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DataFrame.RepartitionByRange Method

Definition

Overloads

RepartitionByRange(Column[])

Returns a new DataFrame partitioned by the given partitioning expressions, using spark.sql.shuffle.partitions as number of partitions. The resulting Dataset is range partitioned.

RepartitionByRange(Int32, Column[])

Returns a new DataFrame partitioned by the given partitioning expressions into numPartitions. The resulting DataFrame is range partitioned.

RepartitionByRange(Column[])

Returns a new DataFrame partitioned by the given partitioning expressions, using spark.sql.shuffle.partitions as number of partitions. The resulting Dataset is range partitioned.

public Microsoft.Spark.Sql.DataFrame RepartitionByRange (params Microsoft.Spark.Sql.Column[] partitionExprs);
member this.RepartitionByRange : Microsoft.Spark.Sql.Column[] -> Microsoft.Spark.Sql.DataFrame
Public Function RepartitionByRange (ParamArray partitionExprs As Column()) As DataFrame

Parameters

partitionExprs
Column[]

Partitioning expressions

Returns

DataFrame object

Applies to

RepartitionByRange(Int32, Column[])

Returns a new DataFrame partitioned by the given partitioning expressions into numPartitions. The resulting DataFrame is range partitioned.

public Microsoft.Spark.Sql.DataFrame RepartitionByRange (int numPartitions, params Microsoft.Spark.Sql.Column[] partitionExprs);
member this.RepartitionByRange : int * Microsoft.Spark.Sql.Column[] -> Microsoft.Spark.Sql.DataFrame
Public Function RepartitionByRange (numPartitions As Integer, ParamArray partitionExprs As Column()) As DataFrame

Parameters

numPartitions
Int32

Number of partitions

partitionExprs
Column[]

Partitioning expressions

Returns

DataFrame object

Applies to