I had expericne with mapr where small files are much worse. Mapr can keep (only keep) small files better agreed. Storing is not the answer, You wanted to run the job and what happens? A container stores files and container gets replicated, that means one container (of 256MB or 128MB or what ever size it is configured) is Replicated. The moment you start m/r job (and don’t use combinerinputfile format) you are actually launching jobs on the three nodes due To data localization issue.
Small files are bad with Hadoop and worse with mapr when you wanted to run job and good with storing. Sam From: MBA <[email protected]<mailto:[email protected]>> Reply-To: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Date: Sunday, July 20, 2014 at 9:54 PM To: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Subject: Re: Merging small files It isn’t? I don’t wanna hijack the thread or anything but it seems to me that MapR is an implementation of Hadoop and this is a great place to discuss it’s merits vis a vis the Hortonworks or Cloudera offering. A little bit more on topic: Every single thing I read or watch about Hadoop says that many small files is a bad idea and that you should merge them into larger files. I’ll take this a step further. If your invoice data is so small, perhaps Hadoop isn’t the proper solution to whatever it is you are trying to do and a more traditional RDBMS approach would be more appropriate. Someone suggested HBase and I was going to suggest maybe one of the other NoSQL databases, however, I remember that Eddie Satterly of Splunk says that financial data is the ONE use case where a traditional approach is more appropriate. You can watch his talk here: https://www.youtube.com/watch?v=-N9i-YXoQBE&index=77&list=WL Adaryl "Bob" Wakefield, MBA Principal Mass Street Analytics 913.938.6685 www.linkedin.com/in/bobwakefieldmba From: Kilaru, Sambaiah<mailto:[email protected]> Sent: Sunday, July 20, 2014 3:47 AM To: [email protected]<mailto:[email protected]> Subject: Re: Merging small files This is not place to discuss merits or demerits of MapR, Small files screw up very badly with Mapr. Small files go into one container (to fill up 256MB or what ever container size) and with locality most Of the mappers go to three datanodes. You should be looking into sequence file format. Thanks, Sam From: "M. C. Srivas" <[email protected]<mailto:[email protected]>> Reply-To: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Date: Sunday, July 20, 2014 at 8:01 AM To: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Subject: Re: Merging small files You should look at MapR .... a few 100's of billions of small files is absolutely no problem. (disc: I work for MapR) On Sat, Jul 19, 2014 at 10:29 AM, Shashidhar Rao <[email protected]<mailto:[email protected]>> wrote: Hi , Has anybody worked in retail use case. If my production Hadoop cluster block size is 256 MB but generally if we have to process retail invoice data , each invoice data is merely let's say 4 KB . Do we merge the invoice data to make one large file say 1 GB . What is the best practice in this scenario Regards Shashi
