Which three Lookup types may be performed in the Lookup stage?

07/05/2019 Off By admin

Which three Lookup types may be performed in the Lookup stage?

The Lookup stage can have a reference link, a single input link, a single output link, and a single rejects link.

How does Lookup work in DataStage?

The Lookup stage is a processing stage that is used to perform lookup operations on a data set read into memory from any other Parallel job stage that can output data. As the Lookup stage reads each line, it uses the key to look up the state in the lookup table.

What are the join operation performed in Lookup stage?

Use the Join stage when: Joining large tables (you will run out of RAM with the Lookup stage). Doing outer joins (left, right, full outer). Joining multiple tables with the same keys.

What action is taken when a lookup fails to find a matching key column?

To specify the action taken if a lookup on a link fails: Choose an action from the Lookup Failure list….Possible actions are:

  • Continue. The fields from that link are set to NULL if the field is nullable, or to a default value if not.
  • Drop.
  • Fail.
  • Reject.

In which situation is it appropriate to use a sparse lookup?

Typically, you use a sparse lookup when the target table is too large to fit in memory. You can also use the sparse lookup method for real-time jobs. You can use the sparse lookup method only in parallel jobs.

Which stage requires most memory in DataStage?

Lookup stage
The Lookup stage is most appropriate when the reference data for all Lookup stages in a job is small enough to fit into available physical memory. Each lookup reference requires a contiguous block of physical memory. The Lookup stage requires all but the first input (the primary input) to fit into physical memory.

What is sequential file in DataStage?

The Sequential File stage is a file stage that allows you to read data from or write data one or more flat files. The stage can have a single input link or a single output link, and a single rejects link. You can specify that single files can be read by multiple nodes.

What is the difference between normal lookup and sparse lookup?

Normal will provide data for an in-memory look up whereas Sparse will access the database directly. Normal might provide poor performance when the reference data is huge as it has to load large data into memory.

Why is the sparse lookup in DataStage faster than normal lookup?

Sparse Lookup directly hits the database. If the input stream data is less and reference data is more like 1:100 or more in such cases sparse lookup is better. Sparse Lookup,we can only have one reference link.

Which is faster lookup or joiner?

Sometimes joiner gives more performance and sometimes lookups. In case of Flat file, generally, sorted joiner is more effective than lookup, because sorted joiner uses join conditions and caches less rows. Lookup caches always whole file.

What is difference between lookup and join?

What is the difference between lookup,and join? Pavan Kurapati (Trifacta, Inc.) A lookup compares each value in the selected column against the values in a selected column of the target dataset. A join is a standard operation for merging the data from two different datasets.

When to use the lookup stage in a job?

The Lookup stage is most appropriate when the reference data for all lookup stages in a job is small enough to fit into available physical memory. Each lookup reference requires a contiguous block of shared memory.

Do you need to sort links in lookup stage?

Lookup stages do not require data on the input link or reference links to be sorted. Be aware, though, that large in-memory lookup tables will degrade performance because of their paging requirements.

What are the lookup columns of the output data set?

Each record of the output data set contains columns from a source record plus columns from all the corresponding lookup records where corresponding source and lookup records have the same value for the lookup key columns. The lookup key columns do not have to have the same names in the primary and the reference links.

Why are in memory lookup tables degrading performance?

Be aware, though, that large in-memory lookup tables will degrade performance because of their paging requirements. Each record of the output data set contains columns from a source record plus columns from all the corresponding lookup records where corresponding source and lookup records have the same value for the lookup key columns.