elasticsearch中的聚合查询统计实例
今天需要做一些最简单的聚合查询
COUNT(*)
SQL
$ cat << EOF | ./es_query.py http://127.0.0.1:9200 select count(*) from quote EOF
{"count(*)": 20994400}
Elasticsearch
{ "aggs": {}, "size": 0 }
{ "hits": { "hits": [], "total": 20994400, "max_score": 0.0 }, "_shards": { "successful": 1, "failed": 0, "total": 1 }, "took": 26, "timed_out": false }
这个就不算聚合,只是看了一下最终满足过滤条件的 total hits count。
COUNT(ipo_year)
这个和 COUNT(*) 的区别是 COUNT(ipo_year) 要求字段必须有值才算一个。
$ cat << EOF | ./es_query.py http://127.0.0.1:9200 select count(ipo_year) from symbol EOF
{"count(ipo_year)": 2898}
Elasticsearch
{ "aggs": { "count(ipo_year)": { "value_count": { "field": "ipo_year" } } }, "size": 0 }
{ "hits": { "hits": [], "total": 6714, "max_score": 0.0 }, "_shards": { "successful": 1, "failed": 0, "total": 1 }, "took": 55, "aggregations": { "count(ipo_year)": { "value": 2898 } }, "timed_out": false }
Profile
[ { "query": [ { "query_type": "MatchAllDocsQuery", "lucene": "*:*", "time": "0.3204170000ms", "breakdown": { "score": 0, "create_weight": 10688, "next_doc": 278660, "match": 0, "build_scorer": 31069, "advance": 0 } } ], "rewrite_time": 2279, "collector": [ { "name": "MultiCollector", "reason": "search_multi", "time": "2.957183000ms", "children": [ { "name": "TotalHitCountCollector", "reason": "search_count", "time": "0.2319240000ms" }, { "name": "ValueCountAggregator: [count(ipo_year)]", "reason": "aggregation", "time": "1.999916000ms" } ] } ] } ]
这是我们的第一个聚合例子。可以从profile结果看出来,其实现方式在采集文档的时候加上了ValueCountAggregator统计了字段非空的文档数量。
COUNT(DISTINCT ipo_year)
SQL
$ cat << EOF | ./es_query.py http://127.0.0.1:9200 select count(distinct ipo_year) from symbol EOF
{"count(distinct ipo_year)": 39}
Elasticsearch
{ "aggs": { "count(distinct ipo_year)": { "cardinality": { "field": "ipo_year" } } }, "size": 0 }
{ "hits": { "hits": [], "total": 6714, "max_score": 0.0 }, "_shards": { "successful": 1, "failed": 0, "total": 1 }, "took": 24, "aggregations": { "count(distinct ipo_year)": { "value": 39 } }, "timed_out": false }
Profile
[ { "query": [ { "query_type": "MatchAllDocsQuery", "lucene": "*:*", "time": "0.2033600000ms", "breakdown": { "score": 0, "create_weight": 7501, "next_doc": 162905, "match": 0, "build_scorer": 32954, "advance": 0 } } ], "rewrite_time": 2300, "collector": [ { "name": "MultiCollector", "reason": "search_multi", "time": "2.438386000ms", "children": [ { "name": "TotalHitCountCollector", "reason": "search_count", "time": "0.2240230000ms" }, { "name": "CardinalityAggregator: [count(distinct ipo_year)]", "reason": "aggregation", "time": "1.471620000ms" } ] } ] } ]
这个例子里 ValueCountAggregator 变成了 CardinalityAggregator
SUM(market_cap)
MIN/MAX/AVG/SUM 这几个简单的聚合也是支持的
$ cat << EOF | ./es_query.py http://127.0.0.1:9200 select sum(market_cap) from symbol EOF
{"sum(market_cap)": 11454155180142.0}
Elasticsearch
{ "aggs": { "sum(market_cap)": { "sum": { "field": "market_cap" } } }, "size": 0 }
{ "hits": { "hits": [], "total": 6714, "max_score": 0.0 }, "_shards": { "successful": 1, "failed": 0, "total": 1 }, "took": 15, "aggregations": { "sum(market_cap)": { "value": 11454155180142.0 } }, "timed_out": false }
Profile
[ { "query": [ { "query_type": "MatchAllDocsQuery", "lucene": "*:*", "time": "0.2026870000ms", "breakdown": { "score": 0, "create_weight": 8097, "next_doc": 163069, "match": 0, "build_scorer": 31521, "advance": 0 } } ], "rewrite_time": 2151, "collector": [ { "name": "MultiCollector", "reason": "search_multi", "time": "2.461247000ms", "children": [ { "name": "TotalHitCountCollector", "reason": "search_count", "time": "0.3302140000ms" }, { "name": "SumAggregator: [sum(market_cap)]", "reason": "aggregation", "time": "1.102363000ms" } ] } ] } ]
过滤 + 聚合
SQL
$ cat << EOF | ./es_query.py http://127.0.0.1:9200 select sum(market_cap) from symbol where ipo_year=1998 EOF
{"sum(market_cap)": 107049150786.0}
Elasticsearch
{ "query": { "term": { "ipo_year": 1998 } }, "aggs": { "sum(market_cap)": { "sum": { "field": "market_cap" } } }, "size": 0 }
{ "hits": { "hits": [], "total": 56, "max_score": 0.0 }, "_shards": { "successful": 1, "failed": 0, "total": 1 }, "took": 11, "aggregations": { "sum(market_cap)": { "value": 107049150786.0 } }, "timed_out": false }
Profile
[ { "query": [ { "query_type": "TermQuery", "lucene": "ipo_year:`N", "time": "0.4526400000ms", "breakdown": { "score": 0, "create_weight": 220579, "next_doc": 159412, "match": 0, "build_scorer": 72649, "advance": 0 } } ], "rewrite_time": 3750, "collector": [ { "name": "MultiCollector", "reason": "search_multi", "time": "0.2203470000ms", "children": [ { "name": "TotalHitCountCollector", "reason": "search_count", "time": "0.009478000000ms" }, { "name": "SumAggregator: [sum(market_cap)]", "reason": "aggregation", "time": "0.1557820000ms" } ] } ] } ]
query 过滤完,然后再计算 aggs