far better than the older mysql)

    5. > Use Slow Query Log (always have it on!)

      for what? use Slow Query Log for develop

      >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()

      Do not use SQL_CALC_FOUND_ROWS too, because it is slow (no much faster than COUNT).

      > pare down cron scripts
      you can solve some task with cron scripts, but at this time load increasing at server, its no good really

      > Don’t use ORDER BY RAND() if you have > ~2K records
      do not use ORDER BY RAND() never. You know range ID’s (last auto_increment, for ex.) and generate random value from script

    6. Hi there, thanks for the helpful list.

      If I may just ask about point no. 24: “separate text/blobs from metadata, don’t put text/blobs in results if you don’t need them”.

      How exactly is this division achieved?
      Do you have two tables (or two databases?) one holding blobs, and the other, metadata (with a foreign key)?
      Is this a secure and reliable strategy?
      Are there certain things I need be warned of?

      Thanks for your time.

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