The Lookup stage is most appropriate when the reference data for all Lookup
stage s in a job is small enough to fit into available physical memory. Each lookup
reference requires a contiguous block of shared memory.
If the datasets are
larger than available memory resources, the JOIN or MERGE stage must be
used.
Limit the use of database Sparse Lookups (available in the DB2 Enterprise,
Oracle Enterprise, and ODBC Enterprise stages) to scenarios where the number
of input rows is significantly smaller (for example, 1:100 or more) than the
number of reference rows.
Sparse Lookups might also be appropriate for exception-based processing when
the number of exceptions is a small fraction of the main input data. It is best to
test both the Sparse and Normal to see which actually performs best, and to
retest if the relative volumes of data change dramatically.
stage s in a job is small enough to fit into available physical memory. Each lookup
reference requires a contiguous block of shared memory.
If the datasets are
larger than available memory resources, the JOIN or MERGE stage must be
used.
Limit the use of database Sparse Lookups (available in the DB2 Enterprise,
Oracle Enterprise, and ODBC Enterprise stages) to scenarios where the number
of input rows is significantly smaller (for example, 1:100 or more) than the
number of reference rows.
Sparse Lookups might also be appropriate for exception-based processing when
the number of exceptions is a small fraction of the main input data. It is best to
test both the Sparse and Normal to see which actually performs best, and to
retest if the relative volumes of data change dramatically.
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