trait ContinuousPartitionReaderFactory extends PartitionReaderFactory
A variation on PartitionReaderFactory that returns ContinuousPartitionReader
instead of PartitionReader. It's used for continuous streaming processing.
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3.0.0
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- ContinuousPartitionReaderFactory
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abstract
def
createReader(partition: InputPartition): ContinuousPartitionReader[InternalRow]
Returns a row-based partition reader to read data from the given
InputPartition.Returns a row-based partition reader to read data from the given
InputPartition.Implementations probably need to cast the input partition to the concrete
InputPartitionclass defined for the data source.- Definition Classes
- ContinuousPartitionReaderFactory → PartitionReaderFactory
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def
createColumnarReader(partition: InputPartition): ContinuousPartitionReader[ColumnarBatch]
Returns a columnar partition reader to read data from the given
InputPartition.Returns a columnar partition reader to read data from the given
InputPartition.Implementations probably need to cast the input partition to the concrete
InputPartitionclass defined for the data source.- Definition Classes
- ContinuousPartitionReaderFactory → PartitionReaderFactory
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def
supportColumnarReads(partition: InputPartition): Boolean
Returns true if the given
InputPartitionshould be read by Spark in a columnar way.Returns true if the given
InputPartitionshould be read by Spark in a columnar way. This means, implementations must also implement#createColumnarReader(InputPartition)for the input partitions that this method returns true.As of Spark 2.4, Spark can only read all input partition in a columnar way, or none of them. Data source can't mix columnar and row-based partitions. This may be relaxed in future versions.
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- PartitionReaderFactory
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