2020. 1. 24. 04:06ㆍ카테고리 없음
The Slowly Changing Dimension problem is a common one particular to data warehousing.There are in general three ways to solve this type of problem, and they are categorized as follows: Type 1: The new record replaces the original record. If you want R.NET to grab a whole load of numbers in this fashion, it’s very easy. Finally, it’s a case of setting up the output from the calculator to be equal to the first value in x. This is because we’re expecting x to be only one value anyway.
I was loading data using SQL.Loader and when making the control file I used the table definition and accidentally left the INTEGER data type on the 'version' line.And in the 'version' field (data type integer) it inserted the value 808594481.I'm having a hard time understanding how it processed this value - I'm assuming it took it as a literal. But is that the sum of the ASCII representations of each letter?NOPE! SELECT ASCII('I')+ascii('N')+ASCII('T')+ASCII('E')+ASCII('G')+ASCII('E')+ASCII('G')+ASCII('E')+ASCII('R')FROM SYS.DUALreturns 666 (which, btw is hilarious).concatenate ascii values?
Sql Loader Example
WhyIncremental?. Speed.Opting to do a full load on larger datasets will take a great amount oftime and other server resources. Ideally all the data loads are performedovernight with the expectation of completing them before users can see thedata the next day. The overnight window may not be enough time forthe full load to complete. Preserving history.When dealing with a OLTP source that is not designed to keep history, afull load will remove history from the destination as well, since fullload will remove all the records first, remember! So a full load will notallow you to preserve history in the data warehouse.