docs: add description for histogram function
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@ -261,6 +261,66 @@ taos> select hyperloglog(dbig) from shll;
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Query OK, 1 row(s) in set (0.008388s)
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Query OK, 1 row(s) in set (0.008388s)
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```
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```
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### HISTOGRAM
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```
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SELECT HISTOGRAM(field_name，bin_type, bin_description, normalized) FROM tb_name [WHERE clause];
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```
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**功能说明**：统计数据按照用户指定区间的分布。
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**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。
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**应用字段**：数值型字段。
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**支持的版本**：2.6.0.0 及以后的版本。
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**适用于**: 表和超级表。
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**说明**：
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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"。
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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)：
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- "user_input": "[1, 3, 5, 7]"
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用户指定 bin 的具体数值。
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- "linear_bin": "{"start": 0.0, "width": 5.0, "count": 5, "infinity": true}"
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"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，
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生成区间为[-inf, 0.0, 5.0, 10.0, 15.0, 20.0, +inf]。
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- "log_bin": "{"start":1.0, "factor": 2.0, "count": 5, "infinity": true}"
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"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，
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生成区间为[-inf, 1.0, 2.0, 4.0, 8.0, 16.0, +inf]。
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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。
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**示例**：
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```sql
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taos> SELECT HISTOGRAM(voltage, "user_input", "[1,3,5,7]", 1) FROM meters;
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histogram(voltage, "user_input", "[1,3,5,7]", 1) |
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=======================================================
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{"lower_bin":1, "upper_bin":3, "count":0.333333} |
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{"lower_bin":3, "upper_bin":5, "count":0.333333} |
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{"lower_bin":5, "upper_bin":7, "count":0.333333} |
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Query OK, 3 row(s) in set (0.004273s)
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taos> SELECT HISTOGRAM(voltage, 'linear_bin', '{"start": 1, "width": 3, "count": 3, "infinity": false}', 0) FROM meters;
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histogram(voltage, 'linear_bin', '{"start": 1, "width": 3, " |
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===================================================================
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{"lower_bin":1, "upper_bin":4, "count":3} |
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{"lower_bin":4, "upper_bin":7, "count":3} |
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{"lower_bin":7, "upper_bin":10, "count":3} |
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Query OK, 3 row(s) in set (0.004887s)
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taos> SELECT HISTOGRAM(voltage, 'log_bin', '{"start": 1, "factor": 3, "count": 3, "infinity": true}', 0) FROM meters;
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histogram(voltage, 'log_bin', '{"start": 1, "factor": 3, "count" |
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===================================================================
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{"lower_bin":-inf, "upper_bin":1, "count":3} |
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{"lower_bin":1, "upper_bin":3, "count":2} |
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{"lower_bin":3, "upper_bin":9, "count":6} |
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{"lower_bin":9, "upper_bin":27, "count":3} |
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{"lower_bin":27, "upper_bin":inf, "count":1} |
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```
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## 选择函数
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## 选择函数
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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。
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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。
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@ -259,6 +259,72 @@ taos> select hyperloglog(dbig) from shll;
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Query OK, 1 row(s) in set (0.008388s)
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Query OK, 1 row(s) in set (0.008388s)
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```
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```
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### HISTOGRAM
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```
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SELECT HISTOGRAM(field_name，bin_type, bin_description, normalized) FROM tb_name [WHERE clause];
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```
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**Description**：Returns count of data points in user-specified ranges.
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**Return value type**：Double or INT64, depends on normalized parameter settings.
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**Applicable column type**：Numerical types.
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**Applicable versions**：Since version 2.6.0.0.
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**Applicable table types**: table, STable
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**说明**：
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1. bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin"。
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2. bin_description: parameter to describe how to generate buckets，can be in the following JSON formats for each bin_type respectively:
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- "user_input": "[1, 3, 5, 7]"
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User defined specified bin values.
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- "linear_bin": "{"start": 0.0, "width": 5.0, "count": 5, "infinity": true}"
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"start" - bin starting point.
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"width" - bin offset.
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"count" - number of bins generated.
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"infinity" - whether to add（-inf, inf）as start/end point in generated set of bins.
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The above "linear_bin" descriptor generates a set of bins: [-inf, 0.0, 5.0, 10.0, 15.0, 20.0, +inf].
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- "log_bin": "{"start":1.0, "factor": 2.0, "count": 5, "infinity": true}"
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"start" - bin starting point.
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"factor" - exponential factor of bin offset.
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"count" - number of bins generated.
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"infinity" - whether to add（-inf, inf）as start/end point in generated range of bins.
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The above "log_bin" descriptor generates a set of bins:[-inf, 1.0, 2.0, 4.0, 8.0, 16.0, +inf].
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3. normalized: setting to 1/0 to turn on/off result normalization.
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**示例**：
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```sql
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taos> SELECT HISTOGRAM(voltage, "user_input", "[1,3,5,7]", 1) FROM meters;
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histogram(voltage, "user_input", "[1,3,5,7]", 1) |
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=======================================================
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{"lower_bin":1, "upper_bin":3, "count":0.333333} |
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{"lower_bin":3, "upper_bin":5, "count":0.333333} |
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{"lower_bin":5, "upper_bin":7, "count":0.333333} |
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Query OK, 3 row(s) in set (0.004273s)
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taos> SELECT HISTOGRAM(voltage, 'linear_bin', '{"start": 1, "width": 3, "count": 3, "infinity": false}', 0) FROM meters;
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histogram(voltage, 'linear_bin', '{"start": 1, "width": 3, " |
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===================================================================
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{"lower_bin":1, "upper_bin":4, "count":3} |
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{"lower_bin":4, "upper_bin":7, "count":3} |
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{"lower_bin":7, "upper_bin":10, "count":3} |
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Query OK, 3 row(s) in set (0.004887s)
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taos> SELECT HISTOGRAM(voltage, 'log_bin', '{"start": 1, "factor": 3, "count": 3, "infinity": true}', 0) FROM meters;
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histogram(voltage, 'log_bin', '{"start": 1, "factor": 3, "count" |
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===================================================================
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{"lower_bin":-inf, "upper_bin":1, "count":3} |
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{"lower_bin":1, "upper_bin":3, "count":2} |
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{"lower_bin":3, "upper_bin":9, "count":6} |
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{"lower_bin":9, "upper_bin":27, "count":3} |
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{"lower_bin":27, "upper_bin":inf, "count":1} |
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```
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## Selection Functions
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## Selection Functions
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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.
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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.
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