spark InterpretedSafeProjection 源码

spark InterpretedSafeProjection 代码

文件路径：/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/InterpretedSafeProjection.scala

/*
 * 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
import org.apache.spark.sql.catalyst.expressions.aggregate.NoOp
import org.apache.spark.sql.catalyst.util.{ArrayBasedMapData, ArrayData, GenericArrayData, MapData}
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._


/**
 * An interpreted version of a safe projection.
 *
 * @param expressions that produces the resulting fields. These expressions must be bound
 *                    to a schema.
 */
class InterpretedSafeProjection(expressions: Seq[Expression]) extends Projection {

  private[this] val subExprEliminationEnabled = SQLConf.get.subexpressionEliminationEnabled
  private[this] lazy val runtime =
    new SubExprEvaluationRuntime(SQLConf.get.subexpressionEliminationCacheMaxEntries)
  private[this] val exprs = if (subExprEliminationEnabled) {
    runtime.proxyExpressions(expressions)
  } else {
    expressions
  }

  private[this] val mutableRow = new SpecificInternalRow(expressions.map(_.dataType))

  private[this] val exprsWithWriters = expressions.zipWithIndex.filter {
    case (NoOp, _) => false
    case _ => true
  }.map { case (e, i) =>
    val converter = generateSafeValueConverter(e.dataType)
    val writer = InternalRow.getWriter(i, e.dataType)
    val f = if (!e.nullable) {
      (v: Any) => writer(mutableRow, converter(v))
    } else {
      (v: Any) => {
        if (v == null) {
          mutableRow.setNullAt(i)
        } else {
          writer(mutableRow, converter(v))
        }
      }
    }
    (exprs(i), f)
  }

  private def generateSafeValueConverter(dt: DataType): Any => Any = dt match {
    case ArrayType(elemType, _) =>
      val elementConverter = generateSafeValueConverter(elemType)
      v => {
        val arrayValue = v.asInstanceOf[ArrayData]
        val result = new Array[Any](arrayValue.numElements())
        arrayValue.foreach(elemType, (i, e) => {
          result(i) = elementConverter(e)
        })
        new GenericArrayData(result)
      }

    case st: StructType =>
      val fieldTypes = st.fields.map(_.dataType)
      val fieldConverters = fieldTypes.map(generateSafeValueConverter)
      v => {
        val row = v.asInstanceOf[InternalRow]
        val ar = new Array[Any](row.numFields)
        var idx = 0
        while (idx < row.numFields) {
          ar(idx) = fieldConverters(idx)(row.get(idx, fieldTypes(idx)))
          idx += 1
        }
        new GenericInternalRow(ar)
      }

    case MapType(keyType, valueType, _) =>
      lazy val keyConverter = generateSafeValueConverter(keyType)
      lazy val valueConverter = generateSafeValueConverter(valueType)
      v => {
        val mapValue = v.asInstanceOf[MapData]
        val keys = mapValue.keyArray().toArray[Any](keyType)
        val values = mapValue.valueArray().toArray[Any](valueType)
        val convertedKeys = keys.map(keyConverter)
        val convertedValues = values.map(valueConverter)
        ArrayBasedMapData(convertedKeys, convertedValues)
      }

    case udt: UserDefinedType[_] =>
      generateSafeValueConverter(udt.sqlType)

    case _ => identity
  }

  override def apply(row: InternalRow): InternalRow = {
    if (subExprEliminationEnabled) {
      runtime.setInput(row)
    }

    var i = 0
    while (i < exprsWithWriters.length) {
      val (expr, writer) = exprsWithWriters(i)
      writer(expr.eval(row))
      i += 1
    }
    mutableRow
  }
}

/**
 * Helper functions for creating an [[InterpretedSafeProjection]].
 */
object InterpretedSafeProjection {

  /**
   * Returns an [[SafeProjection]] for given sequence of bound Expressions.
   */
  def createProjection(exprs: Seq[Expression]): Projection = {
    // We need to make sure that we do not reuse stateful expressions.
    val cleanedExpressions = exprs.map(_.transform {
      case s: Stateful => s.freshCopy()
    })
    new InterpretedSafeProjection(cleanedExpressions)
  }
}

相关信息

spark 源码目录

相关文章

spark AliasHelper 源码

spark ApplyFunctionExpression 源码

spark AttributeSet 源码

spark BloomFilterMightContain 源码

spark BoundAttribute 源码

spark CallMethodViaReflection 源码

spark Cast 源码

spark CodeGeneratorWithInterpretedFallback 源码

spark DynamicPruning 源码

spark EquivalentExpressions 源码