Many small files could cause technical issues in both hdfs and spark
though, they do not
generate many stages and tasks in the recent version of spark.

// maropu

On Fri, May 20, 2016 at 2:41 PM, Gavin Yue <yue.yuany...@gmail.com> wrote:

> For logs file I would suggest save as gziped text file first.  After
> aggregation, convert them into parquet by merging a few files.
>
>
>
> On May 19, 2016, at 22:32, Deng Ching-Mallete <och...@apache.org> wrote:
>
> IMO, it might be better to merge or compact the parquet files instead of
> keeping lots of small files in the HDFS. Please refer to [1] for more info.
>
> We also encountered the same issue with the slow query, and it was indeed
> caused by the many small parquet files. In our case, we were processing
> large data sets with batch jobs instead of a streaming job. To solve our
> issue, we just did a coalesce to reduce the number of partitions before
> saving as parquet format.
>
> HTH,
> Deng
>
> [1] http://blog.cloudera.com/blog/2009/02/the-small-files-problem/
>
> On Fri, May 20, 2016 at 1:50 PM, 王晓龙/01111515 <roland8...@cmbchina.com>
> wrote:
>
>> I’m using a spark streaming program to store log message into parquet
>> file every 10 mins.
>> Now, when I query the parquet, it usually takes hundreds of thousands of
>> stages to compute a single count.
>> I looked into the parquet file’s path and find a great amount of small
>> files.
>>
>> Do the small files caused the problem? Can I merge them, or is there a
>> better way to solve it?
>>
>> Lots of thanks.
>>
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Takeshi Yamamuro

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