private def isGeometryField()

in spark/spark-3.3/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/GeoParquetSchemaConverter.scala [109:200]
72 lines of code
41 McCabe index (conditional complexity)

  private def isGeometryField(fieldName: String): Boolean =
    geoParquetMetaData.columns.contains(fieldName)

  private def convertPrimitiveField(field: PrimitiveType): DataType = {
    val typeName = field.getPrimitiveTypeName
    val originalType = field.getOriginalType

    def typeString =
      if (originalType == null) s"$typeName" else s"$typeName ($originalType)"

    def typeNotSupported() =
      throw new IllegalArgumentException(s"Parquet type not supported: $typeString")

    def typeNotImplemented() =
      throw new IllegalArgumentException(s"Parquet type not yet supported: $typeString")

    def illegalType() =
      throw new IllegalArgumentException(s"Illegal Parquet type: $typeString")

    // When maxPrecision = -1, we skip precision range check, and always respect the precision
    // specified in field.getDecimalMetadata.  This is useful when interpreting decimal types stored
    // as binaries with variable lengths.
    def makeDecimalType(maxPrecision: Int = -1): DecimalType = {
      val precision = field.getDecimalMetadata.getPrecision
      val scale = field.getDecimalMetadata.getScale

      ParquetSchemaConverter.checkConversionRequirement(
        maxPrecision == -1 || 1 <= precision && precision <= maxPrecision,
        s"Invalid decimal precision: $typeName cannot store $precision digits (max $maxPrecision)")

      DecimalType(precision, scale)
    }

    typeName match {
      case BOOLEAN => BooleanType

      case FLOAT => FloatType

      case DOUBLE => DoubleType

      case INT32 =>
        originalType match {
          case INT_8 => ByteType
          case INT_16 => ShortType
          case INT_32 | null => IntegerType
          case DATE => DateType
          case DECIMAL => makeDecimalType(Decimal.MAX_INT_DIGITS)
          case UINT_8 => typeNotSupported()
          case UINT_16 => typeNotSupported()
          case UINT_32 => typeNotSupported()
          case TIME_MILLIS => typeNotImplemented()
          case _ => illegalType()
        }

      case INT64 =>
        originalType match {
          case INT_64 | null => LongType
          case DECIMAL => makeDecimalType(Decimal.MAX_LONG_DIGITS)
          case UINT_64 => typeNotSupported()
          case TIMESTAMP_MICROS => TimestampType
          case TIMESTAMP_MILLIS => TimestampType
          case _ => illegalType()
        }

      case INT96 =>
        ParquetSchemaConverter.checkConversionRequirement(
          assumeInt96IsTimestamp,
          "INT96 is not supported unless it's interpreted as timestamp. " +
            s"Please try to set ${SQLConf.PARQUET_INT96_AS_TIMESTAMP.key} to true.")
        TimestampType

      case BINARY =>
        originalType match {
          case UTF8 | ENUM | JSON => StringType
          case null if isGeometryField(field.getName) => GeometryUDT
          case null if assumeBinaryIsString => StringType
          case null => BinaryType
          case BSON => BinaryType
          case DECIMAL => makeDecimalType()
          case _ => illegalType()
        }

      case FIXED_LEN_BYTE_ARRAY =>
        originalType match {
          case DECIMAL => makeDecimalType(Decimal.maxPrecisionForBytes(field.getTypeLength))
          case INTERVAL => typeNotImplemented()
          case _ => illegalType()
        }

      case _ => illegalType()
    }
  }