Developer Transformation Guide

10.5.3
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Groups in Match Analysis

A match analysis mapping can take a long time to run because of the number of data comparisons that the transformation must perform. The number of comparisons relates to the number of data values on the ports that you select.

The following table shows the number of calculations that a mapping performs for different numbers of data values on a single port:

Number of data values	Number of comparisons
10,000	50 million
100,000	5,000 million
1 million	500,000 million

To reduce the time that the mapping takes to run, assign the input data records to groups. A group is a set of records that contain identical values on a port that you specify. When you perform match analysis on grouped data, the Match transformation analyzes the records within each group. The transformation does not compare the records in one group with the records in another group. The groups reduce the overall number of comparisons that the transformation must perform without any loss of accuracy in the mapping analysis.

Consider the following rules and guidelines when you organize data into groups:

The port on which you group the data is the group key port. A group key port must contain a range of duplicate values, such as a city name or a state name in an address data set. If the mapping data does not contain a usable group key port, use the Key Generator to create the port from the current mapping data. Connect the group key output port from the Key Generator transformation to the Match transformation.

You can also use the Key Generator transformation to add sequence identifiers to the mapping data.

Field match operations must specify a group key port. If you configure the Match transformation for identity analysis, do not select a group key port. The identity analysis generates group keys for the identity index data.

Do not specify a group key port that you plan to use in the match analysis.

When you create groups, you must verify that the groups are a valid size. If the groups are too small, the match analysis might not find all the duplicate data in the data set. If the groups are too large, the match analysis might return false duplicates. Select group keys that create an average group size of 10,000 records.

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Developer Transformation Guide

Developer Transformation Guide

Groups in Match Analysis

Groups in Match Analysis