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. Jan 20, 2021 · repartitionByRange will partition the data based on a range of the column values. This is usually used for continuous (not discrete) values such as any kind of numbers.
YouTube Excerpt: In this PySpark tutorial, learn how to optimize your Spark DataFrames using the
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