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Posted to issues@spark.apache.org by "Josh Rosen (JIRA)" <ji...@apache.org> on 2016/11/30 17:40:58 UTC
[jira] [Updated] (SPARK-18362) Use TextFileFormat in implementation
of CSVFileFormat
[ https://issues.apache.org/jira/browse/SPARK-18362?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Josh Rosen updated SPARK-18362:
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Description: Spark's CSVFileFormat data source uses inefficient methods for reading files during schema inference and does not benefit from file listing / IO performance improvements made in Spark 2.0. In order to fix this performance problem, we should re-implement those read paths in terms of TextFileFormat. (was: Spark's CSVFileFormat and JsonFileFormat data sources use inefficient methods for reading files during schema inference and do not benefit from file listing / IO performance improvements made in Spark 2.0. In order to fix this performance problem, we should re-implement those read paths in terms of TextFileFormat.)
> Use TextFileFormat in implementation of CSVFileFormat
> -----------------------------------------------------
>
> Key: SPARK-18362
> URL: https://issues.apache.org/jira/browse/SPARK-18362
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Josh Rosen
> Assignee: Josh Rosen
>
> Spark's CSVFileFormat data source uses inefficient methods for reading files during schema inference and does not benefit from file listing / IO performance improvements made in Spark 2.0. In order to fix this performance problem, we should re-implement those read paths in terms of TextFileFormat.
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