abstract class BaseRelation extends AnyRef
Represents a collection of tuples with a known schema. Classes that extend BaseRelation must
be able to produce the schema of their data in the form of a StructType
. Concrete
implementation should inherit from one of the descendant Scan
classes, which define various
abstract methods for execution.
BaseRelations must also define an equality function that only returns true when the two instances will return the same data. This equality function is used when determining when it is safe to substitute cached results for a given relation.
- Annotations
- @Stable()
- Since
1.3.0
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Instance Constructors
- new BaseRelation()
Abstract Value Members
- abstract def schema: StructType
- abstract def sqlContext: SQLContext
Concrete Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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-
def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
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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
- 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.
-
final
def
notify(): Unit
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final
def
notifyAll(): Unit
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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.
- 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).
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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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.
- Since
1.6.0
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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