Using Amazon Elasticsearch with Amazon QuickSight - Amazon QuickSight

Using Amazon Elasticsearch with Amazon QuickSight

Following, you can find how to connect to your Amazon Elasticsearch Service data using Amazon QuickSight.

Creating a New QuickSight Data Source Connection for Elasticsearch

Following, you can find how to connect to Amazon Elasticsearch Service from Amazon QuickSight.

Before you can proceed, Amazon QuickSight needs to be authorized to connect to Amazon Elasticsearch Service. If connections aren't enabled, you get an error when you try to connect. A QuickSight administrator can authorize connections to AWS resources.

To authorize QuickSight to initiate a connection to Amazon Elasticsearch Service

  1. Open the menu by clicking on your profile icon at top right, then choose Manage QuickSight. If you don't see the Manage QuickSight option on your profile menu, ask your QuickSight administrator for assistance.

  2. Choose Security & permissions, Add or remove.

  3. Enable the option for Amazon Elasticsearch.

  4. Choose Update.

After Elasticsearch is accessible, you create a data source so people can use the specified domains.

To connect to Amazon Elasticsearch

  1. Begin by creating a new dataset. Choose Datasets from the navigation pane at left, then choose New Dataset.

  2. Choose the Amazon Elasticsearch data source card.

  3. For Data source name, enter a descriptive name for your Elasticsearch data source connection, for example Elasticsearch ML Data. Because you can create many datasets from a connection to Elasticsearch, it's best to keep the name simple.

  4. For Connection type, choose the network you want to use. This can be a virtual private cloud (VPC) based on Amazon VPC or a public network. The list of VPCs contains the names of VPC connections, rather than VPC IDs. These names are defined by the QuickSight administrator.

  5. For Domain, choose the Elasticsearch domain that you want to connect to.

  6. Choose Validate connection to check that you can successfully connect to Elasticsearch.

  7. Choose Create data source to proceed.

  8. For Tables, choose the one you want to use, then choose Select to continue.

  9. Do one of the following:

    • To import your data into the QuickSight in-memory engine (called SPICE), choose Import to SPICE for quicker analytics. For information about how to enable importing Elasticsearch data, see Authorizing Connections to Amazon Elasticsearch.

    • To allow QuickSight to run a query against your data each time you refresh the dataset or use the analysis or dashboard, choose Directly query your data.

      To enable autorefresh on a published dashboard that uses Elasticsearch data, the Elasticsearch dataset needs to use a direct query.

  10. Choose Edit/Preview and then Save to save your dataset and close it.

Managing Permissions for Elasticsearch Data

The following procedure describes how to view, add, and revoke permissions to allow access to the same Amazon Elasticsearch data source. The people that you add need to be active users in QuickSight before you can add them.

To edit permissions on a data source

  1. Choose Datasets at left, then scroll down to find the data source card for your Amazon Elasticsearch Service connection. An example might be US Amazon Elasticsearch Service Data.

  2. Choose the Amazon Elasticsearch data source card.

  3. Choose Share data source. A list of current permissions appears.

  4. To add permissions, choose Invite users, then follow these steps:

    1. Add people to allow them to use the same data source.

    2. When you're finished adding everyone that you want to add, choose the Permission that you want to apply.

  5. (Optional) To edit permissions, you can choose user or owner.

    • Choose user to allow read access.

    • Choose owner to allow that user to edit, share, or delete this QuickSight data source.

  6. (Optional) To revoke permissions, choose Revoke access. After you revoke someone's access, they can't create new datasets from this data source. However, their existing datasets still have access to this data source.

  7. When you are finished, choose Close.

Adding a New QuickSight Dataset for Amazon Elasticsearch Service

After you have an existing data source connection for Amazon Elasticsearch, you can create Elasticsearch datasets to use for analysis.

To create a dataset using Amazon Elasticsearch

  1. From the start page, choose Datasets, New dataset.

  2. Scroll down to the data source card for your Elasticsearch connection. If you have many data sources, you can use the search bar at the top of the page to find your data source with a partial match on the name.

  3. Choose the Amazon Elasticsearch data source card, and then choose Create data set.

  4. For Tables, choose the Elasticsearch index that you want to use.

  5. Choose Edit/Preview.

  6. Choose Save to save and close the dataset.

Adding Amazon Elasticsearch Service Data to an Analysis

After you have an Elasticsearch dataset available, you can add it to a QuickSight analysis. Before you begin, make sure that you have an existing dataset that contains the Elasticsearch data that you want to use.

To add Amazon Elasticsearch data to an analysis

  1. Choose Analyses at left.

  2. Do one of the following:

    • To create a new analysis, choose New analysis at right.

    • To add to an existing analysis, open the analysis that you want to edit.

      • Choose the pencil icon near at top left.

      • Choose Add data set.

  3. Choose the Amazon Elasticsearch dataset that you want to add.

    For information on using Elasticsearch in visualizations, see Limitations for Using Elasticsearch.

  4. For more information, see Working with Analyses.

Limitations for Using Elasticsearch

The following limitations apply to using Elasticsearch datasets:

  • Elasticsearch datasets support a subset of the visual types, sort options, and filter options.

  • To enable autorefresh on a published dashboard that uses Elasticsearch data, the Elasticsearch dataset needs to use a direct query.

  • Multiple subquery operations aren't supported. To avoid errors during visualization, don't add multiple fields to a field well, use one or two fields per visualization, and avoid using the Color field well.

  • Custom SQL isn't supported.

  • Crossdataset joins and self joins aren't supported.

  • Calculated fields aren't supported.

  • The "other" category isn't supported. If you use an Elasticsearch dataset with a visualization that supports the "other" category, disable the "other" category by using the menu on the visual.