Hello Henrik, My guess would be that the timeouts you are seeing in python are causing this - when the python client encounters a timeout, it retries the request, thinking something went wrong. Thus if your timeout is too small it can actually lead to spamming the cluster - when the python client encounters a timeout the request is still running in the server so each retry will spawn another bulk request being processed.
The solution should be to make the timeout for your python client higher. I am starting to consider this a bug so I created a ticket to fix it, you can track it on github: https://github.com/elasticsearch/elasticsearch-py/issues/128 Hope this helps, Honza On Tue, Sep 23, 2014 at 9:48 PM, Henrik Ossipoff Hansen <henrik.ossip...@gmail.com> wrote: > We're currently working with re-indexing one of our indexes on one of our > test servers, and we appear to be having issues. The operation should be > fairly obvious, and there's not a lot of data -- around 320.000 total > documents in the index, at around 1.15GB of data. We scan from the old > index, and bulk index 1000 documents at a time (we've also tried 500 > documents at a time to no avail). Since our production indexes are more > around the 30GB size, we're a bit discouraged by hitting this wall. > > Once in a while, we get a random "resource not available" error, but they > usually resolves themselves and go away -- however, after indexing around > 260.000 documents, the Python script starts behaving weirdly, throwing a lot > of resource not available errors. A full gist is here: > https://gist.github.com/HenrikOssipoff/ac63060d4c18182719dd (note that this > is Python 3.4, so chained exceptions and everything -- the top exception is > not actually the important one). > > Now, thing is. During this time, Elasticsearch itself seems fine, and the > system is generally available for querying. The JVM heap is fine, and the > Elasticsearch log itself has absolutely no warnings or errors (log level > INFO enabled). > > Our next course of action will be try to doing this by just cURLs outside of > Python, or even enabling debug logging in Elasticsearch, but we wanted to > see if anyone has some ideas for what could be the course. > > It seems logical, that since it only happens every one in a while, and gets > worse the more documents we index, it has something to do with the amount of > _bulk indexes we do, but we can't seem to find anything in logs or stats > that support this. > > Any help appreciated, or any pointers in the right direction. > > Thank you! > > Regards, > Henrik Ossipoff Hansen > > -- > You received this message because you are subscribed to the Google Groups > "elasticsearch" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to elasticsearch+unsubscr...@googlegroups.com. > To view this discussion on the web visit > https://groups.google.com/d/msgid/elasticsearch/2afa6d99-b9d4-42a2-9f4e-b717a3a41251%40googlegroups.com. > For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to elasticsearch+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/CABfdDioPUGyaJQmOXPv9SUoTfynDbTfnvfAQnrQGGhE_NVr1GA%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
