[
https://issues.apache.org/jira/browse/BEAM-9363?focusedWorklogId=432249&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-432249
]
ASF GitHub Bot logged work on BEAM-9363:
----------------------------------------
Author: ASF GitHub Bot
Created on: 08/May/20 20:19
Start Date: 08/May/20 20:19
Worklog Time Spent: 10m
Work Description: amaliujia commented on a change in pull request #10946:
URL: https://github.com/apache/beam/pull/10946#discussion_r422353370
##########
File path:
sdks/java/extensions/sql/src/main/java/org/apache/beam/sdk/extensions/sql/impl/rel/BeamTableFunctionScanRel.java
##########
@@ -0,0 +1,157 @@
+/*
+ * 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.beam.sdk.extensions.sql.impl.rel;
+
+import static
org.apache.beam.vendor.calcite.v1_20_0.com.google.common.base.Preconditions.checkArgument;
+
+import java.lang.reflect.Type;
+import java.util.List;
+import java.util.Set;
+import org.apache.beam.sdk.extensions.sql.impl.planner.BeamCostModel;
+import org.apache.beam.sdk.extensions.sql.impl.planner.NodeStats;
+import org.apache.beam.sdk.extensions.sql.impl.utils.CalciteUtils;
+import org.apache.beam.sdk.schemas.Schema;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.transforms.windowing.FixedWindows;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.PCollectionList;
+import org.apache.beam.sdk.values.Row;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.plan.RelOptCluster;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.plan.RelOptPlanner;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.plan.RelTraitSet;
+import org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rel.RelNode;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rel.core.TableFunctionScan;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rel.metadata.RelColumnMapping;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rel.metadata.RelMetadataQuery;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rel.type.RelDataType;
+import org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rex.RexCall;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rex.RexInputRef;
+import
org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rex.RexLiteral;
+import org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rex.RexNode;
+import org.joda.time.Duration;
+
+public class BeamTableFunctionScanRel extends TableFunctionScan implements
BeamRelNode {
+ public BeamTableFunctionScanRel(
+ RelOptCluster cluster,
+ RelTraitSet traitSet,
+ List<RelNode> inputs,
+ RexNode rexCall,
+ Type elementType,
+ RelDataType rowType,
+ Set<RelColumnMapping> columnMappings) {
+ super(cluster, traitSet, inputs, rexCall, elementType, rowType,
columnMappings);
+ }
+
+ @Override
+ public TableFunctionScan copy(
+ RelTraitSet traitSet,
+ List<RelNode> list,
+ RexNode rexNode,
+ Type type,
+ RelDataType relDataType,
+ Set<RelColumnMapping> set) {
+ return new BeamTableFunctionScanRel(
+ getCluster(), traitSet, list, rexNode, type, relDataType,
columnMappings);
+ }
+
+ @Override
+ public PTransform<PCollectionList<Row>, PCollection<Row>> buildPTransform() {
+ return new Transform();
+ }
+
+ private class Transform extends PTransform<PCollectionList<Row>,
PCollection<Row>> {
+
+ @Override
+ public PCollection<Row> expand(PCollectionList<Row> input) {
+ checkArgument(
+ input.size() == 1,
+ "Wrong number of inputs for %s: %s",
+ BeamTableFunctionScanRel.class.getSimpleName(),
+ input);
+ checkArgument(
+ ((RexCall) getCall()).getOperator().getName().equals("TUMBLE"),
+ "Only support TUMBLE table-valued function");
+ RexCall call = ((RexCall) getCall());
+ RexInputRef wmCol = (RexInputRef) call.getOperands().get(1);
+ PCollection<Row> upstream = input.get(0);
+ Schema outputSchema = CalciteUtils.toSchema(getRowType());
+ return upstream
+ .apply(
+ ParDo.of(
+ new FixedWindowDoFn(
+
FixedWindows.of(durationParameter(call.getOperands().get(2))),
+ wmCol.getIndex(),
+ outputSchema)))
+ .setRowSchema(outputSchema);
+ }
+ }
+
+ private Duration durationParameter(RexNode node) {
+ return Duration.millis(longValue(node));
+ }
+
+ private long longValue(RexNode operand) {
+ if (operand instanceof RexLiteral) {
+ return ((Number) RexLiteral.value(operand)).longValue();
+ } else {
+ throw new IllegalArgumentException(String.format("[%s] is not valid.",
operand));
+ }
+ }
+
+ private static class FixedWindowDoFn extends DoFn<Row, Row> {
+ private int windowFieldIndex;
+ private FixedWindows windowFn;
+ private Schema outputSchema;
+
+ public FixedWindowDoFn(FixedWindows windowFn, int windowFieldIndex, Schema
schema) {
+ this.windowFn = windowFn;
+ this.windowFieldIndex = windowFieldIndex;
+ this.outputSchema = schema;
+ }
+
+ @ProcessElement
+ public void processElement(ProcessContext c) {
+ Row row = c.element();
+ IntervalWindow window =
windowFn.assignWindow(row.getDateTime(windowFieldIndex).toInstant());
+ Row.Builder builder = Row.withSchema(outputSchema);
+ builder.addValues(row.getValues());
+ // TODO: add window_start and window_end;
+ builder.addValue(window.start());
+ builder.addValue(window.end());
+ c.output(builder.build());
+ }
+ }
+
+ @Override
+ public NodeStats estimateNodeStats(RelMetadataQuery mq) {
+ return BeamSqlRelUtils.getNodeStats(getInput(0), mq);
+ }
+
+ @Override
+ public BeamCostModel beamComputeSelfCost(RelOptPlanner planner,
RelMetadataQuery mq) {
+ NodeStats inputEstimates = BeamSqlRelUtils.getNodeStats(getInput(0), mq);
+
+ final double rowSize = getRowType().getFieldCount();
+ final double cpu = inputEstimates.getRowCount() *
inputEstimates.getRowCount() * rowSize;
+ final double cpuRate = inputEstimates.getRate() *
inputEstimates.getWindow() * rowSize;
Review comment:
I believe it is carried over from a class in BeamSQL. Such computation
was a part of a intern project before about SQL cost based optimization.
Let me do some research and see how it should work.
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Issue Time Tracking
-------------------
Worklog Id: (was: 432249)
Time Spent: 4h (was: 3h 50m)
> BeamSQL windowing as TVF
> ------------------------
>
> Key: BEAM-9363
> URL: https://issues.apache.org/jira/browse/BEAM-9363
> Project: Beam
> Issue Type: New Feature
> Components: dsl-sql, dsl-sql-zetasql
> Reporter: Rui Wang
> Assignee: Rui Wang
> Priority: Major
> Time Spent: 4h
> Remaining Estimate: 0h
>
> This Jira tracks the implementation for
> https://s.apache.org/streaming-beam-sql
> TVF is table-valued function, which is a SQL feature that produce a table as
> function's output.
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