Jörg, thanks for the plugin to help as a starting point for plugin
development.

Although I have built a few plugins during the years, they were river or
analysis plugins, which are fairly easy. Writing a custom action required a
lot more digging, especially since there are very few to learn from. I
still would like to see a write-up regarding the different families of
transport actions: BroadcastOperationRequest,
MasterNodeOperationRequest, NodesOperationRequest,
SingleShardOperationRequest, SingleCustomOperationRequest,
etc. What is the difference? I understand it now, but it should be
documented. There is little documentation about the internals and there are
no code level comments.  I always meant to experiment with the different
action hierarchies via simple plugins and document my findings. Perhaps one
day...

Cheers,

Ivan


On Wed, Jun 4, 2014 at 1:09 AM, [email protected] <[email protected]
> wrote:

> Sorry, the plugin is outdated, a better start is by looking at
>
>
> http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/index-modules-similarity.html
>
> Jörg
>
>
> On Wed, Jun 4, 2014 at 10:07 AM, [email protected] <
> [email protected]> wrote:
>
>> You need resources on all nodes that hold shards, you can not do it with
>> just one instance, because ES index is distributed. Rescoring would be very
>> expensive if you did it on an extra central instance with an extra
>> scatter/gather phase. It is also very expensive in scripting.
>>
>> A better method is a similarity plugin like
>> https://github.com/tlrx/elasticsearch-custom-similarity-provider
>>
>> Not sure how your code looks like though, maybe you can share it with the
>> community?
>>
>> Jörg
>>
>>
>>
>> On Wed, Jun 4, 2014 at 2:55 AM, virgil <[email protected]> wrote:
>>
>>> The problem is that only one copy of HashMap is needed to customize
>>> score of
>>> all documents in the cluster. But as we have to install the plugin on all
>>> nodes, the actual memory used is multiplied by the number of nodes in
>>> cluster. I try to figure out one way to save the memory. Tried on
>>> non-data
>>> node, but it seems not working.
>>>
>>>
>>>
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>>
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