Contents
- 1 How can lookup transformation improve performance?
- 2 What are lookup tables and why use them?
- 3 How do you perform a performance tuning in Informatica?
- 4 When to use a lookup table in a control system?
- 5 How to improve the performance of Informatica lookups?
- 6 Can a lookup table be larger than the memory available?
How can lookup transformation improve performance?
To improve lookup performance for relational or flat file sources, enable lookup caching in the transformation. When you enable caching, the Data Integration Service caches the lookup table. When you run the mapping, the Data Integration Service queries the lookup cache instead of the lookup table.
What are lookup tables and why use them?
A lookup table is normally a table that acts as a “master list” for something and you use it to look up a business key value (like “Make”) in exachange for it’s identifier (like the id column) for use in some other table’s foreign key column.
Why lookup is an active transformation?
Use a Lookup transformation to retrieve data based on a specified lookup condition. When you configure the Lookup transformation to return multiple rows, the Lookup transformation is an active transformation. You can use multiple Lookup transformations in a mapping.
How do you perform a performance tuning in Informatica?
Performance Tuning in Informatica: Complete Tutorial
- Always prefer to perform joins in the database if possible, as database joins are faster than joins created in Informatica joiner transformation.
- Sort the data before joining if possible, as it decreases the disk I/O performed during joining.
When to use a lookup table in a control system?
In data acquisition and control systems, lookup tables are commonly used to undertake the following operations in: 1 The application of calibration data, so as to apply corrections to uncalibrated measurement or setpoint values; and 2 Undertaking measurement unit conversion; and 3 Performing generic user-defined computations.
How are lookup tables used in data analysis?
In data analysis applications, such as image processing, a lookup table (LUT) is used to transform the input data into a more desirable output format. For example, a grayscale picture of the planet Saturn will be transformed into a color image to emphasize the differences in its rings.
How to improve the performance of Informatica lookups?
To sum up, it is possible to enhance Informatica lookups by using different set of configurations in order to increase performance as well as save resources and time. However, before applying any of the mentioned features, an analysis of the tables and the SQL queries involved needs to be done.
Can a lookup table be larger than the memory available?
One is the amount of memory that is available: one cannot construct a lookup table larger than the space available for the table, although it is possible to construct disk-based lookup tables at the expense of lookup time.