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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2020/07/06 03:08:59 UTC
[GitHub] [beam] jhnmora000 commented on a change in pull request #11975: [BEAM-9198] BeamSQL aggregation analytics functionality
jhnmora000 commented on a change in pull request #11975:
URL: https://github.com/apache/beam/pull/11975#discussion_r449962950
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File path: sdks/java/extensions/sql/src/main/java/org/apache/beam/sdk/extensions/sql/impl/rel/BeamWindowRel.java
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@@ -0,0 +1,317 @@
+/*
+ * 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 java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+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.transform.agg.AggregationCombineFnAdapter;
+import org.apache.beam.sdk.extensions.sql.impl.utils.CalciteUtils;
+import org.apache.beam.sdk.schemas.Schema;
+import org.apache.beam.sdk.transforms.Combine;
+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.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.RelFieldCollation;
+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.AggregateCall;
+import org.apache.beam.vendor.calcite.v1_20_0.org.apache.calcite.rel.core.Window;
+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.RexLiteral;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Lists;
+
+public class BeamWindowRel extends Window implements BeamRelNode {
+ public BeamWindowRel(
+ RelOptCluster cluster,
+ RelTraitSet traitSet,
+ RelNode input,
+ List<RexLiteral> constants,
+ RelDataType rowType,
+ List<Group> groups) {
+ super(cluster, traitSet, input, constants, rowType, groups);
+ }
+
+ @Override
+ public PTransform<PCollectionList<Row>, PCollection<Row>> buildPTransform() {
+ Schema outputSchema = CalciteUtils.toSchema(getRowType());
+ final List<FieldAggregation> analyticFields = Lists.newArrayList();
+ this.groups.stream()
+ .forEach(
+ anAnalyticGroup -> {
+ List<Integer> partitionKeysDef = anAnalyticGroup.keys.toList();
+ List<Integer> orderByKeys = Lists.newArrayList();
+ List<Boolean> orderByDirections = Lists.newArrayList();
+ List<Boolean> orderByNullDirections = Lists.newArrayList();
+ anAnalyticGroup.orderKeys.getFieldCollations().stream()
+ .forEach(
+ fc -> {
+ orderByKeys.add(fc.getFieldIndex());
+ orderByDirections.add(
+ fc.direction == RelFieldCollation.Direction.ASCENDING);
+ orderByNullDirections.add(
+ fc.nullDirection == RelFieldCollation.NullDirection.FIRST);
+ });
+ int lowerB = Integer.MAX_VALUE; // Unbounded by default
+ int upperB = Integer.MAX_VALUE; // Unbounded by default
+ if (anAnalyticGroup.lowerBound.isCurrentRow()) {
+ lowerB = 0;
+ } else if (anAnalyticGroup.lowerBound.isPreceding()) {
+ // pending
+ } else if (anAnalyticGroup.lowerBound.isFollowing()) {
+ // pending
+ }
+ if (anAnalyticGroup.upperBound.isCurrentRow()) {
+ upperB = 0;
+ } else if (anAnalyticGroup.upperBound.isPreceding()) {
+ // pending
+ } else if (anAnalyticGroup.upperBound.isFollowing()) {
+ // pending
+ }
+ final int lowerBFinal = lowerB;
+ final int upperBFinal = upperB;
+ List<AggregateCall> aggregateCalls = anAnalyticGroup.getAggregateCalls(this);
+ aggregateCalls.stream()
+ .forEach(
+ anAggCall -> {
+ List<Integer> argList = anAggCall.getArgList();
+ Schema.Field field =
+ CalciteUtils.toField(anAggCall.getName(), anAggCall.getType());
+ Combine.CombineFn combineFn =
+ AggregationCombineFnAdapter.createCombineFn(
+ anAggCall, field, anAggCall.getAggregation().getName());
+ FieldAggregation fieldAggregation =
+ new FieldAggregation(
+ partitionKeysDef,
+ orderByKeys,
+ orderByDirections,
+ orderByNullDirections,
+ lowerBFinal,
+ upperBFinal,
+ anAnalyticGroup.isRows,
+ argList,
+ combineFn,
+ field);
+ analyticFields.add(fieldAggregation);
+ });
+ });
+
+ return new Transform(outputSchema, analyticFields);
+ }
+
+ private static class FieldAggregation implements Serializable {
+
+ private List<Integer> partitionKeys;
+ private List<Integer> orderKeys;
+ private List<Boolean> orderOrientations;
+ private List<Boolean> orderNulls;
+ private int lowerLimit = Integer.MAX_VALUE;
+ private int upperLimit = Integer.MAX_VALUE;
+ private boolean rows = true;
+ private List<Integer> inputFields;
+ private Combine.CombineFn combineFn;
+ private Schema.Field outputField;
+
+ public FieldAggregation(
+ List<Integer> partitionKeys,
+ List<Integer> orderKeys,
+ List<Boolean> orderOrientations,
+ List<Boolean> orderNulls,
+ int lowerLimit,
+ int upperLimit,
+ boolean rows,
+ List<Integer> inputFields,
+ Combine.CombineFn combineFn,
+ Schema.Field outputField) {
+ this.partitionKeys = partitionKeys;
+ this.orderKeys = orderKeys;
+ this.orderOrientations = orderOrientations;
+ this.orderNulls = orderNulls;
+ this.lowerLimit = lowerLimit;
+ this.upperLimit = upperLimit;
+ this.rows = rows;
+ this.inputFields = inputFields;
+ this.combineFn = combineFn;
+ this.outputField = outputField;
+ }
+ }
+
+ @Override
+ public NodeStats estimateNodeStats(RelMetadataQuery mq) {
+ NodeStats inputStat = BeamSqlRelUtils.getNodeStats(this.input, mq);
+ return inputStat;
+ }
+
+ @Override
+ public BeamCostModel beamComputeSelfCost(RelOptPlanner planner, RelMetadataQuery mq) {
+ NodeStats inputStat = BeamSqlRelUtils.getNodeStats(this.input, mq);
+ float multiplier = 1f + 0.125f;
+ return BeamCostModel.FACTORY.makeCost(
+ inputStat.getRowCount() * multiplier, inputStat.getRate() * multiplier);
+ }
+
+ private static class Transform extends PTransform<PCollectionList<Row>, PCollection<Row>> {
+
+ private Schema outputSchema;
+ private List<FieldAggregation> aggFields;
+
+ public Transform(Schema schema, List<FieldAggregation> fieldAgg) {
+ this.outputSchema = schema;
+ this.aggFields = fieldAgg;
+ }
+
+ @Override
+ public PCollection<Row> expand(PCollectionList<Row> input) {
+ PCollection<Row> inputData = input.get(0);
+ Schema inputSchema = inputData.getSchema();
+ for (FieldAggregation af : aggFields) {
+ if (af.partitionKeys.isEmpty()) {
+ // This sections simulate a KV Row
+ // Similar to the output of Group.byFieldIds
+ // When no partitions are specified
+ Schema inputSch = inputData.getSchema();
+ Schema mockKeySchema =
+ Schema.of(Schema.Field.of("mock", Schema.FieldType.STRING.withNullable(true)));
+ Schema simulatedKeyValueSchema =
+ Schema.of(
+ Schema.Field.of("key", Schema.FieldType.row(mockKeySchema)),
+ Schema.Field.of(
+ "value", Schema.FieldType.iterable(Schema.FieldType.row(inputSch))));
+ PCollection<Iterable<Row>> apply =
+ inputData.apply(org.apache.beam.sdk.schemas.transforms.Group.globally());
+ inputData =
+ apply
+ .apply(ParDo.of(uniquePartition(mockKeySchema, simulatedKeyValueSchema)))
+ .setRowSchema(simulatedKeyValueSchema);
+ } else {
+ org.apache.beam.sdk.schemas.transforms.Group.ByFields<Row> myg =
+ org.apache.beam.sdk.schemas.transforms.Group.byFieldIds(af.partitionKeys);
+ inputData = inputData.apply("partitionBy", myg);
Review comment:
I added a comment in the JIRA issue of the project [`issue`](https://issues.apache.org/jira/browse/BEAM-9198?focusedCommentId=17151728&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-17151728)
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