pgaref commented on a change in pull request #1649: URL: https://github.com/apache/hive/pull/1649#discussion_r528797991
########## File path: ql/src/java/org/apache/hadoop/hive/ql/exec/vector/ptf/VectorPTFEvaluatorCountDistinct.java ########## @@ -0,0 +1,112 @@ +/* + * 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.HashSet; +import java.util.Set; + +import org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector; +import org.apache.hadoop.hive.ql.exec.vector.ColumnVector; +import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch; +import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression; +import org.apache.hadoop.hive.ql.metadata.HiveException; +import org.apache.hadoop.hive.ql.plan.ptf.WindowFrameDef; +import org.apache.hive.common.util.Murmur3; + +import com.google.common.base.Preconditions; + +/** + * This class evaluates count(column) for a PTF group where a distinct keyword is applied to the + * partitioning column itself, e.g.: + * + * SELECT + * txt1, + * txt2, + * count(distinct txt1) over(partition by txt1) as n, + * count(distinct txt2) over(partition by txt2) as m + * FROM example; + * + * In this case, the framework is still supposed to ensure sorting + * on the key (let's say txt1 for the first Reducer stage), but the original + * VectorPTFEvaluatorCount is not aware that a distinct keyword was applied + * to the key column. This case would be simple, because such function should + * return 1 every time. However, that's just a corner-case, a real scenario is + * when the partitioning column is not the same. In such cases, a real count + * distinct implementation is needed: + * + * SELECT + * txt1, + * txt2, + * count(distinct txt2) over(partition by txt1) as n, + * count(distinct txt1) over(partition by txt2) as m + * FROM example; + */ +public abstract class VectorPTFEvaluatorCountDistinct extends VectorPTFEvaluatorCount { + + protected Set<Object> uniqueObjects; + + public VectorPTFEvaluatorCountDistinct(WindowFrameDef windowFrameDef, + VectorExpression inputVecExpr, int outputColumnNum) { + super(windowFrameDef, inputVecExpr, outputColumnNum); + resetEvaluator(); + } + + @Override + public void evaluateGroupBatch(VectorizedRowBatch batch) throws HiveException { + + evaluateInputExpr(batch); + + // We do not filter when PTF is in reducer. + Preconditions.checkState(!batch.selectedInUse); + + final int size = batch.size; + if (size == 0) { + return; + } + ColumnVector colVector = batch.cols[inputColumnNum]; + if (colVector.isRepeating) { + if (colVector.noNulls || !colVector.isNull[0]) { + countValue(colVector, 0); + } + } else { + boolean[] batchIsNull = colVector.isNull; + for (int i = 0; i < size; i++) { + if (!batchIsNull[i]) { + countValue(colVector, i); + } + } + } + } + + protected void countValue(ColumnVector colVector, int i) { + Object value = getValue(colVector, i); + if (!uniqueObjects.contains(value)) { + uniqueObjects.add(value); Review comment: We do check if the element is present twice here -- add method already checks if the element is part of the Set so we dont need to call contains. I would just add a comment here instead. ########## File path: ql/src/java/org/apache/hadoop/hive/ql/exec/vector/ptf/VectorPTFEvaluatorCountDistinct.java ########## @@ -0,0 +1,112 @@ +/* + * 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.HashSet; +import java.util.Set; + +import org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector; +import org.apache.hadoop.hive.ql.exec.vector.ColumnVector; +import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch; +import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression; +import org.apache.hadoop.hive.ql.metadata.HiveException; +import org.apache.hadoop.hive.ql.plan.ptf.WindowFrameDef; +import org.apache.hive.common.util.Murmur3; + +import com.google.common.base.Preconditions; + +/** + * This class evaluates count(column) for a PTF group where a distinct keyword is applied to the + * partitioning column itself, e.g.: + * + * SELECT + * txt1, + * txt2, + * count(distinct txt1) over(partition by txt1) as n, + * count(distinct txt2) over(partition by txt2) as m + * FROM example; + * + * In this case, the framework is still supposed to ensure sorting + * on the key (let's say txt1 for the first Reducer stage), but the original + * VectorPTFEvaluatorCount is not aware that a distinct keyword was applied + * to the key column. This case would be simple, because such function should + * return 1 every time. However, that's just a corner-case, a real scenario is + * when the partitioning column is not the same. In such cases, a real count + * distinct implementation is needed: + * + * SELECT + * txt1, + * txt2, + * count(distinct txt2) over(partition by txt1) as n, + * count(distinct txt1) over(partition by txt2) as m + * FROM example; + */ +public abstract class VectorPTFEvaluatorCountDistinct extends VectorPTFEvaluatorCount { + + protected Set<Object> uniqueObjects; + + public VectorPTFEvaluatorCountDistinct(WindowFrameDef windowFrameDef, + VectorExpression inputVecExpr, int outputColumnNum) { + super(windowFrameDef, inputVecExpr, outputColumnNum); + resetEvaluator(); + } + + @Override + public void evaluateGroupBatch(VectorizedRowBatch batch) throws HiveException { + + evaluateInputExpr(batch); + + // We do not filter when PTF is in reducer. + Preconditions.checkState(!batch.selectedInUse); + + final int size = batch.size; + if (size == 0) { + return; + } + ColumnVector colVector = batch.cols[inputColumnNum]; + if (colVector.isRepeating) { + if (colVector.noNulls || !colVector.isNull[0]) { + countValue(colVector, 0); + } + } else { + boolean[] batchIsNull = colVector.isNull; + for (int i = 0; i < size; i++) { + if (!batchIsNull[i]) { + countValue(colVector, i); Review comment: Instead of updating the inherited count variable we could override getLongGroupResult() with uniqueObjects.size ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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