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. 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