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spark:recipes:reading-text-files [2025/10/15 20:11]
straka [Number of Partitions: Compressed File] 		spark:recipes:reading-text-files [2025/10/15 20:13] (current)
straka [Number of Partitions: Multiple Files in a Directory]
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 When the input file is a directory, each file is read in separate partitions. The minimum number of partitions given as second argument to ''textFile'' is applied only to the first file (if it is not compressed). Other uncompressed files are split only into 32MB chunks, or into 1 partition if compressed. When the input file is a directory, each file is read in separate partitions. The minimum number of partitions given as second argument to ''textFile'' is applied only to the first file (if it is not compressed). Other uncompressed files are split only into 32MB chunks, or into 1 partition if compressed.
  
-Note that when there are many files (as for example in ''/net/projects/spark-example-data/hamledt-cs-conll''), the number of partitions can be quite large, which slows down the computation. In that case, ''coalesce'' can be used to decrease the number of partitions efficiently (by merging existing partitions without running the ''repartition''):+Note that when there are many files (thousands or more, as for example in ''/net/projects/spark-example-data/hamledt-cs-conll''), the number of partitions can be quite large, which slows down the computation. In that case, ''coalesce'' can be used to decrease the number of partitions efficiently (by merging existing partitions without running the ''repartition''):
 <file python> <file python>
 conll_lines = sc.textFile("/net/projects/spark-example-data/hamledt-cs-conll").coalesce(3*sc.defaultParallelism) conll_lines = sc.textFile("/net/projects/spark-example-data/hamledt-cs-conll").coalesce(3*sc.defaultParallelism)

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