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MySQL Replication: Getting Most
      from the Slaves
                 April 23, 2009
                 Percona Performance
                 Conference
                 Santa Clara,CA
                 by Peter Zaitsev, Percona Inc
-2-



             The Slaves Problem
• The problems you have if you want to scale with
  multiple slaves
  – How to keep write rate down
     • High write rate allows you to have little reads per slave
  – How to utilize slave resources efficiently
     • Space and Memory Application
  – How to Make your application to be able to maximize slave
     usage
Is this the right problem ?
• Many small-medium size applications use replication
  for HA only
  – It may be cheaper to have slave just for standby
• Very large scale applications use sharding
  – Using only 1-2 slaves per shard
• Should you cache more in memcache ?
Reducing Write Rate
Optimize Replication Traffic
• Refer to “Fighting MySQL Replication Lag”
  presentation
• Analyze your write queries
  – Optimize them
     • Proper indexing
     • Split frequently changed vs rarely changed data
  – Merge them (ie counters)
  – Throw them away
     • Temporary tables used for selects
Reduce Replication Traffic
• Do you need to replicate all tables ?
  – I prefer at least one full slave for high availability
• Can you move some tables to other instance ?
• Does all writes have to happen to the database at
  all?
  – Sessions/counters in memcache
• Do you need all indexes on the slave ?
• Does the slave have to have same storage engine ?
• Can you move some updates bypassing replication
  – Periodic table dump/physical copy
Utilizing Slave Resources
High end storage is expensive
• High end IO subsystem is not cheap
   – Both classical hard drives and SSDs
• Many full slaves = a lot of duplication
• Partial solutions
   – Sharding
   – Consolidation (less slaves = less duplication)
   – Partial replication
      • Select tables to replicate
      • Archive data from slaves more promptly
Memory Duplication
• Contents of cache memory is highly duplicated
   – Which is a waste too
• Partial solutions
   – Session stickiness
   – Data driven routing
      • All users below 10000 read from server A, rest from B
   – Query type routing
      • Different queries are done from different slaves
• Makes slave high availability handling harder
Slave Specialization
• Using different storage engine
  – MyISAM, while Master is Innodb
     • Beware, there are some problems mixing storage engines
• Using different index structure
  – Different slaves serving different query types can have
    different indexes
• MyISAM with Full Text Search is both different
  storage engine and different indexes
Using Slave in Application
Dealing with Stale Data
•   Query Based
•   Session Based
•   Data Versioning
•   There are more but these are most important
Query Based
• Some queries can read stale data
  – Send them to the slaves
• Other queries need real time data
  – So they have to run in master
• Monitor slave delay and kick off slaves too far behind
  from read pool.
Session Based
• The user which did modification sees the current
  data
  – Reads the master long enough for slave to catch up
• The user which did not write the data recently
  – Can read from the slave
  – Should be “sticky” as we do not want going back in time on
    repeated reads.
• Trickier to implement because requires tracking “real
  writes” on the application
  –
Data Versioning
• Multiple Flavors
  – We compare the version on the slave to current version.
     • Re-read from master if it is too old
• Memcache can be used to keep object versions
• “Object” - reasonable size
  – “User”, “Blog” is a decent choice
• Binary Log position is the good version
  – Can check version on the slave by SHOW SLAVE STATUS
     • No true data read from slave needed until version confirmed
The End

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My S Q L Replication Getting The Most From Slaves

  • 1. MySQL Replication: Getting Most from the Slaves April 23, 2009 Percona Performance Conference Santa Clara,CA by Peter Zaitsev, Percona Inc
  • 2. -2- The Slaves Problem • The problems you have if you want to scale with multiple slaves – How to keep write rate down • High write rate allows you to have little reads per slave – How to utilize slave resources efficiently • Space and Memory Application – How to Make your application to be able to maximize slave usage
  • 3. Is this the right problem ? • Many small-medium size applications use replication for HA only – It may be cheaper to have slave just for standby • Very large scale applications use sharding – Using only 1-2 slaves per shard • Should you cache more in memcache ?
  • 5. Optimize Replication Traffic • Refer to “Fighting MySQL Replication Lag” presentation • Analyze your write queries – Optimize them • Proper indexing • Split frequently changed vs rarely changed data – Merge them (ie counters) – Throw them away • Temporary tables used for selects
  • 6. Reduce Replication Traffic • Do you need to replicate all tables ? – I prefer at least one full slave for high availability • Can you move some tables to other instance ? • Does all writes have to happen to the database at all? – Sessions/counters in memcache • Do you need all indexes on the slave ? • Does the slave have to have same storage engine ? • Can you move some updates bypassing replication – Periodic table dump/physical copy
  • 8. High end storage is expensive • High end IO subsystem is not cheap – Both classical hard drives and SSDs • Many full slaves = a lot of duplication • Partial solutions – Sharding – Consolidation (less slaves = less duplication) – Partial replication • Select tables to replicate • Archive data from slaves more promptly
  • 9. Memory Duplication • Contents of cache memory is highly duplicated – Which is a waste too • Partial solutions – Session stickiness – Data driven routing • All users below 10000 read from server A, rest from B – Query type routing • Different queries are done from different slaves • Makes slave high availability handling harder
  • 10. Slave Specialization • Using different storage engine – MyISAM, while Master is Innodb • Beware, there are some problems mixing storage engines • Using different index structure – Different slaves serving different query types can have different indexes • MyISAM with Full Text Search is both different storage engine and different indexes
  • 11. Using Slave in Application
  • 12. Dealing with Stale Data • Query Based • Session Based • Data Versioning • There are more but these are most important
  • 13. Query Based • Some queries can read stale data – Send them to the slaves • Other queries need real time data – So they have to run in master • Monitor slave delay and kick off slaves too far behind from read pool.
  • 14. Session Based • The user which did modification sees the current data – Reads the master long enough for slave to catch up • The user which did not write the data recently – Can read from the slave – Should be “sticky” as we do not want going back in time on repeated reads. • Trickier to implement because requires tracking “real writes” on the application –
  • 15. Data Versioning • Multiple Flavors – We compare the version on the slave to current version. • Re-read from master if it is too old • Memcache can be used to keep object versions • “Object” - reasonable size – “User”, “Blog” is a decent choice • Binary Log position is the good version – Can check version on the slave by SHOW SLAVE STATUS • No true data read from slave needed until version confirmed