class KeyGroupedPartitioning extends Partitioning
Represents a partitioning where rows are split across partitions based on the
partition transform expressions returned by KeyGroupedPartitioning#keys.
Note: Data source implementations should make sure for a single partition, all of its rows
must be evaluated to the same partition value after being applied by
KeyGroupedPartitioning#keys expressions. Different partitions can share the same
partition value: Spark will group these into a single logical partition during planning phase.
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- @Evolving()
- Source
- KeyGroupedPartitioning.java
- Since
3.3.0
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- new KeyGroupedPartitioning(keys: Array[Expression], numPartitions: Int)
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- def keys(): Array[Expression]
Returns the partition transform expressions for this partitioning.
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- def numPartitions(): Int
Returns the number of partitions that the data is split across.
Returns the number of partitions that the data is split across.
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- KeyGroupedPartitioning → Partitioning
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(Since version 9)