DateTimeGroupingElem

outputName

the name of the column in the Druid resultset

druidColumn

the Druid Dimension this is mapped to

formatToApply

in Druid Spark DateTime Expressions handled as TimeFormatExtractionFunctionSpec; this specifies the format to apply on the Druid Dimension.

tzForFormat

see above

pushedExpression

this controls the expression evlaution that happens on return from Druid. So for expression like

to_date(cast(dateCol as DateType))

to_date(cast(DruidValue, DatetYpe))

on the resultset of Druid. This is required because Dates are Ints and Timestamps are Longs in Spark, whereas the value coming out of Druid is an ISO DateTime String.

inputFormat

format to use to parse input value.

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Instance Constructors

new DateTimeGroupingElem(outputName: String, druidColumn: DruidRelationColumn, formatToApply: String, tzForFormat: Option[String], pushedExpression: Expression, inputFormat: Option[String] = scala.None)
outputName
the name of the column in the Druid resultset
druidColumn
the Druid Dimension this is mapped to
formatToApply
in Druid Spark DateTime Expressions handled as TimeFormatExtractionFunctionSpec; this specifies the format to apply on the Druid Dimension.
tzForFormat
see above
pushedExpression
this controls the expression evlaution that happens on return from Druid. So for expression like
```
to_date(cast(dateCol as DateType))
```
```
to_date(cast(DruidValue, DatetYpe))
```
on the resultset of Druid. This is required because Dates are Ints and Timestamps are Longs in Spark, whereas the value coming out of Druid is an ISO DateTime String.
inputFormat
format to use to parse input value.

Value Members

final def !=(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def !=(arg0: Any): Boolean

Definition Classes
Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def ==(arg0: Any): Boolean

Definition Classes
Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val druidColumn: DruidRelationColumn

the Druid Dimension this is mapped to
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
val formatToApply: String

in Druid Spark DateTime Expressions handled as TimeFormatExtractionFunctionSpec; this specifies the format to apply on the Druid Dimension.
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
val inputFormat: Option[String]

format to use to parse input value.
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val outputName: String

the name of the column in the Druid resultset
val pushedExpression: Expression

this controls the expression evlaution that happens on return from Druid.
this controls the expression evlaution that happens on return from Druid. So for expression like
```
to_date(cast(dateCol as DateType))
```
```
to_date(cast(DruidValue, DatetYpe))
```
on the resultset of Druid. This is required because Dates are Ints and Timestamps are Longs in Spark, whereas the value coming out of Druid is an ISO DateTime String.
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val tzForFormat: Option[String]

see above
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

case class DateTimeGroupingElem(outputName: String, druidColumn: DruidRelationColumn, formatToApply: String, tzForFormat: Option[String], pushedExpression: Expression, inputFormat: Option[String] = scala.None) extends Product with Serializable

Instance Constructors

new DateTimeGroupingElem(outputName: String, druidColumn: DruidRelationColumn, formatToApply: String, tzForFormat: Option[String], pushedExpression: Expression, inputFormat: Option[String] = scala.None)

Value Members

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

val druidColumn: DruidRelationColumn

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

val formatToApply: String

final def getClass(): Class[_]

val inputFormat: Option[String]

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val outputName: String

val pushedExpression: Expression

final def synchronized[T0](arg0: ⇒ T0): T0

val tzForFormat: Option[String]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped