Type Members

1.  case class ArrayType(elementType: DataType, containsNull: Boolean) extends DataType with Product with Serializable

   The data type for collections of multiple values.

   The data type for collections of multiple values. Internally these are represented as columns that contain a scala.collection.Seq.

   Please use DataTypes.createArrayType() to create a specific instance.

   An ArrayType object comprises two fields, elementType: DataType and containsNull: Boolean. The field of elementType is used to specify the type of array elements. The field of containsNull is used to specify if the array has null values.

   elementType

   The data type of values.

   containsNull

   Indicates if values have null values

   Annotations

   @Stable()

   Since

   1.3.0

2.  abstract class AtomicType extends DataType

   An internal type used to represent everything that is not null, UDTs, arrays, structs, and maps.

   An internal type used to represent everything that is not null, UDTs, arrays, structs, and maps.

   Attributes

   protected[sql]

3.  class BinaryType extends AtomicType

   The data type representing Array[Byte] values.

   The data type representing Array[Byte] values. Please use the singleton DataTypes.BinaryType.

   Annotations

   @Stable()

4.  class BooleanType extends AtomicType

   The data type representing Boolean values.

   The data type representing Boolean values. Please use the singleton DataTypes.BooleanType.

   Annotations

   @Stable()

   Since

   1.3.0

5.  class ByteType extends IntegralType

   The data type representing Byte values.

   The data type representing Byte values. Please use the singleton DataTypes.ByteType.

   Annotations

   @Stable()

   Since

   1.3.0

6.  class CalendarIntervalType extends DataType

   The data type representing calendar intervals.

   The data type representing calendar intervals. The calendar interval is stored internally in three components: an integer value representing the number of months in this interval, an integer value representing the number of days in this interval, a long value representing the number of microseconds in this interval.

   Please use the singleton DataTypes.CalendarIntervalType to refer the type.

   Annotations

   @Stable()

   Since

   1.5.0

   Note

   Calendar intervals support comparison and ordering since 3.0.0.

7.  case class CharType(length: Int) extends HiveStringType with Product with Serializable

   Hive char type.

   Hive char type. Similar to other HiveStringType's, these datatypes should only used for parsing, and should NOT be used anywhere else. Any instance of these data types should be replaced by a StringType before analysis.

8.  abstract class DataType extends AbstractDataType

   The base type of all Spark SQL data types.

   The base type of all Spark SQL data types.

   Annotations

   @Stable() @JsonSerialize() @JsonDeserialize()

   Since

   1.3.0

9.  class DataTypes extends AnyRef

   To get/create specific data type, users should use singleton objects and factory methods provided by this class.

   To get/create specific data type, users should use singleton objects and factory methods provided by this class.

   Since

   1.3.0

10.  class DateType extends AtomicType

    The date type represents a valid date in the proleptic Gregorian calendar.

    The date type represents a valid date in the proleptic Gregorian calendar. Valid range is [0001-01-01, 9999-12-31].

    Please use the singleton DataTypes.DateType to refer the type.

    Annotations

    @Stable()

    Since

    1.3.0

11.  final class Decimal extends Ordered[Decimal] with Serializable

    A mutable implementation of BigDecimal that can hold a Long if values are small enough.

    A mutable implementation of BigDecimal that can hold a Long if values are small enough.

    The semantics of the fields are as follows: - _precision and _scale represent the SQL precision and scale we are looking for - If decimalVal is set, it represents the whole decimal value - Otherwise, the decimal value is longVal / (10 ** _scale)

    Note, for values between -1.0 and 1.0, precision digits are only counted after dot.

    Annotations

    @Unstable()

12.  case class DecimalType(precision: Int, scale: Int) extends FractionalType with Product with Serializable

    The data type representing java.math.BigDecimal values.

    The data type representing java.math.BigDecimal values. A Decimal that must have fixed precision (the maximum number of digits) and scale (the number of digits on right side of dot).

    The precision can be up to 38, scale can also be up to 38 (less or equal to precision).

    The default precision and scale is (10, 0).

    Please use DataTypes.createDecimalType() to create a specific instance.

    Annotations

    @Stable()

    Since

    1.3.0

13.  class DoubleType extends FractionalType

    The data type representing Double values.

    The data type representing Double values. Please use the singleton DataTypes.DoubleType.

    Annotations

    @Stable()

    Since

    1.3.0

14.  class FloatType extends FractionalType

    The data type representing Float values.

    The data type representing Float values. Please use the singleton DataTypes.FloatType.

    Annotations

    @Stable()

    Since

    1.3.0

15.  sealed abstract class HiveStringType extends AtomicType

    A hive string type for compatibility.

    A hive string type for compatibility. These datatypes should only used for parsing, and should NOT be used anywhere else. Any instance of these data types should be replaced by a StringType before analysis.

16.  class IntegerType extends IntegralType

    The data type representing Int values.

    The data type representing Int values. Please use the singleton DataTypes.IntegerType.

    Annotations

    @Stable()

    Since

    1.3.0

17.  class LongType extends IntegralType

    The data type representing Long values.

    The data type representing Long values. Please use the singleton DataTypes.LongType.

    Annotations

    @Stable()

    Since

    1.3.0

18.  case class MapType(keyType: DataType, valueType: DataType, valueContainsNull: Boolean) extends DataType with Product with Serializable

    The data type for Maps.

    The data type for Maps. Keys in a map are not allowed to have null values.

    Please use DataTypes.createMapType() to create a specific instance.

    keyType

    The data type of map keys.

    valueType

    The data type of map values.

    valueContainsNull

    Indicates if map values have null values.

    Annotations

    @Stable()

19.  sealed class Metadata extends Serializable

    Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean, Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and Array[Metadata].

    Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean, Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and Array[Metadata]. JSON is used for serialization.

    The default constructor is private. User should use either MetadataBuilder or Metadata.fromJson() to create Metadata instances.

    Annotations

    @Stable()

    Since

    1.3.0

20.  class MetadataBuilder extends AnyRef

    Builder for Metadata.

    Builder for Metadata. If there is a key collision, the latter will overwrite the former.

    Annotations

    @Stable()

    Since

    1.3.0

21.  class NullType extends DataType

    The data type representing NULL values.

    The data type representing NULL values. Please use the singleton DataTypes.NullType.

    Annotations

    @Stable()

    Since

    1.3.0

22.  abstract class NumericType extends AtomicType

    Numeric data types.

    Numeric data types.

    Annotations

    @Stable()

    Since

    1.3.0

23.  case class ObjectType(cls: Class[_]) extends DataType with Product with Serializable

    Represents a JVM object that is passing through Spark SQL expression evaluation.

24.  class SQLUserDefinedType extends Annotation with Annotation with ClassfileAnnotation
25.  class ShortType extends IntegralType

    The data type representing Short values.

    The data type representing Short values. Please use the singleton DataTypes.ShortType.

    Annotations

    @Stable()

    Since

    1.3.0

26.  class StringType extends AtomicType

    The data type representing String values.

    The data type representing String values. Please use the singleton DataTypes.StringType.

    Annotations

    @Stable()

    Since

    1.3.0

27.  case class StructField(name: String, dataType: DataType, nullable: Boolean = true, metadata: Metadata = Metadata.empty) extends Product with Serializable

    A field inside a StructType.

    A field inside a StructType.

    name

    The name of this field.

    dataType

    The data type of this field.

    nullable

    Indicates if values of this field can be null values.

    metadata

    The metadata of this field. The metadata should be preserved during transformation if the content of the column is not modified, e.g, in selection.

    Annotations

    @Stable()

    Since

    1.3.0

28.  case class StructType(fields: Array[StructField]) extends DataType with Seq[StructField] with Product with Serializable

    A StructType object can be constructed by

    A StructType object can be constructed by

    StructType(fields: Seq[StructField])

    For a StructType object, one or multiple StructFields can be extracted by names. If multiple StructFields are extracted, a StructType object will be returned. If a provided name does not have a matching field, it will be ignored. For the case of extracting a single StructField, a null will be returned.

    Scala Example:

    import org.apache.spark.sql._
    import org.apache.spark.sql.types._
    
    val struct =
      StructType(
        StructField("a", IntegerType, true) ::
        StructField("b", LongType, false) ::
        StructField("c", BooleanType, false) :: Nil)
    
    // Extract a single StructField.
    val singleField = struct("b")
    // singleField: StructField = StructField(b,LongType,false)
    
    // If this struct does not have a field called "d", it throws an exception.
    struct("d")
    // java.lang.IllegalArgumentException: d does not exist.
    //   ...
    
    // Extract multiple StructFields. Field names are provided in a set.
    // A StructType object will be returned.
    val twoFields = struct(Set("b", "c"))
    // twoFields: StructType =
    //   StructType(StructField(b,LongType,false), StructField(c,BooleanType,false))
    
    // Any names without matching fields will throw an exception.
    // For the case shown below, an exception is thrown due to "d".
    struct(Set("b", "c", "d"))
    // java.lang.IllegalArgumentException: d does not exist.
    //    ...

    A org.apache.spark.sql.Row object is used as a value of the StructType.

    Scala Example:

    import org.apache.spark.sql._
    import org.apache.spark.sql.types._
    
    val innerStruct =
      StructType(
        StructField("f1", IntegerType, true) ::
        StructField("f2", LongType, false) ::
        StructField("f3", BooleanType, false) :: Nil)
    
    val struct = StructType(
      StructField("a", innerStruct, true) :: Nil)
    
    // Create a Row with the schema defined by struct
    val row = Row(Row(1, 2, true))

    Annotations

    @Stable()

    Since

    1.3.0

29.  class TimestampType extends AtomicType

    The timestamp type represents a time instant in microsecond precision.

    The timestamp type represents a time instant in microsecond precision. Valid range is [0001-01-01T00:00:00.000000Z, 9999-12-31T23:59:59.999999Z] where the left/right-bound is a date and time of the proleptic Gregorian calendar in UTC+00:00.

    Please use the singleton DataTypes.TimestampType to refer the type.

    Annotations

    @Stable()

    Since

    1.3.0

30.  case class VarcharType(length: Int) extends HiveStringType with Product with Serializable

    Hive varchar type.

    Hive varchar type. Similar to other HiveStringType's, these datatypes should only used for parsing, and should NOT be used anywhere else. Any instance of these data types should be replaced by a StringType before analysis.