**Return value type**: If all input strings are VARCHAR type, the result is VARCHAR type too. If any one of input strings is NCHAR type, then the result is NCHAR. If input strings contain NULL value, the result is NULL.
**Return value type**: If all input strings are VARCHAR type, the result is VARCHAR type too. If any one of input strings is NCHAR type, then the result is NCHAR. If input strings contain NULL value, the result is NULL.
**Applicable data types**: VARCHAR, NCHAR. At least 2 input strings are requird, and at most 8 input strings are allowed.
**Applicable data types**: VARCHAR, NCHAR. At least 2 input strings are required, and at most 8 input strings are allowed.
**Applicable table types**: table, STable.
**Applicable table types**: table, STable.
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@@ -290,7 +290,7 @@ SELECT CONCAT_WS(separator, str1|column1, str2|column2, ...) FROM { tb_name | st
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@@ -290,7 +290,7 @@ SELECT CONCAT_WS(separator, str1|column1, str2|column2, ...) FROM { tb_name | st
**Return value type**: If all input strings are VARCHAR type, the result is VARCHAR type too. If any one of input strings is NCHAR type, then the result is NCHAR. If input strings contain NULL value, the result is NULL.
**Return value type**: If all input strings are VARCHAR type, the result is VARCHAR type too. If any one of input strings is NCHAR type, then the result is NCHAR. If input strings contain NULL value, the result is NULL.
**Applicable data types**: VARCHAR, NCHAR. At least 3 input strings are requird, and at most 9 input strings are allowed.
**Applicable data types**: VARCHAR, NCHAR. At least 3 input strings are required, and at most 9 input strings are allowed.
**More explanations**: The benefit of using hyperloglog algorithm is that the memory usage is under control when the data volume is huge. However, when the data volume is very small, the result may be not accurate, it's recommented to use `select count(data) from (select unique(col) as data from table)` in this case.
**More explanations**: The benefit of using hyperloglog algorithm is that the memory usage is under control when the data volume is huge. However, when the data volume is very small, the result may be not accurate, it's recommented to use `select count(data) from (select unique(col) as data from table)` in this case.
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@@ -751,14 +753,14 @@ SELECT HISTOGRAM(field_name,bin_type, bin_description, normalized) FROM tb_nam
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@@ -751,14 +753,14 @@ SELECT HISTOGRAM(field_name,bin_type, bin_description, normalized) FROM tb_nam
**Return value type**:DOUBLE or BIGINT, depends on normalized parameter settings.
**Return value type**:DOUBLE or BIGINT, depends on normalized parameter settings.
**Applicable column type**:Numerical types.
**Applicable data type**:Numerical types.
**Applicable table types**: table, STable.
**Applicable table types**: table, STable.
**Explanations**:
**Explanations**:
1. bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin"。
- bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin"。
2. bin_description: parameter to describe the rule to generate buckets,can be in the following JSON formats for each bin_type respectively:
- bin_description: parameter to describe the rule to generate buckets,can be in the following JSON formats for each bin_type respectively:
- "user_input": "[1, 3, 5, 7]": User specified bin values.
- "user_input": "[1, 3, 5, 7]": User specified bin values.
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@@ -776,7 +778,7 @@ SELECT HISTOGRAM(field_name,bin_type, bin_description, normalized) FROM tb_nam
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@@ -776,7 +778,7 @@ SELECT HISTOGRAM(field_name,bin_type, bin_description, normalized) FROM tb_nam
"infinity" - whether to add(-inf, inf)as start/end point in generated range of bins.
"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].
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.
- normalized: setting to 1/0 to turn on/off result normalization.
**Return value type**: Same as the data type of the column being operated upon.
**Return value type**: Same as the data type of the column being operated upon.
**Applicable column types**: Numeric types.
**Applicable data types**: Numeric types.
**Applicable table types**: table, STable.
**Applicable table types**: table, STable.
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@@ -939,7 +941,7 @@ SELECT MODE(field_name) FROM tb_name [WHERE clause];
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@@ -939,7 +941,7 @@ SELECT MODE(field_name) FROM tb_name [WHERE clause];
**Return value type**:Same as the data type of the column being operated upon.
**Return value type**:Same as the data type of the column being operated upon.
**Applicable column types**: All data types.
**Applicable data types**: All data types.
**More explanations**:Considering the number of returned result set is unpredictable, it's suggested to limit the number of unique values to 100,000, otherwise error will be returned.
**More explanations**:Considering the number of returned result set is unpredictable, it's suggested to limit the number of unique values to 100,000, otherwise error will be returned.