DSXchange

Hi,
Im using 8.5.
and, I do need to send older version of records to rejections which will be used by other process, hence I can not apply remove duplicates.

So, in this situation, do I need to use double sort stages?

No. I will get duplicates based on 'Name'. I will not get duplication combination of 2 fields(name and version (or) name and timestamp)

It is taking combination all 3 fields as a group. So for all the records I'm getting create key value '1'

My job design is Table -----Sort-----File While extracting, in a query I added name in ascending, version and timestamp in descending. in sort stage, I applied hash partition and sort on 'Name'. And gave key as 'Name'. For a few records I got '1' for first record (which are max of version & time...

Hi, My input is like below. Name,Version_No,Timestamp,detail AAA,03,9/10/2013 03:51:57,qwer AAA,02,9/10/2013 02:40:17,rfgt AAA,04,9/10/2013 03:55:40,asdf1 BBB,01,9/9/2013 03:25:57,uyhj0 BBB,02,9/9/2013 03:51:45,wert CCC,02,9/9/2013 02:30:50,uyhj12 CCC,03,9/9/2013 02:35:40,uyhj23 I need to process th...

I was to told to omit the record if it has other than alphanumeric and speacial characters.

Hello, I have staging table of around 70 columns with the datatype CHAR. I'm not doing any validation and transformation before load to staging. So I can expect junk or unknown or unwanted values in almost all the columns. for eg., Date or integer field may contain alphanumeric values.Varchar field ...

Hi,
If possible, Could you be more specific?

Hi, I have a scenario in which I receive files on hourly basis. Sometimes I may receive file with data of mutiple hours.(ie., not only data of that hour alone, but also data of its previous hours). Data will be in ascending order ( I mean, data of old hours at first and data of latest hour at last )...

Thanks Ray.
It worked. Double convert is the perfect technique. hence marking as resolved

Hi,

How will it work?. Because target Datasets have diff metatada

SURA wrote:If i would be in your position, i will create a master job which will do all the transformations for all the target tables and my final targetwill be dataset files. Then have on multiple instance job with RCP to load the data.

My job reads large file. I have a column from which I identify the type. Based on type, I segregate data in Transformer and taking 10 diff output links to target tables.

I do receive records not more than 10k(sometimes 0 records) per each table per run and table is going to be truncate and load. I need suggestion on which of below option is better.
1. To have all 10 tables load in single job
2. Design 10 individual jobs and run parallely

Hello
Just need an idea on how many tables can be loaded using single job.
- Tables are independent
- Apprx. each table may receive records in thousands per run
- Only insert
In my case, I have source data which is of diff types which needs to be loaded in more than 10 tables based on type.

Its CHAR(5)