Hi there, we have a small Spark cluster running and are processing around 40 GB of Gzip-compressed JSON data per day. I have written a couple of word count-like Scala jobs that essentially pull in all the data, do some joins, group bys and aggregations. A job takes around 40 minutes to complete.
Now one of the data scientists on the team wants to do write some jobs using Python. To learn Spark, he rewrote one of my Scala jobs in Python. From the API-side, everything looks more or less identical. However his jobs take between 5-8 hours to complete! We can also see that the execution plan is quite different, I’m seeing writes to the output much later than in Scala. Is Python I/O really that slow? Thanks - Marius --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
