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https://issues.apache.org/jira/browse/SPARK-28590?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Albertus Kelvin updated SPARK-28590:
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Description:
When I want to use BasicProfiler with different sorters in sort_stats, I
sometimes need to create a custom profiler and implement the show() method only
to replace the following line: stats.sort_stats("time",
"cumulative").print_stats().
I think it'd be better if the users are able to specify the sorters without
creating a custom profiler.
I implemented the changes in PySpark only.
To apply the setter and getter methods, one can use the following way:
{code:python}
conf = SparkConf().set("spark.python.profile", "true")
# use BasicProfiler
sc = SparkContext('local', 'test', conf=conf)
sc.profiler_collector.profiler_cls.set_sort_stats_sorters(BasicProfiler,
['ncalls', 'tottime', 'name']
{code}
was:
When doing profiling using custom profilers, I sometimes need to re-create
another custom profiler class when using different sorter in *sort_stats*. I
think it would be better if the users are able to set their own sorting columns
preference. To do this, I thought of creating a *setter* method in the
*Profiler* class (python/pyspark/profiler.py).
FYI, I implemented the changes in PySpark only.
> Add sort_stats Setter for Custom Profiler
> -----------------------------------------
>
> Key: SPARK-28590
> URL: https://issues.apache.org/jira/browse/SPARK-28590
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 2.4.0
> Reporter: Albertus Kelvin
> Priority: Minor
>
> When I want to use BasicProfiler with different sorters in sort_stats, I
> sometimes need to create a custom profiler and implement the show() method
> only to replace the following line: stats.sort_stats("time",
> "cumulative").print_stats().
> I think it'd be better if the users are able to specify the sorters without
> creating a custom profiler.
> I implemented the changes in PySpark only.
> To apply the setter and getter methods, one can use the following way:
> {code:python}
> conf = SparkConf().set("spark.python.profile", "true")
> # use BasicProfiler
> sc = SparkContext('local', 'test', conf=conf)
> sc.profiler_collector.profiler_cls.set_sort_stats_sorters(BasicProfiler,
> ['ncalls', 'tottime', 'name']
> {code}
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