[GitHub] [iotdb] ericpai commented on a diff in pull request #6661: [IOTDB-3784] tag aggregation: basic support

[GitBox <gi...@apache.org>]

ericpai commented on code in PR #6661:
URL: https://github.com/apache/iotdb/pull/6661#discussion_r990608376


##########
docs/zh/UserGuide/Query-Data/Aggregate-Query.md:
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@@ -448,9 +448,175 @@ Total line number = 7
 It costs 0.004s
 ```
 
+## 标签聚合查询
+
+IoTDB 还支持通过 `GROUP BY TAGS` 语句根据时间序列中定义的标签的键值做聚合查询。
+
+我们先在 IoTDB 中写入如下示例数据，稍后会以这些数据为例介绍标签聚合查询。
+
+这些是某工厂 `factory1` 在多个城市的多个车间的设备温度数据， 时间范围为 [1000, 10000)。
+
+时间序列路径中的设备一级是设备唯一标识。城市信息 `city` 和车间信息 `workshop` 则被建模在该设备时间序列的标签中。
+其中，设备 `d1`、`d2` 在 `Beijing` 的 `w1` 车间， `d3`、`d4` 在 `Beijing` 的 `w2` 车间，`d5`、`d6` 在 `Shanghai` 的 `w1` 车间，`d7` 在 `Shanghai` 的 `w2` 车间。
+`d8` 和 `d9` 设备目前处于调试阶段，还未被分配到具体的城市和车间，所以其相应的标签值为空值。
+
+```SQL
+set storage group to root.factory1;
+create timeseries root.factory1.d1.temperature with datatype=FLOAT tags(city=Beijing, workshop=w1);
+create timeseries root.factory1.d2.temperature with datatype=FLOAT tags(city=Beijing, workshop=w1);
+create timeseries root.factory1.d3.temperature with datatype=FLOAT tags(city=Beijing, workshop=w2);
+create timeseries root.factory1.d4.temperature with datatype=FLOAT tags(city=Beijing, workshop=w2);
+create timeseries root.factory1.d5.temperature with datatype=FLOAT tags(city=Shanghai, workshop=w1);
+create timeseries root.factory1.d6.temperature with datatype=FLOAT tags(city=Shanghai, workshop=w1);
+create timeseries root.factory1.d7.temperature with datatype=FLOAT tags(city=Shanghai, workshop=w2);
+create timeseries root.factory1.d8.temperature with datatype=FLOAT;
+create timeseries root.factory1.d9.temperature with datatype=FLOAT;
+
+insert into root.factory1.d1(time, temperature) values(1000, 104.0);
+insert into root.factory1.d1(time, temperature) values(3000, 104.2);
+insert into root.factory1.d1(time, temperature) values(5000, 103.3);
+insert into root.factory1.d1(time, temperature) values(7000, 104.1);
+
+insert into root.factory1.d2(time, temperature) values(1000, 104.4);
+insert into root.factory1.d2(time, temperature) values(3000, 103.7);
+insert into root.factory1.d2(time, temperature) values(5000, 103.3);
+insert into root.factory1.d2(time, temperature) values(7000, 102.9);
+
+insert into root.factory1.d3(time, temperature) values(1000, 103.9);
+insert into root.factory1.d3(time, temperature) values(3000, 103.8);
+insert into root.factory1.d3(time, temperature) values(5000, 102.7);
+insert into root.factory1.d3(time, temperature) values(7000, 106.9);
+
+insert into root.factory1.d4(time, temperature) values(1000, 103.9);
+insert into root.factory1.d4(time, temperature) values(5000, 102.7);
+insert into root.factory1.d4(time, temperature) values(7000, 106.9);
+
+insert into root.factory1.d5(time, temperature) values(1000, 112.9);
+insert into root.factory1.d5(time, temperature) values(7000, 113.0);
+
+insert into root.factory1.d6(time, temperature) values(1000, 113.9);
+insert into root.factory1.d6(time, temperature) values(3000, 113.3);
+insert into root.factory1.d6(time, temperature) values(5000, 112.7);
+insert into root.factory1.d6(time, temperature) values(7000, 112.3);
+
+insert into root.factory1.d7(time, temperature) values(1000, 101.2);
+insert into root.factory1.d7(time, temperature) values(3000, 99.3);
+insert into root.factory1.d7(time, temperature) values(5000, 100.1);
+insert into root.factory1.d7(time, temperature) values(7000, 99.8);
+
+insert into root.factory1.d8(time, temperature) values(1000, 50.0);
+insert into root.factory1.d8(time, temperature) values(3000, 52.1);
+insert into root.factory1.d8(time, temperature) values(5000, 50.1);
+insert into root.factory1.d8(time, temperature) values(7000, 50.5);
+
+insert into root.factory1.d9(time, temperature) values(1000, 50.3);
+insert into root.factory1.d9(time, temperature) values(3000, 52.1);
+```
+
+### 单标签聚合查询
+
+用户想统统计该工厂每个地区的设备的温度的平均值，可以使用如下查询语句

Review Comment:
   Fixed.



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