使用pyes进行弹性搜索 [英] elastic search performance using pyes

问题描述

很抱歉交叉发布.以下问题也发布在Elastic Search的Google网上论坛上.

Sorry for cross posting.The following question is also posted on Elastic Search's google group.

简而言之，我试图找出为什么在包含约1.5密耳记录的ES索引上进行搜索时无法获得最佳性能的原因.

In short I am trying to find out why I am not able to get optimal performance while doing searches on a ES index which contains about 1.5 millon records.

目前，我能够在2秒内获得大约500-1000次搜索.我认为这应该快几个数量级.另外，目前我不使用节俭.

Currently I am able to get about 500-1000 searches in 2 seconds. I would think that this should be orders of magnitudes faster. Also currently I am not using thrift.

这是我检查效果的方式.

Here is how I am checking the performance.

使用pyes的0.19.1版本(从github尝试了稳定版和开发版)使用0.13.8版本的请求

Using 0.19.1 version of pyes (tried both stable and dev version from github) Using 0.13.8 version of requests

conn = ES(['localhost:9201'],timeout=20,bulk_size=1000)
loop_start = time.clock()
q1 = TermQuery("tax_name","cellvibrio")
for x in xrange(1000000):
    if x % 1000 == 0 and x > 0:
        loop_check_point = time.clock()
        print 'took %s secs to search %d records' % (loop_check_point-loop_start,x)

    results = conn.search(query=q1)
    if results:
        for r in results:
            pass
#            print len(results)
    else:
        pass

感谢您可以提供的任何帮助，以帮助我扩大搜索范围.

Appreciate any help that you can give to help me scaleup the searches.

谢谢！

推荐答案

不仅仅是并发吗?

您正在按顺序执行所有查询.因此，查询必须先完成，然后才能进行下一个查询.如果您对服务器的RTT为1毫秒，则每秒将请求数限制为1000.

You're doing all your queries in sequence. So a query has to finish before the next one can come in to play. If you have a 1ms RTT to the server, this will limit you to 1000 requests per second.

尝试并行运行脚本的几个实例，看看所获得的性能如何.

Try to run a few instances of your script in parallel and see what kind of performance you got.

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