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https://issues.apache.org/jira/browse/STORM-1416?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15082054#comment-15082054
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ASF GitHub Bot commented on STORM-1416:
---------------------------------------
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
> Add documentation for windowing state store functionality
> ----------------------------------------------------------
>
> Key: STORM-1416
> URL: https://issues.apache.org/jira/browse/STORM-1416
> Project: Apache Storm
> Issue Type: Sub-task
> Reporter: Arun Mahadevan
> Assignee: Arun Mahadevan
>
> Documentation for windowing state store and pruning added as a part of
> STORM-1175 and STORM-1176.
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