spark LogicalRelation 源码

spark LogicalRelation 代码

文件路径：/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.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.execution.datasources

import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
import org.apache.spark.sql.catalyst.catalog.CatalogTable
import org.apache.spark.sql.catalyst.expressions.{AttributeMap, AttributeReference}
import org.apache.spark.sql.catalyst.plans.QueryPlan
import org.apache.spark.sql.catalyst.plans.logical.{ExposesMetadataColumns, LeafNode, LogicalPlan, Statistics}
import org.apache.spark.sql.catalyst.util.{truncatedString, CharVarcharUtils}
import org.apache.spark.sql.sources.BaseRelation

/**
 * Used to link a [[BaseRelation]] in to a logical query plan.
 */
case class LogicalRelation(
    relation: BaseRelation,
    output: Seq[AttributeReference],
    catalogTable: Option[CatalogTable],
    override val isStreaming: Boolean)
  extends LeafNode with MultiInstanceRelation with ExposesMetadataColumns {

  // Only care about relation when canonicalizing.
  override def doCanonicalize(): LogicalPlan = copy(
    output = output.map(QueryPlan.normalizeExpressions(_, output)),
    catalogTable = None)

  override def computeStats(): Statistics = {
    catalogTable
      .flatMap(_.stats.map(_.toPlanStats(output, conf.cboEnabled || conf.planStatsEnabled)))
      .getOrElse(Statistics(sizeInBytes = relation.sizeInBytes))
  }

  /** Used to lookup original attribute capitalization */
  val attributeMap: AttributeMap[AttributeReference] = AttributeMap(output.map(o => (o, o)))

  /**
   * Returns a new instance of this LogicalRelation. According to the semantics of
   * MultiInstanceRelation, this method returns a copy of this object with
   * unique expression ids. We respect the `expectedOutputAttributes` and create
   * new instances of attributes in it.
   */
  override def newInstance(): LogicalRelation = {
    this.copy(output = output.map(_.newInstance()))
  }

  override def refresh(): Unit = relation match {
    case fs: HadoopFsRelation => fs.location.refresh()
    case _ =>  // Do nothing.
  }

  override def simpleString(maxFields: Int): String = {
    s"Relation ${catalogTable.map(_.identifier.unquotedString).getOrElse("")}" +
      s"[${truncatedString(output, ",", maxFields)}] $relation"
  }

  override lazy val metadataOutput: Seq[AttributeReference] = relation match {
    case relation: HadoopFsRelation =>
      val resolve = conf.resolver
      val outputNames = outputSet.map(_.name)
      def isOutputColumn(col: AttributeReference): Boolean = {
        outputNames.exists(name => resolve(col.name, name))
      }
      // filter out the metadata struct column if it has the name conflicting with output columns.
      // if the file has a column "_metadata",
      // then the data column should be returned not the metadata struct column
      Seq(FileFormat.createFileMetadataCol(relation.fileFormat)).filterNot(isOutputColumn)
    case _ => Nil
  }

  override def withMetadataColumns(): LogicalRelation = {
    if (metadataOutput.nonEmpty) {
      this.copy(output = output ++ metadataOutput)
    } else {
      this
    }
  }
}

object LogicalRelation {
  def apply(relation: BaseRelation, isStreaming: Boolean = false): LogicalRelation = {
    // The v1 source may return schema containing char/varchar type. We replace char/varchar
    // with "annotated" string type here as the query engine doesn't support char/varchar yet.
    val schema = CharVarcharUtils.replaceCharVarcharWithStringInSchema(relation.schema)
    LogicalRelation(relation, schema.toAttributes, None, isStreaming)
  }

  def apply(relation: BaseRelation, table: CatalogTable): LogicalRelation = {
    // The v1 source may return schema containing char/varchar type. We replace char/varchar
    // with "annotated" string type here as the query engine doesn't support char/varchar yet.
    val schema = CharVarcharUtils.replaceCharVarcharWithStringInSchema(relation.schema)
    LogicalRelation(relation, schema.toAttributes, Some(table), false)
  }
}

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