Step by Step Guide to Building a Databricks API Integration in PHP

Introduction

Hey there, fellow developer! Ready to supercharge your PHP project with Databricks? You're in for a treat. Databricks API is a powerhouse for managing your data analytics and machine learning workflows. And guess what? We're going to make it even easier with the codibly/databricks-bundle package. Let's dive in!

Prerequisites

Before we get our hands dirty, make sure you've got:

• A PHP environment that's up and running
• Composer installed (because who doesn't love dependency management?)
• A Databricks account with API credentials in hand

Got all that? Great! Let's move on.

Installation

First things first, let's get that package installed. Fire up your terminal and run:

composer require codibly/databricks-bundle

Easy peasy, right?

Configuration

Now, let's set up those API credentials. Create a .env file if you haven't already, and add:

DATABRICKS_HOST=your-workspace-url
DATABRICKS_TOKEN=your-access-token

Next, configure the bundle in your PHP project. If you're using Symfony, add this to your config/packages/databricks.yaml:

databricks:
    host: '%env(DATABRICKS_HOST)%'
    token: '%env(DATABRICKS_TOKEN)%'

For other frameworks, you'll need to load these environment variables yourself. No sweat!

Basic Usage

Time to get that Databricks client up and running:

use Codibly\DatabricksBundle\DatabricksClient;

$client = new DatabricksClient($host, $token);

Let's make your first API call:

$clusters = $client->cluster()->list();

Boom! You've just listed all your Databricks clusters. How cool is that?

Common API Operations

Now that you're rolling, let's look at some common operations:

Cluster Management

// Create a cluster
$clusterId = $client->cluster()->create([
    'cluster_name' => 'My Awesome Cluster',
    'spark_version' => '7.3.x-scala2.12',
    'node_type_id' => 'i3.xlarge',
    'num_workers' => 2
]);

// Start a cluster
$client->cluster()->start($clusterId);

// Terminate a cluster
$client->cluster()->delete($clusterId);

Job Management

// Create a job
$jobId = $client->jobs()->create([
    'name' => 'My Cool Job',
    'new_cluster' => [
        'spark_version' => '7.3.x-scala2.12',
        'node_type_id' => 'i3.xlarge',
        'num_workers' => 2
    ],
    'notebook_task' => [
        'notebook_path' => '/Users/[email protected]/My Notebook'
    ]
]);

// Run a job
$runId = $client->jobs()->runNow($jobId);

Workspace Management

// List workspace contents
$contents = $client->workspace()->list('/Users/[email protected]');

// Import a notebook
$client->workspace()->import('/Users/[email protected]/New Notebook', 'PYTHON', 'SOURCE', file_get_contents('my_notebook.py'));

DBFS Operations

// List DBFS contents
$files = $client->dbfs()->list('/');

// Upload a file
$client->dbfs()->put('/my_file.txt', file_get_contents('local_file.txt'));

Error Handling and Best Practices

Always wrap your API calls in try-catch blocks:

try {
    $result = $client->cluster()->list();
} catch (\Exception $e) {
    // Handle the error
    echo "Oops! " . $e->getMessage();
}

And remember, Databricks has rate limits. Be nice to the API, and it'll be nice to you!

Advanced Usage

Want to customize your API requests? No problem:

$client->setHttpClient(new \GuzzleHttp\Client([
    'timeout' => 30,
    'verify' => false
]));

Testing

Don't forget to test your integration! Here's a quick example using PHPUnit:

use PHPUnit\Framework\TestCase;

class DatabricksIntegrationTest extends TestCase
{
    public function testClusterList()
    {
        $client = new DatabricksClient($host, $token);
        $clusters = $client->cluster()->list();
        $this->assertIsArray($clusters);
    }
}

Conclusion

And there you have it! You're now a Databricks API integration ninja. Remember, this is just scratching the surface. The Databricks API has tons more to offer, so don't be afraid to explore.

For more details, check out the codibly/databricks-bundle documentation and the official Databricks API docs.

Now go forth and build something awesome! Happy coding!