anishshri-db commented on code in PR #45932: URL: https://github.com/apache/spark/pull/45932#discussion_r1563050397
########## sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/ListStateImplWithTTL.scala: ########## @@ -0,0 +1,220 @@ +/* + * 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.sql.execution.streaming + +import org.apache.spark.sql.Encoder +import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder +import org.apache.spark.sql.execution.streaming.TransformWithStateKeyValueRowSchema.{KEY_ROW_SCHEMA, VALUE_ROW_SCHEMA_WITH_TTL} +import org.apache.spark.sql.execution.streaming.state.{NoPrefixKeyStateEncoderSpec, StateStore, StateStoreErrors} +import org.apache.spark.sql.streaming.{ListState, TTLConfig} +import org.apache.spark.util.NextIterator + +/** + * Provides concrete implementation for list of values associated with a state variable + * used in the streaming transformWithState operator. + * + * @param store - reference to the StateStore instance to be used for storing state + * @param stateName - name of logical state partition + * @param keyEnc - Spark SQL encoder for key + * @param valEncoder - Spark SQL encoder for value Review Comment: Can we update the comment to match the args ? ########## sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/TTLState.scala: ########## @@ -75,7 +75,7 @@ trait TTLState { * * @return true if the state was cleared, false otherwise. Review Comment: Could we update this too ? ########## sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StatefulProcessorHandleSuite.scala: ########## @@ -237,13 +237,33 @@ class StatefulProcessorHandleSuite extends StateVariableSuiteBase { } } + test(s"ttl States are populated for listState and timeMode=ProcessingTime") { + tryWithProviderResource(newStoreProviderWithStateVariable(true)) { provider => + val store = provider.getStore(0) + val handle = new StatefulProcessorHandleImpl(store, + UUID.randomUUID(), keyExprEncoder, TimeMode.ProcessingTime(), + batchTimestampMs = Some(10)) + + val listStateWithTTL = handle.getListState("testState", + Encoders.STRING, TTLConfig(Duration.ofHours(1))) + + // create another state without TTL, this should not be captured in the handle + handle.getListState("testState", Encoders.STRING) + + assert(handle.ttlStates.size() === 1) + assert(handle.ttlStates.get(0) === listStateWithTTL) + } + } + + Review Comment: nit: extra newline ? ########## sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/ListStateImplWithTTL.scala: ########## @@ -0,0 +1,220 @@ +/* + * 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.sql.execution.streaming + +import org.apache.spark.sql.Encoder +import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder +import org.apache.spark.sql.execution.streaming.TransformWithStateKeyValueRowSchema.{KEY_ROW_SCHEMA, VALUE_ROW_SCHEMA_WITH_TTL} +import org.apache.spark.sql.execution.streaming.state.{NoPrefixKeyStateEncoderSpec, StateStore, StateStoreErrors} +import org.apache.spark.sql.streaming.{ListState, TTLConfig} +import org.apache.spark.util.NextIterator + +/** + * Provides concrete implementation for list of values associated with a state variable + * used in the streaming transformWithState operator. + * + * @param store - reference to the StateStore instance to be used for storing state + * @param stateName - name of logical state partition + * @param keyEnc - Spark SQL encoder for key + * @param valEncoder - Spark SQL encoder for value + * @tparam S - data type of object that will be stored in the list + */ +class ListStateImplWithTTL[S]( + store: StateStore, + stateName: String, + keyExprEnc: ExpressionEncoder[Any], + valEncoder: Encoder[S], + ttlConfig: TTLConfig, + batchTimestampMs: Long) + extends SingleKeyTTLStateImpl(stateName, store, batchTimestampMs) with ListState[S] { + + private lazy val keySerializer = keyExprEnc.createSerializer() + + private lazy val stateTypesEncoder = StateTypesEncoder( + keySerializer, valEncoder, stateName, hasTtl = true) + + private lazy val ttlExpirationMs = + StateTTL.calculateExpirationTimeForDuration(ttlConfig.ttlDuration, batchTimestampMs) + + initialize() + + private def initialize(): Unit = { + store.createColFamilyIfAbsent(stateName, KEY_ROW_SCHEMA, VALUE_ROW_SCHEMA_WITH_TTL, + NoPrefixKeyStateEncoderSpec(KEY_ROW_SCHEMA), useMultipleValuesPerKey = true) + } + + /** Whether state exists or not. */ + override def exists(): Boolean = { + get().nonEmpty + } + + /** + * Get the state value if it exists. If the state does not exist in state store, an + * empty iterator is returned. + */ + override def get(): Iterator[S] = { + val encodedKey = stateTypesEncoder.encodeGroupingKey() + val unsafeRowValuesIterator = store.valuesIterator(encodedKey, stateName) + + new NextIterator[S] { + + override protected def getNext(): S = { + val iter = unsafeRowValuesIterator.dropWhile { row => + stateTypesEncoder.isExpired(row, batchTimestampMs) + } + + if (iter.hasNext) { + val currentRow = iter.next() + stateTypesEncoder.decodeValue(currentRow) + } else { + finished = true + null.asInstanceOf[S] + } + } + + override protected def close(): Unit = {} + } + } + + /** Update the value of the list. */ + override def put(newState: Array[S]): Unit = { + validateNewState(newState) + + val serializedGroupingKey = stateTypesEncoder.serializeGroupingKey() + val encodedKey = stateTypesEncoder.encodeSerializedGroupingKey(serializedGroupingKey) + var isFirst = true + + newState.foreach { v => + val encodedValue = stateTypesEncoder.encodeValue(v, ttlExpirationMs) + if (isFirst) { + store.put(encodedKey, encodedValue, stateName) + isFirst = false + } else { + store.merge(encodedKey, encodedValue, stateName) + } + } + upsertTTLForStateKey(serializedGroupingKey) + } + + /** Append an entry to the list. */ + override def appendValue(newState: S): Unit = { + StateStoreErrors.requireNonNullStateValue(newState, stateName) + val serializedGroupingKey = stateTypesEncoder.serializeGroupingKey() + store.merge(stateTypesEncoder.encodeSerializedGroupingKey(serializedGroupingKey), + stateTypesEncoder.encodeValue(newState, ttlExpirationMs), stateName) + upsertTTLForStateKey(serializedGroupingKey) + } + + /** Append an entire list to the existing value. */ + override def appendList(newState: Array[S]): Unit = { + validateNewState(newState) + + val serializedGroupingKey = stateTypesEncoder.serializeGroupingKey() + val encodedKey = stateTypesEncoder.encodeSerializedGroupingKey(serializedGroupingKey) + newState.foreach { v => + val encodedValue = stateTypesEncoder.encodeValue(v, ttlExpirationMs) + store.merge(encodedKey, encodedValue, stateName) + } + upsertTTLForStateKey(serializedGroupingKey) + } + + /** Remove this state. */ + override def clear(): Unit = { + store.remove(stateTypesEncoder.encodeGroupingKey(), stateName) + } + + private def validateNewState(newState: Array[S]): Unit = { + StateStoreErrors.requireNonNullStateValue(newState, stateName) + StateStoreErrors.requireNonEmptyListStateValue(newState, stateName) + + newState.foreach { v => + StateStoreErrors.requireNonNullStateValue(v, stateName) + } + } + + /** + * Review Comment: nit: extra empty line ? ########## sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StatefulProcessorHandleSuite.scala: ########## @@ -237,13 +237,33 @@ class StatefulProcessorHandleSuite extends StateVariableSuiteBase { } } + test(s"ttl States are populated for listState and timeMode=ProcessingTime") { + tryWithProviderResource(newStoreProviderWithStateVariable(true)) { provider => + val store = provider.getStore(0) + val handle = new StatefulProcessorHandleImpl(store, + UUID.randomUUID(), keyExprEncoder, TimeMode.ProcessingTime(), + batchTimestampMs = Some(10)) + + val listStateWithTTL = handle.getListState("testState", + Encoders.STRING, TTLConfig(Duration.ofHours(1))) + + // create another state without TTL, this should not be captured in the handle + handle.getListState("testState", Encoders.STRING) + + assert(handle.ttlStates.size() === 1) + assert(handle.ttlStates.get(0) === listStateWithTTL) + } + } + + test(s"ttl States are not populated for timeMode=None") { tryWithProviderResource(newStoreProviderWithStateVariable(true)) { provider => val store = provider.getStore(0) val handle = new StatefulProcessorHandleImpl(store, UUID.randomUUID(), keyExprEncoder, TimeMode.None()) handle.getValueState("testState", Encoders.STRING) + handle.getListState("testState", Encoders.STRING) Review Comment: Could we use a different name for the state variable ? -- This is an automated message from the Apache Git Service. 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