This quickstart guide will help you start with Oxla Cloud by setting up workloads using a sample dataset.

Step 1. Create an Account

Create an account here or login using your credentials.

Step 2. Set Up Data Storage with Sample Data

  1. Once logged in, go to the Overview or Data section and choose the Create Data Storage button. Specify the data storage name and select one of the pre-loaded datasets. In this case, we’ll use the eCommerce dataset.
  1. Please wait a moment until your data storage is created.

Step 3. Initiate a Cluster

Now, create a cluster to query the sample database stored in the data storage we’ve just set up.

  1. Go to the Clusters section and click the Start a new Cluster button. Alternatively, access the ”Use to create cluster” option directly.
  1. Fill in the required fields, and choose a single node for simpler environments.
  1. Click ”Start Cluster” and wait for it to be up and running.

Step 4. Connect to Oxla SaaS

Once your cluster is up and running, connect to Oxla SaaS using the command you got when you created the cluster or in the connection details modal. This command logs you into the Oxla database using your connection details.

You can also connect to Oxla SaaS using Looker or Tableplus, which offer distinct features and interfaces that can meet your specific needs. For example, you can use Looker to convert data into graphs and charts based on a query’s results.

Step 5. Querying Data

Once connected to Oxla SaaS, you can perform queries using your chosen dataset. For example, below is a sample query to find the Top 3 Sold Parts in the eCommerce dataset.

SELECT p.p_name AS part_name, 
       SUM(l.lo_quantity) AS total_quantity_sold, 
       SUM(l.lo_revenue) AS total_revenue
FROM lineorder l
JOIN part p ON l.lo_partkey = p.p_partkey
GROUP BY p.p_name
ORDER BY total_revenue DESC

The result displays the three most sold parts based on the quantity sold.

     part_name     | total_quantity_sold | total_revenue 
 aquamarine beige  |             3871448 |  562986438412
 aquamarine black  |             3662718 |  521680920074
 aquamarine bisque |             3692528 |  519083669350
(3 rows)
Next, you can explore other datasets and run other sample queries. Please refer to the Introduction page.

Step 6. Manage Your Cluster

While your cluster is active, you can stop its operations whenever necessary. Once you stop the cluster, it won’t consume any credits or funds.

When you’re finished with your tests you can also delete the cluster. Deleting the cluster only releases the compute resources and doesn’t remove the data itself.

Deleting a cluster is only possible for clusters in a STOPPED or FAILED state.