![]() If we truncate the part of date like microseconds, milliseconds, second, minute, hour, day, week, month, quarter, year, decade, century, a millennium from the specific date, then we need to pass the particular parameter in the first argument using date_trunc function in redshift. If we want to truncate the timestamp value from minute, then we need to pass the minute argument with the date_trunc function. We can also use the date_trunc function with a group by and order by clauses to retrieve the data as per order or per clause, we used in our query. To use the date_trunc function, we need the data type of column as date type format. ![]() SELECT date_trunc ('year', salesid) from sales group by date_trunc ('year', salesid) So at the time of executing the below query, it will issue the error that the function will not be matching the argument types. In the below example, we have used column name as salesid this column contains the data type as integer. The below example shows that to use the date_trunc function, we need data type of column as date type format. ![]() We cannot use the date_trunc function on a string or numeric data type columns. We can specify the date part as a date type column name or weeks, months, year, day, seconds, minute. To use the date_trunc function in redshift, it will require the date part. Using the function, we can truncate the hour, weeks, months, year, day, seconds, minute etc. interval: This parameter is nothing but the interval argument, which was we have to pass with the date_trunc function in redshift.īelow is the field or interval argument of precision, which was used to truncate the date using the date_trunc function in redshift.īasically, we can say that the function will work on only the date type column or value.This parameter is also converting the expression into the timestamp format. timestamp: Using the date_trunc function, we can also use the timestamp value, which was used to convert the timestamp column into the timestamp.We have to specify the column name which data type contains the date value. column name: We are using column name to truncate the specified timestamp value from the date column.This is an essential parameter of the date_trunc function in redshift. datepart: Using this parameter, we have to truncate the specified timestamp value.If suppose we want to remove unwanted details from the date and time, then we have using the date_trunc function in redshift. We are using this function for date and time values. date_trunc: This function in redshift is similar to trunc, which was used for numbers.
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