“搜索API"和统计信息组 [英] "Search APIs" and stats groups
问题描述
在搜索API 中，有一个部分将统计信息组称为:
In Search APIs there is a section called Stats groups as:
搜索可以与统计信息组相关联，从而维护每个组的统计汇总.以后可以使用indexs stats API专门检索它.例如，这是一个搜索主体请求，该请求将请求与两个不同的组相关联:
A search can be associated with stats groups, which maintains a statistics aggregation per group. It can later be retrieved using the indices stats API specifically. For example, here is a search body request that associate the request with two different groups:
{
"query" : {
"match_all" : {}
},
"stats" : ["group1", "group2"]
}
我的问题是，什么是 stat组，我们如何创建它们以及在哪里使用它们?
My question is, what is a stat group, how do we create them, and where are they used?
似乎这些组与 _stats 有关.正如@evanv所提到的，在索引统计.但是该文档并未说明如何创建组.另外，我找不到使用 _search API的方法.我说，但是，使用 _stats 下的 search 可以得到一些东西，
It seems these groups are related to _stats. As @evanv mentioned, there's a bit more of an explanation under Index stats. But that document doesn't explain how to create groups. Also, I can't find a way to use those using _search API. I cound, however, get something using the search under _stats using:
GET /_stats/search?groups=search,indexing
所以我的问题仍然存在:
So my questions are still there:
- 如何与
_searchAPI一起使用? - 我如何理解这些组中报告的数字?
- 如何创建一个组?如果那样的话！
- how do I use this with
_searchAPI? - how do I make sense of the numbers reported in these groups?
- how do I create a group? If that makes sense!
似乎您可以通过在操作中包含 stats 参数来创建这些组.例如，如果我提交此查询5次:
It seems you create those groups by including the stats parameter in your operation. For instance, if I submit this query 5 times:
GET /twitter/tweet/_search
{
"query": {
"match_all": {
}
},
"stats": [
"makes_no_sense"
]
}
如果尚不存在的话，它将创建一个新的组，称为"makes_no_sense"，将该操作合并到该组中，然后当我得到索引的统计信息时:
It will create a new group if it does't already exist, called "makes_no_sense", acossiates the operation to that group, and then when I get the stats of the index as:
GET /_stats/search?groups=makes_no_sense
响应将在 search 下将 makes_no_sense 作为一个组，包括:
the response would include makes_no_sense as a group under search, as:
{
"_shards": {
"total": 43,
"successful": 22,
"failed": 0
},
"_all": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 37983,
"query_time_in_millis": 2695,
"query_current": 0,
"fetch_total": 37796,
"fetch_time_in_millis": 1472,
"fetch_current": 0,
"scroll_total": 5,
"scroll_time_in_millis": 266,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0,
"groups": {
"makes_no_sense": {
"query_total": 5,
"query_time_in_millis": 0,
"query_current": 0,
"fetch_total": 5,
"fetch_time_in_millis": 0,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 37983,
"query_time_in_millis": 2695,
"query_current": 0,
"fetch_total": 37796,
"fetch_time_in_millis": 1472,
"fetch_current": 0,
"scroll_total": 5,
"scroll_time_in_millis": 266,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0,
"groups": {
"makes_no_sense": {
"query_total": 5,
"query_time_in_millis": 0,
"query_current": 0,
"fetch_total": 5,
"fetch_time_in_millis": 0,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
}
}
},
"indices": {
"bank": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 180,
"query_time_in_millis": 369,
"query_current": 0,
"fetch_total": 71,
"fetch_time_in_millis": 35,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 180,
"query_time_in_millis": 369,
"query_current": 0,
"fetch_total": 71,
"fetch_time_in_millis": 35,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
},
"twitter": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 19,
"query_time_in_millis": 1,
"query_current": 0,
"fetch_total": 19,
"fetch_time_in_millis": 0,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0,
"groups": {
"makes_no_sense": {
"query_total": 5,
"query_time_in_millis": 0,
"query_current": 0,
"fetch_total": 5,
"fetch_time_in_millis": 0,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 19,
"query_time_in_millis": 1,
"query_current": 0,
"fetch_total": 19,
"fetch_time_in_millis": 0,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0,
"groups": {
"makes_no_sense": {
"query_total": 5,
"query_time_in_millis": 0,
"query_current": 0,
"fetch_total": 5,
"fetch_time_in_millis": 0,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
}
}
},
"test": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 45,
"query_time_in_millis": 6,
"query_current": 0,
"fetch_total": 10,
"fetch_time_in_millis": 1,
"fetch_current": 0,
"scroll_total": 5,
"scroll_time_in_millis": 266,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 45,
"query_time_in_millis": 6,
"query_current": 0,
"fetch_total": 10,
"fetch_time_in_millis": 1,
"fetch_current": 0,
"scroll_total": 5,
"scroll_time_in_millis": 266,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
},
".kibana": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 37689,
"query_time_in_millis": 2303,
"query_current": 0,
"fetch_total": 37688,
"fetch_time_in_millis": 1386,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 37689,
"query_time_in_millis": 2303,
"query_current": 0,
"fetch_total": 37688,
"fetch_time_in_millis": 1386,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
},
"blogs": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 40,
"query_time_in_millis": 11,
"query_current": 0,
"fetch_total": 6,
"fetch_time_in_millis": 1,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 40,
"query_time_in_millis": 11,
"query_current": 0,
"fetch_total": 6,
"fetch_time_in_millis": 1,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
},
"customer": {
"primaries": {
"search": {
"open_contexts": 0,
"query_total": 10,
"query_time_in_millis": 5,
"query_current": 0,
"fetch_total": 2,
"fetch_time_in_millis": 49,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
},
"total": {
"search": {
"open_contexts": 0,
"query_total": 10,
"query_time_in_millis": 5,
"query_current": 0,
"fetch_total": 2,
"fetch_time_in_millis": 49,
"fetch_current": 0,
"scroll_total": 0,
"scroll_time_in_millis": 0,
"scroll_current": 0,
"suggest_total": 0,
"suggest_time_in_millis": 0,
"suggest_current": 0
}
}
}
}
}
现在我的问题是:
- 如何在其他操作(例如创建/更新/删除)中使用/创建那些组?
推荐答案
它们是在每个索引级别维护的计数器和元数据的混合.如果您有一个索引"foo"，然后转到 localhost:9200/foo/_stats?pretty& human ，则会看到大量有关该索引的大小，搜索请求数量的信息已发布给索引，有多少个获取请求，为该索引缓存了多少数据等.要创建统计信息组，您只需添加
They are a mix of counters and metadata that are maintained on a per index level. If you have an index "foo" and you go to localhost:9200/foo/_stats?pretty&human, you'll see a bunch of information about how big the index is, how many search requests have been issued to the index, how many get requests, how much data is cached for that index, etc. To create a stats group, you can simply include
"stats" : ["stat_1", "stat_2", .... "stat_n"]
在您的请求中.
当您访问 localhost:9200/foo/_stats?pretty& human 时，您会在已定义的统计信息组上看到统计信息.
And when you visit localhost:9200/foo/_stats?pretty&human, you'll see stats on the stats groups you've defined.
You can learn more about the metrics that are stored here: https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-stats.html
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