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The exponent has and optional leading minus sign. The mantissa has an optional leading minus sign followed by one digit to the left of the decimal point, and the minimal number of digits greater than zero to the right. ![]() Otherwise, Databricks uses a mantissa followed by E and an exponent. If the absolute number is less that 10,000,000 and greater or equal than 0.001, the result is expressed without scientific notation with at least one digit on either side of the decimal point. If the targetType is DECIMAL(p, s) with s greater 0, a decimal point is added and trailing zeros are added up to scale. The result is the literal number with an optional minus-sign and no leading zeros except for the single digit to the left of the decimal point. If the targetType is a STRING type and sourceExpr is of type: If the lower_unit is SECOND, fractional seconds are stored to the right of the decimal point.įor all other intervals the result is always an integral number. Given an INTERVAL upper_unit TO lower_unit the result is measured in total number of lower_unit. If the result is outside the range of targetType, an overflow error is raised.Īpplies to: Databricks SQL Databricks Runtime 11.2 and above Otherwise, the result is rounded to a fit the available scale of targetType. If targetType is an integral numeric, the result is truncated to a whole number. The result is the number of seconds elapsed between 00:00:00 UTC and sourceExpr. Use try_cast to turn overflow and invalid format errors into NULL. If the value is outside the range of the targetType, an overflow error is raised. ![]() If sourceExpr doesn’t comply with the format for literal values, an error is raised. SourceExpr is read as a literal value of the targetType. Use try_cast to turn overflow errors into NULL. If the value is outside the range of targetType, an overflow error is raised. ![]() Otherwise, the result is sourceExpr rounded to a fit the available scale of targetType. If targetType is an integral numeric, the result is sourceExpr truncated to a whole number. The result is a NULL of the specified numeric type. If the targetType is a numeric and sourceExpr is of type: INSERT OVERWRITE DIRECTORY with Hive format.Privileges and securable objects in the Hive metastore.Privileges and securable objects in Unity Catalog.Integration with Hive UDFs, UDAFs, and UDTFs.User-defined aggregate functions (UDAFs).Alphabetical list of built-in functions.>= CONVERT(datetime, ' 00:00:00', 120)ĪND < CONVERT(datetime, ' 00:00:00', 120) īeing explicit about types is a very good habit to get into, particularly when dealing with dates and times. That said, there are good reasons (as Aaron points out in his answer) to use a half-open range instead of BETWEEN (I use style 120 below just for variety): SELECT COUNT(*) Being explicit about the data type and string style results in the following: SELECT COUNT(*) The question uses strings in ODBC canonical (with milliseconds) format (style 121). When working with strings and date/time types, CONVERT is to be preferred because it provides a style parameter to explicitly define the string format. SQL Server provides the CAST and CONVERT functions for this purpose. ![]() In my view, the neatest way to avoid these types of issues is to be explicit about types. Without explicit information about the format of the strings, SQL Server follows its convoluted rules for interpreting strings as datetimes. To compare those literals with the datetime column, SQL Server attempts to convert the strings to datetime types, according to the rules of data type precedence. The literals you are providing for comparison to the Created column are strings. I do not understand why the data is being converted from varchar to datetime when 'Created' is set to datetime
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