PostgreSQL

If you’re new to Unstructured, read this note first.

Before you can create a source connector, you must first sign in to your Unstructured account:

• If you do not already have an Unstructured account, go to https://unstructured.io/contact and fill out the online form to indicate your interest.
• If you already have an Unstructured account, sign in by using the URL of the sign in page that Unstructured provided to you when your Unstructured account was created. If you do not have this URL, contact Unstructured Sales at [e-mail].

After you sign in, the Unstructured user interface (UI) appears, which you use to get your Unstructured API key. To learn how, watch this 40-second how-to video.

After you create the source connector, add it along with a destination connector to a workflow. Then run the worklow as a job. To learn how, try out the hands-on Workflow Endpoint quickstart, go directly to the quickstart notebook, or watch the two 4-minute video tutorials for the Unstructured Python SDK.

You can also create source connectors with the Unstructured user interface (UI). Learn how.

If you need help, reach out to the community on Slack, or contact us directly.

You are now ready to start creating a source connector! Keep reading to learn how.

Ingest your files into Unstructured from PostgreSQL.

The requirements are as follows.

• For the Unstructured UI or the Unstructured API, local PostgreSQL installations are not supported.
• For Unstructured Ingest, local and non-local PostgreSQL installations are supported.

The following video shows how to set up Amazon RDS for PostgreSQL:

The following video shows how to set up Azure Database for PostgreSQL:

• A PostgreSQL instance.

  • Create an Amazon RDS for PostgreSQL instance.
  • Create an Azure Database for PostgreSQL server.
  • Install PostgreSQL locally.

• The host name and port number for the instance.

  • For Amazon RDS for PostgreSQL, learn how to get the host name and port number.
  • For Azure Database for PostgreSQL, learn how to get the host. The port number is 5432.
  • For local PostgreSQL installations, these values are in the postgresql.conf file’s listen_addresses and port settings. This file should be on the same machine as the instance. These values might also already be set as environment variables named PGHOST and PGPORT on the same machine as the instance.
  • For other installation types, see your PostgreSQL provider’s documentation.

• Depending on your network security requirements, you might need to allow access to your instance only from specific IP addresses.

  To get Unstructured’s IP address ranges, go to https://assets.p6m.u10d.net/publicitems/ip-prefixes.json and allow all of the ip_prefix fields’ values that are listed.

  These IP address ranges are subject to change. You can always find the latest ones in the preceding file.

  To learn how to allow these IP address ranges, see your PostgreSQL provider’s documentation, for example with Amazon RDS for PostgreSQL or Azure Database for PostgreSQL.

  For Amazon RDS for PostgreSQL, Amazon recommends that you set the instance’s Public access setting to No by default, as this approach is more secure. This means that no resources can connect to the instance outside of the instance’s associated Virtual Private Cloud (VPC) without extra configuration. Learn more. Access an Amazon RDS instance in a VPC.

  If you must enable public access, set the instance’s Public access setting to Yes, and then adjust the instance’s related security group to allow this access. Learn how.

  Troubleshoot issues with connecting to Amazon RDS instances.

• A database in the instance.

  • For Amazon RDS for PostgreSQL and Azure Database for PostgreSQL, the default database name is postgres unless a custom database name was specified during the instance creation process.
  • For local PostgreSQL installations, learn how to create a database.
  • For other installation types, see your PostgreSQL provider’s documentation.

• A table in the database. Learn how to create a table.

  The table’s schema must match the schema of the documents that Unstructured produces. Unstructured cannot provide a schema that is guaranteed to work in all circumstances. This is because these schemas will vary based on your source files’ types; how you want Unstructured to partition, chunk, and generate embeddings; any custom post-processing code that you run; and other factors.

  You can adapt the following table schema example for your own needs:

  PostgreSQL

  CREATE TABLE elements (
      id UUID PRIMARY KEY,
      record_id VARCHAR,
      element_id VARCHAR,
      text TEXT,
      embeddings DECIMAL [],
      parent_id VARCHAR,
      page_number INTEGER,
      is_continuation BOOLEAN,
      orig_elements TEXT,
      partitioner_type VARCHAR
  );
  

  See also:

  • CREATE TABLE for PostgreSQL
  • CREATE TABLE for PostrgreSQL with pgvector
  • Unstructured document elements and metadata

  The following video shows how to use the psql utility to connect to PostgreSQL, list databases, and list and create tables:

• A user in the database, and a password for the user.

  • For Amazon RDS for PostgreSQL, learn how to create a user.
  • For Azure Database for PostgreSQL, learn how to create a user.
  • For local PostgreSQL installations, learn how to create a user.
  • For other installation types, see your PostgreSQL provider’s documentation.

• Database access for the user.

  • For Amazon RDS for PostgreSQL, learn how to control user access.
  • For Azure Database for PostgreSQL, learn how to control user access.
  • For local PostgreSQL installations, learn how to give database access to a user.
  • For other installation types, see your PostgreSQL provider’s documentation.

To create an PostgreSQL source connector, see the following examples.

Python SDK

import os

from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateSourceRequest
from unstructured_client.models.shared import (
    CreateSourceConnector,
    SourceConnectorType,
    PostgresSourceConnectorConfigInput
)

with UnstructuredClient(api_key_auth=os.getenv("UNSTRUCTURED_API_KEY")) as client:
    response = client.sources.create_source(
        request=CreateSourceRequest(
            create_source_connector=CreateSourceConnector(
                name="<name>",
                type=SourceConnectorType.POSTGRES,
                config=PostgresSourceConnectorConfigInput(
                    host="<host>",
                    database="<database>",
                    port="<port>",
                    username="<username>",
                    password="<password>",
                    table_name="<table_name>",
                    batch_size=<batch-size>,
                    id_column="<id-column>",
                    fields=[
                        "<field>",
                        "<field>"
                    ]
                )
            )
        )
    )

    print(response.source_connector_information)

Replace the preceding placeholders as follows:

• <name> (required) - A unique name for this connector.
• <host> (required) - The host name.
• <database> (required) - The name of the database.
• <port> (required) - The port number.
• <username> (required) - The username.
• <password> (required) - The user’s password.
• <table_name> (required) - The name of the table in the database.
• <batch-size> - The maximum number of rows to transmit at a time. The default is 100 if not otherwise specified.
• <id-column> (required, source connector only) - The name of the ID column in the table.
• For fields (source connector only), set one or more <field> values, with each value representing the name of a column to process (including the specified <id-column> column). The default is all columns if not otherwise specified.

Learn more

•   PostgreSQL Integration in the Unstructured Platform

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