Aggregator transformation
is used to perform aggregate calculations, such as averages and sums. The Data
Integration Service performs aggregate calculations as it reads and stores data
group and row data in an aggregate cache.
The transformation
language has the following aggregate functions
AVG
COUNT
FIRST
LAST
MAX
MEDIAN
MIN
PERCENTILE
STDDEV
SUM
VARIANCE
An Aggregator
transformation has the following port types
Input Receives
data from upstream transformations.
Output Provides
the return value of an expression.
Pass-Through Passes data unchanged.
Variable Used for local variables.
Group by Indicates how to create groups. When
grouping data, the Aggregator transformation outputs the last row of each group
unless otherwise specified.
Advanced
properties for an Aggregator transformations
Cache Directory
Local directory
where the Data Integration Service creates the index cache files and data cache
files. If you have enabled incremental aggregation, the Data Integration
Service creates a backup of the files each time you run the mapping. The cache
directory must contain enough disk space for two sets of the files.
Data Cache Size
Data cache size for
the transformation.
Index Cache Size
Index cache size for
the transformation.
Sorted Input
Select this option
only if the mapping passes sorted data to the Aggregator transformation.
Tracing Level
Amount of detail that appears in the log for this transformation. You can choose terse, normal, verbose initialization, or verbose data. Default is normal.
Amount of detail that appears in the log for this transformation. You can choose terse, normal, verbose initialization, or verbose data. Default is normal.
Tips to Improve performance while using Aggregator
Transformation
- Use sorted input to decrease the use of aggregate caches. Sorted input reduces the amount of data cached during mapping run and improves performance. Use this option with the Sorter transformation to pass sorted data to the Aggregator transformation.
- Limit the number of connected input/output or output ports to reduce the amount of data the Aggregator transformation stores in the data cache.
- If you use a Filter transformation in the mapping, place the transformation before the Aggregator transformation to reduce unnecessary aggregation.
Scenario For Aggregator Transformation
Calculate total
salaries paid to employees in each department
*In case of any questions, feel free to leave comments on this page and I would get back as soon as I can.