org.apache.hadoop.hive.ql.exec.vector.ptf.VectorPTFEvaluatorCount Maven / Gradle / Ivy

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/*
 * 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 org.apache.hadoop.hive.ql.exec.vector.ColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.ColumnVector.Type;
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 com.google.common.base.Preconditions;

/**
 * This class evaluates count(column) for a PTF group.
 *
 * Count any rows of the group where the input column/expression is non-null.
 */
public class VectorPTFEvaluatorCount extends VectorPTFEvaluatorBase {

  protected long count;

  public VectorPTFEvaluatorCount(WindowFrameDef windowFrameDef, VectorExpression inputVecExpr,
      int outputColumnNum) {
    super(windowFrameDef, inputVecExpr, outputColumnNum);
    resetEvaluator();
  }

  @Override
  public void evaluateGroupBatch(VectorizedRowBatch batch)
      throws HiveException {

    evaluateInputExpr(batch);

    // Count non-null column rows.

    // 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]) {
        count += size;
      }
    } else if (colVector.noNulls) {
      count += size;
    } else {
      boolean[] batchIsNull = colVector.isNull;
      int i = 0;
      while (batchIsNull[i]) {
        if (++i >= size) {
          return;
        }
      }
      long varCount = 1;
      i++;
      for (; i < size; i++) {
        if (!batchIsNull[i]) {
          varCount++;
        }
      }
      count += varCount;
    }
  }

  @Override
  public boolean streamsResult() {
    // We must evaluate whole group before producing a result.
    return false;
  }

  @Override
  public boolean isGroupResultNull() {
    return false;
  }

  @Override
  public Type getResultColumnVectorType() {
    return Type.LONG;
  }

  @Override
  public Object getGroupResult() {
    return count;
  }

  @Override
  public void resetEvaluator() {
    count = 0;
  }
}