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  1. Spark
  2. SPARK-32989

Performance regression when selecting from str_to_map

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Details

    • Bug
    • Status: Resolved
    • Minor
    • Resolution: Fixed
    • 3.0.1
    • 3.1.0
    • SQL
    • None

    Description

      When I create a map using str_to_map and select more than a single value, I notice a notable performance regression in 3.0.1 compared to 2.4.7. When selecting a single value, the performance is the same. Plans are identical between versions.

      It seems like in 2.x the map from str_to_map is preserved for a given row, but in 3.x it's recalculated for each column. One hint that it might be the case is that when I tried forcing materialisation of said map in 3.x (by a coalesce, don't know if there's a better way), I got the performance roughly to 2.x levels.

      Here's a reproducer (the csv in question gets autogenerated by the python code):

      $ head regression.csv 
      foo
      foo=bar&baz=bak&bar=foo
      foo=bar&baz=bak&bar=foo
      foo=bar&baz=bak&bar=foo
      foo=bar&baz=bak&bar=foo
      foo=bar&baz=bak&bar=foo
      ... (10M more rows)
      
      import time
      import os
      
      import pyspark  
      from pyspark.sql import SparkSession
      
      import pyspark.sql.functions as f
      
      if __name__ == '__main__':
          print(pyspark.__version__)
          spark = SparkSession.builder.getOrCreate()
      
          filename = 'regression.csv'
          if not os.path.isfile(filename):
              with open(filename, 'wt') as fw:
                  fw.write('foo\n')
                  for _ in range(10_000_000):
                      fw.write('foo=bar&baz=bak&bar=foo\n')
      
          df = spark.read.option('header', True).csv(filename)
          t = time.time()
          dd = (df
                  .withColumn('my_map', f.expr('str_to_map(foo, "&", "=")'))
                  .select(
                      f.col('my_map')['foo'],
                  )
              )
          dd.write.mode('overwrite').csv('tmp')
          t2 = time.time()
          print('selected one', t2 - t)
      
          dd = (df
                  .withColumn('my_map', f.expr('str_to_map(foo, "&", "=")'))
                  # .coalesce(100) # forcing evaluation before selection speeds it up in 3.0.1
                  .select(
                      f.col('my_map')['foo'],
                      f.col('my_map')['bar'],
                      f.col('my_map')['baz'],
                  )
              )
          dd.explain(True)
          dd.write.mode('overwrite').csv('tmp')
          t3 = time.time()
          print('selected three', t3 - t2)
      

      Results for 2.4.7 and 3.0.1, both installed from PyPI, Python 3.7, macOS (times are in seconds)

      # 3.0.1
      # selected one 6.375471830368042                                                  
      # selected three 14.847578048706055
      
      # 2.4.7
      # selected one 6.679579019546509                                                  
      # selected three 6.5622029304504395  
      

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            viirya L. C. Hsieh
            ondrej Ondrej Kokes
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            Dates

              Created:
              Updated:
              Resolved:

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