使用 https://github.com/taowen/es-monitor 可以用 SQL 進行 elasticsearch 的查詢。今天需要做一些最簡單的聚合查詢

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 }

這個就不算聚合，只是看了一下最終滿足過濾條件的 total hits count。

COUNT(ipo_year)

這個和 COUNT(*) 的區(qū)別是 COUNT(ipo_year) 要求字段必須有值才算一個。

$ 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"}]}]} ]

這是我們的第一個聚合例子?？梢詮膒rofile結(jié)果看出來，其實現(xiàn)方式在采集文檔的時候加上了ValueCountAggregator統(tǒng)計了字段非空的文檔數(shù)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"}]}]} ]

這個例子里 ValueCountAggregator 變成了 CardinalityAggregator

SUM(market_cap)

MIN/MAX/AVG/SUM 這幾個簡單的聚合也是支持的

$ 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"}]}]} ]

過濾 + 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 過濾完，然后再計算 aggs

總結(jié)

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