提交 8a9e3ed7 编写于 作者: J jiajingbin

docs: update 06-stream.md for stream-computing

上级 06aac0fc
...@@ -71,7 +71,7 @@ Query OK, 4 rows in database (0.012033s) ...@@ -71,7 +71,7 @@ Query OK, 4 rows in database (0.012033s)
``` ```
## 示例二 ## 示例二
查询所有电表中电压等于 220V 的数据,对过滤出的电表电流数据进行四舍五入运算,同时将主键时间戳列转换为 bigint 类型,并对采集的数据按表名分组 某运营商平台要采集机房所有服务器的系统资源指标,包含 cpu、内存、网络延迟等,采集后需要对数据进行四舍五入运算,将地域和服务器名以下划线拼接,然后将结果按时间排序并以服务器名分组输出到新的数据表中
### 创建 DB 和原始数据表 ### 创建 DB 和原始数据表
首先准备数据,完成建库、建一张超级表和多张子表操作 首先准备数据,完成建库、建一张超级表和多张子表操作
...@@ -80,47 +80,49 @@ Query OK, 4 rows in database (0.012033s) ...@@ -80,47 +80,49 @@ Query OK, 4 rows in database (0.012033s)
drop database if exists stream_db; drop database if exists stream_db;
create database stream_db; create database stream_db;
create stable stream_db.meters (ts timestamp, current float, voltage int) TAGS (location varchar(64), groupId int); create stable stream_db.idc (ts timestamp, cpu float, mem float, latency float) TAGS (location varchar(64), groupId int);
create table stream_db.d1001 using stream_db.meters tags("beijing", 1); create table stream_db.server01 using stream_db.idc tags("beijing", 1);
create table stream_db.d1002 using stream_db.meters tags("shanghai", 2); create table stream_db.server02 using stream_db.idc tags("shanghai", 2);
create table stream_db.d1003 using stream_db.meters tags("beijing", 2); create table stream_db.server03 using stream_db.idc tags("beijing", 2);
create table stream_db.d1004 using stream_db.meters tags("tianjin", 3); create table stream_db.server04 using stream_db.idc tags("tianjin", 3);
create table stream_db.d1005 using stream_db.meters tags("shanghai", 1); create table stream_db.server05 using stream_db.idc tags("shanghai", 1);
``` ```
### 创建流 ### 创建流
```sql ```sql
create stream stream2 into stream_db.stream2_output_stb as select ts,cast(ts as bigint),round(current),location from stream_db.meters where voltage=220 partition by tbname; create stream stream2 into stream_db.stream2_output_stb as select ts, concat_ws("_", location, tbname) as server_location, round(cpu) as cpu, round(mem) as mem, round(latency) as latency from stream_db.idc partition by tbname order by ts;
``` ```
### 写入数据 ### 写入数据
```sql ```sql
insert into stream_db.d1001 values(now-14h, 10.3, 210); insert into stream_db.server01 values(now-14h, 50.9, 654.8, 23.11);
insert into stream_db.d1001 values(now-13h, 13.5, 220); insert into stream_db.server01 values(now-13h, 13.5, 221.2, 11.22);
insert into stream_db.d1002 values(now-12h, 14.7, 218); insert into stream_db.server02 values(now-12h, 154.7, 218.3, 22.33);
insert into stream_db.d1002 values(now-11h, 10.5, 220); insert into stream_db.server02 values(now-11h, 120.5, 111.5, 5.55);
insert into stream_db.d1003 values(now-10h, 11.5, 220); insert into stream_db.server03 values(now-10h, 101.5, 125.6, 5.99);
insert into stream_db.d1003 values(now-9h, 12.3, 215); insert into stream_db.server03 values(now-9h, 12.3, 165.6, 6.02);
insert into stream_db.d1004 values(now-8h, 11.5, 220); insert into stream_db.server04 values(now-8h, 160.9, 120.7, 43.51);
insert into stream_db.d1004 values(now-7h, 15.3, 217); insert into stream_db.server04 values(now-7h, 240.9, 520.7, 54.55);
insert into stream_db.d1005 values(now-6h, 16.5, 216); insert into stream_db.server05 values(now-6h, 190.9, 320.7, 55.43);
insert into stream_db.d1005 values(now-5h, 12.3, 220); insert into stream_db.server05 values(now-5h, 110.9, 600.7, 35.54);
``` ```
### 查询以观查结果 ### 查询以观查结果
```sql ```sql
taos> select * from stream_db.stream2_output_stb; taos> select ts, server_location, cpu, mem, latency from stream_db.stream2_output_stb;
ts | cast(ts as bigint) | round(current) | location | group_id | ts | server_location | cpu | mem | latency |
================================================================================================================================== ================================================================================================================================
2022-08-08 09:29:55.557 | 1659922195557 | 12.00000 | beijing | 7226905450883977166 | 2022-08-09 21:24:56.785 | beijing_server01 | 51.00000 | 655.00000 | 23.00000 |
2022-08-08 11:29:55.570 | 1659929395570 | 12.00000 | tianjin | 7226905450884501455 | 2022-08-09 22:24:56.795 | beijing_server01 | 14.00000 | 221.00000 | 11.00000 |
2022-08-08 08:29:55.549 | 1659918595549 | 11.00000 | shanghai | 7226905450883452877 | 2022-08-09 23:24:56.806 | shanghai_server02 | 155.00000 | 218.00000 | 22.00000 |
2022-08-08 06:29:55.534 | 1659911395534 | 14.00000 | beijing | 7226905450882928588 | 2022-08-10 00:24:56.815 | shanghai_server02 | 121.00000 | 112.00000 | 6.00000 |
2022-08-08 14:29:56.175 | 1659940196175 | 12.00000 | shanghai | 7226905450895708112 | 2022-08-10 01:24:56.826 | beijing_server03 | 102.00000 | 126.00000 | 6.00000 |
Query OK, 5 rows in database (0.015235s) 2022-08-10 02:24:56.838 | beijing_server03 | 12.00000 | 166.00000 | 6.00000 |
2022-08-10 03:24:56.846 | tianjin_server04 | 161.00000 | 121.00000 | 44.00000 |
2022-08-10 04:24:56.853 | tianjin_server04 | 241.00000 | 521.00000 | 55.00000 |
2022-08-10 05:24:56.866 | shanghai_server05 | 191.00000 | 321.00000 | 55.00000 |
2022-08-10 06:24:57.301 | shanghai_server05 | 111.00000 | 601.00000 | 36.00000 |
Query OK, 10 rows in database (0.022950s)
``` ```
## 示例三
...待续
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