【02】把 Elasticsearch 当数据库使：过滤和排序

使用 https://github.com/taowen/es-monitor 可以用 SQL 进行 elasticsearch 的查询。本章介绍简单的文档过滤条件

exchange='nyse'

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol where exchange='nyse' limit 1
EOF
{"sector": "n/a", "_type": "symbol", "market_cap": 4469064, "name": "3D Systems Corporation", "exchange": "nyse", "symbol": "DDD", "last_sale": 807, "_index": "symbol", "ipo_year": null, "_id": "AVLqbUjEQ3iIyyVFLQgV", "industry": "Technology"}

Elasticsearch

{"query": {"term": {"exchange": "nyse"}}, "size": 1
}
{"hits": {"hits": [{"_score": 1.728313, "_type": "symbol", "_id": "AVLqbUjEQ3iIyyVFLQgV", "_source": {"sector": "n/a", "market_cap": 4469064, "name": "3D Systems Corporation", "exchange": "nyse", "symbol": "DDD", "last_sale": 807, "ipo_year": null, "industry": "Technology"}, "_index": "symbol"}], "total": 3240, "max_score": 1.728313}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 6, "timed_out": false
}

Profile

[{"query": [{"query_type": "TermQuery","lucene": "exchange:nyse","time": "2.336230000ms","breakdown": {"score": 470159,"create_weight": 417360,"next_doc": 786055,"match": 0,"build_scorer": 662656,"advance": 0}}],"rewrite_time": 3566,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "1.561495000ms"}]}
]

exchange='nyse' AND sector='Technology'

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol where exchange='nyse' and sector='Technology' limit 1
EOF
{"sector": "Technology", "_type": "symbol", "market_cap": 4469064, "name": "3D Systems Corporation", "exchange": "nyse", "symbol": "DDD", "last_sale": 807, "_index": "symbol", "ipo_year": null, "_id": "AVLqdtWhQ3iIyyVFLSJQ", "industry": "Computer Software: Prepackaged Software"}

Elasticsearch

{"query": {"bool": {"filter": [{"term": {"exchange": "nyse"}}, {"term": {"sector": "Technology"}}]}}, "size": 1
}
{"hits": {"hits": [{"_score": 0.0, "_type": "symbol", "_id": "AVLqdtWhQ3iIyyVFLSJQ", "_source": {"sector": "Technology", "market_cap": 4469064, "name": "3D Systems Corporation", "exchange": "nyse", "symbol": "DDD", "last_sale": 807, "ipo_year": null, "industry": "Computer Software: Prepackaged Software"}, "_index": "symbol"}], "total": 186, "max_score": 0.0}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 5, "timed_out": false
}

Profile

[{"query": [{"query_type": "BooleanQuery","lucene": "#exchange:nyse #sector:Technology","time": "3.999703000ms","breakdown": {"score": 54437,"create_weight": 413531,"next_doc": 1213355,"match": 0,"build_scorer": 736504,"advance": 0},"children": [{"query_type": "TermQuery","lucene": "exchange:nyse","time": "1.175638000ms","breakdown": {"score": 0,"create_weight": 186745,"next_doc": 0,"match": 0,"build_scorer": 616840,"advance": 372053}},{"query_type": "TermQuery","lucene": "sector:Technology","time": "0.4062380000ms","breakdown": {"score": 0,"create_weight": 125321,"next_doc": 115632,"match": 0,"build_scorer": 45136,"advance": 120149}}]}],"rewrite_time": 23008,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "0.1031780000ms"}]}
]

last_sale > 985

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol where last_sale > 985 limit 1
EOF
{"sector": "Finance", "_type": "symbol", "market_cap": 42010000, "name": "1347 Capital Corp.", "exchange": "nasdaq", "symbol": "TFSCU", "last_sale": 1005, "_index": "symbol", "ipo_year": 2014, "_id": "AVLqdtWdQ3iIyyVFLRZB", "industry": "Business Services"}

Elasticsearch

{"query": {"range": {"last_sale": {"gt": 985.0}}}, "size": 1
}
{"hits": {"hits": [{"_score": 1.0, "_type": "symbol", "_id": "AVLqdtWdQ3iIyyVFLRZB", "_source": {"sector": "Finance", "market_cap": 42010000, "name": "1347 Capital Corp.", "exchange": "nasdaq", "symbol": "TFSCU", "last_sale": 1005, "ipo_year": 2014, "industry": "Business Services"}, "_index": "symbol"}], "total": 4285, "max_score": 1.0}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 2, "timed_out": false
}

Profile

[{"query": [{"query_type": "MultiTermQueryConstantScoreWrapper","lucene": "last_sale:{985 TO *]","time": "4.684710000ms","breakdown": {"score": 423966,"create_weight": 21384,"next_doc": 469032,"match": 0,"build_scorer": 3770328,"advance": 0}}],"rewrite_time": 10493,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "1.261998000ms"}]}
]

last_sale != 985

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol where last_sale != 985 limit 1
EOF
{"sector": "Finance", "_type": "symbol", "market_cap": null, "name": "1347 Capital Corp.", "exchange": "nasdaq", "symbol": "TFSCR", "last_sale": 16, "_index": "symbol", "ipo_year": 2014, "_id": "AVLqdtWdQ3iIyyVFLRZA", "industry": "Business Services"}

Elasticsearch

{"query": {"bool": {"must_not": {"term": {"last_sale": 985}}}}, "size": 1
}
{"hits": {"hits": [{"_score": 1.0, "_type": "symbol", "_id": "AVLqdtWdQ3iIyyVFLRZA", "_source": {"sector": "Finance", "market_cap": null, "name": "1347 Capital Corp.", "exchange": "nasdaq", "symbol": "TFSCR", "last_sale": 16, "ipo_year": 2014, "industry": "Business Services"}, "_index": "symbol"}], "total": 6708, "max_score": 1.0}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 1, "timed_out": false
}

Profile

[{"query": [{"query_type": "BooleanQuery","lucene": "+*:* -last_sale: Y","time": "14.10871500ms","breakdown": {"score": 3397824,"create_weight": 401619,"next_doc": 7993655,"match": 0,"build_scorer": 141022,"advance": 0},"children": [{"query_type": "MatchAllDocsQuery","lucene": "*:*","time": "1.694079000ms","breakdown": {"score": 974401,"create_weight": 5175,"next_doc": 705676,"match": 0,"build_scorer": 8827,"advance": 0}},{"query_type": "TermQuery","lucene": "last_sale: Y","time": "0.4805160000ms","breakdown": {"score": 0,"create_weight": 342905,"next_doc": 0,"match": 0,"build_scorer": 104919,"advance": 32692}}]}],"rewrite_time": 32619,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "4.604778000ms"}]}
]

exchange='nyse' AND NOT sector='Technology'

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol where exchange='nyse' AND NOT sector='Technology' limit 1
EOF
{"sector": "Health Care", "_type": "symbol", "market_cap": 3865437245, "name": "3M Company", "exchange": "nyse", "symbol": "MMM", "last_sale": 15244, "_index": "symbol", "ipo_year": null, "_id": "AVLqdtWhQ3iIyyVFLSJR", "industry": "Medical/Dental Instruments"}

Elasticsearch

{"query": {"bool": {"filter": [{"term": {"exchange": "nyse"}}], "must_not": [{"term": {"sector": "Technology"}}]}}, "size": 1
}
{"hits": {"hits": [{"_score": 0.0, "_type": "symbol", "_id": "AVLqdtWhQ3iIyyVFLSJR", "_source": {"sector": "Health Care", "market_cap": 3865437245, "name": "3M Company", "exchange": "nyse", "symbol": "MMM", "last_sale": 15244, "ipo_year": null, "industry": "Medical/Dental Instruments"}, "_index": "symbol"}], "total": 3054, "max_score": 0.0}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 5, "timed_out": false
}

Profile

[{"query": [{"query_type": "BooleanQuery","lucene": "#exchange:nyse -sector:Technology","time": "3.078346000ms","breakdown": {"score": 164364,"create_weight": 216094,"next_doc": 1872817,"match": 0,"build_scorer": 114716,"advance": 0},"children": [{"query_type": "TermQuery","lucene": "exchange:nyse","time": "0.4679310000ms","breakdown": {"score": 0,"create_weight": 119897,"next_doc": 290703,"match": 0,"build_scorer": 57331,"advance": 0}},{"query_type": "TermQuery","lucene": "sector:Technology","time": "0.2424240000ms","breakdown": {"score": 0,"create_weight": 62239,"next_doc": 0,"match": 0,"build_scorer": 32978,"advance": 147207}}]}],"rewrite_time": 19262,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "0.5360760000ms"}]}
]

exchange='nyse' OR NOT sector='Technology'

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol where exchange='nyse' OR NOT sector='Technology' limit 1
EOF
{"sector": "Health Care", "_type": "symbol", "market_cap": 3865437245, "name": "3M Company", "exchange": "nyse", "symbol": "MMM", "last_sale": 15244, "_index": "symbol", "ipo_year": null, "_id": "AVLqdtWhQ3iIyyVFLSJR", "industry": "Medical/Dental Instruments"}

Elasticsearch

{"query": {"bool": {"should": [{"term": {"exchange": "nyse"}}, {"bool": {"must_not": [{"term": {"sector": "Technology"}}]}}]}}, "size": 1
}
{"hits": {"hits": [{"_score": 0.99838185, "_type": "symbol", "_id": "AVLqdtWhQ3iIyyVFLSJR", "_source": {"sector": "Health Care", "market_cap": 3865437245, "name": "3M Company", "exchange": "nyse", "symbol": "MMM", "last_sale": 15244, "ipo_year": null, "industry": "Medical/Dental Instruments"}, "_index": "symbol"}], "total": 6245, "max_score": 0.99838185}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 9, "timed_out": false
}

Profile

[{"query": [{"query_type": "BooleanQuery","lucene": "exchange:nyse (-sector:Technology +*:*)","time": "21.24846700ms","breakdown": {"score": 4197895,"create_weight": 815882,"next_doc": 5963510,"match": 0,"build_scorer": 3902610,"advance": 0},"children": [{"query_type": "TermQuery","lucene": "exchange:nyse","time": "1.099460000ms","breakdown": {"score": 219612,"create_weight": 529960,"next_doc": 266196,"match": 0,"build_scorer": 83692,"advance": 0}},{"query_type": "BooleanQuery","lucene": "-sector:Technology +*:*","time": "5.269110000ms","breakdown": {"score": 1221522,"create_weight": 209290,"next_doc": 1693148,"match": 0,"build_scorer": 521166,"advance": 0},"children": [{"query_type": "TermQuery","lucene": "sector:Technology","time": "0.6576720000ms","breakdown": {"score": 0,"create_weight": 141704,"next_doc": 0,"match": 0,"build_scorer": 274371,"advance": 241597}},{"query_type": "MatchAllDocsQuery","lucene": "*:*","time": "0.9663120000ms","breakdown": {"score": 441766,"create_weight": 5317,"next_doc": 508525,"match": 0,"build_scorer": 10704,"advance": 0}}]}]}],"rewrite_time": 61389,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "4.847758000ms"}]}
]

date > now() - INTERVAL '60 DAYS'

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from quote where "date" > now() - interval '30 DAYS' limit 1
EOF

这个 now() 和 interval 的语法是和postgresql一致的（http://www.postgresql.org/docs/9.1/static/functions-datetime.html）

{"volume": 118900, "_type": "quote", "_index": "quote", "symbol": "AMRS", "adj_close": 147, "high": 149, "low": 138, "date": "2016-02-16", "close": 147, "_id": "AMRS-2016-02-16", "open": 140}

Elasticsearch

{"query": {"range": {"date": {"gt": 1453212988000}}}, "size": 1
}

查询是和普通的大于一样的。

symbol LIKE 'AAP%'

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol WHERE symbol LIKE 'AAP%'
EOF
{"sector": "Technology", "_type": "symbol", "market_cap": 522690000000, "name": "Apple Inc.", "exchange": "nasdaq", "symbol": "AAPL", "last_sale": 9427, "_index": "symbol", "ipo_year": 1980, "_id": "AVL0FqFJog4u0JP7lzka", "industry": "Computer Manufacturing"}
{"sector": "Finance", "_type": "symbol", "market_cap": 105960000, "name": "Atlantic Alliance Partnership Corp.", "exchange": "nasdaq", "symbol": "AAPC", "last_sale": 1019, "_index": "symbol", "ipo_year": 2015, "_id": "AVL0FqFJog4u0JP7lzlf", "industry": "Business Services"}
{"sector": "Consumer Services", "_type": "symbol", "market_cap": 148395246, "name": "Advance Auto Parts Inc", "exchange": "nyse", "symbol": "AAP", "last_sale": 13857, "_index": "symbol", "ipo_year": null, "_id": "AVL0FqFQog4u0JP7l0R7", "industry": "Other Specialty Stores"}

Elasticsearch

{"query": {"wildcard": {"symbol": "AAP*"}}
}
{"hits": {"hits": [{"_score": 1.0, "_type": "symbol", "_id": "AVL0FqFJog4u0JP7lzka", "_source": {"sector": "Technology", "market_cap": 522690000000, "name": "Apple Inc.", "exchange": "nasdaq", "symbol": "AAPL", "last_sale": 9427, "ipo_year": 1980, "industry": "Computer Manufacturing"}, "_index": "symbol"}, {"_score": 1.0, "_type": "symbol", "_id": "AVL0FqFJog4u0JP7lzlf", "_source": {"sector": "Finance", "market_cap": 105960000, "name": "Atlantic Alliance Partnership Corp.", "exchange": "nasdaq", "symbol": "AAPC", "last_sale": 1019, "ipo_year": 2015, "industry": "Business Services"}, "_index": "symbol"}, {"_score": 1.0, "_type": "symbol", "_id": "AVL0FqFQog4u0JP7l0R7", "_source": {"sector": "Consumer Services", "market_cap": 148395246, "name": "Advance Auto Parts Inc", "exchange": "nyse", "symbol": "AAP", "last_sale": 13857, "ipo_year": null, "industry": "Other Specialty Stores"}, "_index": "symbol"}], "total": 3, "max_score": 1.0}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 29, "timed_out": false
}

Profile

[{"query": [{"query_type": "MultiTermQueryConstantScoreWrapper","lucene": "symbol:AAP*","time": "5.018644000ms","breakdown": {"score": 3186,"create_weight": 34308,"next_doc": 31760,"match": 0,"build_scorer": 4949390,"advance": 0}},{"query_type": "BooleanQuery","lucene": "symbol:AAP symbol:AAPC symbol:AAPL","time": "4.731495000ms","breakdown": {"score": 0,"create_weight": 205709,"next_doc": 26459,"match": 0,"build_scorer": 4299185,"advance": 0},"children": [{"query_type": "TermQuery","lucene": "symbol:AAP","time": "0.09350600000ms","breakdown": {"score": 0,"create_weight": 15337,"next_doc": 4021,"match": 0,"build_scorer": 74148,"advance": 0}},{"query_type": "TermQuery","lucene": "symbol:AAPC","time": "0.07045600000ms","breakdown": {"score": 0,"create_weight": 6874,"next_doc": 1225,"match": 0,"build_scorer": 62357,"advance": 0}},{"query_type": "TermQuery","lucene": "symbol:AAPL","time": "0.03618000000ms","breakdown": {"score": 0,"create_weight": 4934,"next_doc": 1253,"match": 0,"build_scorer": 29993,"advance": 0}}]}],"rewrite_time": 25703,"collector": [{"name": "SimpleTopScoreDocCollector","reason": "search_top_hits","time": "0.04072600000ms"}]}
]}
]

从profile结果可以看出，所谓的LIKE查询，其实不是一个个去查文档。而是先从字典表里把这个字段的所有的符合LIKE条件的term查出来，然后去查满足这些term的文档。把LIKE变成一堆=条件的OR来处理的。

ORDER BY name

SQL

$ cat << EOF | ./es_query.py http://127.0.0.1:9200
select * from symbol order by name limit 1
EOF
{"sector": "n/a", "_type": "symbol", "market_cap": 72460000, "name": "iShares 0-5 Year Investment Grade Corporate Bond ETF", "exchange": "nasdaq", "symbol": "SLQD", "last_sale": 4997, "_index": "symbol", "ipo_year": null, "_id": "AVLqdtWfQ3iIyyVFLRwf", "industry": "n/a"}

Elasticsearch

{"sort": [{"name": "asc"}], "size": 1
}
{"hits": {"hits": [{"sort": ["0"], "_type": "symbol", "_source": {"sector": "n/a", "market_cap": 72460000, "name": "iShares 0-5 Year Investment Grade Corporate Bond ETF", "exchange": "nasdaq", "symbol": "SLQD", "last_sale": 4997, "ipo_year": null, "industry": "n/a"}, "_score": null, "_index": "symbol", "_id": "AVLqdtWfQ3iIyyVFLRwf"}], "total": 6714, "max_score": null}, "_shards": {"successful": 1, "failed": 0, "total": 1}, "took": 4, "timed_out": false
}

Profile

[{"query": [{"query_type": "MatchAllDocsQuery","lucene": "*:*","time": "1.379354000ms","breakdown": {"score": 0,"create_weight": 32506,"next_doc": 850386,"match": 0,"build_scorer": 496462,"advance": 0}}],"rewrite_time": 18167,"collector": [{"name": "SimpleFieldCollector","reason": "search_top_hits","time": "1.225077000ms"}]}
]

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