Thanks guys!
On Jun 5, 2014 7:17 AM, "Michael McCandless" <
[email protected]> wrote:

> 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 <[email protected]>
> 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" <[email protected]> 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 <[email protected]> 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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