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From Harshit Mathur <mathursh...@gmail.com>
Subject Re: Large number of small files
Date Fri, 24 Apr 2015 09:48:02 GMT
Use can use combine file input format, it will save the large number of
mappers. And as per my understanding of your problem that one of your job
will run of past 3 months of data while other might run on past 6 months
data.
For this you can run a pre processing job which will just output a file
having the paths of the files within your desired time range of 3 months or
6 months. Then use multiple file input format to pass all these paths in
your mapper.



On Fri, Apr 24, 2015 at 3:03 PM, Chandra Mohan, Ananda Vel Murugan <
Ananda.Murugan@honeywell.com> wrote:

>  Marko,
>
>
>
> Parquet file would be created once when you load the data. You don’t have
> to store your small files in HDFS just for the reason of subseting the data
> by time range. You can store data and metadata in same Parquet file. As
> already pointed out, parquet files work well other tools in Hadoop
> ecosystem. Apart from performance of your map reduce jobs, other aspect is
> storage efficiency. Serialization formats like Avro and Parquet provide
> better compression and hence data occupies less space.
>
>
>
> Regards,
>
> Anand
>
>
>
> *From:* Alexander Alten-Lorenz [mailto:wget.null@gmail.com]
> *Sent:* Friday, April 24, 2015 2:49 PM
> *To:* user@hadoop.apache.org
> *Subject:* Re: Large number of small files
>
>
>
> Marko,
>
>
>
> Cassandra is an noSQL DB like HBase for Hadoop is. Pro and cons wouldn't
> be discussed here.
>
>
>
> Parquet is an columnar based storage format. It is - high level - a bit
> like a NoSQL DB, but on the storage level. it allows users to "query" the
> data with MR, Pig or similar tools. Additionally, Parquet works perfectly
> with Hive and Cloudera Impala as well as Apache Dremel.
>
>
>
> https://parquet.incubator.apache.org/documentation/latest/
>
>
> http://www.cloudera.com/content/cloudera/en/documentation/cloudera-impala/v2-0-x/topics/impala_parquet.html
>
>
> https://zoomdata.zendesk.com/hc/en-us/articles/200865073-Loading-My-CSV-Data-into-Impala-as-a-Parquet-Table
>
>
>
>
> --
>
> Alexander Alten-Lorenz
> m: wget.null@gmail.com
> b: mapredit.blogspot.com
>
>
>
>  On Apr 24, 2015, at 11:10 AM, Marko Dinic <marko.dinic@nissatech.com>
> wrote:
>
>
>
> Anand,
>
> Thank you for your answer, but wouldn't that mean that I would have to
> serialize the files each time I need to run the job? And I would still need
> to save the original files, so the NameNode still needs to take care of
> them?
>
> Please correct me if I'm missing something, I'm not very experienced with
> Hadoop.
>
> What do you think about using Cassandra?
>
> Thanks
>
> On Fri 24 Apr 2015 11:03:19 AM CEST, Chandra Mohan, Ananda Vel Murugan
> wrote:
>
>  Apart from databases like Cassandra, you may check serialization formats
> like Avro or Parquet
>
> Regards,
> Anand
>
> -----Original Message-----
> From: Marko Dinic [mailto:marko.dinic@nissatech.com
> <marko.dinic@nissatech.com>]
> Sent: Friday, April 24, 2015 2:23 PM
> To: user@hadoop.apache.org
> Subject: Large number of small files
>
> Hello,
>
> I'm not sure if this is the place to ask this question, but I'm still
> hopping for an answer/advice.
>
> Large number of small files are uploaded, about 8KB. I am aware that this
> is not something that you're hopping for when working with Hadoop.
>
> I was thinking about using HAR files and combined input, or sequence
> files. The problem is, files are timestamped, and I need different subset
> in different time, for example - one job needs to run on files that are
> uploaded during last 3 months, while next job might consider last 6 months.
> Naturally, as time passes different subset of files is needed.
>
> This means that I would need to make a sequence file (or a HAR) each time
> I run a job, to have smaller number of mappers. On the other hand, I need
> the original files so I could subset them. This means that DataNode is at
> constant pressure, saving all of this in its memory.
>
> How can I solve this problem?
>
> I was also considering using Cassandra, or something like that, and to
> save the file content inside of it, instead of saving it to files on HDFS.
> FIle content is actually some measurement, that is, a vector of numbers,
> with some metadata.
>
> Thanks
>
>
>



-- 
Harshit Mathur

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