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[MINOR][BUILD] Fix javadoc8 break
## What changes were proposed in this pull request? Several javadoc8 breaks have been introduced. This PR proposes fix those instances so that we can build Scala/Java API docs. ``` [error] .../spark/sql/core/target/java/org/apache/spark/sql/streaming/GroupState.java:6: error: reference not found [error] * <code>flatMapGroupsWithState</code> operations on {link KeyValueGroupedDataset}. [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/streaming/GroupState.java:10: error: reference not found [error] * Both, <code>mapGroupsWithState</code> and <code>flatMapGroupsWithState</code> in {link KeyValueGroupedDataset} [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/streaming/GroupState.java:51: error: reference not found [error] * {link GroupStateTimeout.ProcessingTimeTimeout}) or event time (i.e. [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/streaming/GroupState.java:52: error: reference not found [error] * {link GroupStateTimeout.EventTimeTimeout}). [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/streaming/GroupState.java:158: error: reference not found [error] * Spark SQL types (see {link Encoder} for more details). [error] ^ [error] .../spark/mllib/target/java/org/apache/spark/ml/fpm/FPGrowthParams.java:26: error: bad use of '>' [error] * Number of partitions (>=1) used by parallel FP-growth. By default the param is not set, and [error] ^ [error] .../spark/sql/core/src/main/java/org/apache/spark/api/java/function/FlatMapGroupsWithStateFunction.java:30: error: reference not found [error] * {link org.apache.spark.sql.KeyValueGroupedDataset#flatMapGroupsWithState( [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/KeyValueGroupedDataset.java:211: error: reference not found [error] * See {link GroupState} for more details. [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/KeyValueGroupedDataset.java:232: error: reference not found [error] * See {link GroupState} for more details. [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/KeyValueGroupedDataset.java:254: error: reference not found [error] * See {link GroupState} for more details. [error] ^ [error] .../spark/sql/core/target/java/org/apache/spark/sql/KeyValueGroupedDataset.java:277: error: reference not found [error] * See {link GroupState} for more details. [error] ^ [error] .../spark/core/target/java/org/apache/spark/TaskContextImpl.java:10: error: reference not found [error] * {link TaskMetrics} &amp; {link MetricsSystem} objects are not thread safe. [error] ^ [error] .../spark/core/target/java/org/apache/spark/TaskContextImpl.java:10: error: reference not found [error] * {link TaskMetrics} &amp; {link MetricsSystem} objects are not thread safe. [error] ^ [info] 13 errors ``` ``` jekyll 3.3.1 | Error: Unidoc generation failed ``` ## How was this patch tested? Manually via `jekyll build` Author: hyukjinkwon <[email protected]> Closes #17389 from HyukjinKwon/minor-javadoc8-fix.
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core/src/main/scala/org/apache/spark/TaskContextImpl.scala

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@@ -38,7 +38,7 @@ import org.apache.spark.util._
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* callbacks are protected by locking on the context instance. For instance, this ensures
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* that you cannot add a completion listener in one thread while we are completing (and calling
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* the completion listeners) in another thread. Other state is immutable, however the exposed
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* [[TaskMetrics]] & [[MetricsSystem]] objects are not thread safe.
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* `TaskMetrics` & `MetricsSystem` objects are not thread safe.
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*/
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private[spark] class TaskContextImpl(
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val stageId: Int,

mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala

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@@ -69,8 +69,8 @@ private[fpm] trait FPGrowthParams extends Params with HasPredictionCol {
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def getMinSupport: Double = $(minSupport)
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/**
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* Number of partitions (>=1) used by parallel FP-growth. By default the param is not set, and
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* partition number of the input dataset is used.
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* Number of partitions (at least 1) used by parallel FP-growth. By default the param is not
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* set, and partition number of the input dataset is used.
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* @group expertParam
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*/
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@Since("2.2.0")

sql/core/src/main/java/org/apache/spark/api/java/function/FlatMapGroupsWithStateFunction.java

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@@ -27,7 +27,7 @@
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/**
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* ::Experimental::
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* Base interface for a map function used in
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* {@link org.apache.spark.sql.KeyValueGroupedDataset#flatMapGroupsWithState(
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* {@code org.apache.spark.sql.KeyValueGroupedDataset.flatMapGroupsWithState(
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* FlatMapGroupsWithStateFunction, org.apache.spark.sql.streaming.OutputMode,
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* org.apache.spark.sql.Encoder, org.apache.spark.sql.Encoder)}
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* @since 2.1.1

sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala

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@@ -298,7 +298,7 @@ class KeyValueGroupedDataset[K, V] private[sql](
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* For a static batch Dataset, the function will be invoked once per group. For a streaming
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* Dataset, the function will be invoked for each group repeatedly in every trigger, and
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* updates to each group's state will be saved across invocations.
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* See [[GroupState]] for more details.
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* See `GroupState` for more details.
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*
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* @tparam S The type of the user-defined state. Must be encodable to Spark SQL types.
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* @tparam U The type of the output objects. Must be encodable to Spark SQL types.
@@ -328,7 +328,7 @@ class KeyValueGroupedDataset[K, V] private[sql](
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* For a static batch Dataset, the function will be invoked once per group. For a streaming
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* Dataset, the function will be invoked for each group repeatedly in every trigger, and
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* updates to each group's state will be saved across invocations.
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* See [[GroupState]] for more details.
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* See `GroupState` for more details.
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*
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* @tparam S The type of the user-defined state. Must be encodable to Spark SQL types.
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* @tparam U The type of the output objects. Must be encodable to Spark SQL types.
@@ -360,7 +360,7 @@ class KeyValueGroupedDataset[K, V] private[sql](
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* For a static batch Dataset, the function will be invoked once per group. For a streaming
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* Dataset, the function will be invoked for each group repeatedly in every trigger, and
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* updates to each group's state will be saved across invocations.
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* See [[GroupState]] for more details.
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* See `GroupState` for more details.
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*
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* @tparam S The type of the user-defined state. Must be encodable to Spark SQL types.
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* @tparam U The type of the output objects. Must be encodable to Spark SQL types.
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* For a static batch Dataset, the function will be invoked once per group. For a streaming
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* Dataset, the function will be invoked for each group repeatedly in every trigger, and
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* updates to each group's state will be saved across invocations.
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* See [[GroupState]] for more details.
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* See `GroupState` for more details.
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*
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* @tparam S The type of the user-defined state. Must be encodable to Spark SQL types.
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* @tparam U The type of the output objects. Must be encodable to Spark SQL types.

sql/core/src/main/scala/org/apache/spark/sql/streaming/GroupState.scala

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@@ -18,18 +18,18 @@
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package org.apache.spark.sql.streaming
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import org.apache.spark.annotation.{Experimental, InterfaceStability}
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import org.apache.spark.sql.{Encoder, KeyValueGroupedDataset}
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import org.apache.spark.sql.KeyValueGroupedDataset
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import org.apache.spark.sql.catalyst.plans.logical.LogicalGroupState
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/**
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* :: Experimental ::
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*
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* Wrapper class for interacting with per-group state data in `mapGroupsWithState` and
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* `flatMapGroupsWithState` operations on [[KeyValueGroupedDataset]].
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* `flatMapGroupsWithState` operations on `KeyValueGroupedDataset`.
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*
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* Detail description on `[map/flatMap]GroupsWithState` operation
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* --------------------------------------------------------------
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* Both, `mapGroupsWithState` and `flatMapGroupsWithState` in [[KeyValueGroupedDataset]]
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* Both, `mapGroupsWithState` and `flatMapGroupsWithState` in `KeyValueGroupedDataset`
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* will invoke the user-given function on each group (defined by the grouping function in
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* `Dataset.groupByKey()`) while maintaining user-defined per-group state between invocations.
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* For a static batch Dataset, the function will be invoked once per group. For a streaming
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* `[map|flatMap]GroupsWithState`, but the exact timeout duration/timestamp is configurable per
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* group by calling `setTimeout...()` in `GroupState`.
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* - Timeouts can be either based on processing time (i.e.
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* [[GroupStateTimeout.ProcessingTimeTimeout]]) or event time (i.e.
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* [[GroupStateTimeout.EventTimeTimeout]]).
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* `GroupStateTimeout.ProcessingTimeTimeout`) or event time (i.e.
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* `GroupStateTimeout.EventTimeTimeout`).
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* - With `ProcessingTimeTimeout`, the timeout duration can be set by calling
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* `GroupState.setTimeoutDuration`. The timeout will occur when the clock has advanced by the set
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* duration. Guarantees provided by this timeout with a duration of D ms are as follows:
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* }}}
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*
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* @tparam S User-defined type of the state to be stored for each group. Must be encodable into
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* Spark SQL types (see [[Encoder]] for more details).
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* Spark SQL types (see `Encoder` for more details).
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* @since 2.2.0
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*/
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@Experimental
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/**
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* Set the timeout duration for this key as a string. For example, "1 hour", "2 days", etc.
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*
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* @note, ProcessingTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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* @note ProcessingTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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*/
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@throws[IllegalArgumentException]("if 'duration' is not a valid duration")
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@throws[IllegalStateException]("when state is either not initialized, or already removed")
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* Set the timeout timestamp for this key as milliseconds in epoch time.
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* This timestamp cannot be older than the current watermark.
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*
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* @note, EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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* @note EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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*/
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def setTimeoutTimestamp(timestampMs: Long): Unit
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* The final timestamp (including the additional duration) cannot be older than the
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* current watermark.
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*
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* @note, EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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* @note EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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*/
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def setTimeoutTimestamp(timestampMs: Long, additionalDuration: String): Unit
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* Set the timeout timestamp for this key as a java.sql.Date.
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* This timestamp cannot be older than the current watermark.
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*
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* @note, EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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* @note EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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*/
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def setTimeoutTimestamp(timestamp: java.sql.Date): Unit
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* The final timestamp (including the additional duration) cannot be older than the
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* current watermark.
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*
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* @note, EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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* @note EventTimeTimeout must be enabled in `[map/flatmap]GroupsWithStates`.
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*/
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def setTimeoutTimestamp(timestamp: java.sql.Date, additionalDuration: String): Unit
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}

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