transportClient链接elasticsearch6.2.4报找不到可用节点

kobe 发起了问题 • 1 人关注 • 0 个回复 • 2811 次浏览 • 2018-05-21 17:18 • 来自相关话题

跨集群数据同步方案讨论

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luyuncheng 回复了问题 • 16 人关注 • 3 个回复 • 18556 次浏览 • 2019-04-11 11:33 • 来自相关话题

elasticSearch window启动提示不应有\common

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jianlam 回复了问题 • 5 人关注 • 4 个回复 • 5723 次浏览 • 2018-10-27 23:57 • 来自相关话题

ES的写入调优索引分片数量是根据大小来分配，还是文档数量多少来分配！？

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xiongchaochao 回复了问题 • 4 人关注 • 2 个回复 • 5647 次浏览 • 2018-05-22 09:36 • 来自相关话题

ES权威指南-取回一个文档疑问，求大神解答

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bill 回复了问题 • 4 人关注 • 2 个回复 • 3170 次浏览 • 2018-05-21 14:09 • 来自相关话题

【分享】想用ELK做日志分析的TX们可以参考啦~~~

hw_cloudsearch 发表了文章 • 1 个评论 • 3889 次浏览 • 2018-05-21 11:24 • 来自相关话题

https://forum.huaweicloud.com/thread-8494-1-1.html

Elasticsearch如何实现 SQL语句中 Group By 和 Limit 的功能

rockybean 发表了文章 • 2 个评论 • 19055 次浏览 • 2018-05-21 07:45 • 来自相关话题

有 SQL 背景的同学在学习 Elasticsearch 时，面对一个查询需求，不由自主地会先思考如何用 SQL 来实现，然后再去想 Elasticsearch 的 Query DSL 如何实现。那么本篇就给大家讲一条常见的 SQL 语句如何用 Elasticsearch 的查询语言实现。

1. SQL语句

假设我们有一个汽车的数据集，每个汽车都有车型、颜色等字段，我希望获取颜色种类大于1个的前2车型。假设汽车的数据模型如下：

json { "model":"modelA", "color":"red" } 

假设我们有一个 cars 表，通过如下语句创建测试数据。

sql INSERT INTO cars (model,color) VALUES ('A','red'); INSERT INTO cars (model,color) VALUES ('A','white'); INSERT INTO cars (model,color) VALUES ('A','black'); INSERT INTO cars (model,color) VALUES ('A','yellow'); INSERT INTO cars (model,color) VALUES ('B','red'); INSERT INTO cars (model,color) VALUES ('B','white'); INSERT INTO cars (model,color) VALUES ('C','black'); INSERT INTO cars (model,color) VALUES ('C','red'); INSERT INTO cars (model,color) VALUES ('C','white'); INSERT INTO cars (model,color) VALUES ('C','yellow'); INSERT INTO cars (model,color) VALUES ('C','blue'); INSERT INTO cars (model,color) VALUES ('D','red'); INSERT INTO cars (model,color) VALUES ('A','red'); 

那么实现我们需求的 SQL 语句也比较简单，实现如下：

sql SELECT model,COUNT(DISTINCT color) color_count FROM cars GROUP BY model HAVING color_count > 1 ORDER BY color_count desc LIMIT 2; 

这条查询语句中 Group By 是按照 model 做分组， Having color_count>1 限定了车型颜色种类大于1，ORDER BY color_count desc 限定结果按照颜色种类倒序排列，而 LIMIT 2 限定只返回前3条数据。

那么在 Elasticsearch 中如何实现这个需求呢？

2. 在 Elasticsearch 模拟测试数据

首先我们需要先在 elasticsearch 中插入测试的数据，这里我们使用 bulk 接口 ，如下所示：

 POST _bulk {"index":{"_index":"cars","_type":"doc","_id":"1"}} {"model":"A","color":"red"} {"index":{"_index":"cars","_type":"doc","_id":"2"}} {"model":"A","color":"white"} {"index":{"_index":"cars","_type":"doc","_id":"3"}} {"model":"A","color":"black"} {"index":{"_index":"cars","_type":"doc","_id":"4"}} {"model":"A","color":"yellow"} {"index":{"_index":"cars","_type":"doc","_id":"5"}} {"model":"B","color":"red"} {"index":{"_index":"cars","_type":"doc","_id":"6"}} {"model":"B","color":"white"} {"index":{"_index":"cars","_type":"doc","_id":"7"}} {"model":"C","color":"black"} {"index":{"_index":"cars","_type":"doc","_id":"8"}} {"model":"C","color":"red"} {"index":{"_index":"cars","_type":"doc","_id":"9"}} {"model":"C","color":"white"} {"index":{"_index":"cars","_type":"doc","_id":"10"}} {"model":"C","color":"yellow"} {"index":{"_index":"cars","_type":"doc","_id":"11"}} {"model":"C","color":"blue"} {"index":{"_index":"cars","_type":"doc","_id":"12"}} {"model":"D","color":"red"} {"index":{"_index":"cars","_type":"doc","_id":"13"}} {"model":"A","color":"red"} 

其中 index 为 cars，type 为 doc，所有数据与mysql 数据保持一致。大家可以在 Kibana 的 Dev Tools 中执行上面的命令，然后执行下面的查询语句验证数据是否已经成功存入。

 GET cars/_search 

3. Group By VS Terms/Metric Aggregation

SQL 中 Group By 语句在 Elasticsearch 中对应的是 Terms Aggregation，即分桶聚合，对应 Group By color 的语句如下所示：

json GET cars/_search { "size":0, "aggs":{ "models":{ "terms":{ "field":"model.keyword" } } } } 

结果如下：

json { "took": 161, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 13, "max_score": 0, "hits": [] }, "aggregations": { "models": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": "A", "doc_count": 5 }, { "key": "C", "doc_count": 5 }, { "key": "B", "doc_count": 2 }, { "key": "D", "doc_count": 1 } ] } } } 

我们看 aggregations 这个 key 下面的即为返回结果。

SQL 语句中还有一项是 COUNT(DISTINCT color) color_count 用于计算每个 model 的颜色数，在 Elasticsearch 中我们需要使用一个指标类聚合 Cardinality ，进行不同值计数。语句如下：

sql GET cars/_search { "size": 0, "aggs": { "models": { "terms": { "field": "model.keyword" }, "aggs": { "color_count": { "cardinality": { "field": "color.keyword" } } } } } } 

其返回结果如下：

json { "took": 74, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 13, "max_score": 0, "hits": [] }, "aggregations": { "models": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": "A", "doc_count": 5, "color_count": { "value": 4 } }, { "key": "C", "doc_count": 5, "color_count": { "value": 5 } }, { "key": "B", "doc_count": 2, "color_count": { "value": 2 } }, { "key": "D", "doc_count": 1, "color_count": { "value": 1 } } ] } } } 

结果中 color_count 即为每个 model 的颜色数，但这里所有的模型都返回了，我们只想要颜色数大于1的模型，因此这里还要加一个过滤条件。

4. Having Condition VS Bucket Filter Aggregation

Having color_count > 1 在 Elasticsearch 中对应的是 Bucket Filter 聚合，语句如下所示：

json GET cars/_search { "size": 0, "aggs": { "models": { "terms": { "field": "model.keyword" }, "aggs": { "color_count": { "cardinality": { "field": "color.keyword" } }, "color_count_filter": { "bucket_selector": { "buckets_path": { "colorCount": "color_count" }, "script": "params.colorCount>1" } } } } } } 

返回结果如下：

json { "took": 39, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 13, "max_score": 0, "hits": [] }, "aggregations": { "models": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": "A", "doc_count": 5, "color_count": { "value": 4 } }, { "key": "C", "doc_count": 5, "color_count": { "value": 5 } }, { "key": "B", "doc_count": 2, "color_count": { "value": 2 } } ] } } } 

此时返回结果只包含颜色数大于1的模型，但大家会发现颜色数多的 C 不是在第一个位置，我们还需要做排序处理。

5. Order By Limit VS Bucket Sort Aggregation

ORDER BY color_count desc LIMIT 3 在 Elasticsearch 中可以使用 Bucket Sort 聚合实现，语句如下所示：

sql GET cars/_search { "size": 0, "aggs": { "models": { "terms": { "field": "model.keyword" }, "aggs": { "color_count": { "cardinality": { "field": "color.keyword" } }, "color_count_filter": { "bucket_selector": { "buckets_path": { "colorCount": "color_count" }, "script": "params.colorCount>1" } }, "color_count_sort": { "bucket_sort": { "sort": { "color_count": "desc" }, "size": 2 } } } } } } 

返回结果如下：

json { "took": 32, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 13, "max_score": 0, "hits": [] }, "aggregations": { "models": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": "C", "doc_count": 5, "color_count": { "value": 5 } }, { "key": "A", "doc_count": 5, "color_count": { "value": 4 } } ] } } } 

至此我们便将 SQL 语句实现的功能用 Elasticsearch 查询语句实现了。对比 SQL 语句与 Elasticsearch 的查询语句，大家会发现后者复杂了很多，但并非无章可循，随着大家对常见语法越来越熟悉，相信一定会越写越得心应手！