0
在Search APIs有一个叫统计组为部分：“搜索API”和统计组
一个搜索可以用统计组相关联，它保持每组统计汇总。它可以稍后使用索引统计API特别检索。例如，下面是搜索的身体要求，即与两个不同的组请求关联的：
{
"query" : {
"match_all" : {}
},
"stats" : ["group1", "group2"]
}
我的问题是，什么是统计组，我们如何创建它们，以及它们在哪里使用？
编辑1：
看来这些组涉及_stats。正如@evanv所说，在Index stats下有更多的解释。但是，该文件不解释如何创建组。另外，我找不到使用_search API的方法。我cound，然而，使用使用search得到的东西_stats下：
GET /_stats/search?groups=search,indexing
所以我的问题依然存在：
- 我怎么使用这跟
_searchAPI？ - 我该如何理解这些群组中报告的数字？如何创建组？如果这是有道理的！
编辑2：
看来你通过在你的操作stats参数创建这些组。举例来说，如果我提交这个查询5次：
GET /twitter/tweet/_search
{
"query": {
"match_all": {
}
},
"stats": [
"makes_no_sense"
]
}
它将创建，如果它简化版，已经存在一个新的群体，被称为“makes_no_sense”，acossiates操作该组，然后当我得到的该指数的统计：
GET /_stats/search?groups=makes_no_sense
响应将包括makes_no_sense为search下一个组，如：
{
"_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：
- 我该如何在创建/更新/删除等操作中使用/创建那些组？