pyspark.rdd.repartition

pyspark.rdd.repartition() is a method in PySpark that allows you to change the number of partitions in an RDD (Resilient Distributed Dataset). It shuffles the data across the partitions and creates new partitions based on the specified number.

The method takes a single argument, which is the desired number of partitions. For example, if you have an RDD with 100 partitions and you want to reduce it to 50 partitions, you can use the repartition() method as follows:

rdd = rdd.repartition(50)

Note that repartition() is a costly operation, as it involves shuffling the data across the cluster. Therefore, it is recommended to use it only when necessary and to choose the number of partitions carefully based on the size of the data and the available resources.