Could you add a counter in your JS app to make sure you sent all docs?
I suspect something wrong in your index process
--
David ;-)
Twitter : @dadoonet / @elasticsearchfr / @scrutmydocs
> Le 1 mai 2015 à 20:40, Blake McBride <blake1...@gmail.com> a écrit :
>
> The log only contains:
>
> [2015-05-01 18:22:10,398][INFO ][cluster.metadata ]
> [mmsapp-na-component] [components-1430504530354] creating index, cause [api],
> templates [], shards [5]/[1], mappings [index_name, component]
>
> Each document is being added individually from JavaScript via:
>
> exports.addDoc = function (index, type, id, doc, callback) {
> if (client !== undefined) {
> var json = {
> index: index,
> type: type,
> id: id,
> body: doc
> };
> client.create(json, callback);
> } else if (callback !== undefined) {
> callback('elastic search not connected', undefined);
> }
> };
>
>
>
>> On Friday, May 1, 2015 at 11:42:12 AM UTC-5, David Pilato wrote:
>> If you have nothing in logs it could mean that you have an issue with your
>> injector.
>> May be you are using bulk but you don't check the bulk response?
>>
>> David
>>
>>> Le 1 mai 2015 à 18:36, Blake McBride <blak...@gmail.com> a écrit :
>>>
>>> Greetings,
>>>
>>> I have two similar but unrelated machines. I am adding 50,000+ documents
>>> to each. Afterwards, one shows the 50,000+ documents and the other only
>>> shows 10,500. The second machine seems to be capping out at 10,500. Why,
>>> and how can I correct this? The relevant facts are as follows:
>>>
>>> 1. Both machines are current 64 bit Linux machines with at least 8GB of
>>> RAM and more than sufficient disk space.
>>>
>>> 2. Both have current 64 bit Java 7 and elasticsearch 1.5.1. ES is running
>>> local to each machine.
>>>
>>> 3. Both machines are running the exact same program to load up ES. Each
>>> has nearly default ES config files (just different names).
>>>
>>> 4. The program keeps a counter of the number of times documents are added
>>> to ES, and the return codes of each add is checked. Both are 50,000+.
>>>
>>> 5. When I do a the same query on each machine with curl, the good machine
>>> shows a max_score of 8.2, the bad machine shows .499 - remember, same set
>>> of documents and same search query.
>>>
>>>
>>> I've spent a day on this, and I am running out of ideas. Any help would
>>> sure be appreciated.
>>>
>>> Blake McBride
>>>
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