case class ConsoleRelation(sqlContext: SQLContext, data: DataFrame) extends BaseRelation with Product with Serializable
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Instance Constructors
- new ConsoleRelation(sqlContext: SQLContext, data: DataFrame)
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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def
clone(): AnyRef
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- val data: DataFrame
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final
def
eq(arg0: AnyRef): Boolean
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def
finalize(): Unit
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def
isInstanceOf[T0]: Boolean
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def
ne(arg0: AnyRef): Boolean
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def
needConversion: Boolean
Whether does it need to convert the objects in Row to internal representation, for example: java.lang.String to UTF8String java.lang.Decimal to Decimal
Whether does it need to convert the objects in Row to internal representation, for example: java.lang.String to UTF8String java.lang.Decimal to Decimal
If
needConversion
isfalse
, buildScan() should return anRDD
ofInternalRow
- Definition Classes
- BaseRelation
- Since
1.4.0
- Note
The internal representation is not stable across releases and thus data sources outside of Spark SQL should leave this as true.
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
schema: StructType
- Definition Classes
- ConsoleRelation → BaseRelation
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def
sizeInBytes: Long
Returns an estimated size of this relation in bytes.
Returns an estimated size of this relation in bytes. This information is used by the planner to decide when it is safe to broadcast a relation and can be overridden by sources that know the size ahead of time. By default, the system will assume that tables are too large to broadcast. This method will be called multiple times during query planning and thus should not perform expensive operations for each invocation.
- Definition Classes
- BaseRelation
- Since
1.3.0
- Note
It is always better to overestimate size than underestimate, because underestimation could lead to execution plans that are suboptimal (i.e. broadcasting a very large table).
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val
sqlContext: SQLContext
- Definition Classes
- ConsoleRelation → BaseRelation
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
unhandledFilters(filters: Array[Filter]): Array[Filter]
Returns the list of Filters that this datasource may not be able to handle.
Returns the list of Filters that this datasource may not be able to handle. These returned Filters will be evaluated by Spark SQL after data is output by a scan. By default, this function will return all filters, as it is always safe to double evaluate a Filter. However, specific implementations can override this function to avoid double filtering when they are capable of processing a filter internally.
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- BaseRelation
- Since
1.6.0
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final
def
wait(): Unit
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def
wait(arg0: Long, arg1: Int): Unit
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wait(arg0: Long): Unit
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