Each set of data loaded to Elasticsearch has an index pattern. In the previous section, the Shakespeare data set has an index named shakespeare, and the accounts data set has an index named bank. An index pattern is a string with optional wildcards that can match multiple indices. For example, in the common logging use case, a typical index name contains the date in YYYY.MM.DD format, and an index pattern for May would look something like logstash-2015.05*.

For this tutorial, any pattern that matches the name of an index we’ve loaded will work. Open a browser and navigate to localhost:5601. Click the Management tab, then the Index Patterns tab. Click Add New to define a new index pattern. Two of the sample data sets, the Shakespeare plays and the financial accounts, don’t contain time-series data. Make sure the Index contains time-based events box is unchecked when you create index patterns for these data sets. Specify shakes* as the index pattern for the Shakespeare data set and click Create to define the index pattern, then define a second index pattern named ba*.

The Logstash data set does contain time-series data, so after clicking Add New to define the index for this data set, make sure the Index contains time-based events box is checked and select the @timestamp field from the Time-field name drop-down.

When you define an index pattern, indices that match that pattern must exist in Elasticsearch. Those indices must contain data.