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The following commit(s) were added to refs/heads/release-1.6 by this push:
new ca65e94 [FLINK-9637] [docs] Add public user documentation for state
TTL feature
ca65e94 is described below
commit ca65e9490eda09f28754da395be5948756fd2614
Author: Andrey Zagrebin <[email protected]>
AuthorDate: Fri Jul 20 14:57:08 2018 +0200
[FLINK-9637] [docs] Add public user documentation for state TTL feature
This closes #6379.
---
docs/dev/stream/state/state.md | 127 +++++++++++++++++++++++++++++++++++++++++
1 file changed, 127 insertions(+)
diff --git a/docs/dev/stream/state/state.md b/docs/dev/stream/state/state.md
index 44a3653..fb78776 100644
--- a/docs/dev/stream/state/state.md
+++ b/docs/dev/stream/state/state.md
@@ -266,6 +266,133 @@ a `ValueState`. Once the count reaches 2 it will emit the
average and clear the
we start over from `0`. Note that this would keep a different state value for
each different input
key if we had tuples with different values in the first field.
+### State Time-To-Live (TTL)
+
+A *time-to-live* (TTL) can be assigned to the keyed state of any type. If a
TTL is configured and a
+state value has expired, the stored value will be cleaned up on a best effort
basis which is
+discussed in more detail below.
+
+All state collection types support per-entry TTLs. This means that list
elements and map entries
+expire independently.
+
+In order to use state TTL one must first build a `StateTtlConfig`
configuration object. The TTL
+functionality can then be enabled in any state descriptor by passing the
configuration:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+import org.apache.flink.api.common.state.StateTtlConfig;
+import org.apache.flink.api.common.state.ValueStateDescriptor;
+import org.apache.flink.api.common.time.Time;
+
+StateTtlConfig ttlConfig = StateTtlConfig
+ .newBuilder(Time.seconds(1))
+ .setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite)
+ .setStateVisibility(StateTtlConfig.StateVisibility.NeverReturnExpired)
+ .build();
+
+ValueStateDescriptor<String> stateDescriptor = new
ValueStateDescriptor<>("text state", String.class);
+stateDescriptor.enableTimeToLive(ttlConfig);
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+import org.apache.flink.api.common.state.StateTtlConfig
+import org.apache.flink.api.common.state.ValueStateDescriptor
+import org.apache.flink.api.common.time.Time
+
+val ttlConfig = StateTtlConfig
+ .newBuilder(Time.seconds(1))
+ .setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite)
+ .setStateVisibility(StateTtlConfig.StateVisibility.NeverReturnExpired)
+ .build
+
+val stateDescriptor = new ValueStateDescriptor[String]("text state",
classOf[String])
+stateDescriptor.enableTimeToLive(ttlConfig)
+{% endhighlight %}
+</div>
+</div>
+
+The configuration has several options to consider:
+
+The first parameter of the `newBuilder` method is mandatory, it is the
time-to-live value.
+
+The update type configures when the state TTL is refreshed (by default
`OnCreateAndWrite`):
+
+ - `StateTtlConfig.UpdateType.OnCreateAndWrite` - only on creation and write
access
+ - `StateTtlConfig.UpdateType.OnReadAndWrite` - also on read access
+
+The state visibility configures whether the expired value is returned on read
access
+if it is not cleaned up yet (by default `NeverReturnExpired`):
+
+ - `StateTtlConfig.StateVisibility.NeverReturnExpired` - expired value is
never returned
+ - `StateTtlConfig.StateVisibility.ReturnExpiredIfNotCleanedUp` - returned if
still available
+
+In case of `NeverReturnExpired`, the expired state behaves as if it does not
exist anymore,
+even if it still has to be removed. The option can be useful for use cases
+where data has to become unavailable for read access strictly after TTL,
+e.g. application working with privacy sensitive data.
+
+Another option `ReturnExpiredIfNotCleanedUp` allows to return the expired
state before its cleanup.
+
+**Notes:**
+
+- The state backends store the timestamp of the last modification along with
the user value,
+which means that enabling this feature increases consumption of state storage.
+Heap state backend stores an additional Java object with a reference to the
user state object
+and a primitive long value in memory. The RocksDB state backend adds 8 bytes
per stored value, list entry or map entry.
+
+- Only TTLs in reference to *processing time* are currently supported.
+
+- Trying to restore state, which was previously configured without TTL, using
TTL enabled descriptor or vice versa
+will lead to compatibility failure and `StateMigrationException`.
+
+- The TTL configuration is not part of check- or savepoints but rather a way
of how Flink treats it in the currently running job.
+
+#### Cleanup of Expired State
+
+Currently, expired values are only removed when they are read out explicitly,
+e.g. by calling `ValueState.value()`.
+
+<span class="label label-danger">Attention</span> This means that by default
if expired state is not read,
+it won't be removed, possibly leading to ever growing state. This might change
in future releases.
+
+Additionally, you can activate the cleanup at the moment of taking the full
state snapshot which
+will reduce its size. The local state is not cleaned up under the current
implementation
+but it will not include the removed expired state in case of restoration from
the previous snapshot.
+It can be configured in `StateTtlConfig`:
+
+<div class="codetabs" markdown="1">
+<div data-lang="java" markdown="1">
+{% highlight java %}
+import org.apache.flink.api.common.state.StateTtlConfig;
+import org.apache.flink.api.common.time.Time;
+
+StateTtlConfig ttlConfig = StateTtlConfig
+ .newBuilder(Time.seconds(1))
+ .cleanupFullSnapshot()
+ .build();
+{% endhighlight %}
+</div>
+
+<div data-lang="scala" markdown="1">
+{% highlight scala %}
+import org.apache.flink.api.common.state.StateTtlConfig
+import org.apache.flink.api.common.time.Time
+
+val ttlConfig = StateTtlConfig
+ .newBuilder(Time.seconds(1))
+ .cleanupFullSnapshot
+ .build
+{% endhighlight %}
+</div>
+</div>
+
+This option is not applicable for the incremental checkpointing in the RocksDB
state backend.
+
+More strategies will be added in the future for cleaning up expired state
automatically in the background.
+
### State in the Scala DataStream API
In addition to the interface described above, the Scala API has shortcuts for
stateful
