what is the difference between the join and look up
explin me one exmple
Answers were Sorted based on User's Feedback
Answer / ankit gosain
Difference Between Join & Lookup:
1. In join stage you can do Inner Join, Left outer, Right
Outer and Full outer join, while in Lookup stage you can do
Inner join & Left outer join only.
2. In join stage you can't have a reject link, while in
lookup stage you can have a reject link for Unmatched
Primary records.
3. In join stage sorted data is mandatory, while in lookup
stage sorted data is not mandatory for lookup source.
4. Join stage requires Hash Partitioned data, while lookup
stage requires Entire partitioned lookup data.
5. In case of Join, Disk I/O is more while it's very less
in case of lookup (since at the time of matching, complete
lookup data is present in the memory).
6. In case of Join Stage, the key column name must be the
same in both the sources, while in case of lookup stage
it's not mandatory.
Cheers,
Ankit :)
| Is This Answer Correct ? | 4 Yes | 0 No |
join lookup
i/p names- left,right,intermediate primary,secondary
join ops - left,right,inner,fullout left,inner
in & out - n i/p(s)-left,right,inner n i/p(s) normal
2 i/p(s)-full outer 2 i/p(s) sparse
1 o/p 1 o/p
rejects - n/a one
sort data- Mandatory optional
KcolNames- Mandatory optional
deduplica- no problem warnings in secondary.
memory - light high
| Is This Answer Correct ? | 0 Yes | 0 No |
1.Join needs key column metadata should be same|Lookup key column metadata its not mandatory to be same
2.Implement Four join in JOIN|But in Lookup only TWO JOIN(left outer,INNER)
3.JOIN does not have reject link | LOOKUP has one reject link
4.Data should be sorted and default is hash partioning |LOOKUP data need not to be in sort and default partioning is ENTIRE
5.Performance is HIGH in JOIN | Performance is less in JOIN
6.Duplicate will arise in JOIN|can handle Duplicate in LOOKUP
| Is This Answer Correct ? | 0 Yes | 0 No |
1.What is the flow of Transformer? 2.How can you do INDEX table in DataStage level?
What is use Array size in datastage
I have the following columns in the EMP table Empid,Empname,Sal,month(Sal),year(Sal) and DOB(let us say the dob is 15th-Jan-1981) Desing a job such that the output contains the following empname,year(sal),tot(sal) and current age i.e. whether 18yrs or so on
What are the steps required to kill the job in Datastage?
What are the different type of jobs in datastage?
what r the stages mostly used in realtime scenarios
Differentiate between Join, Merge and Lookup stage?
What is oci?
what is time dimension? and how to populate time demension
what should be ensure to run the sequence job so that if its get aborted in 10th job before 9job should get succeeded?
AGGREGATOR default datatype
in job of 30 one job is very slow due to this entire job is very slow how can u know which job is slow?