Github user HeartSaVioR commented on a diff in the pull request: https://github.com/apache/storm/pull/984#discussion_r48799230 --- Diff: docs/documentation/State-checkpointing.md --- @@ -0,0 +1,147 @@ +# State support in core storm +Storm core has abstractions for bolts to save and retrieve the state of its operations. There is a default in-memory +based state implementation and also a Redis backed implementation that provides state persistence. + +## State management +Bolts that requires its state to be managed and persisted by the framework should implement the `IStatefulBolt` interface or +extend the `BaseStatefulBolt` and implement `void initState(T state)` method. The `initState` method is invoked by the framework +during the bolt initialization with the previously saved state of the bolt. This is invoked after prepare but before the bolt starts +processing any tuples. + +Currently the only kind of `State` implementation that is supported is `KeyValueState` which provides key-value mapping. + +For example a word count bolt could use the key value state abstraction for the word counts as follows. + +1. Extend the BaseStatefulBolt and type parameterize it with KeyValueState which would store the mapping of word to count. +2. The bolt gets initialized with its previously saved state in the init method. This will contain the word counts +last committed by the framework during the previous run. +3. In the execute method, update the word count. + + ```java + public class WordCountBolt extends BaseStatefulBolt<KeyValueState<String, Long>> { + private KeyValueState<String, Long> wordCounts; + ... + @Override + public void initState(KeyValueState<String, Long> state) { + wordCounts = state; + } + @Override + public void execute(Tuple tuple, BasicOutputCollector collector) { + String word = tuple.getString(0); + Integer count = wordCounts.get(word, 0); + count++; + wordCounts.put(word, count); + collector.emit(new Values(word, count)); + } + ... + } + ``` +4. The framework periodically checkpoints the state of the bolt (default every second). The frequency +can be changed by setting the storm config `topology.state.checkpoint.interval.ms` +5. For state persistence, use a state provider that supports persistence by setting the `topology.state.provider` in the +storm config. E.g. for using Redis based key-value state implementation set `topology.state.provider: org.apache.storm.redis.state.RedisKeyValueStateProvider` +in storm.yaml. The provider implementation jar should be in the class path, which in this case means putting the `storm-redis-*.jar` +in the extlib directory. +6. The state provider properties can be overridden by setting `topology.state.provider.config`. For Redis state this is a +json config with the following properties. + + ``` + { + "keyClass": "Optional fully qualified class name of the Key type.", + "valueClass": "Optional fully qualified class name of the Value type.", + "keySerializerClass": "Optional Key serializer implementation class.", + "valueSerializerClass": "Optional Value Serializer implementation class.", + "jedisPoolConfig": { + "host": "localhost", + "port": 6379, + "timeout": 2000, + "database": 0, + "password": "xyz" + } + } + ``` + +## Checkpoint mechanism +Checkpoint is triggered by an internal checkpoint spout at the specified `topology.state.checkpoint.interval.ms`. If there is +at-least one `IStatefulBolt` in the topology, the checkpoint spout is automatically added by the topology builder . For stateful topologies, +the topology builder wraps the `IStatefulBolt` in a `StatefulBoltExecutor` which handles the state commits on receiving the checkpoint tuples. +The non stateful bolts are wrapped in a `CheckpointTupleForwarder` which just forwards the checkpoint tuples so that the checkpoint tuples +can flow through the topology DAG. The checkpoint tuples flow through a separate internal stream namely `$checkpoint`. The topology builder +wires the checkpoint stream across the whole topology with the checkpoint spout at the root. + +``` + default default default +[spout1] ---------------> [statefulbolt1] ----------> [bolt1] --------------> [statefulbolt2] + | ----------> --------------> + | ($chpt) ($chpt) + | +[$checkpointspout] _______| ($chpt) +``` + +At checkpoint intervals the checkpoint tuples are emitted by the checkpoint spout. On receiving a checkpoint tuple, the state of the bolt +is saved and then the checkpoint tuple is forwarded to the next component. Each bolt waits for the checkpoint to arrive on all its input +streams before it saves its state so that the state represents a consistent state across the topology. Once the checkpoint spout receives +ACK from all the bolts, the state commit is complete and the transaction is recorded as committed by the checkpoint spout. + +The state commit works like a three phase commit protocol with a prepare and commit phase so that the state across the topology is saved +in a consistent and atomic manner. + +### Recovery +The recovery phase is triggered when the topology is started for the first time. If the previous transaction was not successfully +prepared, a `rollback` message is sent across the topology so that if a bolt has some prepared transactions it can be discarded. +If the previous transaction was prepared successfully but not committed, a `commit` message is sent across the topology so that +the prepared transactions can be committed. After these steps are complete, the bolts are initialized with the state. + +The recovery is also triggered if one of the bolts fails to acknowledge the checkpoint message or say a worker crashed in +the middle. Thus when the worker is restarted by the supervisor, the checkpoint mechanism makes sure that the bolt gets +initialized with its previous state and the checkpointing continues from the point where it left off. + +### Guarantee +Storm relies on the acking mechanism to replay tuples in case of failures. It is possible that the state is committed +but the worker crashes before acking the tuples. In this case the tuples are replayed causing duplicate state updates. +Also currently the StatefulBoltExecutor continues to process the tuples from a stream after it has received a checkpoint +tuple on one stream while waiting for checkpoint to arrive on other input streams for saving the state. This can also cause +duplicate state updates during recovery. + +The state abstraction does not eliminate duplicate evaluations and currently provides only at-least once guarantee. + +### IStateful bolt hooks +IStatefult bolt interface provides hook methods where in the stateful bolts could implement some custom actions. --- End diff -- IStatefult -> IStateful
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