Consider you want to perform an incremental load between Source and Target table. Let assume you have both source and target table in MS SQL database. Perform the below steps for incremental loading:
1. Create a reference table for incremental load in target database (e.g., dbo.Incrementalload with columns TableName and Incrementaldate1). Your table will look like this:
---------------------------------------------------------------
TableName | Incrementaldate1 | Incrementaldate2
----------------------------------------------------------------
Event | 2000-01-01 | NULL
----------------------------------------------------------------
User | 2010-01-01 | NULL
----------------------------------------------------------------
2. Design your Talend job as like below:
![](data:image/png;base64,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)
3. Create a context variable 'Incrementaldate1'
4. In tMSSQLInput_2: Get incremental date to assign to context variable.
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)
5. tJavaRow_1: Assign incremental date to context variable.
![](data:image/png;base64,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)
6. tMSSQLInput_3: Retrive data from source.
In WHERE condition call the context variable.
7. tMSSQLOutput_2: Load data to target table.
8. tMSSQLRow_2 : Update the Incrementaldate1 in IncrementalLoad table with Talend Getdate()
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)
So in next load, only the data with modified date greater than incremental date will be retrieved and loaded.
1. Create a reference table for incremental load in target database (e.g., dbo.Incrementalload with columns TableName and Incrementaldate1). Your table will look like this:
---------------------------------------------------------------
TableName | Incrementaldate1 | Incrementaldate2
----------------------------------------------------------------
Event | 2000-01-01 | NULL
----------------------------------------------------------------
User | 2010-01-01 | NULL
----------------------------------------------------------------
2. Design your Talend job as like below:
3. Create a context variable 'Incrementaldate1'
4. In tMSSQLInput_2: Get incremental date to assign to context variable.
5. tJavaRow_1: Assign incremental date to context variable.
6. tMSSQLInput_3: Retrive data from source.
In WHERE condition call the context variable.
7. tMSSQLOutput_2: Load data to target table.
8. tMSSQLRow_2 : Update the Incrementaldate1 in IncrementalLoad table with Talend Getdate()
So in next load, only the data with modified date greater than incremental date will be retrieved and loaded.
same date is taken from incremental load and again put back in same table . So the date remains same in incremental load table
ReplyDeleteHi Sir,
ReplyDeleteCould you please explain why you added "minus -15 in the below query.
"select incrementaldate1-15 from dbo.incrementalload where ******.
Thanks
shridhar
Sir where is your source table
ReplyDeletethe variable is not passing in the where condition ....any other thing want to predefined
ReplyDelete