Merge pull request #16825 from taosdata/fix/maxmin_type
fix(query): restrict max/min function input type not including timestamp type
This commit is contained in:
Shengliang Guan
GitHub
commit
06e38c1dcc
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@ -126,7 +126,7 @@ SELECT COS(field_name) FROM { tb_name | stb_name } [WHERE clause]
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SELECT FLOOR(field_name) FROM { tb_name | stb_name } [WHERE clause];
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```
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**Description**: The rounded down value of a specific field
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**Description**: The rounded down value of a specific field
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**More explanations**: The restrictions are same as those of the `CEIL` function.
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#### LOG
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@ -173,7 +173,7 @@ SELECT POW(field_name, power) FROM { tb_name | stb_name } [WHERE clause]
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SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause];
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```
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**Description**: The rounded value of a specific field.
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**Description**: The rounded value of a specific field.
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**More explanations**: The restrictions are same as those of the `CEIL` function.
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@ -434,7 +434,7 @@ SELECT TO_ISO8601(ts[, timezone]) FROM { tb_name | stb_name } [WHERE clause];
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**More explanations**:
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- You can specify a time zone in the following format: [z/Z, +/-hhmm, +/-hh, +/-hh:mm]。 For example, TO_ISO8601(1, "+00:00").
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- If the input is a UNIX timestamp, the precision of the returned value is determined by the digits of the input timestamp
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- If the input is a UNIX timestamp, the precision of the returned value is determined by the digits of the input timestamp
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- If the input is a column of TIMESTAMP type, the precision of the returned value is same as the precision set for the current data base in use
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@ -769,14 +769,14 @@ SELECT HISTOGRAM(field_name，bin_type, bin_description, normalized) FROM tb_nam
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**Explanations**：
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- bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin"。
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- 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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- 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 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. "width" - bin offset. "count" - number of bins generated. "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. "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.
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The above "linear_bin" descriptor generates a set of bins: [-inf, 1.0, 2.0, 4.0, 8.0, 16.0, +inf].
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@ -862,9 +862,9 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] RA
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- `INTERP` is used to get the value that matches the specified time slice from a column. If no such value exists an interpolation value will be returned based on `FILL` parameter.
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- The input data of `INTERP` is the value of the specified column and a `where` clause can be used to filter the original data. If no `where` condition is specified then all original data is the input.
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- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1<=timestamp2. timestamp1 is the starting point of the output time range and must be specified. timestamp2 is the ending point of the output time range and must be specified.
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- The number of rows in the result set of `INTERP` is determined by the parameter `EVERY`. Starting from timestamp1, one interpolation is performed for every time interval specified `EVERY` parameter.
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- Interpolation is performed based on `FILL` parameter.
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- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1<=timestamp2. timestamp1 is the starting point of the output time range and must be specified. timestamp2 is the ending point of the output time range and must be specified.
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- The number of rows in the result set of `INTERP` is determined by the parameter `EVERY`. Starting from timestamp1, one interpolation is performed for every time interval specified `EVERY` parameter.
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- Interpolation is performed based on `FILL` parameter.
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- `INTERP` can only be used to interpolate in single timeline. So it must be used with `partition by tbname` when it's used on a STable.
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### LAST
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@ -917,7 +917,7 @@ SELECT MAX(field_name) FROM { tb_name | stb_name } [WHERE clause];
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**Return value type**:Same as the data type of the column being operated upon
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**Applicable data types**: Numeric, Timestamp
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**Applicable data types**: Numeric
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**Applicable table types**: standard tables and supertables
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@ -932,7 +932,7 @@ SELECT MIN(field_name) FROM {tb_name | stb_name} [WHERE clause];
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**Return value type**:Same as the data type of the column being operated upon
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**Applicable data types**: Numeric, Timestamp
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**Applicable data types**: Numeric
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**Applicable table types**: standard tables and supertables
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@ -968,7 +968,7 @@ SELECT SAMPLE(field_name, K) FROM { tb_name | stb_name } [WHERE clause]
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**Applicable table types**: standard tables and supertables
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**More explanations**:
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**More explanations**:
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This function cannot be used in expression calculation.
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- Must be used with `PARTITION BY tbname` when it's used on a STable to force the result on each single timeline
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@ -1046,10 +1046,10 @@ SELECT CSUM(field_name) FROM { tb_name | stb_name } [WHERE clause]
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**Applicable table types**: standard tables and supertables
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**More explanations**:
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**More explanations**:
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- Arithmetic operation can't be performed on the result of `csum` function
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- Can only be used with aggregate functions This function can be used with supertables and standard tables.
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- Can only be used with aggregate functions This function can be used with supertables and standard tables.
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- Must be used with `PARTITION BY tbname` when it's used on a STable to force the result on each single timeline
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@ -1067,8 +1067,8 @@ SELECT DERIVATIVE(field_name, time_interval, ignore_negative) FROM tb_name [WHER
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**Applicable table types**: standard tables and supertables
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**More explanation**:
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**More explanation**:
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- It can be used together with `PARTITION BY tbname` against a STable.
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- It can be used together with a selected column. For example: select \_rowts, DERIVATIVE() from。
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@ -1086,7 +1086,7 @@ SELECT {DIFF(field_name, ignore_negative) | DIFF(field_name)} FROM tb_name [WHER
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**Applicable table types**: standard tables and supertables
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**More explanation**:
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**More explanation**:
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- The number of result rows is the number of rows subtracted by one, no output for the first row
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- It can be used together with a selected column. For example: select \_rowts, DIFF() from。
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@ -1123,9 +1123,9 @@ SELECT MAVG(field_name, K) FROM { tb_name | stb_name } [WHERE clause]
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**Applicable table types**: standard tables and supertables
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**More explanations**:
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- Arithmetic operation can't be performed on the result of `MAVG`.
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**More explanations**:
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- Arithmetic operation can't be performed on the result of `MAVG`.
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- Can only be used with data columns, can't be used with tags. - Can't be used with aggregate functions.
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- Must be used with `PARTITION BY tbname` when it's used on a STable to force the result on each single timeline
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@ -127,7 +127,7 @@ SELECT COS(field_name) FROM { tb_name | stb_name } [WHERE clause]
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SELECT FLOOR(field_name) FROM { tb_name | stb_name } [WHERE clause];
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```
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**功能说明**：获得指定字段的向下取整数的结果。
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**功能说明**：获得指定字段的向下取整数的结果。
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其他使用说明参见 CEIL 函数描述。
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#### LOG
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@ -174,7 +174,7 @@ SELECT POW(field_name, power) FROM { tb_name | stb_name } [WHERE clause]
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SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause];
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```
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**功能说明**：获得指定字段的四舍五入的结果。
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**功能说明**：获得指定字段的四舍五入的结果。
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其他使用说明参见 CEIL 函数描述。
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@ -435,7 +435,7 @@ SELECT TO_ISO8601(ts[, timezone]) FROM { tb_name | stb_name } [WHERE clause];
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**使用说明**：
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- timezone 参数允许输入的时区格式为: [z/Z, +/-hhmm, +/-hh, +/-hh:mm]。例如，TO_ISO8601(1, "+00:00")。
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- 如果输入是表示 UNIX 时间戳的整形，返回格式精度由时间戳的位数决定;
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- 如果输入是表示 UNIX 时间戳的整形，返回格式精度由时间戳的位数决定;
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- 如果输入是 TIMESTAMP 类型的列，返回格式的时间戳精度与当前 DATABASE 设置的时间精度一致。
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@ -770,14 +770,14 @@ SELECT HISTOGRAM(field_name，bin_type, bin_description, normalized) FROM tb_nam
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**详细说明**：
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- 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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- 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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- 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）作为区间起点和终点，
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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）作为区间起点和终点，
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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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@ -918,7 +918,7 @@ SELECT MAX(field_name) FROM { tb_name | stb_name } [WHERE clause];
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**返回数据类型**：同应用的字段。
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**适用数据类型**：数值类型，时间戳类型。
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**适用数据类型**：数值类型。
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**适用于**：表和超级表。
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@ -933,7 +933,7 @@ SELECT MIN(field_name) FROM {tb_name | stb_name} [WHERE clause];
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**返回数据类型**：同应用的字段。
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**适用数据类型**：数值类型，时间戳类型。
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**适用数据类型**：数值类型。
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**适用于**：表和超级表。
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@ -969,7 +969,7 @@ SELECT SAMPLE(field_name, K) FROM { tb_name | stb_name } [WHERE clause]
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**适用于**：表和超级表。
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**使用说明**：
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**使用说明**：
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- 不能参与表达式计算；该函数可以应用在普通表和超级表上；
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- 使用在超级表上的时候，需要搭配 PARTITION by tbname 使用，将结果强制规约到单个时间线。
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@ -1047,10 +1047,10 @@ SELECT CSUM(field_name) FROM { tb_name | stb_name } [WHERE clause]
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**适用于**：表和超级表。
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**使用说明**：
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**使用说明**：
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- 不支持 +、-、*、/ 运算，如 csum(col1) + csum(col2)。
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- 只能与聚合（Aggregation）函数一起使用。 该函数可以应用在普通表和超级表上。
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- 只能与聚合（Aggregation）函数一起使用。 该函数可以应用在普通表和超级表上。
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- 使用在超级表上的时候，需要搭配 PARTITION BY tbname使用，将结果强制规约到单个时间线。
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@ -1068,8 +1068,8 @@ SELECT DERIVATIVE(field_name, time_interval, ignore_negative) FROM tb_name [WHER
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**适用于**：表和超级表。
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**使用说明**:
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**使用说明**:
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- DERIVATIVE 函数可以在由 PARTITION BY 划分出单独时间线的情况下用于超级表（也即 PARTITION BY tbname）。
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- 可以与选择相关联的列一起使用。 例如: select \_rowts, DERIVATIVE() from。
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@ -1087,7 +1087,7 @@ SELECT {DIFF(field_name, ignore_negative) | DIFF(field_name)} FROM tb_name [WHER
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**适用于**：表和超级表。
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**使用说明**:
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**使用说明**:
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- 输出结果行数是范围内总行数减一，第一行没有结果输出。
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- 可以与选择相关联的列一起使用。 例如: select \_rowts, DIFF() from。
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@ -1124,9 +1124,9 @@ SELECT MAVG(field_name, K) FROM { tb_name | stb_name } [WHERE clause]
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**适用于**：表和超级表。
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**使用说明**：
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- 不支持 +、-、*、/ 运算，如 mavg(col1, k1) + mavg(col2, k1);
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**使用说明**：
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- 不支持 +、-、*、/ 运算，如 mavg(col1, k1) + mavg(col2, k1);
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- 只能与普通列，选择（Selection）、投影（Projection）函数一起使用，不能与聚合（Aggregation）函数一起使用；
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- 使用在超级表上的时候，需要搭配 PARTITION BY tbname使用，将结果强制规约到单个时间线。
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@ -311,22 +311,6 @@ static int32_t translateInOutStr(SFunctionNode* pFunc, char* pErrBuf, int32_t le
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return TSDB_CODE_SUCCESS;
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}
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static int32_t translateMinMax(SFunctionNode* pFunc, char* pErrBuf, int32_t len) {
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if (1 != LIST_LENGTH(pFunc->pParameterList)) {
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return invaildFuncParaNumErrMsg(pErrBuf, len, pFunc->functionName);
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}
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uint8_t paraType = ((SExprNode*)nodesListGetNode(pFunc->pParameterList, 0))->resType.type;
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if (!IS_TIMESTAMP_TYPE(paraType) && !IS_NUMERIC_TYPE(paraType) && !IS_NULL_TYPE(paraType)) {
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return invaildFuncParaTypeErrMsg(pErrBuf, len, pFunc->functionName);
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} else if (IS_NULL_TYPE(paraType)) {
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paraType = TSDB_DATA_TYPE_BIGINT;
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}
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pFunc->node.resType = (SDataType){.bytes = tDataTypes[paraType].bytes, .type = paraType};
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return TSDB_CODE_SUCCESS;
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}
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static int32_t translateTrimStr(SFunctionNode* pFunc, char* pErrBuf, int32_t len, bool isLtrim) {
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if (1 != LIST_LENGTH(pFunc->pParameterList)) {
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return invaildFuncParaNumErrMsg(pErrBuf, len, pFunc->functionName);
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@ -2076,7 +2060,7 @@ const SBuiltinFuncDefinition funcMgtBuiltins[] = {
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.name = "min",
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.type = FUNCTION_TYPE_MIN,
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.classification = FUNC_MGT_AGG_FUNC | FUNC_MGT_SPECIAL_DATA_REQUIRED | FUNC_MGT_SELECT_FUNC,
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.translateFunc = translateMinMax,
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.translateFunc = translateInOutNum,
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.dataRequiredFunc = statisDataRequired,
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.getEnvFunc = getMinmaxFuncEnv,
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.initFunc = minmaxFunctionSetup,
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@ -2091,7 +2075,7 @@ const SBuiltinFuncDefinition funcMgtBuiltins[] = {
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.name = "max",
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.type = FUNCTION_TYPE_MAX,
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.classification = FUNC_MGT_AGG_FUNC | FUNC_MGT_SPECIAL_DATA_REQUIRED | FUNC_MGT_SELECT_FUNC,
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.translateFunc = translateMinMax,
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.translateFunc = translateInOutNum,
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.dataRequiredFunc = statisDataRequired,
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.getEnvFunc = getMinmaxFuncEnv,
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.initFunc = minmaxFunctionSetup,
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@ -1204,7 +1204,7 @@ int32_t doMinMaxHelper(SqlFunctionCtx* pCtx, int32_t isMinFunc) {
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pBuf->tuplePos = saveTupleData(pCtx, index, pCtx->pSrcBlock);
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}
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} else {
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if (IS_SIGNED_NUMERIC_TYPE(type) || IS_TIMESTAMP_TYPE(type)) {
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if (IS_SIGNED_NUMERIC_TYPE(type)) {
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int64_t prev = 0;
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GET_TYPED_DATA(prev, int64_t, type, &pBuf->v);
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@ -1263,7 +1263,7 @@ int32_t doMinMaxHelper(SqlFunctionCtx* pCtx, int32_t isMinFunc) {
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int32_t start = pInput->startRowIndex;
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int32_t numOfRows = pInput->numOfRows;
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if (IS_SIGNED_NUMERIC_TYPE(type) || IS_TIMESTAMP_TYPE(type) || type == TSDB_DATA_TYPE_BOOL) {
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if (IS_SIGNED_NUMERIC_TYPE(type) || type == TSDB_DATA_TYPE_BOOL) {
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if (type == TSDB_DATA_TYPE_TINYINT || type == TSDB_DATA_TYPE_BOOL) {
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int8_t* pData = (int8_t*)pCol->pData;
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int8_t* val = (int8_t*)&pBuf->v;
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@ -1357,7 +1357,7 @@ int32_t doMinMaxHelper(SqlFunctionCtx* pCtx, int32_t isMinFunc) {
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numOfElems += 1;
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}
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} else if (type == TSDB_DATA_TYPE_BIGINT || type == TSDB_DATA_TYPE_TIMESTAMP) {
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} else if (type == TSDB_DATA_TYPE_BIGINT) {
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int64_t* pData = (int64_t*)pCol->pData;
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int64_t* val = (int64_t*)&pBuf->v;
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@ -38,18 +38,7 @@ class TDTestCase:
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elif i>=9:
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tdSql.checkData(0, 0, np.max(floatData))
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tdSql.query(f"select max(now()) from {dbname}.stb_1")
|
||||
tdSql.checkRows(1)
|
||||
|
||||
tdSql.query(f"select last(ts) from {dbname}.stb_1")
|
||||
lastTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select max(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, lastTs)
|
||||
|
||||
tdSql.query(f"select last(ts) from {dbname}.stb")
|
||||
lastTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select max(ts) from {dbname}.stb")
|
||||
tdSql.checkData(0, 0, lastTs)
|
||||
tdSql.error(f"select max(now()) from {dbname}.stb_1")
|
||||
|
||||
tdSql.query(f"select max(col1) from {dbname}.stb_1 where col2<=5")
|
||||
tdSql.checkData(0,0,5)
|
||||
|
|
@ -78,13 +67,7 @@ class TDTestCase:
|
|||
elif i>=9:
|
||||
tdSql.checkData(0, 0, np.max(floatData))
|
||||
|
||||
tdSql.query(f"select max(now()) from {dbname}.ntb")
|
||||
tdSql.checkRows(1)
|
||||
|
||||
tdSql.query(f"select last(ts) from {dbname}.ntb")
|
||||
lastTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select max(ts) from {dbname}.ntb")
|
||||
tdSql.checkData(0, 0, lastTs)
|
||||
tdSql.error(f"select max(now()) from {dbname}.ntb")
|
||||
|
||||
tdSql.query(f"select max(col1) from {dbname}.ntb where col2<=5")
|
||||
tdSql.checkData(0,0,5)
|
||||
|
|
|
|||
|
|
@ -37,6 +37,8 @@ class TDTestCase:
|
|||
floatData.append(i + 0.1)
|
||||
|
||||
# max verifacation
|
||||
tdSql.error(f"select min(now()) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col7) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col8) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col9) from {dbname}.stb_1")
|
||||
|
|
@ -67,20 +69,9 @@ class TDTestCase:
|
|||
tdSql.query(f"select min(col1) from {dbname}.stb_1 where col2>=5")
|
||||
tdSql.checkData(0,0,5)
|
||||
|
||||
tdSql.query(f"select min(now()) from {dbname}.stb_1")
|
||||
tdSql.checkRows(1)
|
||||
|
||||
tdSql.query(f"select first(ts) from {dbname}.stb_1")
|
||||
firstTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, firstTs)
|
||||
|
||||
tdSql.query(f"select first(ts) from {dbname}.stb_1")
|
||||
firstTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, firstTs)
|
||||
|
||||
|
||||
tdSql.error(f"select min(now()) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col7) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col8) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col9) from {dbname}.stb_1")
|
||||
|
|
@ -111,19 +102,8 @@ class TDTestCase:
|
|||
tdSql.query(f"select min(col1) from {dbname}.stb where col2>=5")
|
||||
tdSql.checkData(0,0,5)
|
||||
|
||||
tdSql.query(f"select min(now()) from {dbname}.stb_1")
|
||||
tdSql.checkRows(1)
|
||||
|
||||
tdSql.query(f"select first(ts) from {dbname}.stb_1")
|
||||
firstTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, firstTs)
|
||||
|
||||
tdSql.query(f"select first(ts) from {dbname}.stb_1")
|
||||
firstTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, firstTs)
|
||||
|
||||
tdSql.error(f"select min(now()) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.error(f"select min(col7) from {dbname}.ntb")
|
||||
tdSql.error(f"select min(col8) from {dbname}.ntb")
|
||||
tdSql.error(f"select min(col9) from {dbname}.ntb")
|
||||
|
|
@ -154,19 +134,6 @@ class TDTestCase:
|
|||
tdSql.query(f"select min(col1) from {dbname}.ntb where col2>=5")
|
||||
tdSql.checkData(0,0,5)
|
||||
|
||||
tdSql.query(f"select min(now()) from {dbname}.stb_1")
|
||||
tdSql.checkRows(1)
|
||||
|
||||
tdSql.query(f"select first(ts) from {dbname}.stb_1")
|
||||
firstTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, firstTs)
|
||||
|
||||
tdSql.query(f"select first(ts) from {dbname}.stb_1")
|
||||
firstTs = tdSql.getData(0, 0)
|
||||
tdSql.query(f"select min(ts) from {dbname}.stb_1")
|
||||
tdSql.checkData(0, 0, firstTs)
|
||||
|
||||
|
||||
def stop(self):
|
||||
tdSql.close()
|
||||
|
|
|
|||
Loading…
Reference in New Issue