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Zookeeper big sonata

  1. 1. Introduction to Zookeeper Anh Le @BigSonata
  2. 2. What is a Distributed System? A distributed system consists of multiple computers that communicate through a computer network and interact with each other to achieve a common goal. -Wikipedia
  3. 3. Coordination in a Distributed System? Coordination: An act that multiple nodes must perform together. Examples: Leader Election Managing group membership Managing metadata Synchronization (Semaphore, Mutex...)
  4. 4. Coordination in a Distributed System? To coordinate, processes can Exchange messages through network Read/Write using shared storage Use distributed locks Problems for exchanging messages Message delays Processor speed Clock drift
  5. 5. Use case for Master-Work Applications Problems Master crashes Worker crashes Communication failures
  6. 6. Use case for Master-Work Applications Problems for Master Crashes Use a backup master Recover the latest state ? Backup master may suspect the primary master has crashed ? !> Split Brain scenario
  7. 7. Use case for Master-Work Applications Problems for Worker Crashes Master must detect worker crashes Recover assigned tasks Problems for Communication Failures Execute a same task only once
  8. 8. Introduction to ZooKeeper An open source, performant coordination service for distributed applications Was a sub project of Hadoop but is now a Apache top-level project Exposes common services in simple interface Leader Election Naming Configuration management Locks & Synchronization Group Service → Don't have to write them from scratch
  9. 9. ZooKeeper Use cases Distributed Cluster Management Node join/leave Node statuses in real time Distributed synchronization Locks Barriers Queues
  10. 10. ZooKeeper Use cases Apache Hbase use ZooKeeper to Elect a cluster master Keep track of available servers Keep cluster metadata Apache Kafka use Zookeeper to Detect crashes Implement topic discovery Maintain state for topics
  11. 11. ZooKeeper Guarantees Sequential Consistency: Updates are applied in order Atomicity: Updates either succeed or fail Single System Image: A client sees the same view of the service regardless of the ZK server it connects to. Reliability: Updates persists once applied, till overwritten by some clients. Timeliness: The clients’ view of the system is guaranteed to be up- to-date within a certain time bound. (Eventual Consistency)
  12. 12. ZooKeeper Services All machines store a copy of the data (in memory) A leader is elected on service startup Clients only connect to a single server & maintains a TCP connection. Client can read from any server, writes go through the leader & needs majority consensus.
  13. 13. ZooKeeper Data Model ZooKeeper has a hierarchal name space. Each node is called as a ZNode. Every ZNode has data (given as byte[]) ZNode paths: canonical, absolute, slash-separated no relative references. names can have Unicode characters
  14. 14. ZNode Maintain a stat structure with version numbers for data changes, ACL changes and timestamps. Version numbers increases with changes Data is read and written in its entirety
  15. 15. ZNode types Persistent Nodes exists till explicitly deleted Ephemeral Nodes exists as long as the session is active can’t have children Sequence Nodes (Unique Naming) append a monotonically increasing counter to the end of path applies to both persistent & ephemeral nodes
  16. 16. ZNode watches Clients can set watches on znodes: NodeChildrenChanged NodeCreated NodeDataChanged NodeDeleted Changes to a znode trigger the watch and ZooKeeper sends the client a notification. Watches are one time triggers. Watches are always ordered. Client sees watched event before new ZNode data.
  17. 17. ZNode APIs String create(path, data, acl, flags) void delete(path, expectedVersion) Stat setData(path, data, expectedVersion) (data, Stat) getData(path, watch) Stat exists(path, watch) String[] getChildren(path, watch) → Each API has its own asynchronous version also
  18. 18. ZooKeeper Recipes
  19. 19. Recipe: Leader Election /master
  20. 20. Recipe: Leader Election Continuous watching on znodes requires reset of watches after every events / triggers Too many watches on a single znode creates the “herd effect” - causing bursts of traffic and limiting scalability
  21. 21. Recipe: Leader Election (Improved) 1.All participants create an ephemeral-sequential node on the same election path. 2.The node with the smallest sequence number is the leader. 3.Each “follower” node listens to the node with the next lower seq. number 4.Upon leader removal go to election-path and find a new leader, or become the leader if it has the lowest sequence number. 1.Upon session expiration check the election state and go to election if needed
  22. 22. Zookeeper Programming Demo
  23. 23. Zookeeper Programming
  24. 24. Zookeeper Programming
  25. 25. Zookeeper Programming Difficult to use Zookeeper APIs Connection Issues: Initial connection: Requires a handshake before executing any operations (create(), delete()...) Session expiration: Clients are expected to watch for this state and close and re-create the ZooKeeper instance.
  26. 26. Zookeeper Programming Difficult to use Zookeeper APIs Recoverable Errors: When creating a sequential ZNode on the server, there is the possibility that the server will successfully create the ZNode but crash prior to returning the node name to the client. There are several recoverable exceptions thrown by the ZooKeeper client. Users are expected to catch these exceptions and retry the operation.
  27. 27. Zookeeper Programming Difficult to use Zookeeper APIs Recipes: The standard ZooKeeper "recipes" (locks, leaders, etc.) are only minimally described and subtly difficult to write correctly..
  28. 28. Zookeeper Programming with Curator lCurator- The Netflix Zookeeper library
  29. 29. Zookeeper Programming with Curator
  30. 30. Zookeeper Programming with Curator
  31. 31. Zookeeper for Our Systems