![]() ![]() When mapping columns in source and select transformations, you can add either fixed mapping or rule-based mappings. :::image type="content" source="media/data-flow/column-pattern-004.png" alt-text="Screenshot shows the Derived column's flatten structure."::: Rule-based mapping in select and sink You can use the column patterns that would look like this sample, which flattens the geography hierarchy into a relational table form: For structures and maps, use the derived column transformation with column patterns to form your flattened relational table from the hierarchies. When your data has complex structures like arrays, hierarchical structures, and maps, you can use the Flatten transformation to unroll arrays and denormalize your data. :::image type="content" source="media/data-flow/patterns-hierarchy.png" alt-text="Screenshot shows hierarchical column pattern."::: Flattening structures You can then build matching patterns for properties within that chosen hierarchy. Expand the section Each MoviesStruct that matches where you will be prompted for each hierarchy in your data stream. You can build pattern matching inside of complex hierarchical structures as well. :::image type="content" source="media/data-flow/columnpattern3.png" alt-text="Screenshot shows the Output schema tab."::: Hierarchical pattern matching To verify your matching condition is correct, you can validate the output schema of defined columns in the Inspect tab or get a snapshot of the data in the Data preview tab. The value of each column is the existing value rounded to two decimal points. By stating $$ as the column name field, each matched column is updated with the same name. The above column pattern matches every column of type double and creates one derived column per match. :::image type="content" source="media/data-flow/edit-column-pattern.png" alt-text="Screenshot shows the Derived column's settings tab."::: The pattern will affect any column, drifted or defined, where the condition returns true. Create a boolean expression that matches columns based on the name, type, stream, origin, and position of the column. Use the expression builder to enter the match condition. :::image type="content" source="media/data-flow/add-column-pattern.png" alt-text="Screenshot shows the plus icon to Add column pattern."::: To add a column pattern in a derived column, aggregate, or window transformation, click on Add above the column list or the plus icon next to an existing derived column. Column patterns in derived column and aggregate For example, wanting to cast every column that has 'total' in its column name into a double. If you wish to do a common operation on a large group of columns. ![]() If incoming source fields change often such as the case of changing columns in text files or NoSQL databases.There are two scenarios where column patterns are useful: You can define patterns to match columns based on name, data type, stream, origin, or position instead of requiring exact field names. This matching is known as column patterns. Several mapping data flow transformations allow you to reference template columns based on patterns instead of hard-coded column names. Select a rule you want to move up or down and use the corresponding arrow to move it.Using column patterns in mapping data flow You can rearrange this order using the arrow buttons on the right side. This means if you have more than one rule for the same set of cells, each rule applies in the order it’s shown. The rules listed in the tool are in the order that they apply. RELATED: How to Sort by Date in Microsoft Excel Rearrange Your Rules ![]() This is also handy if you want to apply the same rule to another cell range. You can click “Duplicate Rule” for the first one, then click “Edit Rule” for the copied one and make your adjustments. ![]() But you also want a rule so that dates this week are highlighted in yellow. Maybe you created a rule based on date so that all dates last week are highlighted in green. So, once you delete a conditional formatting rule here, it’s removed for good.Īn easy way to set up a similar conditional formatting rule is by duplicating a current one. If you want to remove a rule completely, click “Delete Rule.” Just be aware that you will not be asked to confirm this action. ![]()
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