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Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
Distributed Coordination with Python
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Distributed Coordination with Python

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This talk covers why Apache Zookeeper is a good fit for coordinating processes in a distributed environment, prior Python attempts at a client and the current state of the art Python client library, …

This talk covers why Apache Zookeeper is a good fit for coordinating processes in a distributed environment, prior Python attempts at a client and the current state of the art Python client library, how unifying development efforts to merge several Python client libraries has paid off, features available to Python processes, and how to gracefully handle failures in a set of distributed processes.

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  • 1. DISTRIBUTED COORDINATION WITH PYTHON BenBangert mozilla
  • 2. Toolsof theTrade
  • 3. DISTRIBUTED COORDINATION IS NOT... • Distributed Databases (Cassandra, Riak) • Distributed Computing (Hadoop, etc.) • Distributed Event Analysis (Storm)
  • 4. TheCommonElement
  • 5. Apache Zookeeper
  • 6. ZooKeeperisacentralizedservicefor maintainingconfigurationinformation, naming,providingdistributedsynchronization, andprovidinggroupservices.
  • 7. ZOOKEEPER
  • 8. WHY NOT USE... • Memcached? • MongoDB? • Postgres/MySQL?
  • 9. Hierarchical data structure in znodes
  • 10. • Session Based • Znode watches • Ephemeral and Sequential Znodes
  • 11. • Last for duration of client session • Session dies when connection is closed or expires • Can’t have children znodes EPHEMERAL ZNODES
  • 12. SEQUENTIAL ZNODES • Supply a node name (or not), get node name back with a trailing sequence number (0001, 0002, 0003, etc.) • Can be combined with ephemeral flag
  • 13. BASIC COMMANDS • create(PATH, DATA...) • get(PATH...) • get_children(PATH...) • set(PATH, DATA...) • delete(PATH...)
  • 14. PYTHON CLIENTS • txzookeeper • kazoo • unified client that works with gevent • implements wire protocol in pure Python
  • 15. USE KAZOO
  • 16. EASY TO USE from kazoo.client import KazooClient client = KazooClient() client.start()
  • 17. USE CASES
  • 18. CONFIGURATION • Store settings in node data • Organize node structure • Set watches on nodes of interest
  • 19. PARTY MEMBERSHIP • Join a party, find out who else is around • Elect a leader if desired • Recipe in Kazoo
  • 20. LOCKS • Lock a resource for a single client • Lock a resource for multiple clients (Semaphore) • Hard to write properly • Recipe in Kazoo
  • 21. BUILDING HIGHER LEVEL ABSTRACTIONS ON ZOOKEEPER
  • 22. CAVEAT
  • 23. DO NOT IMPLEMENT YOURSELF USE THE RECIPE
  • 24. BASIC STEPS • Create lock parent node if needed • Create ephemeral+sequence node under parent, store node name returned • Get children of lock node • Sort children list by sequence number • First child in the list has the lock!
  • 25. THINGS TO WATCH OUT FOR • Avoid the thundering herd, use watches only when needed • When our node isn’t the lowest, watch the one in front of us • Only one client wanting a lock is ‘woken’ when the lock is released by a different client
  • 26. HANDLING FAILURE
  • 27. ROBUST CODE TAKES EFFORT • What happens when a server fails? • What happens when the client fails? • What happens when we don’t know if the server has failed?
  • 28. STOPPING WHEN UNCERTAIN
  • 29. A BIT BETTER VERSION...
  • 30. EVEN BETTER
  • 31. FAILURE WILL HAPPEN • Fail fast, fail completely. • Session expiration is a good time to sys.exit • Always include jitter (kazoo includes jitter on its connection and command retry operations) • Consider what exceptions can occur in any code relying on a distributed system
  • 32. • Distributed systems are hard • Use existing battle-proven tools (Zookeeper, Kazoo) • Always consider everything that can fail, and how • Be wary of tools that don’t tell you how they fail • Read Kyle Kingsbury’s Jepsen posts to see examples of systems failing: http://aphyr.com/tags/jepsen
  • 33. FIN
  • 34. QUESTIONS?

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