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https://issues.apache.org/jira/browse/SPARK-32989?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17202812#comment-17202812
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Ondrej Kokes commented on SPARK-32989:
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[~hyukjin.kwon] I've added a file generator in the python code, so it can be
run without prepping the input file
> Performance regression when selecting from str_to_map
> -----------------------------------------------------
>
> Key: SPARK-32989
> URL: https://issues.apache.org/jira/browse/SPARK-32989
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.1
> Reporter: Ondrej Kokes
> Priority: Minor
>
> 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):
> {code:java}
> $ 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)
> {code}
> {code:python}
> import time
> import pyspark
> from pyspark.sql import SparkSession
> import pyspark.sql.functions as f
> if __name__ == '__main__':
> print(pyspark.__version__)
> spark = SparkSession.builder.getOrCreate()
> df = spark.read.option('header', True).csv('regression.csv')
> 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)
> {code}
> Results for 2.4.7 and 3.0.1, both installed from PyPI, Python 3.7, macOS
> (times are in seconds)
> {code:java}
> # 3.0.1
> # selected one 6.375471830368042
>
> # selected three 14.847578048706055
> # 2.4.7
> # selected one 6.679579019546509
>
> # selected three 6.5622029304504395
> {code}
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