def apply()

in client-spark/spark-3-columnar-shuffle/src/main/scala/org/apache/spark/sql/execution/columnar/CelebornColumnBuilder.scala [334:369]

• 35 lines of code
• 15 McCabe index (conditional complexity)

  def apply(
      dataType: DataType,
      rowCnt: Int,
      columnName: String,
      encodingEnabled: Boolean,
      encoder: Encoder[_ <: AtomicType]): CelebornColumnBuilder = {
    val builder: CelebornColumnBuilder = dataType match {
      case ByteType => new CelebornByteColumnBuilder
      case BooleanType => new CelebornBooleanColumnBuilder
      case ShortType => new CelebornShortColumnBuilder
      case IntegerType =>
        val builder = new CelebornIntColumnBuilder
        builder.init(encoder.asInstanceOf[Encoder[IntegerType.type]])
        builder
      case LongType =>
        val builder = new CelebornLongColumnBuilder
        builder.init(encoder.asInstanceOf[Encoder[LongType.type]])
        builder
      case FloatType => new CelebornFloatColumnBuilder
      case DoubleType => new CelebornDoubleColumnBuilder
      case StringType =>
        val builder = new CelebornStringColumnBuilder
        builder.init(encoder.asInstanceOf[Encoder[StringType.type]])
        builder
      case dt: DecimalType if dt.precision <= Decimal.MAX_INT_DIGITS =>
        new CelebornCompactMiniDecimalColumnBuilder(dt)
      case dt: DecimalType if dt.precision <= Decimal.MAX_LONG_DIGITS =>
        new CelebornCompactDecimalColumnBuilder(dt)
      case dt: DecimalType => new CelebornDecimalColumnBuilder(dt)
      case other =>
        throw new Exception(s"Unsupported type: $other")
    }

    builder.initialize(rowCnt, columnName, encodingEnabled)
    builder
  }