Add an auto-extracted attribute
You can add an auto-extracted attribute to any root object in your data model.
1. In the Data Model Editor, open the root object you'd like to add an auto-extracted attribute to.
2. Click Add Attribute and select Auto-extracted to define an auto-extracted attribute.
- The Add Auto-Extracted Field dialog appears. It includes a list of fields that can be added to your data model object as auto-extracted attributes.
3. Select the attributes you would like to add to your data model by marking their checkboxes.
- You can select the checkbox in the header to select all fields in the list.
- If you look at the list and don't find the fields you are expecting, try changing the event sample size, which is set to the First 1000 events by default. A larger event sample may contain rare fields that didn't turn up in the first thousand events. For example, you could choose a sample size like the First 10,000 events or the Last 7 days.
4. (Optional) Rename the auto-extracted field.
- If you use Rename, do not include asterisk characters in the new field name.
5. (Optional) Correct the auto-extracted field Type.
6. (Optional) Update the auto-extracted field's status (Optional, Required, Hidden, or Hidden and Required) as necessary.
7. Click Save to add the selected attributes to your root object.
Note: You cannot add auto-extracted attributes to child objects. Child objects inherit auto-extracted attributes from the root object at the top of their object hierarchy.
The list of fields displayed by the Add Auto-Extracted Field dialog includes:
- Fields that are extracted automatically, like
version. This includes fields indexed through structured data inputs, such as fields extracted from the headers of indexed CSV files.
- Field extractions, lookups, or calculated fields that you have defined in Settings or configured in
Expand a field row for a field to see its top ten sample values.
Manually add a field to the set of auto-extracted fields
While building a data model you may find that you are missing certain auto-extracted fields. They could be missing for a variety of reasons. For example:
- You may be building your data model prior to indexing the data that will make up its dataset.
- You are indexing data, but certain rare fields that you expect to see eventually haven't been indexed yet.
- You are utilizing a generating search command like
inputcsvthat adds fields that don't display in this list.
You can manually add auto-extracted attributes to a root object.
Note: Before adding fields manually, try increasing the event sample size as described in the procedure above to pull in rare fields that aren't found in the first thousand events.
1. Click Add by name in the top right-hand corner of the Add Auto-Extracted Field dialog.
- This adds a row to the field table. Note that in the example at the top of this topic a row has been added for a manually added ISBN field.
2. In that row, manually identify the Field name, Type, and status for an auto-extracted attribute.
3. Click Add by name again to add additional attribute rows.
4. Click the X in the top right-hand corner of an added row to remove it.
5. Click Save to save your changes.
- Fields that you've added to the table are added to your root object as Extracted in the Extracted category, along with any selected auto-extracted fields.
Define object attributes
Add an eval expression attribute
This documentation applies to the following versions of Splunk® Enterprise: 6.1, 6.1.1, 6.1.2, 6.1.3, 6.1.4, 6.1.5, 6.1.6, 6.1.7, 6.1.8, 6.1.9, 6.1.10, 6.1.11, 6.1.12, 6.1.13, 6.1.14, 6.2.0, 6.2.1, 6.2.2, 6.2.3, 6.2.4, 6.2.5, 6.2.6, 6.2.7, 6.2.8, 6.2.9, 6.2.10, 6.2.11, 6.2.12, 6.2.13, 6.2.14, 6.2.15, 6.3.0, 6.3.1, 6.3.2, 6.3.3, 6.3.4, 6.3.5, 6.3.6, 6.3.7, 6.3.8, 6.3.9, 6.3.10, 6.3.11, 6.3.12, 6.3.13, 6.3.14, 6.4.0, 6.4.1, 6.4.2, 6.4.3, 6.4.4, 6.4.5, 6.4.6, 6.4.7, 6.4.8, 6.4.9, 6.4.10, 6.4.11