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Johnny W. edited comment on SPARK-15247 at 5/12/16 5:28 AM: ------------------------------------------------------------ Takeshi, thanks for your reply. However, I don't think they are relevant, because even though I have only 1 (very small) file, spark creates n_executors * n_cores tasks, and this is only true for parquet. This issue has been confirmed by others from the community: -- https://www.mail-archive.com/user@spark.apache.org/msg50568.html Is there any walkaround for this without rebuilding spark? was (Author: johnnyws): Takeshi, thanks for your reply. However, I don't think they are relevant, because even though I have only 1 (very small) file, spark creates n_executors * n_cores tasks, and this is only true for parquet. This issue has been confirmed by others from the community: -- https://www.mail-archive.com/user@spark.apache.org/msg50568.html Could you try to reproduce? Is there any walkaround for this? > sqlCtx.read.parquet yields at least n_executors * n_cores tasks > --------------------------------------------------------------- > > Key: SPARK-15247 > URL: https://issues.apache.org/jira/browse/SPARK-15247 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 1.6.0 > Reporter: Johnny W. > > sqlCtx.read.parquet always yields at least n_executors * n_cores tasks, even > though this is only 1 very small file > This issue can increase the latency for small jobs. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org