[GitHub] [flink] godfreyhe commented on a change in pull request #14605: [FLINK-20883][table-planner-blink] Separate the implementation of BatchExecOverAggregate and StreamExecOverAggregate

[GitBox <gi...@apache.org>]

godfreyhe commented on a change in pull request #14605:
URL: https://github.com/apache/flink/pull/14605#discussion_r556397774



##########
File path: flink-table/flink-table-planner-blink/src/main/java/org/apache/flink/table/planner/plan/nodes/exec/stream/StreamExecOverAggregate.java
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@@ -0,0 +1,380 @@
+/*
+ * 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.planner.plan.nodes.exec.stream;
+
+import org.apache.flink.api.dag.Transformation;
+import org.apache.flink.streaming.api.functions.KeyedProcessFunction;
+import org.apache.flink.streaming.api.operators.KeyedProcessOperator;
+import org.apache.flink.streaming.api.transformations.OneInputTransformation;
+import org.apache.flink.table.api.TableConfig;
+import org.apache.flink.table.api.TableException;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.planner.calcite.FlinkTypeFactory;
+import org.apache.flink.table.planner.codegen.CodeGeneratorContext;
+import org.apache.flink.table.planner.codegen.agg.AggsHandlerCodeGenerator;
+import org.apache.flink.table.planner.delegation.PlannerBase;
+import org.apache.flink.table.planner.plan.nodes.exec.ExecEdge;
+import org.apache.flink.table.planner.plan.nodes.exec.ExecNode;
+import org.apache.flink.table.planner.plan.nodes.exec.ExecNodeBase;
+import org.apache.flink.table.planner.plan.nodes.exec.utils.OverSpec;
+import org.apache.flink.table.planner.plan.utils.AggregateInfoList;
+import org.apache.flink.table.planner.plan.utils.AggregateUtil;
+import org.apache.flink.table.planner.plan.utils.KeySelectorUtil;
+import org.apache.flink.table.planner.plan.utils.OverAggregateUtil;
+import org.apache.flink.table.planner.utils.JavaScalaConversionUtil;
+import org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction;
+import org.apache.flink.table.runtime.keyselector.RowDataKeySelector;
+import org.apache.flink.table.runtime.operators.over.ProcTimeRangeBoundedPrecedingFunction;
+import org.apache.flink.table.runtime.operators.over.ProcTimeRowsBoundedPrecedingFunction;
+import org.apache.flink.table.runtime.operators.over.ProcTimeUnboundedPrecedingFunction;
+import org.apache.flink.table.runtime.operators.over.RowTimeRangeBoundedPrecedingFunction;
+import org.apache.flink.table.runtime.operators.over.RowTimeRangeUnboundedPrecedingFunction;
+import org.apache.flink.table.runtime.operators.over.RowTimeRowsBoundedPrecedingFunction;
+import org.apache.flink.table.runtime.operators.over.RowTimeRowsUnboundedPrecedingFunction;
+import org.apache.flink.table.runtime.types.LogicalTypeDataTypeConverter;
+import org.apache.flink.table.runtime.typeutils.InternalTypeInfo;
+import org.apache.flink.table.types.logical.LogicalType;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.table.types.logical.TimestampKind;
+import org.apache.flink.table.types.logical.TimestampType;
+
+import org.apache.calcite.rel.core.AggregateCall;
+import org.apache.calcite.rex.RexLiteral;
+import org.apache.calcite.tools.RelBuilder;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.math.BigDecimal;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.List;
+import java.util.stream.IntStream;
+
+/** Stream {@link ExecNode} for time-based over operator. */
+public class StreamExecOverAggregate extends ExecNodeBase<RowData>
+        implements StreamExecNode<RowData> {
+    private static final Logger LOG = LoggerFactory.getLogger(StreamExecOverAggregate.class);
+
+    private final OverSpec overSpec;
+
+    public StreamExecOverAggregate(
+            OverSpec overSpec, ExecEdge inputEdge, RowType outputType, String description) {
+        super(Collections.singletonList(inputEdge), outputType, description);
+        this.overSpec = overSpec;
+    }
+
+    @SuppressWarnings("unchecked")
+    @Override
+    protected Transformation<RowData> translateToPlanInternal(PlannerBase planner) {
+        if (overSpec.getGroups().size() > 1) {
+            throw new TableException("All aggregates must be computed on the same window.");
+        }
+
+        final OverSpec.GroupSpec group = overSpec.getGroups().get(0);
+        final int[] orderKeys = group.getSort().getFieldIndices();
+        final boolean[] isAscendingOrders = group.getSort().getAscendingOrders();
+        if (orderKeys.length != 1 || isAscendingOrders.length != 1) {
+            throw new TableException("The window can only be ordered by a single time column.");
+        }
+
+        if (!isAscendingOrders[0]) {
+            throw new TableException("The window can only be ordered in ASCENDING mode.");
+        }
+
+        final int[] partitionKeys = overSpec.getPartition().getFieldIndices();
+        final TableConfig tableConfig = planner.getTableConfig();
+        if (partitionKeys.length > 0 && tableConfig.getMinIdleStateRetentionTime() < 0) {
+            LOG.warn(
+                    "No state retention interval configured for a query which accumulates state. "
+                            + "Please provide a query configuration with valid retention interval to prevent "
+                            + "excessive state size. You may specify a retention time of 0 to not clean up the state.");
+        }
+
+        final ExecNode<RowData> inputNode = (ExecNode<RowData>) getInputNodes().get(0);
+        final Transformation<RowData> inputTransform = inputNode.translateToPlan(planner);
+        final RowType inputRowType = (RowType) inputNode.getOutputType();
+
+        final int orderKey = orderKeys[0];
+        final LogicalType orderKeyType = inputRowType.getFields().get(orderKey).getType();
+        // check time field && identify window rowtime attribute
+        final int rowTimeIdx;
+        if (orderKeyType instanceof TimestampType
+                && ((TimestampType) orderKeyType).getKind() == TimestampKind.ROWTIME) {
+            rowTimeIdx = orderKey;
+        } else if (orderKeyType instanceof TimestampType
+                && ((TimestampType) orderKeyType).getKind() == TimestampKind.PROCTIME) {
+            rowTimeIdx = -1;
+        } else {
+            throw new TableException(
+                    "OVER windows' ordering in stream mode must be defined on a time attribute.");
+        }
+
+        final List<RexLiteral> constants = overSpec.getConstants();
+        final List<String> fieldNames = new ArrayList<>(inputRowType.getFieldNames());
+        final List<LogicalType> fieldTypes = new ArrayList<>(inputRowType.getChildren());
+        IntStream.range(0, constants.size()).forEach(i -> fieldNames.add("TMP" + i));
+        for (int i = 0; i < constants.size(); ++i) {
+            fieldNames.add("TMP" + i);
+            fieldTypes.add(FlinkTypeFactory.toLogicalType(constants.get(i).getType()));
+        }
+
+        final RowType aggInputRowType =
+                RowType.of(
+                        fieldTypes.toArray(new LogicalType[0]), fieldNames.toArray(new String[0]));

Review comment:
       I think it's easy for debug




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