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From "Bryan Cutler (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-23030) Decrease memory consumption with toPandas() collection using Arrow
Date Wed, 10 Jan 2018 19:42:00 GMT
Bryan Cutler created SPARK-23030:
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             Summary: Decrease memory consumption with toPandas() collection using Arrow
                 Key: SPARK-23030
                 URL: https://issues.apache.org/jira/browse/SPARK-23030
             Project: Spark
          Issue Type: Sub-task
          Components: PySpark, SQL
    Affects Versions: 2.3.0
            Reporter: Bryan Cutler


Currently with Arrow enabled, calling {{toPandas()}} results in a collection of all partitions
in the JVM in the form of batches of Arrow file format.  Once collected in the JVM, they are
served to the Python driver process. 

I believe using the Arrow stream format can help to optimize this and reduce memory consumption
in the JVM by only loading one record batch at a time before sending it to Python.  This might
also reduce the latency between making the initial call in Python and receiving the first
batch of records.



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