Control write partitioning with Spark

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Control write partitioning with Spark

There does not appear to be a way to write spark jobs to disk using a set partition scheme. This is normally done via dataframe.write.parquet(<path>, partitionBy=['year']), if one is to partition the data by year, for example. I am looking at the API page here:, specifically the function: write_with_schema

What are my options here? Since this is an important requirement for us, what's to stop me from simply using the sqlContext to write to a fixed path in HDFS, using the command I gave above? Can this be hacked somehow, or by using a plugin?

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Alex_Combessie Dataiker
Re: Control write partitioning with Spark

In order to use partitioning in Dataiku, you need to specify it on the output (and possibly input) dataset. You can find more details on this page:

If you set it up accordingly, this file system partitioning setup will be applied to all recipes, including those running on Spark.

Hope it helps,

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