zhuzhurk commented on a change in pull request #17952:
URL: https://github.com/apache/flink/pull/17952#discussion_r759988690
##########
File path:
flink-core/src/main/java/org/apache/flink/configuration/JobManagerOptions.java
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@@ -480,6 +480,47 @@
.withDescription(
"Controls whether partitions should already be
released during the job execution.");
+ @Documentation.Section({
+ Documentation.Sections.EXPERT_SCHEDULING,
+ Documentation.Sections.ALL_JOB_MANAGER
+ })
+ public static final ConfigOption<Integer>
ADAPTIVE_BACH_SCHEDULER_MIN_PARALLELISM =
+ key("jobmanager.scheduler.adaptive-batch.min-parallelism")
+ .intType()
+ .defaultValue(1)
+ .withDescription("The lower bound of allowed parallelism
to set adaptively");
+
+ @Documentation.Section({
+ Documentation.Sections.EXPERT_SCHEDULING,
+ Documentation.Sections.ALL_JOB_MANAGER
+ })
+ public static final ConfigOption<Integer>
ADAPTIVE_BATCH_SCHEDULER_MAX_PARALLELISM =
+ key("jobmanager.scheduler.adaptive-batch.max-parallelism")
+ .intType()
+ .defaultValue(128)
+ .withDescription("The upper bound of allowed parallelism
to set adaptively");
+
+ @Documentation.Section({
+ Documentation.Sections.EXPERT_SCHEDULING,
+ Documentation.Sections.ALL_JOB_MANAGER
+ })
+ public static final ConfigOption<MemorySize>
ADAPTIVE_BATCH_SCHEDULER_DATA_VOLUME_PER_TASK =
+ key("jobmanager.scheduler.adaptive-batch.data-volume-per-task")
+ .memoryType()
+ .defaultValue(MemorySize.ofMebiBytes(1024))
+ .withDescription(
+ "The size of data volume to expect each task
instance to process.");
+
+ @Documentation.Section({
+ Documentation.Sections.EXPERT_SCHEDULING,
+ Documentation.Sections.ALL_JOB_MANAGER
+ })
+ public static final ConfigOption<Integer>
ADAPTIVE_BATCH_SCHEDULER_DEFAULT_SOURCE_PARALLELISM =
+
key("jobmanager.scheduler.adaptive-batch.source-parallelism.default")
+ .intType()
+ .defaultValue(1)
+ .withDescription("The default parallelism of source
vertices.");
Review comment:
I think we should add a limitation of the scope of these config
descriptions.
e.g. The default parallelism of source vertices if %s has been set to %s",
SCHEDULER.key(), AdaptiveBatch.name()
Similar as what we've done in `RestartStrategyOptions`.
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