Hi thanks for the assistance,
1. Standalone 2. df.orderBy(field).limit(5000).write.parquet(...) From: Mich Talebzadeh [mailto:mich.talebza...@gmail.com] Sent: Friday, August 05, 2016 4:33 PM To: Ellafi, Saif A. Cc: user @spark Subject: Re: Applying a limit after orderBy of big dataframe hangs spark Hi, 1. What scheduling are you using standalone, yarn etc? 2. How arte you limiting the df output? HTH Dr Mich Talebzadeh LinkedIn https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw http://talebzadehmich.wordpress.com Disclaimer: Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from relying on this email's technical content is explicitly disclaimed. The author will in no case be liable for any monetary damages arising from such loss, damage or destruction. On 5 August 2016 at 19:54, <saif.a.ell...@wellsfargo.com<mailto:saif.a.ell...@wellsfargo.com>> wrote: Hi all, I am working with a 1.5 billon rows dataframe in a small cluster and trying to apply an orderBy operation by one of the Long Types columns. If I limit such output to some number, say 5 millon, then trying to count, persist or store the dataframe makes spark crash with losing executors and hang ups. Not limiting the dataframe after the order by operation works normally, i.e. it works fine when trying to write the 1.5 billon rows again. Any thoughts? Using spark 1.6.0 scala 2.11 Saif
