xuyangzhong commented on code in PR #26051:
URL: https://github.com/apache/flink/pull/26051#discussion_r1944682832
##########
flink-table/flink-table-planner/src/main/java/org/apache/flink/table/planner/plan/nodes/exec/stream/StreamExecDeduplicate.java:
##########
@@ -339,25 +362,39 @@ OneInputStreamOperator<RowData, RowData>
createDeduplicateOperator() {
}
} else {
if (isAsyncStateEnabled()) {
- AsyncStateRowTimeDeduplicateFunction processFunction =
- new AsyncStateRowTimeDeduplicateFunction(
- rowTypeInfo,
- stateRetentionTime,
- rowtimeIndex,
- generateUpdateBefore,
- generateInsert(),
- keepLastRow);
- return new AsyncKeyedProcessOperator<>(processFunction);
+ if (!keepLastRow && outputInsertOnly) {
+ checkState(canBeInsertOnly(config, keepLastRow));
Review Comment:
nit: can we need to double check the field `outputInsertOnly`?
The same goes for the following.
##########
flink-table/flink-table-planner/src/main/scala/org/apache/flink/table/planner/plan/nodes/physical/stream/StreamPhysicalRank.scala:
##########
@@ -109,28 +109,34 @@ class StreamPhysicalRank(
.item("select", getRowType.getFieldNames.mkString(", "))
}
- private def getDeduplicateDescription(isRowtime: Boolean, isLastRow:
Boolean): String = {
+ private def getDeduplicateDescription(
+ isRowtime: Boolean,
+ isLastRow: Boolean,
+ insertOnly: Boolean): String = {
val fieldNames = getRowType.getFieldNames
val orderString = if (isRowtime) "ROWTIME" else "PROCTIME"
val keep = if (isLastRow) "LastRow" else "FirstRow"
- s"Deduplicate(keep=[$keep],
key=[${partitionKey.toArray.map(fieldNames.get).mkString(", ")}],
order=[$orderString])"
+ s"Deduplicate(keep=[$keep],
key=[${partitionKey.toArray.map(fieldNames.get).mkString(", ")}],
order=[$orderString], outputInsertOnly=[$insertOnly])"
}
override def translateToExecNode(): ExecNode[_] = {
val generateUpdateBefore = ChangelogPlanUtils.generateUpdateBefore(this)
if (RankUtil.canConvertToDeduplicate(this)) {
val keepLastRow = RankUtil.keepLastDeduplicateRow(orderKey)
+ val tableConfig = unwrapTableConfig(this)
+ val outputInsertOnly =
StreamExecDeduplicate.canBeInsertOnly(tableConfig, keepLastRow)
Review Comment:
nit: use `val outputInsertOnly = ChangelogPlanUtils.isInsertOnly(this)`?
##########
flink-table/flink-table-planner/src/main/scala/org/apache/flink/table/planner/plan/optimize/program/FlinkChangelogModeInferenceProgram.scala:
##########
@@ -220,6 +221,38 @@ class FlinkChangelogModeInferenceProgram extends
FlinkOptimizeProgram[StreamOpti
val providedTrait = ModifyKindSetTrait.INSERT_ONLY
createNewNode(rel, children, providedTrait, requiredTrait, requester)
+ case rank: StreamPhysicalRank if RankUtil.isDeduplication(rank) =>
+ val children = visitChildren(rel, ModifyKindSetTrait.ALL_CHANGES)
+ val tableConfig = unwrapTableConfig(rank)
+
+ // if the rank is deduplication and can be executed as insert-only,
forward that information
+ val insertOnly = children
Review Comment:
nit: using `val insertOnly =
children.forall(ChangelogPlanUtils.isInsertOnly)` to resolve idea warning
##########
flink-table/flink-table-planner/src/test/scala/org/apache/flink/table/planner/plan/stream/sql/DeduplicateTest.scala:
##########
@@ -139,14 +139,17 @@ class DeduplicateTest extends TableTestBase {
@Test
def testSimpleFirstRowOnRowtime(): Unit = {
+ // indirectly check output insert only via used SUM or SUM_RETRACT
aggregation function
Review Comment:
Tips, use `util.verifyExplain(sql, ExplainDetail.CHANGELOG_MODE)` can also
print the changelog mode in physical nodes. For example:
```
@Test
def test(): Unit = {
val sql =
"""
| SELECT a, b, c
| FROM (
| SELECT *,
| ROW_NUMBER() OVER (PARTITION BY a ORDER BY rowtime ASC) as
rank_num
| FROM MyTable)
| WHERE rank_num <= 1
""".stripMargin
util.verifyExplain(sql, ExplainDetail.CHANGELOG_MODE)
}
```
Before this pr:
```
== Abstract Syntax Tree ==
LogicalProject(a=[$0], b=[$1], c=[$2])
+- LogicalFilter(condition=[<=($5, 1)])
+- LogicalProject(a=[$0], b=[$1], c=[$2], proctime=[$3], rowtime=[$4],
rank_num=[ROW_NUMBER() OVER (PARTITION BY $0 ORDER BY $4 NULLS FIRST)])
+- LogicalTableScan(table=[[default_catalog, default_database,
MyTable]])
== Optimized Physical Plan ==
Calc(select=[a, b, c], changelogMode=[I,UA,D])
+- Rank(strategy=[AppendFastStrategy], rankType=[ROW_NUMBER],
rankRange=[rankStart=1, rankEnd=1], partitionBy=[a], orderBy=[ROWTIME rowtime
ASC], select=[a, b, c, rowtime], changelogMode=[I,UA,D])
+- Exchange(distribution=[hash[a]], changelogMode=[I])
+- Calc(select=[a, b, c, rowtime], changelogMode=[I])
+- DataStreamScan(table=[[default_catalog, default_database,
MyTable]], fields=[a, b, c, proctime, rowtime], changelogMode=[I])
== Optimized Execution Plan ==
Calc(select=[a, b, c])
+- Deduplicate(keep=[FirstRow], key=[a], order=[ROWTIME],
outputInsertOnly=[false])
+- Exchange(distribution=[hash[a]])
+- Calc(select=[a, b, c, rowtime])
+- DataStreamScan(table=[[default_catalog, default_database,
MyTable]], fields=[a, b, c, proctime, rowtime])
```
After applying this pr:
```
== Abstract Syntax Tree ==
LogicalProject(a=[$0], b=[$1], c=[$2])
+- LogicalFilter(condition=[<=($5, 1)])
+- LogicalProject(a=[$0], b=[$1], c=[$2], proctime=[$3], rowtime=[$4],
rank_num=[ROW_NUMBER() OVER (PARTITION BY $0 ORDER BY $4 NULLS FIRST)])
+- LogicalTableScan(table=[[default_catalog, default_database,
MyTable]])
== Optimized Physical Plan ==
Calc(select=[a, b, c], changelogMode=[I])
+- Rank(strategy=[AppendFastStrategy], rankType=[ROW_NUMBER],
rankRange=[rankStart=1, rankEnd=1], partitionBy=[a], orderBy=[ROWTIME rowtime
ASC], select=[a, b, c, rowtime], changelogMode=[I])
+- Exchange(distribution=[hash[a]], changelogMode=[I])
+- Calc(select=[a, b, c, rowtime], changelogMode=[I])
+- DataStreamScan(table=[[default_catalog, default_database,
MyTable]], fields=[a, b, c, proctime, rowtime], changelogMode=[I])
== Optimized Execution Plan ==
Calc(select=[a, b, c])
+- Deduplicate(keep=[FirstRow], key=[a], order=[ROWTIME],
outputInsertOnly=[true])
+- Exchange(distribution=[hash[a]])
+- Calc(select=[a, b, c, rowtime])
+- DataStreamScan(table=[[default_catalog, default_database,
MyTable]], fields=[a, b, c, proctime, rowtime])
```
##########
flink-table/flink-table-planner/src/main/scala/org/apache/flink/table/planner/plan/optimize/program/FlinkChangelogModeInferenceProgram.scala:
##########
@@ -220,6 +221,38 @@ class FlinkChangelogModeInferenceProgram extends
FlinkOptimizeProgram[StreamOpti
val providedTrait = ModifyKindSetTrait.INSERT_ONLY
createNewNode(rel, children, providedTrait, requiredTrait, requester)
+ case rank: StreamPhysicalRank if RankUtil.isDeduplication(rank) =>
+ val children = visitChildren(rel, ModifyKindSetTrait.ALL_CHANGES)
+ val tableConfig = unwrapTableConfig(rank)
+
+ // if the rank is deduplication and can be executed as insert-only,
forward that information
+ val insertOnly = children
+ .filterNot(
+ rel => {
+ rel.getTraitSet.contains(ModifyKindSetTrait.INSERT_ONLY)
+ })
+ .isEmpty
+
+ val providedTrait = {
+ if (
+ insertOnly && StreamExecDeduplicate.canBeInsertOnly(
Review Comment:
It's a bit strange to use the exec node method in a place that only handles
physical nodes. How about moving this method to `RankUtil` and naming it
something like `RankUtil#outputInsertOnlyInDeduplicate`?
##########
flink-table/flink-table-runtime/src/main/java/org/apache/flink/table/runtime/operators/deduplicate/RowTimeDeduplicateKeepFirstRowFunction.java:
##########
@@ -0,0 +1,115 @@
+/*
+ * 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.flink.table.runtime.operators.deduplicate;
+
+import org.apache.flink.api.common.functions.OpenContext;
+import org.apache.flink.api.common.state.StateTtlConfig;
+import org.apache.flink.api.common.state.ValueState;
+import org.apache.flink.api.common.state.ValueStateDescriptor;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.common.typeinfo.Types;
+import org.apache.flink.streaming.api.functions.KeyedProcessFunction;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.runtime.typeutils.InternalTypeInfo;
+import org.apache.flink.util.Collector;
+
+import static
org.apache.flink.table.runtime.operators.deduplicate.utils.DeduplicateFunctionHelper.checkInsertOnly;
+import static
org.apache.flink.table.runtime.operators.deduplicate.utils.DeduplicateFunctionHelper.shouldKeepCurrentRow;
+import static
org.apache.flink.table.runtime.util.StateConfigUtil.createTtlConfig;
+
+/**
+ * This function is used to deduplicate on keys and keeps only first row on
row time. It produces
+ * append only stream thanks to emitting results only via firing the timers.
+ */
+public class RowTimeDeduplicateKeepFirstRowFunction
+ extends KeyedProcessFunction<RowData, RowData, RowData> {
+
+ private static final long serialVersionUID = 1L;
+
+ // the TypeInformation of the values in the state.
+ private final TypeInformation<RowData> typeInfo;
+ private final long stateRetentionTime;
+ private final int rowtimeIndex;
+
+ // state stores previous message under the key.
+ protected ValueState<RowData> waitingToEmitOnTimerState;
+ protected ValueState<Boolean> alreadyEmittedState;
+
+ public RowTimeDeduplicateKeepFirstRowFunction(
+ InternalTypeInfo<RowData> typeInfo, long minRetentionTime, int
rowtimeIndex) {
+ this.typeInfo = typeInfo;
+ this.stateRetentionTime = minRetentionTime;
+ this.rowtimeIndex = rowtimeIndex;
+ }
+
+ @Override
+ public void open(OpenContext openContext) throws Exception {
+ super.open(openContext);
+
+ // We don't enable TTL on the timer's state, because we rely on the
state cleaning up on
+ // watermark. Also otherwise TTL clean up before firing the watermark
would cause a data
+ // loss.
+ ValueStateDescriptor<RowData> timerStateDesc =
+ new ValueStateDescriptor<>("waiting-to-emit-on-timer",
typeInfo);
+ waitingToEmitOnTimerState =
getRuntimeContext().getState(timerStateDesc);
+
+ ValueStateDescriptor<Boolean> stateDesc =
+ new ValueStateDescriptor<>("already-emitted-state-boolean",
Types.BOOLEAN);
+ StateTtlConfig ttlConfig = createTtlConfig(stateRetentionTime);
+ if (ttlConfig.isEnabled()) {
+ stateDesc.enableTimeToLive(ttlConfig);
+ }
+ alreadyEmittedState = getRuntimeContext().getState(stateDesc);
+ }
+
+ @Override
+ public void processElement(RowData input, Context ctx, Collector<RowData>
out)
+ throws Exception {
+ checkInsertOnly(input);
+ Boolean allreadyEmitted = alreadyEmittedState.value();
+ if (allreadyEmitted != null && allreadyEmitted) {
+ // result has already been emitted, we can not retract/emit
anything different.
+ return;
+ }
+ long rowtime = input.getLong(rowtimeIndex);
+ if (rowtime < ctx.timerService().currentWatermark()) {
Review Comment:
What about introducing a metric to log late num used for debugging just like
other window operators?
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