内容简介:本文详细介绍了不同版本中上篇文章回顾:看示例学awk
本文详细介绍了不同版本中 Elasticsearch SQL的使用方法,总结了实际中常用的方法和操作,并给出了几个具体例子。
上篇文章回顾:看示例学awk
一、5.x中ES-SQL用法
Elasticsearch 5.x版本中,SQL功能还没有集成到Elasticsearch源码中,需要下载第三方插件后才能使用,配置过程如下:
1.安装ES-SQL依赖node npm
ES-SQL 5.x版本以后,安装需要依赖node和npm,先安装node和npm,安装后在检查node及npm的安装,命令如下:
yum -y install nodejs npm node -v npm -v
2.下载ES-SQL并安装
然后切换到ES的根目录下,执行如下命令,下载并安ES-SQL插件:
./bin/elasticsearch-plugin install https://github.com/NLPchina/elasticsearch-sql/releases/download/5.6.3.0/elasticsearch-sql-5.6.3.0.zip
离线包安装可以执行:
./bin/elasticsearch-plugin install file:/elasticsearch-sql-5.6.3.0.zip
3.重启ES服务
执行完上述三步,你就可以使用 SQL 探索数据了,以kibana中的使用为例:
二、6.4 Elasticsearch SQL用法
1
Elasticsearch SQL支持的数据类型
首先我们看下Elasticsearch SQL和标准SQL中数据类型的对应关系:
2
Elasticsearch SQL的使用方式
Elasticsearch SQL支持三种client: REST Interface, command-line,JDBC
2.1 REST Interface
建议先在kibana中测试(可以一次执行多个SQL),查询通过之后把查询copy到项目中进行测试。
6.3+ Elasticsearch SQL有个非常实用的功能,就是可以用translate api把SQL语句翻译成ES DSL语句,对于学习DSL感到头痛的同学有福啦。
2.2 command-line
命令行界面的进入方式:
./elasticsearch-sql-cli IP:PORT(本机ip和es的端口)
进入后的界面如下:
命令行一般作为SQL测试时使用。
2.3 JDBC
该组件为X-Pack中的收费组件,感兴趣的同学可以参考官方文档: https://www.elastic.co/guide/en/elasticsearch/reference/current/sql-jdbc.html
3
常用SQL语句
注意:查询单个索引名一定要用""引上,否则会报错
* 查看当前用户所有的索引: “SHOW TABLES;”
精准查询某个索引:“SHOW TABLES LIKE ‘indexname’;”
通配符查询某些索引:“SHOW TABLES LIKE ‘ ’;”
*查看某个索引结构: “DESCRIBE table;” 或者 “DESC table;”
上面两个命令都是“SHOW COLUMNS [ FROM | IN ] ? table”命令的别名
*查看函数: “SHOW FUNCTIONS [ LIKE? pattern? ]?”
精准查询某个函数:
通配符查询某些函数:
查看所有函数:
常用的聚合函数:
SELECT MIN(value_1) min, MAX(value_1) max, AVG(value_1) avg,SUM(value_1) sum,COUNT(*) count,COUNT(DISTINCT value_1) dictinct_count FROM "micloud_es_sink_zhouyongbo_test-2018.10.19”;
SELECT 语句的语法 排序 如下:
SELECT select_expr [, ...] [ FROM table_name ] [ WHERE condition ] [ GROUP BY grouping_element [, ...] ] [ HAVING condition] [ ORDER BY expression [ ASC | DESC ] [, ...] ] [ LIMIT [ count ] ]
*限定返回数据的条数: “limit”
SELECT * FROM "micloud_es_sink_zhouyongbo_test-2018.10.19” limit 10 ;
注意SQL中的limit比fetch_size中的优先级高,例如下面的例子返回的是5条 :
{ "query": "SELECT * FROM "micloud_es_sink_zhouyongbo_test-2018.10.19” limit 5", "fetch_size":10 }
*排序: “order by + 字段名字 + asc/desc”
SELECT * FROM "micloud_es_sink_zhouyongbo_test-2018.10.19” ORDER BY value_1 asc/desc;
根据多个字段排序:
select city c,value_1 + 1 vp from "micloud_es_sink_zhouyongbo_test-2018.10.19" group by c,vp order by c desc,vp asc;
*WHERE根据条件查询:
WHERE后面跟ES复杂数据类型:
SELECT first_name FROM index WHERE first_name.raw = ‘John’ ;
WHERE后面跟多个查询条件:
SELECT * FROM micloud_es_sink_zhouyongbo_test* where city=‘北京' and value_1=8 ORDER BY value_1 desc ;
*group by分组查询:
根据单个字段分组查询:
select city,count(city) as count_city,sum(value_1) as count_value_1 from "micloud_es_sink_zhouyongbo_test-2018.10.19" group by city;
根据多个字段分组查询:
select city,count(city) count_city,sum(value_1) count_value_1 from "micloud_es_sink_zhouyongbo_test-2018.10.19" group by city,value_1;
对于比较长的字段,也可以对该字段声明别名,并对别名进行分组查询,声明字段别名的“as”可省略:
select city c,count(city) count_city,sum(value_1) count_value_1 from "micloud_es_sink_zhouyongbo_test-2018.10.19" group by c,value_1;
还可以对某字段进行计算,然后按照计算结果分组查询:
select city c,value_1 + 1 vp from "micloud_es_sink_zhouyongbo_test-2018.10.19" group by c,vp;
*HAVING过滤分组结果(ES-SQL引擎同样会在分组之后计算HAVING语句):
Select city c,count(*) count from "micloud_es_sink_zhouyongbo_test-2018.10.19" group by c having count > 53834;
*查询嵌套类型:
select * from zhouyongbo_test04 where love.kaishu=‘鲁公’;
*用通配符查询多个索引:
注意被查询索引必须有相同的mapping,否则会有如下报错:
常用的方法和操作汇总:
*比较操作:
Equality (=)
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 = 6 limit 5;
Inequality (<> or != or <=>)
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 <> 6 limit 5;
Comparison (<, <=, >, >=)
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 >= 6 limit 5;
BETWEEN
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 between 6 and 8 limit 5;
IS NULL/IS NOT NULL
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 is not NULL limit 5;
*逻辑操作:
AND
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 > 5 and value_1 < 7 limit 5;
OR
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where value_1 = 5 or value_1 = 7 limit 5;
NOT
select * from "micloud_es_sink_zhouyongbo_test-2018.10.19" where not value_1 > 5 limit 5;
*数学运算操作:
Add (+)
select 1 + 1 as x;
Subtract (infix -)
select 1 - 1 as x;
Negate (unary -)
select - 1 as x;
Multiply (*)
select 6 * 6 as x;
Divide (/)
select 30 / 5 as x;
Modulo or Reminder(%)
select 30 % 7 as x;
*数学函数:(分为通用函数和三角函数两部分 ):
通用函数:
ABS:求数字的绝对值
select ABS(value_1) from "micloud_es_sink_zhouyongbo_test-2018.10.19" limit 5;
CBRT:求数字的立方根,返回double
select value_1 v,CBRT(value_1) cbrt from "micloud_es_sink_zhouyongbo_test-2018.10.19" limit 5;
CEIL:返回大于或者等于指定表达式最小整数(double)
select value_1 v,CEIL(value_1) from "micloud_es_sink_zhouyongbo_test-2018.10.19" limit 5;
CEILING:等同于CEIL
select value_1 v,CEILING(value_1) from "micloud_es_sink_zhouyongbo_test-2018.10.19" limit 5;
E:返回自然常数e(2.718281828459045)
select value_1,E(value_1) from "micloud_es_sink_zhouyongbo_test-2018.10.19" limit 5;
ROUND:四舍五入精确到个位
select ROUND(-3.14);
FLOOR:向下取整
select FLOOR(3.14);
LOG:计算以2为底的自然对数
select LOG(4);
LOG10:计算以10为底的自然对数
select LOG10(100);
SQRT:求一个非负实数的平方根
select SQRT(9);
EXP:此函数返回e(自然对数的底)的X次方的值
select EXP(3);
EXPM1:返回e x -1
select EXPM1(3);
三角函数:
DEGREES:返回X从弧度转换为度值
select DEGREES(x);
RADIANS:返回X从度转换成弧度的值
select RADIANS(x);
SIN:返回X的正弦
select SIN(x);
COS:返回X,X值是以弧度给出的余弦值
select COS(角度);
TAN:返回参数X,表示以弧度的切线值
select TAN(角度);
ASIN:返回X的反正弦,X的值必须在-1至1范围内,返回NULL
select ASIN(x);
ACOS:返回X的反正弦,X值必须-1到1之间范围否则将返回NULL
select ACOS(x);
ATAN:返回X的反正切
select ATAN(x);
SINH:返回X的双曲正弦值
select SINH(x);
COSH:返回X的双曲余弦值
select COSH(x);
*日期和时间处理相关方法:
YEAR:
SELECT YEAR(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS year;
MONTH_OF_YEAR() or MONTH():
SELECT MONTH(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS month;
WEEK_OF_YEAR() or WEEK():
SELECT WEEK(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS week;
DAY_OF_YEAR() or DOY(),效果等同于EXTRACT(<datetime_function> FROM <expression>):
SELECT DOY(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS day;
DAY_OF_MONTH(), DOM(), or DAY():
SELECT DAY(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS day;
DAY_OF_WEEK() or DOW():
SELECT DOW(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS day;
HOUR_OF_DAY() or HOUR():
SELECT HOUR(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS hour;
MINUTE_OF_DAY():
SELECT MINUTE_OF_DAY(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS minute;
MINUTE_OF_HOUR() or MINUTE():
SELECT MINUTE(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS minute;
SECOND_OF_MINUTE() or SECOND():
SELECT SECOND(CAST('2018-10-23T16:59:27Z' AS TIMESTAMP)) AS second;
如上就是6.4 Elasticsearch SQL支持的主要用法了,如果在优化SQL语句之后还不满足查询需求,可以拿SQL和DSL混用,ES会先根据SQL进行查询,然后根据DSL语句对SQL的执行结果进行二次查询,下面是个小例子:
POST /_xpack/sql?format=txt { "query": "SELECT * FROM library ORDER BY page_count DESC", "filter": { "range": { "page_count": { "gte" : 100, "lte" : 200 } } }, "fetch_size": 5 }
这个查询就会先根据“query”后面的SQL进行查询,然后用执行“filter”和“fetch_size” DSL语法对查询结果进行过滤,进而返回最终结果。
参考文档:
6.4.0 Elasticsearch SQL新特性简介:
https://www.elastic.co/cn/products/stack/elasticsearch-sql
6.4.0 Elasticsearch SQL使用文档:
https://www.elastic.co/guide/en/elasticsearch/reference/current/xpack-sql.html
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