With Hadoop 2.7 or later, set
spark.hadooop.mapreduce.fileoutputcommitter.algorithm.version 2 spark.hadoop.mapreduce.fileoutputcommitter.cleanup.skipped true This switches to a no -rename version of the file output committer, is faster all round. You are still at risk of things going wrong on failure though, and with speculation enabled. you are still at risk o On 25 Aug 2016, at 13:16, Tal Grynbaum <tal.grynb...@gmail.com<mailto:tal.grynb...@gmail.com>> wrote: Is/was there an option similar to DirectParquetOutputCommitter to write json files to S3 ? On Thu, Aug 25, 2016 at 2:56 PM, Takeshi Yamamuro <linguin....@gmail.com<mailto:linguin....@gmail.com>> wrote: Hi, Seems this just prevents writers from leaving partial data in a destination dir when jobs fail. In the previous versions of Spark, there was a way to directly write data in a destination though, Spark v2.0+ has no way to do that because of the critial issue on S3 (See: SPARK-10063). // maropu On Thu, Aug 25, 2016 at 2:40 PM, Tal Grynbaum <tal.grynb...@gmail.com<mailto:tal.grynb...@gmail.com>> wrote: I read somewhere that its because s3 has to know the size of the file upfront I dont really understand this, as to why is it ok not to know it for the temp files and not ok for the final files. The delete permission is the minor disadvantage from my side, the worst thing is that i have a cluster of 100 machines sitting idle for 15 minutes waiting for copy to end. Any suggestions how to avoid that? On Thu, Aug 25, 2016, 08:21 Aseem Bansal <asmbans...@gmail.com<mailto:asmbans...@gmail.com>> wrote: Hi When Spark saves anything to S3 it creates temporary files. Why? Asking this as this requires the the access credentails to be given delete permissions along with write permissions. -- --- Takeshi Yamamuro -- Tal Grynbaum / CTO & co-founder m# +972-54-7875797 <Logo-TH.png> mobile retention done right
