def hbaseFieldToScalaType()

in spark/hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/Utils.scala [35:63]

26 lines of code
15 McCabe index (conditional complexity)


  def hbaseFieldToScalaType(f: Field, src: Array[Byte], offset: Int, length: Int): Any = {
    if (f.exeSchema.isDefined) {
      // If we have avro schema defined, use it to get record, and then convert them to catalyst data type
      val m = AvroSerdes.deserialize(src, f.exeSchema.get)
      val n = f.avroToCatalyst.map(_(m))
      n.get
    } else {
      // Fall back to atomic type
      f.dt match {
        case BooleanType => src(offset) != 0
        case ByteType => src(offset)
        case ShortType => Bytes.toShort(src, offset)
        case IntegerType => Bytes.toInt(src, offset)
        case LongType => Bytes.toLong(src, offset)
        case FloatType => Bytes.toFloat(src, offset)
        case DoubleType => Bytes.toDouble(src, offset)
        case DateType => new Date(Bytes.toLong(src, offset))
        case TimestampType => new Timestamp(Bytes.toLong(src, offset))
        case StringType => Bytes.toString(src, offset, length)
        case BinaryType =>
          val newArray = new Array[Byte](length)
          System.arraycopy(src, offset, newArray, 0, length)
          newArray
        case _: DecimalType => Bytes.toBigDecimal(src, offset, length)
        // TODO: SparkSqlSerializer.deserialize[Any](src)
        case _ => throw new Exception(s"unsupported data type ${f.dt}")
      }
    }
  }