ramitg254 commented on code in PR #6703: URL: https://github.com/apache/hive/pull/6703#discussion_r3843409346
########## ql/src/java/org/apache/hadoop/hive/ql/exec/vector/ptf/VectorPTFEvaluatorCumeDist.java: ########## @@ -0,0 +1,113 @@ +/* + * 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.hadoop.hive.ql.exec.vector.ptf; + +import java.util.ArrayDeque; +import java.util.Deque; + +import org.apache.hadoop.hive.ql.exec.vector.ColumnVector.Type; +import org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector; +import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch; +import org.apache.hadoop.hive.ql.metadata.HiveException; +import org.apache.hadoop.hive.ql.plan.ptf.WindowFrameDef; + +/** + * This class evaluates cume_dist() for a PTF partition. + * Unlike rank(), cume_dist needs the total partition row count, group row + * count, so it cannot produce a group's + * result while the group is still streaming in. It is therefore a peer group + * aggregated streaming evaluator + * (see {@link VectorPTFEvaluatorBase#isGroupAggregatedStreamingEvaluator()}): a + * first pass over the + * buffered group sizes precomputes each peer group's value via + * {@link #addStreamingGroupResult(int)} + * (after {@link #setPartitionSize(int)} has been called), and the regular + * streaming pass then just + * populates the precomputed values into the output column. + */ +public class VectorPTFEvaluatorCumeDist extends VectorPTFEvaluatorBase { + + /** + * Per peer group cume_dist values computed in the first pass and consumed, in + * order, by the + * streaming pass (one value is popped when a group's last batch is processed). + */ + private final Deque<Double> groupResults = new ArrayDeque<>(); + private int rowPosition; + + public VectorPTFEvaluatorCumeDist(WindowFrameDef windowFrameDef, int outputColumnNum) { + super(windowFrameDef, outputColumnNum); + resetEvaluator(); + } + + @Override + public boolean needPartitionSize() { + return true; + } + + @Override + public boolean isGroupAggregatedStreamingEvaluator() { + return true; + } + + @Override + public void addStreamingGroupResult(int groupRowCount) throws HiveException { + if (partitionSize <= 0) { + throw new HiveException("Partition size must be set before precomputing cume_dist"); + } + rowPosition += groupRowCount; + groupResults.addLast(((double) rowPosition) / partitionSize); + } + + @Override + public void evaluateGroupBatch(VectorizedRowBatch batch) throws HiveException { + Double result = groupResults.peekFirst(); + if (result == null) { + throw new HiveException("cume_dist streaming result is not available for the current group"); + } + DoubleColumnVector outputColVector = (DoubleColumnVector) batch.cols[outputColumnNum]; + outputColVector.isRepeating = true; + outputColVector.noNulls = true; + outputColVector.isNull[0] = false; + outputColVector.vector[0] = result; + } + + @Override + public void doLastBatchWork() { + groupResults.pollFirst(); + } + + @Override + public boolean streamsResult() { + return true; + } Review Comment: yes It is not purely streaming, but does streams result in the outputcolumn vector for every row based on the precomputation we are doing rather than the aggregation functions like avg, sum etc. which just compute their results over data columns and not concerned with output column vector: https://github.com/apache/hive/blob/c56c3f5924c8fba851318087766ba380ed836d06/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/ptf/VectorPTFGroupBatches.java#L443 so we need to bypass that and directly populate the results in https://github.com/apache/hive/blob/c56c3f5924c8fba851318087766ba380ed836d06/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/ptf/VectorPTFOperator.java#L639 So in general we are does streaming results but we can't use that optimization you mentioned because it is not possible to do it on the fly and rather we need to buffer batches so that we can have parition size and other precomputations. I think we can keep it as true -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
