
org.apache.spark.sql.util.ArrowUtils.scala Maven / Gradle / Ivy
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* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.spark.sql.util
import scala.collection.JavaConverters._
import org.apache.arrow.memory.RootAllocator
import org.apache.arrow.vector.complex.MapVector
import org.apache.arrow.vector.types.{DateUnit, FloatingPointPrecision, IntervalUnit, TimeUnit}
import org.apache.arrow.vector.types.pojo.{ArrowType, Field, FieldType, Schema}
import org.apache.spark.sql.errors.QueryExecutionErrors
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._
private[sql] object ArrowUtils {
val rootAllocator = new RootAllocator(Long.MaxValue)
// todo: support more types.
/** Maps data type from Spark to Arrow. NOTE: timeZoneId required for TimestampTypes */
def toArrowType(dt: DataType, timeZoneId: String): ArrowType = dt match {
case BooleanType => ArrowType.Bool.INSTANCE
case ByteType => new ArrowType.Int(8, true)
case ShortType => new ArrowType.Int(8 * 2, true)
case IntegerType => new ArrowType.Int(8 * 4, true)
case LongType => new ArrowType.Int(8 * 8, true)
case FloatType => new ArrowType.FloatingPoint(FloatingPointPrecision.SINGLE)
case DoubleType => new ArrowType.FloatingPoint(FloatingPointPrecision.DOUBLE)
case StringType => ArrowType.Utf8.INSTANCE
case BinaryType => ArrowType.Binary.INSTANCE
case DecimalType.Fixed(precision, scale) => new ArrowType.Decimal(precision, scale)
case DateType => new ArrowType.Date(DateUnit.DAY)
case TimestampType if timeZoneId == null =>
throw new IllegalStateException("Missing timezoneId where it is mandatory.")
case TimestampType => new ArrowType.Timestamp(TimeUnit.MICROSECOND, timeZoneId)
case TimestampNTZType =>
new ArrowType.Timestamp(TimeUnit.MICROSECOND, null)
case NullType => ArrowType.Null.INSTANCE
case _: YearMonthIntervalType => new ArrowType.Interval(IntervalUnit.YEAR_MONTH)
case _: DayTimeIntervalType => new ArrowType.Duration(TimeUnit.MICROSECOND)
case _ =>
throw QueryExecutionErrors.unsupportedDataTypeError(dt.catalogString)
}
def fromArrowType(dt: ArrowType): DataType = dt match {
case ArrowType.Bool.INSTANCE => BooleanType
case int: ArrowType.Int if int.getIsSigned && int.getBitWidth == 8 => ByteType
case int: ArrowType.Int if int.getIsSigned && int.getBitWidth == 8 * 2 => ShortType
case int: ArrowType.Int if int.getIsSigned && int.getBitWidth == 8 * 4 => IntegerType
case int: ArrowType.Int if int.getIsSigned && int.getBitWidth == 8 * 8 => LongType
case float: ArrowType.FloatingPoint
if float.getPrecision() == FloatingPointPrecision.SINGLE => FloatType
case float: ArrowType.FloatingPoint
if float.getPrecision() == FloatingPointPrecision.DOUBLE => DoubleType
case ArrowType.Utf8.INSTANCE => StringType
case ArrowType.Binary.INSTANCE => BinaryType
case d: ArrowType.Decimal => DecimalType(d.getPrecision, d.getScale)
case date: ArrowType.Date if date.getUnit == DateUnit.DAY => DateType
case ts: ArrowType.Timestamp
if ts.getUnit == TimeUnit.MICROSECOND && ts.getTimezone == null => TimestampNTZType
case ts: ArrowType.Timestamp if ts.getUnit == TimeUnit.MICROSECOND => TimestampType
case ArrowType.Null.INSTANCE => NullType
case yi: ArrowType.Interval if yi.getUnit == IntervalUnit.YEAR_MONTH => YearMonthIntervalType()
case di: ArrowType.Duration if di.getUnit == TimeUnit.MICROSECOND => DayTimeIntervalType()
case _ => throw QueryExecutionErrors.unsupportedDataTypeError(dt.toString)
}
/** Maps field from Spark to Arrow. NOTE: timeZoneId required for TimestampType */
def toArrowField(
name: String, dt: DataType, nullable: Boolean, timeZoneId: String): Field = {
dt match {
case ArrayType(elementType, containsNull) =>
val fieldType = new FieldType(nullable, ArrowType.List.INSTANCE, null)
new Field(name, fieldType,
Seq(toArrowField("element", elementType, containsNull, timeZoneId)).asJava)
case StructType(fields) =>
val fieldType = new FieldType(nullable, ArrowType.Struct.INSTANCE, null)
new Field(name, fieldType,
fields.map { field =>
toArrowField(field.name, field.dataType, field.nullable, timeZoneId)
}.toSeq.asJava)
case MapType(keyType, valueType, valueContainsNull) =>
val mapType = new FieldType(nullable, new ArrowType.Map(false), null)
// Note: Map Type struct can not be null, Struct Type key field can not be null
new Field(name, mapType,
Seq(toArrowField(MapVector.DATA_VECTOR_NAME,
new StructType()
.add(MapVector.KEY_NAME, keyType, nullable = false)
.add(MapVector.VALUE_NAME, valueType, nullable = valueContainsNull),
nullable = false,
timeZoneId)).asJava)
case dataType =>
val fieldType = new FieldType(nullable, toArrowType(dataType, timeZoneId), null)
new Field(name, fieldType, Seq.empty[Field].asJava)
}
}
def fromArrowField(field: Field): DataType = {
field.getType match {
case _: ArrowType.Map =>
val elementField = field.getChildren.get(0)
val keyType = fromArrowField(elementField.getChildren.get(0))
val valueType = fromArrowField(elementField.getChildren.get(1))
MapType(keyType, valueType, elementField.getChildren.get(1).isNullable)
case ArrowType.List.INSTANCE =>
val elementField = field.getChildren().get(0)
val elementType = fromArrowField(elementField)
ArrayType(elementType, containsNull = elementField.isNullable)
case ArrowType.Struct.INSTANCE =>
val fields = field.getChildren().asScala.map { child =>
val dt = fromArrowField(child)
StructField(child.getName, dt, child.isNullable)
}
StructType(fields.toSeq)
case arrowType => fromArrowType(arrowType)
}
}
/** Maps schema from Spark to Arrow. NOTE: timeZoneId required for TimestampType in StructType */
def toArrowSchema(schema: StructType, timeZoneId: String): Schema = {
new Schema(schema.map { field =>
toArrowField(field.name, field.dataType, field.nullable, timeZoneId)
}.asJava)
}
def fromArrowSchema(schema: Schema): StructType = {
StructType(schema.getFields.asScala.map { field =>
val dt = fromArrowField(field)
StructField(field.getName, dt, field.isNullable)
}.toSeq)
}
/** Return Map with conf settings to be used in ArrowPythonRunner */
def getPythonRunnerConfMap(conf: SQLConf): Map[String, String] = {
val timeZoneConf = Seq(SQLConf.SESSION_LOCAL_TIMEZONE.key -> conf.sessionLocalTimeZone)
val pandasColsByName = Seq(SQLConf.PANDAS_GROUPED_MAP_ASSIGN_COLUMNS_BY_NAME.key ->
conf.pandasGroupedMapAssignColumnsByName.toString)
val arrowSafeTypeCheck = Seq(SQLConf.PANDAS_ARROW_SAFE_TYPE_CONVERSION.key ->
conf.arrowSafeTypeConversion.toString)
Map(timeZoneConf ++ pandasColsByName ++ arrowSafeTypeCheck: _*)
}
}
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