trait Scan extends AnyRef
A logical representation of a data source scan. This interface is used to provide logical information, like what the actual read schema is.
This logical representation is shared between batch scan, micro-batch streaming scan and
continuous streaming scan. Data sources must implement the corresponding methods in this
interface, to match what the table promises to support. For example, #toBatch() must be
implemented, if the Table that creates this Scan returns
TableCapability#BATCH_READ support in its Table#capabilities().
- Annotations
- @Evolving()
- Source
- Scan.java
- Since
- 3.0.0 
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-   abstract  def readSchema(): StructTypeReturns the actual schema of this data source scan, which may be different from the physical schema of the underlying storage, as column pruning or other optimizations may happen. 
Concrete Value Members
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-    def clone(): AnyRef- Attributes
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-    def columnarSupportMode(): ColumnarSupportModeSubclasses can implement this method to indicate if the support for columnar data should be determined by each partition or is set as a default for the whole scan. Subclasses can implement this method to indicate if the support for columnar data should be determined by each partition or is set as a default for the whole scan. - Since
- 3.5.0 
 
-    def description(): StringA description string of this scan, which may includes information like: what filters are configured for this scan, what's the value of some important options like path, etc. A description string of this scan, which may includes information like: what filters are configured for this scan, what's the value of some important options like path, etc. The description doesn't need to include #readSchema(), as Spark already knows it.By default this returns the class name of the implementation. Please override it to provide a meaningful description. 
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-   final  def notify(): Unit- Definition Classes
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-   final  def notifyAll(): Unit- Definition Classes
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-    def reportDriverMetrics(): Array[CustomTaskMetric]Returns an array of custom metrics which are collected with values at the driver side only. Returns an array of custom metrics which are collected with values at the driver side only. Note that these metrics must be included in the supported custom metrics reported by supportedCustomMetrics.- Since
- 3.4.0 
 
-    def supportedCustomMetrics(): Array[CustomMetric]Returns an array of supported custom metrics with name and description. Returns an array of supported custom metrics with name and description. By default it returns empty array. 
-   final  def synchronized[T0](arg0: => T0): T0- Definition Classes
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-    def toBatch(): BatchReturns the physical representation of this scan for batch query. Returns the physical representation of this scan for batch query. By default this method throws exception, data sources must overwrite this method to provide an implementation, if the Tablethat creates this scan returnsTableCapability#BATCH_READsupport in itsTable#capabilities().If the scan supports runtime filtering and implements SupportsRuntimeFiltering, this method may be called multiple times. Therefore, implementations can cache some state to avoid planning the job twice.- Exceptions thrown
 
-    def toContinuousStream(checkpointLocation: String): ContinuousStreamReturns the physical representation of this scan for streaming query with continuous mode. Returns the physical representation of this scan for streaming query with continuous mode. By default this method throws exception, data sources must overwrite this method to provide an implementation, if the Tablethat creates this scan returnsTableCapability#CONTINUOUS_READsupport in itsTable#capabilities().- checkpointLocation
- a path to Hadoop FS scratch space that can be used for failure recovery. Data streams for the same logical source in the same query will be given the same checkpointLocation. 
 - Exceptions thrown
 
-    def toMicroBatchStream(checkpointLocation: String): MicroBatchStreamReturns the physical representation of this scan for streaming query with micro-batch mode. Returns the physical representation of this scan for streaming query with micro-batch mode. By default this method throws exception, data sources must overwrite this method to provide an implementation, if the Tablethat creates this scan returnsTableCapability#MICRO_BATCH_READsupport in itsTable#capabilities().- checkpointLocation
- a path to Hadoop FS scratch space that can be used for failure recovery. Data streams for the same logical source in the same query will be given the same checkpointLocation. 
 - Exceptions thrown
 
-    def toString(): String- Definition Classes
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-   final  def wait(arg0: Long, arg1: Int): Unit- Definition Classes
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- Deprecated
- (Since version 9)