Elasticsearch:Use the Kibana plugin to query or tag data

Usage notes

• Kibana plugins are supported only on Alibaba Cloud Elasticsearch versions 6.3 and 6.7.

• Before you install a plugin, ensure that your Kibana node has at least 2 vCPUs and 4 GB of memory. If your Kibana node does not meet this requirement, upgrade it. For more information, see upgrade cluster configuration.

• You cannot install custom Kibana plugins.

Procedure

1. Log on to the Alibaba Cloud Elasticsearch console.

2. In the navigation pane on the left, click Elasticsearch Clusters.

3. In the top navigation bar, select a resource group and region.

4. On the Elasticsearch Clusters page, click the ID of the target cluster.

5. In the navigation pane on the left, click Data Visualization.

6. In the Kibana section, click Modify Configuration.

7. In the Plug-in Configuration section, find the plugin that you want to install and click Install in the Actions column.

   Important

   Installing a plugin triggers a restart of the Kibana node. During the restart, Kibana services are unavailable. We recommend performing this operation during off-peak hours.

8. In the Installation Prompt dialog box, click OK.

   After the node restarts, the plugin is installed. The plugin status changes to Installed.

Procedure

1. Log on to the Kibana console of your Alibaba Cloud Elasticsearch cluster.

   For more information, see Log on to the Kibana console.

2. Optional: In the navigation pane on the left, click Management and create an index pattern.

   Important

   If you have already created an index pattern, skip this step.

   1. On the Management page, click Index Patterns in the Kibana section.

   2. On the Create index pattern page, enter an index pattern name. The name must match the index that you want to query.

   3. Click Next step.

      On the Create index pattern page, enter product_info in the Index pattern field. A message indicates that one index matches.

   4. Click Create index pattern.

3. In the navigation pane on the left, click Discover.

4. On the Discover page, in the upper-right corner, click Query.

5. Add query and filter conditions, then click Submit.

   • Click the icon to add a query condition.

   • Click the icon to add a sub-filter condition to the query.

   • Click the icon to delete a query or filter condition.

   BSearch-QueryBuilder supports various query types, such as wildcard queries, multi-condition queries, and queries with custom time ranges. The following examples show how to perform these queries:

   • Wildcard query

     The following example shows a fuzzy search on the Email field. The Email field is required to fuzzy match iga. In the filter conditions, set the field to email, select Wildcard for the match type, enter *iga* as the match value, and then click Submit to run the query.

     The query returns all records where the email contains iga, such as abigail@salazar-family.zzz and abigail@banks-family.zzz. The results also display fields such as customer_first_name, customer_gender, and taxful_total_price.

   • Multi-condition query

     The query conditions in the following example specify that the index must be tryme_book, and a filter must be applied to the Type field. The Type must be University Teaching Aids, Math , Teaching Chinese to Speakers of Other Languages, or University Textbooks. In Query Builder, select the tryme_book index, and select Match as the match type. Add an OR logic group that contains four match conditions for the type field with the values University Teaching Aids, Mathematics, Teaching Chinese to Speakers of Other Languages, and University Textbooks. Click submit to submit the query.

     The query returns multiple matching book documents. Each record displays fields such as author, price, publish, name, and info in JSON format.

   • Query with a custom time range

     You can filter by time fields. This example shows how to filter the utc_time field to query data within the range of [now-240d, now]. Set the filter field to utc_time, select In the last as the condition type, enter 240 days as the value, then click Submit.

     The query returns all data records that match the specified time range (the last 240 days).

Label data using bsearch_label

bsearch_label is a front-end-only data labeling plugin that allows you to label data visually without writing DSL statements. By labeling data, you can assign a special value to a field or add a new field with a specific value. You can then use the labels for aggregation, classification, statistical analysis, or quick filtering.

Procedure

1. Log on to the Kibana console of your target Alibaba Cloud Elasticsearch cluster. For more information, see Connect to a cluster by using Kibana.

2. Optional: In the navigation pane on the left, click Management and create an index pattern. If you have already created an index pattern, skip this step.

   1. On the Management page, click Index Patterns in the Kibana section.

   2. On the Create index pattern page, enter an index pattern name. The name must match the index that you want to query.

   3. Click Next step.

   4. Click Create index pattern.

3. In the navigation pane on the left, click Discover.

4. On the Discover page, in the upper-right corner, click Label.

   The Label button appears only after you install the bsearch_label plugin.

5. Label your data using one of the following methods.