Pseudo GTID and Easy MySQL Replication Topology Management

Use Pseudo-GTID to refactor your MySQL topologies even in the face of crashed servers. Use open source orchestrator to manage, recover & visualize your topologies

Transcript

1. Pseudo-GTID and Easy MySQL Replication Management Shlomi Noach Percona Live, April 2015
2. Overview: • What? Why? • Replication topologies, types • Binary & relay logs • GTID • Pseudo GTID • Failover with Pseudo GTID, bulk operations • Orchestrator • Pseudo GTID & orchestrator @ Booking.com • Demo • Considerations, gotchas & limitations
3. What? Why? • Be happy! • Avoid using GTID. Pseudo GTID offers what GTID offers, without GTID. This includes: • Slave repointing • Failover schemes • With less requirements • And, with larger topologies: faster! • Without upgrading your servers; without installing anything on them; in short: not touching your beloved existing setup • No vendor lockdown; no migration paths 3
4. MySQL replication topologies 4
5. More complex topologies 5
6. Replication topologies, “classic replication” • Single master, multiple slaves • Nested replication: slaves of slaves • Replication load on master, on network • Intermediate masters: • Upgrades • Schema changes • Switching datacenters • Experiments 6
7. Replication topologies, “classic replication” • Too many slaves on a single master: • Can be too much load (network traffic, dedicated connections) • What happens when the master goes down? • Using intermediate masters: • Reduced load • Accumulating slave lag • What happens when the intermediate master goes down? 7
8. Problem: master goes down 8 !! ?
9. Problem: intermediate master goes down 9 !! ?
10. MySQL binary & relay logs 10 Master Slave
11. MySQL binary & relay logs: different languages 11 Master Slave
12. MySQL binary & relay logs: even more languages 12 Master Slave Slave
13. GTID • Every transaction has a unique identifier • When a slave connects to a master, it looks for the last GTID statement it already executed • Available in Oracle MySQL 5.6, MariaDB 10.0 • Completely different implementations; may cause lockup • 5.6 migration path is unacceptable • 5.6 requires binary logs & log-slave-updates enabled on all slaves • 5.6 issues with errant transactions, unexecuted sequences, … • 5.6 requires adaptation of tools / understanding • 5.6 GTID will be the requirement in future Oracle features • MariaDB GTID supports domains; easy to use 13
14. Pseudo GTID • Application-side enhancement • We inject a uniquely identified statement every X seconds. We call it Pseudo GTID. • Pseudo GTID statements are searchable and identifiable in binary and relay logs • Make for “markers” in the binary/relay logs • Injection can be made via MySQL event scheduler or externally • Otherwise non intrusive. No changes to topology/versions/methodologies 14
15. Injecting Pseudo-GTID create event if not exists create_pseudo_gtid_event on schedule every 5 second starts current_timestamp on completion preserve enable do begin set @pseudo_gtid_hint := uuid(); set @_create_statement := concat('drop ', 'view if exists `meta`.`_pseudo_gtid_hint__', @pseudo_gtid_hint, '`'); PREPARE st FROM @_create_statement; EXECUTE st; DEALLOCATE PREPARE st; end $$ 15
16. In the binary logs mysql> show binlog events in 'mysql-bin.015631' \G ... Log_name: mysql-bin.015631 Pos: 1632 Event_type: Query Server_id: 1 End_log_pos: 1799 Info: use `meta`; drop view if exists `meta`.`_pseudo_gtid_hint__50731a22-9ca4- 11e4-aec4-e25ec4bd144f` ... 16
17. Recap: MySQL binary & relay logs 17 Master Slave
18. MySQL binary & relay logs: a virtual contiguous log file 18 Master Slave
19. MySQL binary & relay logs: Pseudo GTID injection 19 Master Slave insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert update drop update insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert update drop insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert
20. insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert Pseudo GTID: repoint, based on binary logs 20 Master Slave insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert update drop update
21. insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert update drop Pseudo GTID: repoint, based on relay logs 21 Master Slave insert > PGTID 17 update delete create > PGTID 82 delete delete > PGTID 56 insert insert update drop update
22. Multiple possible destinations 22 !!
23. Bulk operations 23 !! • If you’re aware of the topology, • Identify slaves that crashed on the same position • Or with the same last pseudo-gtid entry • Significantly reduce access onto failover master • Orchestrator does all that
24. MySQL @ Booking.com • We are a big MySQL shop • We have >2600 production servers (~3300 including experiments & tests) on >110 topologies (aka chains, aka clusters) • As small as 1 server per topology, as large as 400 servers per topology • Two major data centers • All chains are deployed with Pseudo-GTID and controlled by orchestrator 24
25. • command line, web API, web interface • Crawls through your topologies, maps them, persists to backend database • Understands replication, gathers metadata on replicating slaves (Which cluster? Depth?) • Understands rules of replication (SBR, RBR, version compatibility, other configurations you wish you had never heard of) • Can refactor/manipulate topologies • Understands Pseudo-GTID • Detects and recovers outage scenarios Orchestrator: MySQL replication management & visualization tool 25
26. Orchestrator general architecture 26 orchestrator service backend db web API web xface
27. Orchestrator architecture @ Booking.com 27 app leader app app app HTTP load balancer orchestrator-cli on all MySQL nodes
28. • Stack: • golang - in retrospect a very good choice: a lot of concurrency; easy deployment; rapid development • MySQL as backend database (duh) • go-martini web framework • Page generation via dirty JavaScript/jQuery (sue me) • Twitter bootstrap • Graphs via D3, integrated with bootstrap • Development: • Github, completely open source; as generic as possible https://github.com/outbrain/orchestrator/ Orchestrator stack & development 28
29. Live demo
30. In-production experiments, trust • Tested: • 21,138 rematch experiments on 7 topologies (based on binlogs) • 13,872 rematch experiments on 6 topologies (based on relay logs) • 6,246 bounce up and back experiments on 6 topologies • 8,699 regroup, bounce up and back experiments on 9 topologies • ~180 intermediate master automated failover (clean shutdown) • A few dozens intermediate master automated failover (kill -9 / iptables) • Many intermediate master manual failovers • Todo: • Daily (!) controlled intermediate master failover • Not so far in the future: daily (!) controlled master failover 30
31. Considerations, requirements • Works with: • MySQL, MariaDB, using standard, single threaded replication • Supports SRB & RBR • Supports Binlog Servers • When slave has log-slave-updates & sync_binlog=1, implies crash safe replication • log-slave-updates required when slave should be considered to be promoted • Otherwise relay logs work well • But change of master clears relay logs; an additional crash during < injection time may render the instance lost 31
32. Considerations, requirements • Will not work with 5.6 per-schema-parallel-replication (no intended work on that) • Will work with In-order binlog statements applier on slave (true in MariaDB and in MySQL 5.7.5 with slave_preserve_commit_order) • No thoughts yet on multisource 32
33. Considerations, requirements • Allows for queries to execute on slave • But not after the last Pseudo-GTID entry • Will succeed when: • Matching a slave up the topology • Matching below a sibling known to be more advanced • Can succeed when: • Matching below an “uncle”/”cousin”/other relative • If not - then the opposite direction should work • Cannot move slave underneath its own sibling (singularity, universe will collapse) • Replication filters are your own risk 33
34. Considerations, requirements • Therefore, can always recover the death of an intermediate master • (This is partly automated at Booking.com) • Master death topology recovery possible when all immediate slaves have log-slave-updates • Consider actually enforcing such a layer 34
35. Auto pick replacement master 35 !! • Only from slaves with log_slave_updates • Slaves without log_slave_updates might be lost
36. Considerations, requirements • Recovery time depends on binary log parsing speed. Typically, you will need to search throughout the last binary logs • Reduce max_binlog_size, max_relay_log_size • Means more files • Orchestrator already tackled plenty issues involving scanning (many) binlog files 36
37. Gotchas, careful! • SHOW BINLOG EVENTS lockdown! Keep chunk size small http://bugs.mysql.com/bug.php?id=76618 • Make sure Pseudo-GTID injected on master only • log-slave-updates have I/O overhead; incurs more lag; experiments with 5.7 show reduces parallelism • Replication filters may be a necessary evil -- but they are evil! • Relay log purging is is not user-controlled 37
38. Further ideas • Reduce binlog scan time by injecting the master’s binlog position (e.g. output of SHOW MASTER STATUS) within the Pseugo-GTID entry • This allows starting the scan from the given position • Likely to end quickly • Applies for masters only, not for intermediate masters • Use monotonically increasing Pseudo-GTID values • Allows skipping of binary logs that begin with later/greater value than desired one • Agents: • Index the binary logs • Full visibility even with RBR (mysqlbinlog more detailed than SHOW BINLOG EVENTS) 38
39. • Binlog Servers at Booking.com Jean-François Gagné 15 April 2:00PM - 2:50PM @ Ballroom G • Booking.com: Evolution of MySQL System Design Nicolai Plum 16 April 12:50PM - 1:40PM @ Ballroom E See also
40. Questions? @ShlomiNoach http://openark.org http://blog.booking.com Thank you!