Table of Contents


  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Connections
  4. Mappings in the Hadoop Environment
  5. Mapping Objects in the Hadoop Environment
  6. Processing Hierarchical Data on the Spark Engine
  7. Stateful Computing on the Spark Engine
  8. Monitoring Mappings in the Hadoop Environment
  9. Mappings in the Native Environment
  10. Profiles
  11. Native Environment Optimization
  12. Data Type Reference
  13. Complex File Data Object Properties
  14. Function Reference
  15. Parameter Reference

Aggregate Offsets

Aggregate Offsets

An aggregate function performs a calculation on a set of values inside a partition. If the frame offsets are outside the partition, the aggregate function ignores the frame.
If the offsets of a frame are not within the partition or table, the aggregate function calculates within the partition. The function does not return NULL or a default value.
For example, you partition a table by seller ID and you order by quantity. You set the start offset to -3 and the end offset to 4.
The following image shows the partition and frame for the current input row:
The partition includes the current input row plus one row before the current row and two rows after the current row. The frame extends to three rows before the current row and four rows after the current row.
The frame includes eight total rows, but the calculation remains within the partition. If you define an AVG function with this frame, the function calculates the average of the quantities inside the partition and returns 18.75.

Updated December 13, 2018