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# 时间序列管理

## 创建时间序列

根据建立的数据模型，我们可以分别在两个存储组中创建相应的时间序列。创建时间序列的 SQL 语句如下所示：

```
IoTDB > create timeseries root.ln.wf01.wt01.status with datatype=BOOLEAN,encoding=PLAIN
IoTDB > create timeseries root.ln.wf01.wt01.temperature with datatype=FLOAT,encoding=RLE
IoTDB > create timeseries root.ln.wf02.wt02.hardware with datatype=TEXT,encoding=PLAIN
IoTDB > create timeseries root.ln.wf02.wt02.status with datatype=BOOLEAN,encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.status with datatype=BOOLEAN,encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.temperature with datatype=FLOAT,encoding=RLE
```

从 v0.13 起，可以使用简化版的 SQL 语句创建时间序列：

```
IoTDB > create timeseries root.ln.wf01.wt01.status BOOLEAN encoding=PLAIN
IoTDB > create timeseries root.ln.wf01.wt01.temperature FLOAT encoding=RLE
IoTDB > create timeseries root.ln.wf02.wt02.hardware TEXT encoding=PLAIN
IoTDB > create timeseries root.ln.wf02.wt02.status BOOLEAN encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.status BOOLEAN encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.temperature FLOAT encoding=RLE
```

需要注意的是，当创建时间序列时指定的编码方式与数据类型不对应时，系统会给出相应的错误提示，如下所示：
```
IoTDB> create timeseries root.ln.wf02.wt02.status WITH DATATYPE=BOOLEAN, ENCODING=TS_2DIFF
error: encoding TS_2DIFF does not support BOOLEAN
```

详细的数据类型与编码方式的对应列表请参见 [编码方式](../Data-Concept/Encoding.md)。

## 创建对齐时间序列

创建一组对齐时间序列的SQL语句如下所示：

```
IoTDB> CREATE ALIGNED TIMESERIES root.ln.wf01.GPS(latitude FLOAT encoding=PLAIN compressor=SNAPPY, longitude FLOAT encoding=PLAIN compressor=SNAPPY) 
```

一组对齐序列中的序列可以有不同的数据类型、编码方式以及压缩方式。

对齐的时间序列也支持设置别名、标签、属性。

## 删除时间序列

我们可以使用`DELETE TimeSeries <PathPattern>`语句来删除我们之前创建的时间序列。SQL 语句如下所示：

```
IoTDB> delete timeseries root.ln.wf01.wt01.status
IoTDB> delete timeseries root.ln.wf01.wt01.temperature, root.ln.wf02.wt02.hardware
IoTDB> delete timeseries root.ln.wf02.*
```

## 查看时间序列

* SHOW LATEST? TIMESERIES pathPattern? whereClause? limitClause?

  SHOW TIMESERIES 中可以有四种可选的子句，查询结果为这些时间序列的所有信息

时间序列信息具体包括：时间序列路径名，存储组，Measurement 别名，数据类型，编码方式，压缩方式，属性和标签。

示例：

* SHOW TIMESERIES

  展示系统中所有的时间序列信息

* SHOW TIMESERIES <`Path`>

  返回给定路径的下的所有时间序列信息。其中 `Path` 需要为一个时间序列路径或路径模式。例如，分别查看`root`路径和`root.ln`路径下的时间序列，SQL 语句如下所示：

```
IoTDB> show timeseries root.**
IoTDB> show timeseries root.ln.**
```

执行结果分别为：

```
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+
|                     timeseries|   alias|storage group|dataType|encoding|compression|                                       tags|                                              attributes|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+
|root.sgcc.wf03.wt01.temperature|    null|    root.sgcc|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|
|     root.sgcc.wf03.wt01.status|    null|    root.sgcc| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|
|             root.turbine.d1.s1|newAlias| root.turbine|   FLOAT|     RLE|     SNAPPY|{"newTag1":"newV1","tag4":"v4","tag3":"v3"}|{"attr2":"v2","attr1":"newV1","attr4":"v4","attr3":"v3"}|
|     root.ln.wf02.wt02.hardware|    null|      root.ln|    TEXT|   PLAIN|     SNAPPY|                                       null|                                                    null|
|       root.ln.wf02.wt02.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|
|  root.ln.wf01.wt01.temperature|    null|      root.ln|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|
|       root.ln.wf01.wt01.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+
Total line number = 7
It costs 0.016s

+-----------------------------+-----+-------------+--------+--------+-----------+----+----------+
|                   timeseries|alias|storage group|dataType|encoding|compression|tags|attributes|
+-----------------------------+-----+-------------+--------+--------+-----------+----+----------+
|   root.ln.wf02.wt02.hardware| null|      root.ln|    TEXT|   PLAIN|     SNAPPY|null|      null|
|     root.ln.wf02.wt02.status| null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|null|      null|
|root.ln.wf01.wt01.temperature| null|      root.ln|   FLOAT|     RLE|     SNAPPY|null|      null|
|     root.ln.wf01.wt01.status| null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|null|      null|
+-----------------------------+-----+-------------+--------+--------+-----------+----+----------+
Total line number = 4
It costs 0.004s
```

* SHOW TIMESERIES LIMIT INT OFFSET INT

  只返回从指定下标开始的结果，最大返回条数被 LIMIT 限制，用于分页查询。例如：

```
show timeseries root.ln.** limit 10 offset 10
```

* SHOW LATEST TIMESERIES

  表示查询出的时间序列需要按照最近插入时间戳降序排列
  

需要注意的是，当查询路径不存在时，系统会返回 0 条时间序列。

## 统计时间序列总数

IoTDB 支持使用`COUNT TIMESERIES<Path>`来统计一条路径中的时间序列个数。SQL 语句如下所示：
```
IoTDB > COUNT TIMESERIES root.**
IoTDB > COUNT TIMESERIES root.ln.**
IoTDB > COUNT TIMESERIES root.ln.*.*.status
IoTDB > COUNT TIMESERIES root.ln.wf01.wt01.status
```

除此之外，还可以通过定义`LEVEL`来统计指定层级下的时间序列个数。这条语句可以用来统计每一个设备下的传感器数量，语法为：`COUNT TIMESERIES <Path> GROUP BY LEVEL=<INTEGER>`。

例如有如下时间序列（可以使用`show timeseries`展示所有时间序列）：

```
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+
|                     timeseries|   alias|storage group|dataType|encoding|compression|                                       tags|                                              attributes|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+
|root.sgcc.wf03.wt01.temperature|    null|    root.sgcc|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|
|     root.sgcc.wf03.wt01.status|    null|    root.sgcc| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|
|             root.turbine.d1.s1|newAlias| root.turbine|   FLOAT|     RLE|     SNAPPY|{"newTag1":"newV1","tag4":"v4","tag3":"v3"}|{"attr2":"v2","attr1":"newV1","attr4":"v4","attr3":"v3"}|
|     root.ln.wf02.wt02.hardware|    null|      root.ln|    TEXT|   PLAIN|     SNAPPY|                               {"unit":"c"}|                                                    null|
|       root.ln.wf02.wt02.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                    {"description":"test1"}|                                                    null|
|  root.ln.wf01.wt01.temperature|    null|      root.ln|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|
|       root.ln.wf01.wt01.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+
Total line number = 7
It costs 0.004s
```

那么 Metadata Tree 如下所示：

<img style="width:100%; max-width:600px; margin-left:auto; margin-right:auto; display:block;" src="https://user-images.githubusercontent.com/19167280/69792176-1718f400-1201-11ea-861a-1a83c07ca144.jpg">

可以看到，`root`被定义为`LEVEL=0`。那么当你输入如下语句时：

```
IoTDB > COUNT TIMESERIES root.** GROUP BY LEVEL=1
IoTDB > COUNT TIMESERIES root.ln.** GROUP BY LEVEL=2
IoTDB > COUNT TIMESERIES root.ln.wf01.* GROUP BY LEVEL=2
```

你将得到以下结果：

```
IoTDB> COUNT TIMESERIES root.** GROUP BY LEVEL=1
+------------+-----+
|      column|count|
+------------+-----+
|   root.sgcc|    2|
|root.turbine|    1|
|     root.ln|    4|
+------------+-----+
Total line number = 3
It costs 0.002s

IoTDB > COUNT TIMESERIES root.ln.** GROUP BY LEVEL=2
+------------+-----+
|      column|count|
+------------+-----+
|root.ln.wf02|    2|
|root.ln.wf01|    2|
+------------+-----+
Total line number = 2
It costs 0.002s

IoTDB > COUNT TIMESERIES root.ln.wf01.* GROUP BY LEVEL=2
+------------+-----+
|      column|count|
+------------+-----+
|root.ln.wf01|    2|
+------------+-----+
Total line number = 1
It costs 0.002s
```

> 注意：时间序列的路径只是过滤条件，与 level 的定义无关。

## 标签点管理

我们可以在创建时间序列的时候，为它添加别名和额外的标签和属性信息。

标签和属性的区别在于：

* 标签可以用来查询时间序列路径，会在内存中维护标点到时间序列路径的倒排索引：标签 -> 时间序列路径
* 属性只能用时间序列路径来查询：时间序列路径 -> 属性

所用到的扩展的创建时间序列的 SQL 语句如下所示：
```
create timeseries root.turbine.d1.s1(temprature) with datatype=FLOAT, encoding=RLE, compression=SNAPPY tags(tag1=v1, tag2=v2) attributes(attr1=v1, attr2=v2)
```

括号里的`temprature`是`s1`这个传感器的别名。
我们可以在任何用到`s1`的地方，将其用`temprature`代替，这两者是等价的。

> IoTDB 同时支持在查询语句中 [使用 AS 函数](../Reference/DML-Data-Manipulation%20Language.md) 设置别名。二者的区别在于：AS 函数设置的别名用于替代整条时间序列名，且是临时的，不与时间序列绑定；而上文中的别名只作为传感器的别名，与其绑定且可与原传感器名等价使用。

> 注意：额外的标签和属性信息总的大小不能超过`tag_attribute_total_size`.

 * 标签点属性更新
创建时间序列后，我们也可以对其原有的标签点属性进行更新，主要有以下六种更新方式：
* 重命名标签或属性
```
ALTER timeseries root.turbine.d1.s1 RENAME tag1 TO newTag1
```
* 重新设置标签或属性的值
```
ALTER timeseries root.turbine.d1.s1 SET newTag1=newV1, attr1=newV1
```
* 删除已经存在的标签或属性
```
ALTER timeseries root.turbine.d1.s1 DROP tag1, tag2
```
* 添加新的标签
```
ALTER timeseries root.turbine.d1.s1 ADD TAGS tag3=v3, tag4=v4
```
* 添加新的属性
```
ALTER timeseries root.turbine.d1.s1 ADD ATTRIBUTES attr3=v3, attr4=v4
```
* 更新插入别名，标签和属性
> 如果该别名，标签或属性原来不存在，则插入，否则，用新值更新原来的旧值
```
ALTER timeseries root.turbine.d1.s1 UPSERT ALIAS=newAlias TAGS(tag2=newV2, tag3=v3) ATTRIBUTES(attr3=v3, attr4=v4)
```

* 使用标签作为过滤条件查询时间序列
```
* SHOW TIMESERIES (<`PathPattern`>)? WhereClause
```

  返回给定路径的下的所有满足条件的时间序列信息，SQL 语句如下所示：

```
ALTER timeseries root.ln.wf02.wt02.hardware ADD TAGS unit=c
ALTER timeseries root.ln.wf02.wt02.status ADD TAGS description=test1
show timeseries root.ln.** where unit=c
show timeseries root.ln.** where description contains 'test1'
```

执行结果分别为：

```
+--------------------------+-----+-------------+--------+--------+-----------+------------+----------+
|                timeseries|alias|storage group|dataType|encoding|compression|        tags|attributes|
+--------------------------+-----+-------------+--------+--------+-----------+------------+----------+
|root.ln.wf02.wt02.hardware| null|      root.ln|    TEXT|   PLAIN|     SNAPPY|{"unit":"c"}|      null|
+--------------------------+-----+-------------+--------+--------+-----------+------------+----------+
Total line number = 1
It costs 0.005s

+------------------------+-----+-------------+--------+--------+-----------+-----------------------+----------+
|              timeseries|alias|storage group|dataType|encoding|compression|                   tags|attributes|
+------------------------+-----+-------------+--------+--------+-----------+-----------------------+----------+
|root.ln.wf02.wt02.status| null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|{"description":"test1"}|      null|
+------------------------+-----+-------------+--------+--------+-----------+-----------------------+----------+
Total line number = 1
It costs 0.004s
```

> 注意，现在我们只支持一个查询条件，要么是等值条件查询，要么是包含条件查询。当然 where 子句中涉及的必须是标签值，而不能是属性值。

创建对齐时间序列

```
create aligned timeseries root.sg1.d1(s1 INT32 tags(tag1=v1, tag2=v2) attributes(attr1=v1, attr2=v2), s2 DOUBLE tags(tag3=v3, tag4=v4) attributes(attr3=v3, attr4=v4))
```

执行结果如下：

```
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+
|    timeseries|alias|storage group|dataType|encoding|compression|                     tags|                 attributes|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+
|root.sg1.d1.s1| null|     root.sg1|   INT32|     RLE|     SNAPPY|{"tag1":"v1","tag2":"v2"}|{"attr2":"v2","attr1":"v1"}|
|root.sg1.d1.s2| null|     root.sg1|  DOUBLE| GORILLA|     SNAPPY|{"tag4":"v4","tag3":"v3"}|{"attr4":"v4","attr3":"v3"}|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+
```

支持查询：

```
IoTDB> show storage group where tag1='v1'
Msg: 401: Error occurred while parsing SQL to physical plan: line 1:19 mismatched input 'where' expecting {<EOF>, ';'}
IoTDB> show timeseries where tag1='v1'
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+
|    timeseries|alias|storage group|dataType|encoding|compression|                     tags|                 attributes|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+
|root.sg1.d1.s1| null|     root.sg1|   INT32|     RLE|     SNAPPY|{"tag1":"v1","tag2":"v2"}|{"attr2":"v2","attr1":"v1"}|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+
```

上述对时间序列标签、属性的更新等操作都支持。