RegexClean Transformation Two regular expressions are used, a match expression and a replace expression
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RegexClean Transformation Tags

clean regex regular expression Transformation Regex Clean Regex Transformation

RegexClean Transformation Description

Use the power of regular expressions to cleanse your data right there inside the Data Flow. The RegexClean Transformation package includes a full user interface for simple configuration, as well as advanced features such as error output configuration. Two regular expressions are used, a match expression and a replace expression. The transformation is designed around the named capture groups or match groups, and even supports multiple expressions. This allows for rich and complex expressions to be built, all through an easy to reuse transformation where a bespoke Script Component was previously the only alternative. Some simple properties are available for each column selected: Behaviour The two behaviour modes offer similar functionality but with a difference. Replace, replaces tokens with the input, and Emit overwrites the whole string. Cascade Cascade allows you to define multiple expressions, each on a new line. The match expression will be processed into one operation per line, which are then processed in order at run-time. Multiple replace expressions can also be specified, again each on a new line. If there is no corresponding replace expression for a match expression line, then the last replace expression will be used instead. It is common to have multiple match expressions, but only a single replace expression. Match Expression The expression used to define the named capture groups. This is where you can analyse the data, and tag or name elements within it as found by the match expression. Replace Expression The replace determines the final output. It will reference the named groups from the match expression and assembles them into the final output.

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