micheal-o commented on code in PR #53899: URL: https://github.com/apache/spark/pull/53899#discussion_r2756166444
########## sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/OfflineStateRepartitionTransformWithStateIntegrationSuite.scala: ########## @@ -0,0 +1,491 @@ +/* + * 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.state + +import java.time.Duration + +import org.apache.spark.sql.Dataset +import org.apache.spark.sql.execution.datasources.v2.state.StateSourceOptions +import org.apache.spark.sql.execution.streaming.operators.stateful.transformwithstate.timers.TimerStateUtils +import org.apache.spark.sql.execution.streaming.runtime.MemoryStream +import org.apache.spark.sql.functions.{col, timestamp_seconds} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.streaming.{InputEvent, ListStateTTLProcessor, MapInputEvent, MapOutputEvent, MapStateTTLProcessor, MaxEventTimeStatefulProcessor, OutputEvent, OutputMode, RunningCountStatefulProcessorWithProcTimeTimer, TimeMode, Trigger, TTLConfig, ValueStateTTLProcessor} +import org.apache.spark.sql.streaming.util.{MultiStateVarProcessor, MultiStateVarProcessorTestUtils, TimerTestUtils, TTLProcessorUtils} + +/** + * Integration test suite for transformWithState operator repartitioning. + */ +class OfflineStateRepartitionTransformWithStateCkptV1IntegrationSuite + extends OfflineStateRepartitionIntegrationSuiteBase { + + import testImplicits._ + + override def beforeAll(): Unit = { + super.beforeAll() + spark.conf.set(SQLConf.STATE_STORE_CHECKPOINT_FORMAT_VERSION.key, "1") + } + + /** + * Unified helper to build state source options for transformWithState tests. + * Handles basic state variables, timer and TTL column families. + * + * @param columnFamilyNames List of column family names to configure + * @param timeMode Optional TimeMode for timer-based tests (adds READ_REGISTERED_TIMERS) + * @param listStateName Optional list state name for TTL tests (adds FLATTEN_COLLECTION_TYPES) + * @return Map of column family names to their state source options + */ + def buildStateSourceOptionsForTWS( + columnFamilyNames: Seq[String], + timeMode: Option[TimeMode] = None, + listStateName: Option[String] = None): Map[String, Map[String, String]] = { + // Get timer column family names if timeMode is provided + val (keyToTimestampCF, timestampToKeyCF) = timeMode match { + case Some(tm) => TimerStateUtils.getTimerStateVarNames(tm.toString) + case None => (null, null) + } + + columnFamilyNames.map { cfName => + // Determine base options based on column family type + val options = if (cfName == keyToTimestampCF || cfName == timestampToKeyCF) { + // Timer column families + Map(StateSourceOptions.READ_REGISTERED_TIMERS -> "true") + } else if (cfName == StateStore.DEFAULT_COL_FAMILY_NAME) { + throw new IllegalArgumentException("TWS operator shouldn't contain DEFAULT column family") + } else { + // Regular state variable column families + val baseOptions = Map(StateSourceOptions.STATE_VAR_NAME -> cfName) + if (listStateName.contains(cfName)) { + baseOptions + (StateSourceOptions.FLATTEN_COLLECTION_TYPES -> "true") + } else { + baseOptions + } + } + + cfName -> options + }.toMap + } + + def testWithDifferentEncodingType(testNamePrefix: String) + (testFun: Int => Unit): Unit = { + // TODO[SPARK-55301]: add test with "avro" encoding format after SPARK increases test timeout + // because CI signal "sql - other tests" is timing out after adding the integration tests + Seq("unsaferow").foreach { encodingFormat => + testWithAllRepartitionOperations( + s"$testNamePrefix (encoding = $encodingFormat)") { newPartitions => + withSQLConf(SQLConf.STREAMING_STATE_STORE_ENCODING_FORMAT.key -> encodingFormat) { + testFun(newPartitions) + } + } + } + } + + testWithDifferentEncodingType( + "transformWithState with multiple column families") { + newPartitions => + val allColFamilyNames = MultiStateVarProcessorTestUtils.ALL_COLUMN_FAMILIES.toList + val stateSourceOptions = buildStateSourceOptionsForTWS( + allColFamilyNames, + listStateName = Some(MultiStateVarProcessorTestUtils.ITEMS_LIST)) + val selectExprs = MultiStateVarProcessorTestUtils.getColumnFamilyToSelectExprs() + + def buildQuery( + inputData: MemoryStream[String]): Dataset[(String, String, String, String)] = { + inputData.toDS() + .groupByKey(x => x) + .transformWithState(new MultiStateVarProcessor(), + TimeMode.None(), + OutputMode.Update()) + } + + testRepartitionWorkflow[String]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query)( + StartStream(checkpointLocation = checkpointDir), + // Batch 1: Creates state in all column families + AddData(inputData, "a", "b", "c"), + CheckNewAnswer( + ("a", "1", "a", "a=1"), + ("b", "1", "b", "b=1"), + ("c", "1", "c", "c=1")), + // Batch 2: Adds more state + AddData(inputData, "a", "b", "d"), + CheckNewAnswer( + ("a", "2", "a,a", "a=2"), + ("b", "2", "b,b", "b=2"), + ("d", "1", "d", "d=1")), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query)( + StartStream(checkpointLocation = checkpointDir), + // Batch 3: Resume with new data after repartition + AddData(inputData, "a", "c", "e"), + CheckNewAnswer( + ("a", "3", "a,a,a", "a=3"), + ("c", "2", "c,c", "c=2"), + ("e", "1", "e", "e=1")) + ) + }, + storeToColumnFamilyToStateSourceOptions = Map( + StateStoreId.DEFAULT_STORE_NAME -> stateSourceOptions + ), + storeToColumnFamilyToSelectExprs = Map( + StateStoreId.DEFAULT_STORE_NAME -> selectExprs + ) + ) + } + + testWithDifferentEncodingType("transformWithState with eventTime timers") { + newPartitions => + // MaxEventTimeStatefulProcessor uses maxEventTimeState and timerState + val (keyToTimestampCF, timestampToKeyCF) = + TimerStateUtils.getTimerStateVarNames(TimeMode.EventTime().toString) + val columnFamilies = Seq( + "maxEventTimeState", + "timerState", + keyToTimestampCF, + timestampToKeyCF) + val stateSourceOptions = buildStateSourceOptionsForTWS( + columnFamilies, timeMode = Some(TimeMode.EventTime())) + val selectExprs = TimerTestUtils.getTimerColumnFamilyToSelectExprs(TimeMode.EventTime()) + + def buildQuery(inputData: MemoryStream[(String, Long)]): Dataset[(String, Int)] = { + inputData.toDS() + .select(col("_1").as("key"), timestamp_seconds(col("_2")).as("eventTime")) + .withWatermark("eventTime", "10 seconds") + .as[(String, Long)] + .groupByKey(_._1) + .transformWithState( + new MaxEventTimeStatefulProcessor(), + TimeMode.EventTime(), + OutputMode.Update()) + } + + testRepartitionWorkflow[(String, Long)]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir), + // Batch 1: Creates state with event time timers + // MaxEventTimeStatefulProcessor outputs (key, maxEventTimeSec) + AddData(inputData, ("a", 1L), ("b", 2L), ("c", 3L)), + CheckNewAnswer(("a", 1), ("b", 2), ("c", 3)), + // Batch 2: More data - max event time for "a" becomes 12 + AddData(inputData, ("a", 12L)), + CheckNewAnswer(("a", 12)), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir), + // Batch 3: Resume with new data after repartition + // Send event time 18 to advance watermark to (18-10)*1000 = 8000ms + // This fires timers for "b" (at 7000ms) and "c" (at 8000ms) + // Timer expiry outputs (key, -1) + AddData(inputData, ("a", 18L)), + CheckNewAnswer(("a", 18), ("b", -1), ("c", -1)) Review Comment: Add new data for b and c after with lower values than previous (e.g. add b,1 and c,2), to confirm that maxEventTime is correctly updated after the expiry ########## sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/OfflineStateRepartitionTransformWithStateIntegrationSuite.scala: ########## @@ -0,0 +1,491 @@ +/* + * 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.state + +import java.time.Duration + +import org.apache.spark.sql.Dataset +import org.apache.spark.sql.execution.datasources.v2.state.StateSourceOptions +import org.apache.spark.sql.execution.streaming.operators.stateful.transformwithstate.timers.TimerStateUtils +import org.apache.spark.sql.execution.streaming.runtime.MemoryStream +import org.apache.spark.sql.functions.{col, timestamp_seconds} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.streaming.{InputEvent, ListStateTTLProcessor, MapInputEvent, MapOutputEvent, MapStateTTLProcessor, MaxEventTimeStatefulProcessor, OutputEvent, OutputMode, RunningCountStatefulProcessorWithProcTimeTimer, TimeMode, Trigger, TTLConfig, ValueStateTTLProcessor} +import org.apache.spark.sql.streaming.util.{MultiStateVarProcessor, MultiStateVarProcessorTestUtils, TimerTestUtils, TTLProcessorUtils} + +/** + * Integration test suite for transformWithState operator repartitioning. + */ +class OfflineStateRepartitionTransformWithStateCkptV1IntegrationSuite + extends OfflineStateRepartitionIntegrationSuiteBase { + + import testImplicits._ + + override def beforeAll(): Unit = { + super.beforeAll() + spark.conf.set(SQLConf.STATE_STORE_CHECKPOINT_FORMAT_VERSION.key, "1") + } + + /** + * Unified helper to build state source options for transformWithState tests. + * Handles basic state variables, timer and TTL column families. + * + * @param columnFamilyNames List of column family names to configure + * @param timeMode Optional TimeMode for timer-based tests (adds READ_REGISTERED_TIMERS) + * @param listStateName Optional list state name for TTL tests (adds FLATTEN_COLLECTION_TYPES) + * @return Map of column family names to their state source options + */ + def buildStateSourceOptionsForTWS( + columnFamilyNames: Seq[String], + timeMode: Option[TimeMode] = None, + listStateName: Option[String] = None): Map[String, Map[String, String]] = { + // Get timer column family names if timeMode is provided + val (keyToTimestampCF, timestampToKeyCF) = timeMode match { + case Some(tm) => TimerStateUtils.getTimerStateVarNames(tm.toString) + case None => (null, null) + } + + columnFamilyNames.map { cfName => + // Determine base options based on column family type + val options = if (cfName == keyToTimestampCF || cfName == timestampToKeyCF) { + // Timer column families + Map(StateSourceOptions.READ_REGISTERED_TIMERS -> "true") + } else if (cfName == StateStore.DEFAULT_COL_FAMILY_NAME) { + throw new IllegalArgumentException("TWS operator shouldn't contain DEFAULT column family") + } else { + // Regular state variable column families + val baseOptions = Map(StateSourceOptions.STATE_VAR_NAME -> cfName) + if (listStateName.contains(cfName)) { + baseOptions + (StateSourceOptions.FLATTEN_COLLECTION_TYPES -> "true") + } else { + baseOptions + } + } + + cfName -> options + }.toMap + } + + def testWithDifferentEncodingType(testNamePrefix: String) + (testFun: Int => Unit): Unit = { + // TODO[SPARK-55301]: add test with "avro" encoding format after SPARK increases test timeout + // because CI signal "sql - other tests" is timing out after adding the integration tests + Seq("unsaferow").foreach { encodingFormat => + testWithAllRepartitionOperations( + s"$testNamePrefix (encoding = $encodingFormat)") { newPartitions => + withSQLConf(SQLConf.STREAMING_STATE_STORE_ENCODING_FORMAT.key -> encodingFormat) { + testFun(newPartitions) + } + } + } + } + + testWithDifferentEncodingType( + "transformWithState with multiple column families") { + newPartitions => + val allColFamilyNames = MultiStateVarProcessorTestUtils.ALL_COLUMN_FAMILIES.toList + val stateSourceOptions = buildStateSourceOptionsForTWS( + allColFamilyNames, + listStateName = Some(MultiStateVarProcessorTestUtils.ITEMS_LIST)) + val selectExprs = MultiStateVarProcessorTestUtils.getColumnFamilyToSelectExprs() + + def buildQuery( + inputData: MemoryStream[String]): Dataset[(String, String, String, String)] = { + inputData.toDS() + .groupByKey(x => x) + .transformWithState(new MultiStateVarProcessor(), + TimeMode.None(), + OutputMode.Update()) + } + + testRepartitionWorkflow[String]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query)( + StartStream(checkpointLocation = checkpointDir), + // Batch 1: Creates state in all column families + AddData(inputData, "a", "b", "c"), + CheckNewAnswer( + ("a", "1", "a", "a=1"), + ("b", "1", "b", "b=1"), + ("c", "1", "c", "c=1")), + // Batch 2: Adds more state + AddData(inputData, "a", "b", "d"), + CheckNewAnswer( + ("a", "2", "a,a", "a=2"), + ("b", "2", "b,b", "b=2"), + ("d", "1", "d", "d=1")), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query)( + StartStream(checkpointLocation = checkpointDir), + // Batch 3: Resume with new data after repartition + AddData(inputData, "a", "c", "e"), + CheckNewAnswer( + ("a", "3", "a,a,a", "a=3"), + ("c", "2", "c,c", "c=2"), + ("e", "1", "e", "e=1")) + ) + }, + storeToColumnFamilyToStateSourceOptions = Map( + StateStoreId.DEFAULT_STORE_NAME -> stateSourceOptions + ), + storeToColumnFamilyToSelectExprs = Map( + StateStoreId.DEFAULT_STORE_NAME -> selectExprs + ) + ) + } + + testWithDifferentEncodingType("transformWithState with eventTime timers") { + newPartitions => + // MaxEventTimeStatefulProcessor uses maxEventTimeState and timerState + val (keyToTimestampCF, timestampToKeyCF) = + TimerStateUtils.getTimerStateVarNames(TimeMode.EventTime().toString) + val columnFamilies = Seq( + "maxEventTimeState", + "timerState", + keyToTimestampCF, + timestampToKeyCF) + val stateSourceOptions = buildStateSourceOptionsForTWS( + columnFamilies, timeMode = Some(TimeMode.EventTime())) + val selectExprs = TimerTestUtils.getTimerColumnFamilyToSelectExprs(TimeMode.EventTime()) + + def buildQuery(inputData: MemoryStream[(String, Long)]): Dataset[(String, Int)] = { + inputData.toDS() + .select(col("_1").as("key"), timestamp_seconds(col("_2")).as("eventTime")) + .withWatermark("eventTime", "10 seconds") + .as[(String, Long)] + .groupByKey(_._1) + .transformWithState( + new MaxEventTimeStatefulProcessor(), + TimeMode.EventTime(), + OutputMode.Update()) + } + + testRepartitionWorkflow[(String, Long)]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir), + // Batch 1: Creates state with event time timers + // MaxEventTimeStatefulProcessor outputs (key, maxEventTimeSec) + AddData(inputData, ("a", 1L), ("b", 2L), ("c", 3L)), + CheckNewAnswer(("a", 1), ("b", 2), ("c", 3)), + // Batch 2: More data - max event time for "a" becomes 12 + AddData(inputData, ("a", 12L)), + CheckNewAnswer(("a", 12)), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, _) => { + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir), + // Batch 3: Resume with new data after repartition + // Send event time 18 to advance watermark to (18-10)*1000 = 8000ms + // This fires timers for "b" (at 7000ms) and "c" (at 8000ms) + // Timer expiry outputs (key, -1) + AddData(inputData, ("a", 18L)), + CheckNewAnswer(("a", 18), ("b", -1), ("c", -1)) + ) + }, + storeToColumnFamilyToStateSourceOptions = Map( + StateStoreId.DEFAULT_STORE_NAME -> stateSourceOptions + ), + storeToColumnFamilyToSelectExprs = Map( + StateStoreId.DEFAULT_STORE_NAME -> selectExprs + ) + ) + } + + testWithDifferentEncodingType("transformWithState with processing time timers") { + newPartitions => + val schemas = TimerTestUtils.getTimerConfigsForCountState(TimeMode.ProcessingTime()) + val columnFamilies = schemas.keys.toSeq.filterNot(_ == StateStore.DEFAULT_COL_FAMILY_NAME) + val stateSourceOptions = buildStateSourceOptionsForTWS( + columnFamilies, + timeMode = Some(TimeMode.ProcessingTime())) + val selectExprs = TimerTestUtils.getTimerColumnFamilyToSelectExprs(TimeMode.ProcessingTime()) + + def buildQuery(inputData: MemoryStream[String]): Dataset[(String, String)] = { + inputData.toDS() + .groupByKey(x => x) + .transformWithState(new RunningCountStatefulProcessorWithProcTimeTimer(), + TimeMode.ProcessingTime(), + OutputMode.Update()) + } + + testRepartitionWorkflow[String]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, clockOpt) => { + val clock = clockOpt.get + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir, + trigger = Trigger.ProcessingTime("1 second"), + triggerClock = clock), + AddData(inputData, "a", "b"), + AdvanceManualClock(1000), + CheckNewAnswer(("a", "1"), ("b", "1")), + AddData(inputData, "a", "c"), + AdvanceManualClock(1000), + CheckNewAnswer(("a", "2"), ("c", "1")), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, clockOpt) => { + val clock = clockOpt.get + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir, + trigger = Trigger.ProcessingTime("1 second"), + triggerClock = clock), + AddData(inputData, "c", "d"), + AdvanceManualClock(5 * 1000), + // "a" and "c" are expired, and processor fires processing time with "-1" + CheckNewAnswer(("a", "-1"), ("c", "-1"), ("c", "2"), ("d", "1")), + AddData(inputData, "c"), + AdvanceManualClock(1000), + // "c" is cleared after timer went off, so recount from 1 + CheckNewAnswer(("c", "1")) + ) + }, + useManualClock = true, + storeToColumnFamilyToStateSourceOptions = Map( + StateStoreId.DEFAULT_STORE_NAME -> stateSourceOptions + ), + storeToColumnFamilyToSelectExprs = Map( + StateStoreId.DEFAULT_STORE_NAME -> selectExprs + ) + ) + } + + testWithDifferentEncodingType("transformWithState with list and TTL") { + newPartitions => + val schemas = TTLProcessorUtils.getListStateTTLSchemasWithMetadata() + val columnFamilies = schemas.keys.toSeq.filterNot(_ == StateStore.DEFAULT_COL_FAMILY_NAME) + val stateSourceOptions = buildStateSourceOptionsForTWS( + columnFamilies, + listStateName = Some(TTLProcessorUtils.LIST_STATE)) + val selectExprs = TTLProcessorUtils.getTTLSelectExpressions(columnFamilies) + + def buildQuery(inputData: MemoryStream[InputEvent]): Dataset[OutputEvent] = { + val ttlConfig = TTLConfig(ttlDuration = Duration.ofMinutes(1)) + inputData.toDS() + .groupByKey(x => x.key) + .transformWithState(new ListStateTTLProcessor(ttlConfig), + TimeMode.ProcessingTime(), + OutputMode.Update()) + } + + testRepartitionWorkflow[InputEvent]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, clockOpt) => { + val clock = clockOpt.get + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir, + trigger = Trigger.ProcessingTime("1 second"), + triggerClock = clock), + // Batch 1: Clock advances to 1000ms, TTL = 1000 + 60000 = 61000ms + AddData(inputData, InputEvent("k1", "put", 1), + InputEvent("k1", "get_ttl_value_from_state", 0)), + AdvanceManualClock(1 * 1000), + CheckNewAnswer(OutputEvent("k1", 1, true, 61000)), + // Batch 2: Clock advances to 2000ms, TTL = 2000 + 60000 = 62000ms + AddData(inputData, InputEvent("k2", "put", 2), + InputEvent("k2", "get_ttl_value_from_state", 0)), + AdvanceManualClock(1 * 1000), + CheckNewAnswer(OutputEvent("k2", 2, true, 62000)), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, clockOpt) => { + val clock = clockOpt.get + val query = buildQuery(inputData) + testStream(query, OutputMode.Update())( + StartStream(checkpointLocation = checkpointDir, + trigger = Trigger.ProcessingTime("1 second"), + triggerClock = clock), + // Batch 3: Clock advances to 3000ms + // Value 1 has TTL from batch 1 (61000ms), value 3 gets TTL = 3000 + 60000 = 63000ms + AddData(inputData, InputEvent("k1", "append", 3), + InputEvent("k1", "get_ttl_value_from_state", 0), + InputEvent("k1", "get_values_in_min_state", 0)), + AdvanceManualClock(1 * 1000), + CheckNewAnswer( + OutputEvent("k1", 1, true, 61000), + OutputEvent("k1", 3, true, 63000), + OutputEvent("k1", -1, true, 61000)) + ) + }, + useManualClock = true, + storeToColumnFamilyToStateSourceOptions = Map( + StateStoreId.DEFAULT_STORE_NAME -> stateSourceOptions + ), + storeToColumnFamilyToSelectExprs = Map( + StateStoreId.DEFAULT_STORE_NAME -> selectExprs + ) + ) + } + + testWithDifferentEncodingType("transformWithState with map and TTL") { + newPartitions => + val schemas = TTLProcessorUtils.getMapStateTTLSchemasWithMetadata() + val columnFamilies = schemas.keys.toSeq.filterNot(_ == StateStore.DEFAULT_COL_FAMILY_NAME) + val stateSourceOptions = buildStateSourceOptionsForTWS(columnFamilies) + val selectExprs = TTLProcessorUtils.getTTLSelectExpressions(columnFamilies) + + def buildQuery(inputData: MemoryStream[MapInputEvent]): Dataset[MapOutputEvent] = { + val ttlConfig = TTLConfig(ttlDuration = Duration.ofMinutes(1)) + inputData.toDS() + .groupByKey(x => x.key) + .transformWithState(new MapStateTTLProcessor(ttlConfig), + TimeMode.ProcessingTime(), + OutputMode.Update()) + } + + testRepartitionWorkflow[MapInputEvent]( + newPartitions = newPartitions, + setupInitialState = (inputData, checkpointDir, clockOpt) => { + val clock = clockOpt.get + val query = buildQuery(inputData) + testStream(query)( + StartStream(checkpointLocation = checkpointDir, + trigger = Trigger.ProcessingTime("1 second"), + triggerClock = clock), + // Batch 1: Clock advances to 1000ms, TTL = 1000 + 60000 = 61000ms + AddData(inputData, MapInputEvent("a", "key1", "put", 1), + MapInputEvent("a", "key1", "get_ttl_value_from_state", 0)), + AdvanceManualClock(1 * 1000), + CheckNewAnswer(MapOutputEvent("a", "key1", 1, true, 61000)), + // Batch 2: Clock advances to 2000ms, TTL = 2000 + 60000 = 62000ms + AddData(inputData, MapInputEvent("b", "key2", "put", 2), + MapInputEvent("b", "key2", "get_ttl_value_from_state", 0)), + AdvanceManualClock(1 * 1000), + CheckNewAnswer(MapOutputEvent("b", "key2", 2, true, 62000)), + StopStream + ) + }, + verifyResumedQuery = (inputData, checkpointDir, clockOpt) => { + val clock = clockOpt.get + val query = buildQuery(inputData) + testStream(query)( + StartStream(checkpointLocation = checkpointDir, + trigger = Trigger.ProcessingTime("1 second"), + triggerClock = clock), + // Batch 3: Clock advances to 3000ms + // key1 has TTL from batch 1 (61000ms), key3 gets TTL = 3000 + 60000 = 63000ms + AddData(inputData, MapInputEvent("a", "key3", "put", 3), + MapInputEvent("a", "key1", "get_ttl_value_from_state", 0), + MapInputEvent("a", "key3", "get_ttl_value_from_state", 0), + MapInputEvent("a", "key1", "get_values_in_ttl_state", 0) Review Comment: Lets do `iterator` for `a` instead to confirm what is in the main map cf, since we have already done `get_ttl_value_from_state` to confirm the TTL cf -- This is an automated message from the Apache Git Service. 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