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From rednaxelafx <...@git.apache.org>
Subject [GitHub] spark pull request #22355: [SPARK-25358][SQL] MutableProjection supports fal...
Date Tue, 11 Sep 2018 02:07:52 GMT
Github user rednaxelafx commented on a diff in the pull request:

    https://github.com/apache/spark/pull/22355#discussion_r216526434
  
    --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/InterpretedMutableProjection.scala
---
    @@ -0,0 +1,83 @@
    +/*
    + * 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.spark.sql.catalyst.expressions
    +
    +import org.apache.spark.sql.catalyst.InternalRow
    +
    +
    +/**
    + * A [[MutableProjection]] that is calculated by calling `eval` on each of the specified
    + * expressions.
    + *
    + * @param expressions a sequence of expressions that determine the value of each column
of the
    + *                    output row.
    + */
    +class InterpretedMutableProjection(expressions: Seq[Expression]) extends MutableProjection
{
    +  def this(expressions: Seq[Expression], inputSchema: Seq[Attribute]) =
    +    this(expressions.map(BindReferences.bindReference(_, inputSchema)))
    +
    +  private[this] val buffer = new Array[Any](expressions.size)
    +
    +  override def initialize(partitionIndex: Int): Unit = {
    +    expressions.foreach(_.foreach {
    +      case n: Nondeterministic => n.initialize(partitionIndex)
    +      case _ =>
    +    })
    +  }
    +
    +  private[this] val exprArray = expressions.toArray
    +  private[this] var mutableRow: InternalRow = new GenericInternalRow(exprArray.length)
    +  def currentValue: InternalRow = mutableRow
    +
    +  override def target(row: InternalRow): MutableProjection = {
    +    mutableRow = row
    +    this
    +  }
    +
    +  override def apply(input: InternalRow): InternalRow = {
    +    var i = 0
    +    while (i < exprArray.length) {
    +      // Store the result into buffer first, to make the projection atomic (needed by
aggregation)
    +      buffer(i) = exprArray(i).eval(input)
    +      i += 1
    +    }
    +    i = 0
    +    while (i < exprArray.length) {
    +      mutableRow(i) = buffer(i)
    +      i += 1
    +    }
    +    mutableRow
    +  }
    +}
    --- End diff --
    
    +1 on the check for `NoOp`s.


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