Airparser and Databricks Integration

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Automate data extraction from unstructured documents with Airparser, then load it directly into Databricks for analysis. Latenode's visual editor makes complex data pipelines simple to build, while affordable execution-based pricing helps you scale affordably and predictably.

Airparser + Databricks integration

Connect Airparser and Databricks in minutes with Latenode.

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Airparser

Databricks

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Airparser and Databricks

Create a New Scenario to Connect Airparser and Databricks

In the workspace, click the β€œCreate New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Airparser, triggered by another scenario, or executed manually (for testing purposes). In most cases, Airparser or Databricks will be your first step. To do this, click "Choose an app," find Airparser or Databricks, and select the appropriate trigger to start the scenario.

Add the Airparser Node

Select the Airparser node from the app selection panel on the right.

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Configure the Airparser

Click on the Airparser node to configure it. You can modify the Airparser URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Connect Airparser

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Run node once

Add the Databricks Node

Next, click the plus (+) icon on the Airparser node, select Databricks from the list of available apps, and choose the action you need from the list of nodes within Databricks.

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Authenticate Databricks

Now, click the Databricks node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Databricks settings. Authentication allows you to use Databricks through Latenode.

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Configure the Airparser and Databricks Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the Airparser and Databricks Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Airparser, Databricks, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking β€œRun once” and triggering an event to check if the Airparser and Databricks integration works as expected. Depending on your setup, data should flow between Airparser and Databricks (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Airparser and Databricks

Airparser + Databricks + Amazon S3: When a new document is uploaded to Airparser, the data is parsed and stored in Databricks. After successful storage, the original document is archived in Amazon S3.

Databricks + Airparser + Slack: Databricks queries parsed data from Airparser. If an anomaly is detected via a SQL query, a notification is sent to a designated Slack channel.

Airparser and Databricks integration alternatives

About Airparser

Airparser in Latenode extracts data from PDFs, emails, and documents. Automate data entry by feeding parsed content directly into your CRM or database. Use Latenode's logic functions to validate or transform data, then trigger actions like sending notifications or updating records. Scale document processing without complex code.

About Databricks

Use Databricks inside Latenode to automate data processing pipelines. Trigger Databricks jobs based on events, then route insights directly into your workflows for reporting or actions. Streamline big data tasks with visual flows, custom JavaScript, and Latenode's scalable execution engine.

See how Latenode works

FAQ Airparser and Databricks

How can I connect my Airparser account to Databricks using Latenode?

To connect your Airparser account to Databricks on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Airparser and click on "Connect".
  • Authenticate your Airparser and Databricks accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I analyze parsed document data within Databricks?

Yes, you can! Latenode simplifies transferring Airparser data to Databricks for in-depth analysis. Leverage Latenode's no-code blocks and custom JavaScript for streamlined workflows and enhanced data insights.

What types of tasks can I perform by integrating Airparser with Databricks?

Integrating Airparser with Databricks allows you to perform various tasks, including:

  • Automatically transfer parsed data from Airparser to Databricks.
  • Enrich Databricks datasets with structured data from Airparser.
  • Trigger Databricks jobs based on document content parsed by Airparser.
  • Visualize Airparser data stored in Databricks using dashboards.
  • Archive and analyze historical document data in Databricks.

How does Latenode handle Airparser authentication securely?

Latenode uses industry-standard encryption and secure storage to manage your Airparser credentials, ensuring data privacy and protection throughout your workflows.

Are there any limitations to the Airparser and Databricks integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Large data volumes from Airparser may impact Databricks processing times.
  • Complex document structures in Airparser might require custom parsing logic.
  • Real-time data transfer depends on the API rate limits of both services.

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