Aurora (PostgreSQL) - Amazon Kendra

Aurora (PostgreSQL)

Aurora is a relational database management system (RDBMS) built for the cloud. If you are a Aurora user, you can use Amazon Kendra to index your Aurora (PostgreSQL) data source. The Amazon Kendra Aurora (PostgreSQL) data source connector supports Aurora PostgreSQL 1.

You can connect Amazon Kendra to your Aurora (PostgreSQL) data source using the Amazon Kendra console and the TemplateConfiguration API.

For troubleshooting your Amazon Kendra Aurora (PostgreSQL) data source connector, see Troubleshooting data sources.

Supported features

  • Field mappings

  • User context filtering

  • Inclusion/exclusion filters

  • Full and incremental content syncs

  • Virtual private cloud (VPC)

Prerequisites

Before you can use Amazon Kendra to index your Aurora (PostgreSQL) data source, make these changes in your Aurora (PostgreSQL) and AWS accounts.

In Aurora (PostgreSQL), make sure you have:

  • Noted your database user name and password.

    Important

    As a best practice, provide Amazon Kendra with read-only database credentials.

  • Copied your database host url, port, and instance.

  • Checked each document is unique in Aurora (PostgreSQL) and across other data sources you plan to use for the same index. Each data source that you want to use for an index must not contain the same document across the data sources. Document IDs are global to an index and must be unique per index.

In your AWS account, make sure you have:

  • Created an Amazon Kendra index and, if using the API, noted the index ID.

  • Created an IAM role for your data source and, if using the API, noted the ARN of the IAM role.

    Note

    If you change your authentication type and credentials, you must update your IAM role to access the correct AWS Secrets Manager secret ID.

  • Stored your Aurora (PostgreSQL) authentication credentials in an AWS Secrets Manager secret and, if using the API, noted the ARN of the secret.

    Note

    We recommend that you regularly refresh or rotate your credentials and secret. Provide only the necessary access level for your own security. We do not recommend that you re-use credentials and secrets across data sources, and connector versions 1.0 and 2.0 (where applicable).

If you don’t have an existing IAM role or secret, you can use the console to create a new IAM role and Secrets Manager secret when you connect your Aurora (PostgreSQL) data source to Amazon Kendra. If you are using the API, you must provide the ARN of an existing IAM role and Secrets Manager secret, and an index ID.

Connection instructions

To connect Amazon Kendra to your Aurora (PostgreSQL) data source you must provide details of your Aurora (PostgreSQL) credentials so that Amazon Kendra can access your data. If you have not yet configured Aurora (PostgreSQL) for Amazon Kendra see Prerequisites.

Console

To connect Amazon Kendra to Aurora (PostgreSQL)

  1. Sign in to the AWS Management Console and open the Amazon Kendra console.

  2. From the left navigation pane, choose Indexes and then choose the index you want to use from the list of indexes.

    Note

    You can choose to configure or edit your User access control settings under Index settings.

  3. On the Getting started page, choose Add data source.

  4. On the Add data source page, choose Aurora (PostgreSQL) connector, and then choose Add connector. If using version 2 (if applicable), choose Aurora (PostgreSQL) connector with the "V2.0" tag.

  5. On the Specify data source details page, enter the following information:

    1. In Name and description, for Data source name—Enter a name for your data source. You can include hyphens but not spaces.

    2. (Optional) Description—Enter an optional description for your data source.

    3. In Default language—Choose a language to filter your documents for the index. Unless you specify otherwise, the language defaults to English. Language specified in the document metadata overrides the selected language.

    4. In Tags, for Add new tag—Include optional tags to search and filter your resources or track your AWS costs.

    5. Choose Next.

  6. On the Define access and security page, enter the following information:

    1. In Source, enter the following information:

    2. Host – Enter the database host URL, for example: http://instance URL.region.rds.amazonaws.com.

    3. Port – Enter the database port, for example, 5432.

    4. Instance – Enter the database instance, for example postgres.

    5. Enable SSL certificate location—Choose to enter the Amazon S3 path to your SSL certificate file.

    6. In Authentication—enter the following information:

      1. AWS Secrets Manager secret—Choose an existing secret or create a new Secrets Manager secret to store your Aurora (PostgreSQL) authentication credentials. If you choose to create a new secret an AWS Secrets Manager secret window opens.

        1. Enter following information in the Create an AWS Secrets Manager secret window:

          1. Secret name—A name for your secret. The prefix ‘AmazonKendra-Aurora (PostgreSQL)-’ is automatically added to your secret name.

          2. For Database user name, and Password—Enter the authentication credential values you copied from your database.

        2. Choose Save.

    7. Virtual Private Cloud (VPC)—You can choose to use a VPC. If so, you must add Subnets and VPC security groups.

    8. IAM role—Choose an existing IAM role or create a new IAM role to access your repository credentials and index content.

      Note

      IAM roles used for indexes cannot be used for data sources. If you are unsure if an existing role is used for an index or FAQ, choose Create a new role to avoid errors.

    9. Choose Next.

  7. On the Configure sync settings page, enter the following information:

    1. In Sync scope, choose from the following options :

      • SQL query—Enter SQL query statements like SELECT and JOIN operations. SQL queries must be less than 32KB SQL queries must be less than 32KB and not contain any semi-colons (;). Amazon Kendra will crawl all database content that matches your query.

      • Primary key column—Provide the primary key for the database table. This identifies a table within your database.

      • Title column—Provide the name of the document title column within your database table.

      • Body column—Provide the name of the document body column within your database table.

    2. In Additional configuration – optional, choose from the following options to sync specific content instead of syncing all files:

      • Change-detecting columns—Enter the names of the columns that Amazon Kendra will use to detect content changes. Amazon Kendra will re-index content when there is a change in any of these columns.

      • Users' IDs column—Enter the name of the column which contains User IDs to be allowed access to content.

      • Groups column—Enter the name of the column that contains groups to be allowed access to content.

      • Source URLs column—Enter the name of the column which contains Source URLs to be indexed.

      • Time stamps column—Enter the name of the column which contains time stamps. Amazon Kendra uses time stamp information to detect changes in your content and sync only changed content.

      • Time zones column—Enter the name of the column which contains time zones for the content to be crawled.

      • Time stamps format—Enter the name of the column which contains time stamp formats to use to detect content changes and re-sync your content.

    3. Sync mode—Choose how you want to update your index when your data source content changes. When you sync your data source with Amazon Kendra for the first time, all content is crawled and indexed by default. You must run a full sync of your data if your initial sync failed, even if you don't choose full sync as your sync mode option.

      • Full sync: Freshly index all content, replacing existing content each time your data source syncs with your index.

      • New, modified sync: Index only new and modified content each time your data source syncs with your index. Amazon Kendra can use your data source's mechanism for tracking content changes and index content that changed since the last sync.

      • New, modified, deleted sync: Index only new, modified, and deleted content each time your data source syncs with your index. Amazon Kendra can use your data source's mechanism for tracking content changes and index content that changed since the last sync.

    4. In Sync run schedule, for Frequency—How often Amazon Kendra will sync with your data source.

    5. Choose Next.

  8. On the Set field mappings page, enter the following information:

    1. Select from the generated default data source fields—Document IDs, Document titles, and Source URLs—you want to map to Amazon Kendra index.

    2. Add field—To add custom data source fields to create an index field name to map to and the field data type.

    3. Choose Next.

  9. On the Review and create page, check that the information you have entered is correct and then select Add data source. You can also choose to edit your information from this page. Your data source will appear on the Data sources page after the data source has been added successfully.

API

To connect Amazon Kendra to Aurora (PostgreSQL)

You must specify the following using the TemplateConfiguration API:

  • Data source—Specify the data source type as JDBC when you use the TemplateConfiguration JSON schema. Also specify the data source as TEMPLATE when you call the CreateDataSource API.

  • Database type—You must specify the database type as postgresql.

  • SQL query—Specify SQL query statements like SELECT and JOIN operations. SQL queries must be less than 32KB. Amazon Kendra will crawl all database content that matches your query.

  • Sync mode—Specify how Amazon Kendra should update your index when your data source content changes. When you sync your data source with Amazon Kendra for the first time, all content is crawled and indexed by default. You must run a full sync of your data if your initial sync failed, even if you don't choose full sync as your sync mode option. You can choose between:

    • FORCED_FULL_CRAWL to freshly index all content, replacing existing content each time your data source syncs with your index.

    • FULL_CRAWL to index only new, modified, and deleted content each time your data source syncs with your index. Amazon Kendra can use your data source’s mechanism for tracking content changes and index content that changed since the last sync.

    • CHANGE_LOG to index only new and modified content each time your data source syncs with your index. Amazon Kendra can use your data source’s mechanism for tracking content changes and index content that changed since the last sync.

  • Secret Amazon Resource Name (ARN)—Provide the Amazon Resource Name (ARN) of an Secrets Manager secret that contains the authentication credentials you created in your Aurora (PostgreSQL) account. The secret is stored in a JSON structure with the following keys:

    { "user name": "database user name", "password": "password" }
    Note

    We recommend that you regularly refresh or rotate your credentials and secret. Provide only the necessary access level for your own security. We do not recommend that you re-use credentials and secrets across data sources, and connector versions 1.0 and 2.0 (where applicable).

  • IAM role—Specify RoleArn when you call CreateDataSource to provide an IAM role with permissions to access your Secrets Manager secret and to call the required public APIs for the Aurora (PostgreSQL) connector and Amazon Kendra. For more information, see IAM roles for Aurora (PostgreSQL) data sources.

You can also add the following optional features:

  • Virtual Private Cloud (VPC)—Specify VpcConfiguration when you call CreateDataSource. For more information, see Configuring Amazon Kendra to use an Amazon VPC.

  • Inclusion and exclusion filters—You can specify whether to include specific content using user IDs, groups, source URLs, time stamps, and time zones.

  • User context filtering and access control—Amazon Kendra crawls the access control list (ACL) for your documents, if you have an ACL for your documents. The ACL information is used to filter search results based on the user or their group access to documents. For more information, see User context filtering.

  • Field mappings—Choose to map your Aurora (PostgreSQL) data source fields to your Amazon Kendra index fields. For more information, see Mapping data source fields.

    Note

    The document body field or the document body equivalent for your documents is required in order for Amazon Kendra to search your documents. You must map your document body field name in your data source to the index field name _document_body. All other fields are optional.

For a list of other important JSON keys to configure, see Aurora (PostgreSQL) template schema.

Notes

  • Deleted database rows will not be tracked in when Amazon Kendra checks for updated content.

  • The size of field names and values in a row of your database can't exceed 400KB.

  • If you have a large amount of data in your database data source, and do not want Amazon Kendra to index all your database content after the first sync, you can choose to sync only new, modified, or deleted documents.

  • As a best practice, provide Amazon Kendra with read-only database credentials.

  • As a best practice, avoid adding tables with sensitive data or personal identifiable information (PII).