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Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Aggregator transformation
  6. Expression transformation
  7. Filter transformation
  8. Input transformation
  9. Joiner transformation
  10. Lookup transformation
  11. Mapplet transformation
  12. Normalizer transformation
  13. Output transformation
  14. Rank transformation
  15. Router transformation
  16. Sequence transformation
  17. Sorter transformation
  18. SQL transformation
  19. Union transformation

Transformations

Transformations

Field rule configuration examples

Field rule configuration examples

The following examples show how you can configure field rules in a transformation.

Changing incoming field names

You need to create a mapping to gather revenue data from multiple sales locations. You learn that multiple fields from the upstream transformation have the same names as fields in a source transformation. To avoid field name conflicts, you change the field names for all incoming fields so that the source is distinguishable throughout the mapping. To change the names of incoming fields, you create a field rule to rename all fields with the SalesForce_ prefix.
To increase performance, you want to ensure that the data set only includes required data. You determine that information regarding transaction dates is not required, so you remove the data fields from the mapping. You create a rule to exclude fields that are not required. To exclude date fields, you create a rule to exclude fields with a date/time data type.
You review the order of the rules. You want the rule to rename the fields to run after the rule to exclude the date/time fields. You move the rule to remove date/time fields so that it appears before the renaming rule.

Removing patterns in field names

You can use parentheses to group different patterns and use a reference to replace the pattern. In a regular expression, parentheses group the patterns to be matched. You can use a
($)
reference to select a group matched in the input string.
You might need to change patterns in fields between transformations. If fields in an upstream transformation contain the suffix
_out
, you can remove the suffix from the field names in the current transformation. Use the following expression to remove the
_out
suffix:
(.*)_out/$1
. The
(.*)
part of the expression matches all the field name characters,
_out
matches the suffix, and
$1
references the input string specified by the matched
(.*)
field name characters.
The following expression shows another example:
(.*)(_)out/$1
In a matched string of
string_out
, for example, the matches are
$1
for
string
,
$2
for
_
, and
$3
for
out
. The
string
value is referenced by
$1
because
string
is the first group in the match.

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