Skip to main content

SQL DATENAME Function - Year, Quarter, Month, Day, Hour, Minute and Milisecond.

It return specifies the part of the date name and the DATENAME for Date Time such as Year, Quarter, Month, Day, Hour, Minute and Milisecond.

SQL DATENAME Syntax
DATENAME ( datepart , date )

Example

SELECT GETDATE() = 2011-11-29 15:33:17.153

SELECT DATENAME(year, GETDATE())
SELECT DATENAME(yy, GETDATE())
SELECT DATENAME(yy, GETDATE())
- It will return value = 2011

SELECT DATENAME(quarter, GETDATE())
SELECT DATENAME(qq, GETDATE())
SELECT DATENAME(q, GETDATE())
-It will return value = 4 (because 1 quarter equal to 3 month,Detail see below table)
Month
Quarter Value
January - March
1
April - June
2
July - September
3
October - December
4


SELECT DATENAME(month, GETDATE())
SELECT DATENAME(mm, GETDATE())
SELECT DATENAME(m, GETDATE())
- It will return value = November
SELECT DATENAME(dayofyear, GETDATE())
SELECT DATENAME(dy, GETDATE())
SELECT DATENAME(y, GETDATE())
- It will return value = 333 (this is calculate total day from 1 jan 2007 until 28 nov 2011)

SELECT DATENAME(day, GETDATE())
SELECT DATENAME(dd, GETDATE())
SELECT DATENAME(d, GETDATE())
- It will return value = 29

SELECT DATENAME(week, GETDATE())
SELECT DATENAME(wk, GETDATE())
SELECT DATENAME(ww, GETDATE())
- It will return value = 49 (this is 23rd week from 1 jan 2007)

SELECT DATENAME(hour, GETDATE())
SELECT DATENAME(hh, GETDATE())
- It will return value = 15 (time for 24 hour)

SELECT DATENAME(minute, GETDATE())
SELECT DATENAME(mi, GETDATE())
SELECT DATENAME(n, GETDATE())
- It will return value =36 (minute)

SELECT DATENAME(second , GETDATE())
SELECT DATENAME(ss, GETDATE())
SELECT DATENAME(s, GETDATE())
- It will return value = 38 (second)

SELECT DATENAME(millisecond , GETDATE())
SELECT DATENAME(ms, GETDATE())
- It will return value = 763 (milisecond)

Comments

Popular posts from this blog

BIG Data, Hadoop – Chapter 2 - Data Life Cycle

Data Life Cycle The data life cycle is pictorial defined as show below:     As we see, in our current system, we capture/ Extract our data, then we store it and later we process for reporting and analytics. But in case of big data, the problem lies in storing and then processing it faster. Hence Hadoop takes this portion, where it stores the data in effective format (Hadoop distributed File System) and also process using its engine (Map Reduce Engine). Since Map Reduce engine or Hadoop engine need data on HDFS format to process, We have favorable tools available in market to do this operation. As an example, Scoop is a tool which converts RDBMS to HDFS. Likewise we have SAP BOD to convert sap system data to HDFS.

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)" returned message "The Microsoft Access database engine cannot open or write to the file ''. It is already opened exclusively by another user, or you need permission to view and write its data.". Msg 7303, Level 16, State 1, Line 1 Cannot initialize the data source object of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)".

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)" returned message "The Microsoft Access database engine cannot open or write to the file ''. It is already opened exclusively by another user, or you need permission to view and write its data.". Msg 7303, Level 16, State 1, Line 1 Cannot initialize the data source object of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)". If you get this error while Loading Data From Excel to SQL Server, then, close the Excel sheet opened and try to run queries again.