[ https://issues.apache.org/jira/browse/SPARK-23030?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-23030. ---------------------------------- Resolution: Fixed Fix Version/s: 2.4.0 Issue resolved by pull request 21546 [https://github.com/apache/spark/pull/21546] > 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 > Assignee: Bryan Cutler > Priority: Major > Fix For: 2.4.0 > > > 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. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org