I have input col as 12/03/08 viz dd/MM/yy . So I beed it in the format of dd/MM/yyyy . SO I have use the below transformation as :
toString(toDate(col,'dd/MM/yy'),'dd/MM/yyyy')
This works fine.
But at the end i need to conver this col to date datatype with the same format as dd/MM/yyyy . When i do the CAST transformation like
In cast , i have converted it to date and given the format as dd/MM/yyyy .Its giving the date but in default format like dd-MM-yyyy . I need slashes instead of dashes.
I tried to do
toDate( col, 'dd/MM/yyyy') ,Still i get the default format dd-MM-yyyy.
How to fix this.
When you CAST in SQL for conversion, the resulted format is determined by the default format of your database. If you want to ensure that the date is formatted in a specific way, you can use the DATE_FORMAT function in combination with the toDate function.
If you want to get the wanted dd/MM/yy to the format dd/MM/yyyy, you can use the following transformation:
toString(toDate(col, 'dd/MM/yy'), 'dd/MM/yyyy')
This first converts the string to a type using toDate and then formats itt as a string with the wanted format using the toString function.
However, if you then want to convert the string column back to a date datatype with the format dd/MM/yyyy, you cant simply use the CAST function with the desired format, as the resulting format will still be determined by the default format of your database. Instead, you can use the DATE_FORMAT function to format the date as a string with the desired format, and then convert it back to a date datatype using the toDate function.
To convert the string column col back to a date datatype with the format dd/MM/yyyy, you can use the following transformation:
toDate(DATE_FORMAT(col, 'dd/MM/yyyy'), 'dd/MM/yyyy')
This first formats the date in your string column as a string with the desired format using the DATE_FORMAT function, and then converts it back to a date datatype with the same format using the toDate function.
When I tried to display the date column from pyspark dataframe through show() and display(dataframe) ,those format of the data columns are different . Now how do we arrive which date format is being there in dataframe ?
Display : 2018-02-15T06:47:19.000+0000
show : 2018-02-15 06:47:19
Timestamp in dataframe isn't stored as a string - it's stored using internal representation (Long in case of timestamp) that is then converted into text by show or display.
I have tried to insert date into the postgresql in 'dd.mm.yyyy' format.
First inserted the string type, then the date type
moment(new Date()).format('DD.MM.YYYY') but in database format always like 'yyyy-mm-dd'
What can I do?
Plesase, help
I have table which stores datetime as varchar
Format looks like this 2018-07-16 15:00:00.0 ,
I want to parse this to extract only date part so that I use date part to compare with date in string format such as '2018-07-20' in where clause. What is the best way to achieve this in presto?
This particular format (based on example value 2018-07-16 15:00:00.0 in the question) is understood by cast from varchar to timestamp. You then need to extract date part with another cast:
presto> SELECT CAST(CAST('2018-07-16 15:00:00.0' AS timestamp) AS date);
_col0
------------
2018-07-16
(1 row)
I am wanting to parse a string that is currently in the following format:
MM/dd/YYYY hh:MM:ss
to the following format:
YYYY-mm-dd HH:MM:ss
I am wanting to do this within a MongoDB query.