The default merge policy in Lucene (TieredMergePolicy) has a bias towards
segments with more deletes, so it is "trying" to merge those ones away.
 You can increase this bias by setting index.reclaim_deletes_weight (see
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/index-modules-merge.html
) but be careful not to make it so high that awful merges are being
selected.

If you want to see the gory details, as of Elasticsearch 1.2 you can turn
on lucene.iw: TRACE in config/logging.yml to see when merges run, which
segments, how many deletes those segments had, etc.

Mike

http://blog.mikemccandless.com


On Thu, Jun 5, 2014 at 9:12 AM, Shannon Monasco <smona...@gmail.com> wrote:

> I haven't changed my merge settings.  How often should segments be created
> and how often should merges happen naturally?
> On Jun 4, 2014 4:58 PM, "Ivan Brusic" <i...@brusic.com> wrote:
>
>>  Lucene will hold onto deleted documents until a merged is performed. An
>> update in Lucene is basically an atomic delete/insert.
>>
>> An optimize will help reclaim the space used by deleted documents. Did
>> you change your merge settings? Deleted documents should eventually be
>> removed whenever new segments are created.
>>
>> Cheers,
>>
>> Ivan
>>
>>
>> On Tue, Jun 3, 2014 at 8:54 AM, smonasco <smona...@gmail.com> wrote:
>>
>>> I'm starting a project to index log files.  I don't particularly want to
>>> wait until the log files roll over.  There will be files from 100's of apps
>>> running across 100's of machines (not all apps intersect with all machines,
>>> but you get the drift).  Some roll over very fast; some may take days.
>>>
>>> The problem comes that if I am constantly reindexing the same document
>>> (same id) am I loosing all old space (store and or index) or is
>>> Elasticsearch/Lucene smart enough to say here's a new version we'll
>>> overwrite the old store/index entries and point to this one where they are
>>> the same and add new ones.
>>>
>>> Certainly, there is a more sophisticated model that treats every line as
>>> a unique document/row such that this doesn't become an issue, but I'm not
>>> ready to spend that kind of dev and hardware at this issue.  (Our
>>> elasticsearch solution is wrapped in a system that becomes really heavy
>>> handed when indexing such small pieces.)
>>>
>>> --Shannon Monasco
>>>
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