You _could_ do it by using the hash of the unique bits of the log as the
id.  But most systems would support this.

The trouble is that most operations in Elasticsearch are async and
non-atomic.  Operations on ID are atomic and synchronous.


All and all, its not a horrible choice but its not the first tool I'd reach
for.  If your researchers want the data in Elasticsearch in the end I'd go
with the hash hack.  If not I'd investigate some more log processing tools.

It sounds like a fun problem that'd be fun to put together a solution for
but I'm reasonably sure someone has already done this though.  OTOH some
fun mostly right system using hashing to push data to the right node and
time bucketed bloom filters would be fun to build and could probably be
tuned to be pretty good.  But I'm sure smarter people than me have already
solved this problem though.  And open sourced the solution.


Nik

On Mon, Mar 2, 2015 at 9:45 AM, Mihai Lucaciu <[email protected]> wrote:

> Hi,
>
> I am new to Elasticsearch which I understand can do much more than this...
> but could it be used just for that ?
>
> I am storing 100GB of log files daily. The data scientists require this
> log data to not contain duplicate log lines. Duplicates may come within the
> same log file, with two sequential log files - it's better to expect any
> possible scenario.
>
> What I would like to achieve is to use Elasticsearch to detect & remove
> the duplicate log lines from all logs in an HDFS directory. Can this be
> done ?
>
> Thank you,
> Mihai
>
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