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Posted to issues@spark.apache.org by "Bryan Cutler (JIRA)" <ji...@apache.org> on 2018/01/10 19:42:00 UTC
[jira] [Created] (SPARK-23030) Decrease memory consumption with
toPandas() collection using Arrow
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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