spark/src/main/scala/org/apache/druid/spark/v2/reader/DruidInputPartition.scala

/*
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 * 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
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 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
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package org.apache.druid.spark.v2.reader

import org.apache.druid.query.filter.DimFilter
import org.apache.druid.spark.MAPPER
import org.apache.druid.spark.configuration.{Configuration, SerializableHadoopConfiguration}
import org.apache.druid.timeline.DataSegment
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.sources.v2.reader.{InputPartition, InputPartitionReader}
import org.apache.spark.sql.types.StructType

/**
  * Defines a single partition in the dataframe's underlying RDD. This object is generated in the driver and then
  * serialized to the executors where it is responsible for creating the actual ([[InputPartitionReader]]) which
  * does the actual reading.
  */
class DruidInputPartition(
                           segment: DataSegment,
                           schema: StructType,
                           filter: Option[DimFilter],
                           columnTypes: Option[Set[String]],
                           conf: Configuration,
                           useSparkConfForDeepStorage: Boolean,
                           useCompactSketches: Boolean,
                           useDefaultNullHandling: Boolean
                         ) extends InputPartition[InternalRow] {
  // There's probably a better way to do this
  private val session = SparkSession.getActiveSession.get // We're running on the driver, it exists
  private val broadcastConf =
    session.sparkContext.broadcast(
      new SerializableHadoopConfiguration(session.sparkContext.hadoopConfiguration)
    )
  private val serializedSegment: String = MAPPER.writeValueAsString(segment)

  override def createPartitionReader(): InputPartitionReader[InternalRow] = {
    new DruidInputPartitionReader(
      serializedSegment,
      schema,
      filter,
      columnTypes,
      broadcastConf,
      conf,
      useSparkConfForDeepStorage,
      useCompactSketches,
      useDefaultNullHandling
    )
  }
}