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

/*
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 * 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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package org.apache.druid.spark.v2.reader

import org.apache.druid.java.util.common.StringUtils
import org.apache.spark.sql.execution.vectorized.Dictionary

/**
  * A Spark "Dictionary" to back single-valued dimension vectors (e.g. columns of strings).
  *
  * @param lookups A map of id to String to back this Dictionary with.
  */
class SingleValueDimensionDictionary(val lookups: Map[Int, String]) extends Dictionary {
  override def decodeToInt(id: Int): Int = {
    throw new UnsupportedOperationException("SingleValueDimensionDictionary encoding does not support ints!")
  }

  override def decodeToLong(id: Int): Long = {
    throw new UnsupportedOperationException("SingleValueDimensionDictionary encoding does not support longs!")
  }

  override def decodeToFloat(id: Int): Float = {
    throw new UnsupportedOperationException("SingleValueDimensionDictionary encoding does not support floats!")
  }

  override def decodeToDouble(id: Int): Double = {
    throw new UnsupportedOperationException("SingleValueDimensionDictionary encoding does not support doubles!")
  }

  override def decodeToBinary(id: Int): Array[Byte] = {
    // TODO: Figure out if we want toUtf8Nullable or toUtf8WithNullToEmpty. (This is likely related to adding support
    //  for Druid's two null-handling modes)
    StringUtils.toUtf8Nullable(lookups(id))
  }
}