proxysql use case scenarios fosdem17
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ProxySQL Use Case Scenarios
FOSDEM FEB 3 2017
Alkin Tezuysal
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Who am I?
• Alkin TezuysalSr. Technical Manager, Percona@ask_dba
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Top 5 reasons to use ProxySQL
• Improve database operations.
• Understand and solve performance issues.
• Create a proxy layer to shield the database.
• Add High-Availability to database topology.
• Empower the DBAs with great tool.
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ProxySQL Highlights
Scalability High Availability
Advanced Query Support Manageability
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Use case overview - Scalability
Connection Pooling and Multiplexing
Add connection pooling layer
Reduce connection thread overhead
Read / Write SplitMore scalability for any MySQL topology
Must for any heavy workloads
Read / Write Sharding
Effortless sharding implementation
Without Dev. support and cost savings
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Use case overview - High Availability
Seamless Failover Graceful failover support
Query rerouting
Load BalancingAllows easy scaling
For better utilization of servers
Cluster Aware Supports PXC/Galera implementations
Small footprint for big gain
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Use case overview - Advanced Queries
Query caching Cache frequently used data
Adds another cache layer
Query rewrite Add SQL flexibility
Faster problem solving
Query blocking Add database aware firewall
Without App. support
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Use case overview - Advanced Queries
Query mirroringAudit, Analyze, Review, Cache Warming
Allow benchmarking on live data
Query throttlingSet prioritization for important queries
Allows manual intervention to problem queries
Query timeout Add another timeout layer
Flexible query level timeout
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Use case overview - Manageability
Admin Utility Authentication support
Limit user access to database pool
Runtime reconfiguration
On the fly modifications
Configure database without restart or downtime
Monitoring Stats collection and reporting
Investigate database workload
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Scalability with ProxySQL - Connection Pooling
• Any application without persistent connection to database
• PHP applications to be specific without built in connection pool
Application MySQLProxySQL
• Reduces number of new connections to the database
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Scalability with ProxySQL – Connection Multiplexing
• Any application with persistent connection to database
• Java applications to be specific with built in connection pools
Application Pool
MySQL
• Reduce connections similar to Aurora
• Testing being performed for 300K database connections
Application PoolApplication
Pool
ProxySQL
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Scalability with ProxySQL - Read/Write Split
• On the fly Read / Write implementation
• Use read_only flag to switch traffic
Application
MySQL Master
• Load balancing made easy
MySQL Slave
Write hostgroups
Read hostgroups MySQL
Slave
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Scalability with ProxySQL – User and schema level sharding
• Granular sharding per username and schema
• Backend pooling based on user activity to specific schema
Application User A
ProxySQL
• Use advanced sharding to parallelize queries
• Scale beyond the sharding per host limitations.
Application User B
MySQL Master
MySQL Slave
MySQL Master
MySQL Slave
MySQL Master
MySQL Slave
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MySQL SlaveMySQL Master
High Availability with ProxySQL – Seamless failover
• Neither VIP setup nor service discovery needed
• Use read_only flag to switch traffic
Application Pool MySQL Master
• Integration with other HA Managers
Application PoolApplication
Pool
ProxySQL
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High Availability with ProxySQL – Improve Multi DC implementation
• No connection pools latency on SSL connections.
• Costly delays across the water.
MySQL MasterProxySQL
MySQL Master
ProxySQL
Application
DC1
DC2
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High Availability with ProxySQL – Adoption to Clustering
• PXC / Galera / Group ReplicationMySQL
ProxySQL
•
ProxySQL
Application
Node 1
Application
Application
MySQL
Node 2
MySQL
Node 3
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Advanced Queries with ProxySQL – Caching
• Improve performance on read intensive workloads
• Reduce slave provisioning
Application A
ProxySQL
• Improved query cache over default implementation
• Query aware caching over general caching
Application B
MySQL Master
MySQL Slave
MySQL Slave
MySQL Slave
Cache
MySQL Slave
MySQL Slave
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Advanced Queries with ProxySQL – Query Timeout
• Built in query killer a.k.a query sniper
• Adjustable threshold based on query rule
Application A
ProxySQL
• No idle or long running queries
Application B
MySQL Master
MySQL Slave
MySQL Slave
MySQL Slave
Query Timeouts
MySQL Slave
MySQL Slave
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Advanced Queries with ProxySQL – Firewall
• Protect database from unwanted traffic
• Stop unwanted user, account , application (new code)
Application A
ProxySQL
• Fast modification to database behavior
• Added protection for DDOS and other attacks.
Application B
Query Blocking
MySQL Master
MySQL Slave
MySQL Master
MySQL Slave
MySQL Master
MySQL Slave
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Advanced Queries with ProxySQL – Query rewrite engine
• Most wanted feature by DBAs
• Rewrite queries overloading the database on the fly.
Application A
ProxySQL
• Simply buy time until application can be modified
Application B
MySQL Master
MySQL Slave
MySQL Slave
MySQL Slave
Query Rewriting
MySQL Slave
MySQL Slave
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Advanced Queries with ProxySQL – Query retry
• Server failures or maintenance do not loose a query.
• Fails over and resubmits the query to another host.
Application A
ProxySQL
• Improved operation and new way of handling slaves.
Application B
MySQL Master
MySQL Slave
MySQL Slave
MySQL Slave
Query Retry
MySQL Slave
MySQL Slave
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Advanced Queries with ProxySQL – Query routing
• Selective routing based on importance.
• Use metrics based on stats_mysql_query_digest and decide
Application A
ProxySQL
• Go beyond read/write split.
Application B
MySQL Master
MySQL Slave
MySQL Slave
MySQL Slave
Query Routing
MySQL Slave
MySQL Slave
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Advanced Queries with ProxySQL – Query mirroring
• Mirror incoming queries to different back ends
• Use it for audit, analytics, cache warming, benchmarking.
Application A
ProxySQL
Application B
Query Mirroring
MySQL Master
Host A
Host B
MySQL Slave
MySQL Master
MySQL Slave
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Advanced Queries with ProxySQL
Query caching Query Timeout
Query Retry Query Blocking
Query Routing and Mirroring
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Clustered ProxySQL at scale
Tested with:
● 8 app servers with 3k clients’ connections each (24k total)● 4 middle layer proxysqls processing 4k connections each from local
proxysqls (16k total)● 256 backends/shard (meaning 256 routing rules) processing 600
connections each (150k total)• Up to 1M client connections• 1600 backend servers• 2000 query rules• 100k distinct users• up to 750k QPS
DATABASE PERFORMANCE MATTERS
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