Web Reference: Repartition the data into 2 partitions by range in ‘age’ column. For example, the first partition can have (14, "Tom") and (16, "Bob"), and the second partition would have (23, "Alice"). Due to performance reasons this method uses sampling to estimate the ranges. Hence, the output may not be consistent, since sampling can return different values. The sample size can be controlled by the config spark.sql.execution.rangeExchange.sampleSizePerPartition. The repartitionByRange method in PySpark DataFrames redistributes the data of a DataFrame across a specified number of partitions based on the range of values in one or more columns, returning a new DataFrame with the reorganized data.
YouTube Excerpt: In this PySpark tutorial, learn how to optimize your Spark DataFrames using the
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