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Posted to reviews@spark.apache.org by "pengzhon-db (via GitHub)" <gi...@apache.org> on 2023/05/18 22:29:35 UTC
[GitHub] [spark] pengzhon-db commented on a diff in pull request #40959: [SPARK-43511][CONNECT][SS]Implemented MapGroupsWithState and FlatMapGroupsWithState APIs for Spark Connect
pengzhon-db commented on code in PR #40959:
URL: https://github.com/apache/spark/pull/40959#discussion_r1198361197
##########
connector/connect/common/src/main/java/org/apache/spark/api/java/function/FlatMapGroupsWithStateFunction.java:
##########
@@ -0,0 +1,39 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.api.java.function;
+
+import java.io.Serializable;
+import java.util.Iterator;
+
+import org.apache.spark.annotation.Evolving;
+import org.apache.spark.annotation.Experimental;
+import org.apache.spark.sql.streaming.GroupState;
+
+/**
+ * ::Experimental::
+ * Base interface for a map function used in
+ * {@code org.apache.spark.sql.KeyValueGroupedDataset.flatMapGroupsWithState(
+ * FlatMapGroupsWithStateFunction, org.apache.spark.sql.streaming.OutputMode,
+ * org.apache.spark.sql.Encoder, org.apache.spark.sql.Encoder)}
+ * @since 2.1.1
+ */
+@Experimental
+@Evolving
+public interface FlatMapGroupsWithStateFunction<K, V, S, R> extends Serializable {
Review Comment:
Can we not reuse the existing one? Similar for MapGroupsWithStateFunction
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -312,6 +313,154 @@ abstract class KeyValueGroupedDataset[K, V] private[sql] () extends Serializable
cogroupSorted(other)(thisSortExprs: _*)(otherSortExprs: _*)(
UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
+ */
+ def mapGroupsWithState[S: Encoder, U: Encoder](
+ func: (K, Iterator[V], GroupState[S]) => U): Dataset[U] = {
+ mapGroupsWithState(GroupStateTimeout.NoTimeout)(func)
+ }
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ * @param timeoutConf
+ * Timeout configuration for groups that do not receive data for a while.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
Review Comment:
update the version
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -904,6 +905,29 @@ message ApplyInPandasWithState {
string timeout_conf = 7;
}
+message FlatMapGroupsWithState {
+ // (Required) One input relation for CoGroup Map API - applyInPandas.
+ Relation input = 1;
+
+ // Expressions for grouping keys.
+ repeated Expression grouping_expressions = 2;
+
+ // Expressions for grouping keys of the initial input relation.
+ repeated Expression initial_grouping_expressions = 3;
+
+ // (Required) Input user-defined function.
+ CommonInlineUserDefinedFunction func = 4;
+
+ // (Required) Is MapGroupsWithState or not.
+ bool is_map_groups_with_state = 5;
+
+ // (Optional) The output mode of the function.
+ optional string output_mode = 6;
Review Comment:
I don't think we need `optional`
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -312,6 +313,154 @@ abstract class KeyValueGroupedDataset[K, V] private[sql] () extends Serializable
cogroupSorted(other)(thisSortExprs: _*)(otherSortExprs: _*)(
UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
Review Comment:
this version should be updated. Similar for the following methods
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -312,6 +313,154 @@ abstract class KeyValueGroupedDataset[K, V] private[sql] () extends Serializable
cogroupSorted(other)(thisSortExprs: _*)(otherSortExprs: _*)(
UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
+ */
+ def mapGroupsWithState[S: Encoder, U: Encoder](
+ func: (K, Iterator[V], GroupState[S]) => U): Dataset[U] = {
+ mapGroupsWithState(GroupStateTimeout.NoTimeout)(func)
+ }
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ * @param timeoutConf
+ * Timeout configuration for groups that do not receive data for a while.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
+ */
+ def mapGroupsWithState[S: Encoder, U: Encoder](timeoutConf: GroupStateTimeout)(
+ func: (K, Iterator[V], GroupState[S]) => U): Dataset[U] = {
+ throw new UnsupportedOperationException
+ }
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ * @param timeoutConf
+ * Timeout Conf, see GroupStateTimeout for more details
+ * @param initialState
+ * The user provided state that will be initialized when the first batch of data is processed
+ * in the streaming query. The user defined function will be called on the state data even if
+ * there are no other values in the group. To convert a Dataset ds of type Dataset[(K, S)] to
+ * a KeyValueGroupedDataset[K, S] do {{{ds.groupByKey(x => x._1).mapValues(_._2)}}}
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 3.2.0
+ */
+ def mapGroupsWithState[S: Encoder, U: Encoder](
+ timeoutConf: GroupStateTimeout,
+ initialState: KeyValueGroupedDataset[K, S])(
+ func: (K, Iterator[V], GroupState[S]) => U): Dataset[U] = {
+ throw new UnsupportedOperationException
Review Comment:
why this is unsupported?
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -312,6 +313,154 @@ abstract class KeyValueGroupedDataset[K, V] private[sql] () extends Serializable
cogroupSorted(other)(thisSortExprs: _*)(otherSortExprs: _*)(
UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
+ */
+ def mapGroupsWithState[S: Encoder, U: Encoder](
+ func: (K, Iterator[V], GroupState[S]) => U): Dataset[U] = {
+ mapGroupsWithState(GroupStateTimeout.NoTimeout)(func)
+ }
+
+ /**
+ * (Scala-specific) Applies the given function to each group of data, while maintaining a
+ * user-defined per-group state. The result Dataset will represent the objects returned by the
+ * function. For a static batch Dataset, the function will be invoked once per group. For a
+ * streaming Dataset, the function will be invoked for each group repeatedly in every trigger,
+ * and updates to each group's state will be saved across invocations. See
+ * [[org.apache.spark.sql.streaming.GroupState]] for more details.
+ *
+ * @tparam S
+ * The type of the user-defined state. Must be encodable to Spark SQL types.
+ * @tparam U
+ * The type of the output objects. Must be encodable to Spark SQL types.
+ * @param func
+ * Function to be called on every group.
+ * @param timeoutConf
+ * Timeout configuration for groups that do not receive data for a while.
+ *
+ * See [[Encoder]] for more details on what types are encodable to Spark SQL.
+ * @since 2.2.0
+ */
+ def mapGroupsWithState[S: Encoder, U: Encoder](timeoutConf: GroupStateTimeout)(
+ func: (K, Iterator[V], GroupState[S]) => U): Dataset[U] = {
+ throw new UnsupportedOperationException
Review Comment:
why this is unsupported?
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -904,6 +905,29 @@ message ApplyInPandasWithState {
string timeout_conf = 7;
}
+message FlatMapGroupsWithState {
+ // (Required) One input relation for CoGroup Map API - applyInPandas.
Review Comment:
the comment seems not correct
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