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docs: add description for histogram function

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60
docs-cn/12-taos-sql/07-function.md
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@ -261,6 +261,66 @@ taos> select hyperloglog(dbig) from shll;
Query OK, 1 row(s) in set (0.008388s)
```
### HISTOGRAM
```
SELECT HISTOGRAM(field_name，bin_type, bin_description, normalized) FROM tb_name [WHERE clause];
```
**功能说明**：统计数据按照用户指定区间的分布。
**返回结果类型**：如归一化参数 normalized 设置为 1，返回结果为双精度浮点类型 DOUBLE，否则为长整形 INT64。
**应用字段**：数值型字段。
**支持的版本**：2.6.0.0 及以后的版本。
**适用于**: 表和超级表。
**说明**：
1. bin_type 用户指定的分桶类型, 有效输入类型为"user_input“, ”linear_bin", "log_bin"。
2. bin_description 描述如何生成分桶区间，针对三种桶类型，分别为以下描述格式(均为 JSON 格式字符串)：
- "user_input": "[1, 3, 5, 7]"
用户指定 bin 的具体数值。
- "linear_bin": "{"start": 0.0, "width": 5.0, "count": 5, "infinity": true}"
"start" 表示数据起始点，"width" 表示每次 bin 偏移量, "count" 为 bin 的总数，"infinity" 表示是否添加（-inf, inf）作为区间起点跟终点，
生成区间为[-inf, 0.0, 5.0, 10.0, 15.0, 20.0, +inf]。
- "log_bin": "{"start":1.0, "factor": 2.0, "count": 5, "infinity": true}"
"start" 表示数据起始点，"factor" 表示按指数递增的因子，"count" 为 bin 的总数，"infinity" 表示是否添加（-inf, inf）作为区间起点跟终点，
生成区间为[-inf, 1.0, 2.0, 4.0, 8.0, 16.0, +inf]。
3. normalized 是否将返回结果归一化到 0~1 之间 。有效输入为 0 和 1。
**示例**：
```sql
taos> SELECT HISTOGRAM(voltage, "user_input", "[1,3,5,7]", 1) FROM meters;
histogram(voltage, "user_input", "[1,3,5,7]", 1) |
=======================================================
{"lower_bin":1, "upper_bin":3, "count":0.333333} |
{"lower_bin":3, "upper_bin":5, "count":0.333333} |
{"lower_bin":5, "upper_bin":7, "count":0.333333} |
Query OK, 3 row(s) in set (0.004273s)
taos> SELECT HISTOGRAM(voltage, 'linear_bin', '{"start": 1, "width": 3, "count": 3, "infinity": false}', 0) FROM meters;
histogram(voltage, 'linear_bin', '{"start": 1, "width": 3, " |
===================================================================
{"lower_bin":1, "upper_bin":4, "count":3} |
{"lower_bin":4, "upper_bin":7, "count":3} |
{"lower_bin":7, "upper_bin":10, "count":3} |
Query OK, 3 row(s) in set (0.004887s)
taos> SELECT HISTOGRAM(voltage, 'log_bin', '{"start": 1, "factor": 3, "count": 3, "infinity": true}', 0) FROM meters;
histogram(voltage, 'log_bin', '{"start": 1, "factor": 3, "count" |
===================================================================
{"lower_bin":-inf, "upper_bin":1, "count":3} |
{"lower_bin":1, "upper_bin":3, "count":2} |
{"lower_bin":3, "upper_bin":9, "count":6} |
{"lower_bin":9, "upper_bin":27, "count":3} |
{"lower_bin":27, "upper_bin":inf, "count":1} |
```
## 选择函数
在使用所有的选择函数的时候，可以同时指定输出 ts 列或标签列（包括 tbname），这样就可以方便地知道被选出的值是源于哪个数据行的。

66
docs-en/12-taos-sql/07-function.md
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@ -259,6 +259,72 @@ taos> select hyperloglog(dbig) from shll;
Query OK, 1 row(s) in set (0.008388s)
```
### HISTOGRAM
```
SELECT HISTOGRAM(field_name，bin_type, bin_description, normalized) FROM tb_name [WHERE clause];
```
**Description**：Returns count of data points in user-specified ranges.
**Return value type**：Double or INT64, depends on normalized parameter settings.
**Applicable column type**：Numerical types.
**Applicable versions**：Since version 2.6.0.0.
**Applicable table types**: table, STable
**说明**：
1. bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin"。
2. bin_description: parameter to describe how to generate buckets，can be in the following JSON formats for each bin_type respectively:
- "user_input": "[1, 3, 5, 7]"
User defined specified bin values.
- "linear_bin": "{"start": 0.0, "width": 5.0, "count": 5, "infinity": true}"
"start" - bin starting point.
"width" - bin offset.
"count" - number of bins generated.
"infinity" - whether to add（-inf, inf）as start/end point in generated set of bins.
The above "linear_bin" descriptor generates a set of bins: [-inf, 0.0, 5.0, 10.0, 15.0, 20.0, +inf].
- "log_bin": "{"start":1.0, "factor": 2.0, "count": 5, "infinity": true}"
"start" - bin starting point.
"factor" - exponential factor of bin offset.
"count" - number of bins generated.
"infinity" - whether to add（-inf, inf）as start/end point in generated range of bins.
The above "log_bin" descriptor generates a set of bins:[-inf, 1.0, 2.0, 4.0, 8.0, 16.0, +inf].
3. normalized: setting to 1/0 to turn on/off result normalization.
**示例**：
```sql
taos> SELECT HISTOGRAM(voltage, "user_input", "[1,3,5,7]", 1) FROM meters;
histogram(voltage, "user_input", "[1,3,5,7]", 1) |
=======================================================
{"lower_bin":1, "upper_bin":3, "count":0.333333} |
{"lower_bin":3, "upper_bin":5, "count":0.333333} |
{"lower_bin":5, "upper_bin":7, "count":0.333333} |
Query OK, 3 row(s) in set (0.004273s)
taos> SELECT HISTOGRAM(voltage, 'linear_bin', '{"start": 1, "width": 3, "count": 3, "infinity": false}', 0) FROM meters;
histogram(voltage, 'linear_bin', '{"start": 1, "width": 3, " |
===================================================================
{"lower_bin":1, "upper_bin":4, "count":3} |
{"lower_bin":4, "upper_bin":7, "count":3} |
{"lower_bin":7, "upper_bin":10, "count":3} |
Query OK, 3 row(s) in set (0.004887s)
taos> SELECT HISTOGRAM(voltage, 'log_bin', '{"start": 1, "factor": 3, "count": 3, "infinity": true}', 0) FROM meters;
histogram(voltage, 'log_bin', '{"start": 1, "factor": 3, "count" |
===================================================================
{"lower_bin":-inf, "upper_bin":1, "count":3} |
{"lower_bin":1, "upper_bin":3, "count":2} |
{"lower_bin":3, "upper_bin":9, "count":6} |
{"lower_bin":9, "upper_bin":27, "count":3} |
{"lower_bin":27, "upper_bin":inf, "count":1} |
```
## Selection Functions
When any select function is used, timestamp column or tag columns including `tbname` can be specified to show that the selected value are from which rows.