Flink Forward 2015

1. Fault Tolerance and Job
Recovery in Apache Flink™
Till Rohrmann
trohrmann@apache.org
@stsffap

2. 2

3. Better be safe than sorry
 Failures will happen
 EMC estimated $1.7 billion costs due to
data loss and system downtime
 Recovery will save you time and costs
 Switch between algorithms
 Live upgrade of your system
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4. Fault Tolerance
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5. Fault tolerance guarantees
 At most once
• No guarantees at all
 At least once
• For many applications sufficient
 Exactly once
 Flink provides all guarantees
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6. Checkpoints
 Consistent snapshots of distributed data
stream and operator state
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7. Barriers
 Markers for checkpoints
 Injected in the data flow
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8. 8
 Alignment for multi-input operators

9. Operator State
 Stateless operators
 System state
 User defined state
9
ds.filter(_ != 0)
ds.keyBy(0).window(TumblingTimeWindows.of(5, TimeUnit.SECONDS))
public class CounterSum implements RichReduceFunction<Long> {
private OperatorState<Long> counter;
@Override public Long reduce(Long v1, Long v2) throws Exception {
counter.update(counter.value() + 1);
return v1 + v2;
}
@Override public void open(Configuration config) {
counter = getRuntimeContext().getOperatorState(“counter”, 0L, false);
}
}

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12. 12

13. 13

14. Advantages
 Separation of app logic from recovery
• Checkpointing interval is just a config
parameter
 High throughput
• Controllable checkpointing overhead
 Low impact on latency
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15. 15

16. Cluster High Availability
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17. Without high availability
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JobManager
TaskManager

18. With high availability
18
JobManager
TaskManager
Stand-by
JobManager
Apache Zookeeper™
KEEP GOING

19. Persisting jobs
19
JobManager
Client
TaskManagers
Apache Zookeeper™
Job
1. Submit job

20. Persisting jobs
20
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Submit job
2. Persist execution graph

21. Persisting jobs
21
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Submit job
2. Persist execution graph
3. Write handle to ZooKeeper

22. Persisting jobs
22
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Submit job
2. Persist execution graph
3. Write handle to ZooKeeper
4. Deploy tasks

23. Handling checkpoints
23
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Take snapshots

24. Handling checkpoints
24
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Take snapshots
2. Persist snapshots
3. Send handles to JM

25. Handling checkpoints
25
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Take snapshots
2. Persist snapshots
3. Send handles to JM
4. Create global checkpoint

26. Handling checkpoints
26
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Take snapshots
2. Persist snapshots
3. Send handles to JM
4. Create global checkpoint
5. Persist global checkpoint

27. Handling checkpoints
27
JobManager
Client
TaskManagers
Apache Zookeeper™
1. Take snapshots
2. Persist snapshots
3. Send handles to JM
4. Create global checkpoint
5. Persist global checkpoint
6. Write handle to ZooKeeper

28. Conclusion
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30. 30

31. TL;DL
 Job recovery mechanism with low latency
and high throughput
 Exactly one processing semantics
 No single point of failure
 Flink will always keep processing
your data
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32. flink.apache.org
@ApacheFlink