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Elastic PostgreSQL connector reference

Elastic PostgreSQL connector reference

The Elastic PostgreSQL connector is a connector for PostgreSQL. This connector is written in Python using the Elastic connector framework.

This connector uses the generic database connector source code (branch main, compatible with Elastic 9.0). View the specific source code for this connector (branch main, compatible with Elastic 9.0).

Elastic managed connector (Elastic Cloud)

View Elastic managed connector reference

Availability and prerequisites

This connector is available as an Elastic managed connector in Elastic versions 8.8.0 and later. To use this connector natively in Elastic Cloud, satisfy all Elastic managed connector requirements.

Create a PostgreSQL connector

Use the UI

To create a new PostgreSQL connector:

In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
Follow the instructions to create a new native PostgreSQL connector.

For additional operations, see Connectors UI in Kibana.

Use the API

You can use the Elasticsearch Create connector API to create a new native PostgreSQL connector.

For example:

resp = client.connector.put(
    connector_id="my-{service-name-stub}-connector",
    index_name="my-elasticsearch-index",
    name="Content synced from {service-name}",
    service_type="{service-name-stub}",
    is_native=True,
)
print(resp)

PUT _connector/my-postgresql-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from PostgreSQL",
  "service_type": "postgresql",
  "is_native": true
}

You’ll also need to create an API key for the connector to use.

The user needs the cluster privileges manage_api_key, manage_connector and write_connector_secrets to generate API keys programmatically.

To create an API key for the connector:

Run the following command, replacing values where indicated. Note the id and encoded return values from the response:

resp = client.security.create_api_key(
    name="my-connector-api-key",
    role_descriptors={
        "my-connector-connector-role": {
            "cluster": [
                "monitor",
                "manage_connector"
            ],
            "indices": [
                {
                    "names": [
                        "my-index_name",
                        ".search-acl-filter-my-index_name",
                        ".elastic-connectors*"
                    ],
                    "privileges": [
                        "all"
                    ],
                    "allow_restricted_indices": False
                }
            ]
        }
    },
)
print(resp)

const response = await client.security.createApiKey({
  name: "my-connector-api-key",
  role_descriptors: {
    "my-connector-connector-role": {
      cluster: ["monitor", "manage_connector"],
      indices: [
        {
          names: [
            "my-index_name",
            ".search-acl-filter-my-index_name",
            ".elastic-connectors*",
          ],
          privileges: ["all"],
          allow_restricted_indices: false,
        },
      ],
    },
  },
});
console.log(response);

POST /_security/api_key
{
  "name": "my-connector-api-key",
  "role_descriptors": {
    "my-connector-connector-role": {
      "cluster": [
        "monitor",
        "manage_connector"
      ],
      "indices": [
        {
          "names": [
            "my-index_name",
            ".search-acl-filter-my-index_name",
            ".elastic-connectors*"
          ],
          "privileges": [
            "all"
          ],
          "allow_restricted_indices": false
        }
      ]
    }
  }
}

Use the encoded value to store a connector secret, and note the id return value from this response:

resp = client.connector.secret_post(
    body={
        "value": "encoded_api_key"
    },
)
print(resp)

const response = await client.connector.secretPost({
  body: {
    value: "encoded_api_key",
  },
});
console.log(response);

POST _connector/_secret
{
  "value": "encoded_api_key"
}

Use the API key id and the connector secret id to update the connector:

resp = client.connector.update_api_key_id(
    connector_id="my_connector_id>",
    api_key_id="API key_id",
    api_key_secret_id="secret_id",
)
print(resp)

const response = await client.connector.updateApiKeyId({
  connector_id: "my_connector_id>",
  api_key_id: "API key_id",
  api_key_secret_id: "secret_id",
});
console.log(response);

PUT /_connector/my_connector_id>/_api_key_id
{
  "api_key_id": "API key_id",
  "api_key_secret_id": "secret_id"
}

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

Usage

To use this connector as an Elastic managed connector, use the Connector workflow. See Elastic managed connectors.

Users must set track_commit_timestamp to on. To do this, run ALTER SYSTEM SET track_commit_timestamp = on; in PostgreSQL server.

For additional operations, see <←esconnectors-usage>>.

For an end-to-end example of the connector client workflow, see Tutorial.

Compatibility

PostgreSQL versions 11 to 15 are compatible with the Elastic connector.

Configuration

Set the following configuration fields:

Host

The server host address where the PostgreSQL instance is hosted. Examples:

192.158.1.38
demo.instance.demo-region.demo.service.com

Port

The port where the PostgreSQL instance is hosted. Examples:

5432 (default)

Username

The username of the PostgreSQL account.

Password

The password of the PostgreSQL account.

Database

Name of the PostgreSQL database. Examples:

employee_database
customer_database

Schema

The schema of the PostgreSQL database.

Comma-separated List of Tables

A list of tables separated by commas. The PostgreSQL connector will fetch data from all tables present in the configured database, if the value is * . Default value is *. Examples:

table_1, table_2
*

This field can be bypassed when using advanced sync rules.

Enable SSL

Toggle to enable SSL verification. Disabled by default.

SSL Certificate

Content of SSL certificate. If SSL is disabled, the ssl_ca value will be ignored.

Expand to see an example certificate

-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----

Documents and syncs

Tables must be owned by a PostgreSQL user.
Tables with no primary key defined are skipped.
To fetch the last updated time in PostgreSQL, track_commit_timestamp must be set to on. Otherwise, all data will be indexed in every sync.

Files bigger than 10 MB won’t be extracted.
Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync rules

Basic sync rules are identical for all connectors and are available by default.

Advanced sync rules

A full sync is required for advanced sync rules to take effect.

Advanced sync rules are defined through a source-specific DSL JSON snippet.

Example data

Here is some example data that will be used in the following examples.

======= employee table

emp_id	name	age
3	John	28
10	Jane	35
14	Alex	22

======= customer table

c_id	name	age
2	Elm	24
6	Pine	30
9	Oak	34

Advanced sync rules examples

======= Multiple table queries

[
  {
    "tables": [
      "employee"
    ],
    "query": "SELECT * FROM employee"
  },
  {
    "tables": [
      "customer"
    ],
    "query": "SELECT * FROM customer"
  }
]

======= Multiple table queries with id_columns

In 8.15.0, we added a new optional id_columns field in our advanced sync rules for the PostgreSQL connector. Use the id_columns field to ingest tables which do not have a primary key. Include the names of unique fields so that the connector can use them to generate unique IDs for documents.

[
  {
    "tables": [
      "employee"
    ],
    "query": "SELECT * FROM employee",
    "id_columns": ["emp_id"]
  },
  {
    "tables": [
      "customer"
    ],
    "query": "SELECT * FROM customer",
    "id_columns": ["c_id"]
  }
]

This example uses the id_columns field to specify the unique fields emp_id and c_id for the employee and customer tables, respectively.

======= Filtering data with WHERE clause

[
  {
    "tables": ["employee"],
    "query": "SELECT * FROM employee WHERE emp_id > 5"
  }
]

======= JOIN operations

[
  {
    "tables": ["employee", "customer"],
    "query": "SELECT * FROM employee INNER JOIN customer ON employee.emp_id = customer.c_id"
  }
]

When using advanced rules, a query can bypass the configuration field tables. This will happen if the query specifies a table that doesn’t appear in the configuration. This can also happen if the configuration specifies * to fetch all tables while the advanced sync rule requests for only a subset of tables.

Known issues

There are no known issues for this connector. Refer to Known issues for a list of known issues for all connectors.

Troubleshooting

See Troubleshooting.

Security

Self-managed connector

View self-managed connector reference

Availability and prerequisites

This connector is available as a self-managed self-managed connector. To use this connector, satisfy all self-managed connector requirements.

Create a PostgreSQL connector

Use the UI

To create a new PostgreSQL connector:

In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
Follow the instructions to create a new PostgreSQL self-managed connector.

Use the API

You can use the Elasticsearch Create connector API to create a new self-managed PostgreSQL self-managed connector.

For example:

resp = client.connector.put(
    connector_id="my-{service-name-stub}-connector",
    index_name="my-elasticsearch-index",
    name="Content synced from {service-name}",
    service_type="{service-name-stub}",
)
print(resp)

PUT _connector/my-postgresql-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from PostgreSQL",
  "service_type": "postgresql"
}

You’ll also need to create an API key for the connector to use.

The user needs the cluster privileges manage_api_key, manage_connector and write_connector_secrets to generate API keys programmatically.

To create an API key for the connector:

Run the following command, replacing values where indicated. Note the encoded return values from the response:

resp = client.security.create_api_key(
    name="connector_name-connector-api-key",
    role_descriptors={
        "connector_name-connector-role": {
            "cluster": [
                "monitor",
                "manage_connector"
            ],
            "indices": [
                {
                    "names": [
                        "index_name",
                        ".search-acl-filter-index_name",
                        ".elastic-connectors*"
                    ],
                    "privileges": [
                        "all"
                    ],
                    "allow_restricted_indices": False
                }
            ]
        }
    },
)
print(resp)

const response = await client.security.createApiKey({
  name: "connector_name-connector-api-key",
  role_descriptors: {
    "connector_name-connector-role": {
      cluster: ["monitor", "manage_connector"],
      indices: [
        {
          names: [
            "index_name",
            ".search-acl-filter-index_name",
            ".elastic-connectors*",
          ],
          privileges: ["all"],
          allow_restricted_indices: false,
        },
      ],
    },
  },
});
console.log(response);

POST /_security/api_key
{
  "name": "connector_name-connector-api-key",
  "role_descriptors": {
    "connector_name-connector-role": {
      "cluster": [
        "monitor",
        "manage_connector"
      ],
      "indices": [
        {
          "names": [
            "index_name",
            ".search-acl-filter-index_name",
            ".elastic-connectors*"
          ],
          "privileges": [
            "all"
          ],
          "allow_restricted_indices": false
        }
      ]
    }
  }
}

Update your config.yml file with the API key encoded value.

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

Usage

To use this connector as a self-managed connector, see Self-managed connectors.

Users must set track_commit_timestamp to on. To do this, run ALTER SYSTEM SET track_commit_timestamp = on; in PostgreSQL server.

For additional operations, see.

For an end-to-end example of the self-managed connector workflow, see Tutorial.

Compatibility

PostgreSQL versions 11 to 15 are compatible with Elastic connector frameworks.

Configuration

When using the self-managed connector workflow, initially these fields will use the default configuration set in the connector source code.

These configurable fields will be rendered with their respective labels in the Kibana UI. Once connected, users will be able to update these values in Kibana.

Set the following configuration fields:

host

The server host address where the PostgreSQL instance is hosted. Examples:

192.158.1.38
demo.instance.demo-region.demo.service.com

port

The port where the PostgreSQL instance is hosted. Examples:

5432
9090

username

The username of the PostgreSQL account.

password

The password of the PostgreSQL account.

database

Name of the PostgreSQL database. Examples:

employee_database
customer_database

schema

The schema of the PostgreSQL database.

tables

A list of tables separated by commas. The PostgreSQL connector will fetch data from all tables present in the configured database, if the value is * . Default value is *. Examples:

table_1, table_2
*

This field can be bypassed when using advanced sync rules.

ssl_enabled

Whether SSL verification will be enabled. Default value is True.

ssl_ca

Content of SSL certificate (if SSL is enabled). If SSL is disabled, the ssl_ca value will be ignored.

Expand to see an example certificate

-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----

Deployment using Docker

You can deploy the PostgreSQL connector as a self-managed connector using Docker. Follow these instructions.

Step 1: Download sample configuration file

Download the sample configuration file. You can either download it manually or run the following command:

curl https://raw.githubusercontent.com/elastic/connectors/main/config.yml.example --output ~/connectors-config/config.yml

Remember to update the --output argument value if your directory name is different, or you want to use a different config file name.

Step 2: Update the configuration file for your self-managed connector

Update the configuration file with the following settings to match your environment:

elasticsearch.host
elasticsearch.api_key
connectors

If you’re running the connector service against a Dockerized version of Elasticsearch and Kibana, your config file will look like this:

# When connecting to your cloud deployment you should edit the host value
elasticsearch.host: http://host.docker.internal:9200
elasticsearch.api_key: <ELASTICSEARCH_API_KEY>

connectors:
  -
    connector_id: <CONNECTOR_ID_FROM_KIBANA>
    service_type: postgresql
    api_key: <CONNECTOR_API_KEY_FROM_KIBANA> # Optional. If not provided, the connector will use the elasticsearch.api_key instead

Using the elasticsearch.api_key is the recommended authentication method. However, you can also use elasticsearch.username and elasticsearch.password to authenticate with your Elasticsearch instance.

Note: You can change other default configurations by simply uncommenting specific settings in the configuration file and modifying their values.

Step 3: Run the Docker image

Run the Docker image with the Connector Service using the following command:

docker run \
-v ~/connectors-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/integrations/elastic-connectors:9.0.0-beta1.0 \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to DOCKER.md in the elastic/connectors repo for more details.

Find all available Docker images in the official registry.

We also have a quickstart self-managed option using Docker Compose, so you can spin up all required services at once: Elasticsearch, Kibana, and the connectors service. Refer to this README in the elastic/connectors repo for more information.

Documents and syncs

Tables must be owned by a PostgreSQL user.
Tables with no primary key defined are skipped.
To fetch the last updated time in PostgreSQL, track_commit_timestamp must be set to on. Otherwise, all data will be indexed in every sync.

Files bigger than 10 MB won’t be extracted.
Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync rules

Advanced sync rules

A //connectors-sync-types-full, full sync is required for advanced sync rules to take effect.

Advanced sync rules are defined through a source-specific DSL JSON snippet.

Example data

Here is some example data that will be used in the following examples.

======= employee table

emp_id	name	age
3	John	28
10	Jane	35
14	Alex	22

======= customer table

c_id	name	age
2	Elm	24
6	Pine	30
9	Oak	34

Advanced sync rules examples

======== Multiple table queries

[
  {
    "tables": [
      "employee"
    ],
    "query": "SELECT * FROM employee"
  },
  {
    "tables": [
      "customer"
    ],
    "query": "SELECT * FROM customer"
  }
]

======== Multiple table queries with id_columns

In 8.15.0, we added a new optional id_columns field in our advanced sync rules for the PostgreSQL connector. Use the id_columns field to ingest tables which do not have a primary key. Include the names of unique fields so that the connector can use them to generate unique IDs for documents.

[
  {
    "tables": [
      "employee"
    ],
    "query": "SELECT * FROM employee",
    "id_columns": ["emp_id"]
  },
  {
    "tables": [
      "customer"
    ],
    "query": "SELECT * FROM customer",
    "id_columns": ["c_id"]
  }
]

This example uses the id_columns field to specify the unique fields emp_id and c_id for the employee and customer tables, respectively.

======== Filtering data with WHERE clause

[
  {
    "tables": ["employee"],
    "query": "SELECT * FROM employee WHERE emp_id > 5"
  }
]

======== JOIN operations

[
  {
    "tables": ["employee", "customer"],
    "query": "SELECT * FROM employee INNER JOIN customer ON employee.emp_id = customer.c_id"
  }
]

When using advanced rules, a query can bypass the configuration field tables. This will happen if the query specifies a table that doesn’t appear in the configuration. This can also happen if the configuration specifies * to fetch all tables while the advanced sync rule requests for only a subset of tables.

End-to-end testing

The connector framework enables operators to run functional tests against a real data source. Refer to Connector testing for more details.

To perform E2E testing for the PostgreSQL connector, run the following command:

$ make ftest NAME=postgresql

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=postgresql DATA_SIZE=small

Known issues

There are no known issues for this connector. Refer to Known issues for a list of known issues for all connectors.

Troubleshooting

See Troubleshooting.

Security

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