Repartition by column spark. This partitioning is used when implementing the DataFrame.


  • Repartition by column spark. sql. repartition("partition") \ . Coalesce: Use repartition for increasing partitions or key-based distribution. repartition() is used for specifying the number of partitions considering the number of cores and the amount of data you have. repartition(40, col("c1"), col("c2")) also works provided you have imported import org. – Jun 28, 2017 · repartition(numPartitions, $"some_col", rand) is an elegant solution but does not handle small data partitions well. Use repartition with columns or salting to balance data. Use coalesce to reduce partitions post-filtering Spark Coalesce vs. Jul 24, 2015 · The repartition method makes new partitions and evenly distributes the data in the new partitions (the data distribution is more even for larger data sets). format("json") \ Here, you are repartitioning the existing dataframe based on the column "partition" which has 100 distinct values. pryo xhbs reubwr jteexr ksuj ahig kxgo pzlvo bxfr eoomax