Skip to content

Commit 60eaed0

Browse files
committed
Add Hamilton's post about using Databricks SQL Serverless
1 parent 0c7ae72 commit 60eaed0

File tree

1 file changed

+58
-0
lines changed

1 file changed

+58
-0
lines changed
Lines changed: 58 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
1+
----
2+
layout: post
3+
title: "Accelerating Looker with Databricks SQL Serverless"
4+
tags:
5+
- looker
6+
- databricks
7+
- featured
8+
team: Core Platform
9+
author: hamiltonh
10+
----
11+
12+
We recently migrated Looker to a Databricks SQL Serverless, improving our
13+
infrastructure cost and reducing the footprint of infrastructure we need to
14+
worry about! “Databricks SQL” which provides a single load balanced Endpoint
15+
for executing Spark SQL queries across multiple Spark clusters behind the
16+
scenes. “Serverless” is an evolution of that concept, rather than running a SQL
17+
Endpoint in our AWS infrastructure, the entirety of execution happens on the
18+
Databricks side. With a much simpler and faster interface, queries executed in
19+
Looker now return results much faster to our users than ever before!
20+
21+
When we originally provisioned our “Databricks SQL” endpoints, we worked
22+
together with our colleagues at Databricks to ensure [the terraform provider
23+
for Databricks](https://github.com/databricks/terraform-provider-databricks) is
24+
ready for production usage, which as of today is Generally Available. That
25+
original foundation in Terraform allowed us to more easily adopt SQL Serverless
26+
once it was made available to us.
27+
28+
```hcl
29+
resource "databricks_sql_endpoint" "endpoint" {
30+
name = "Looker Serverless"
31+
# ...
32+
enable_serverless_compute = true
33+
# ...
34+
}
35+
```
36+
37+
The feature was literally brand new so there were a few integration hurdles we
38+
had to work through with our colleagues at Databricks, but we got things up and
39+
running in short order. By adopting SQL Serverless, we could avoid setting up
40+
special networking, IAM roles, and other resources within our own AWS account,
41+
we can instead rely on pre-provisioned compute resources within Databricks' own
42+
infrastructure. No more headache of ensuring all of the required infra is in
43+
place and setup correctly!
44+
45+
The switch to Serverless reduced our infra configuration and management
46+
footprint, which by itself is an improvement. We also noticed a significant
47+
reduction in cold start times for the SQL Serverless Endpoint compared to the
48+
standard SQL Endpoint. The faster start-up times meant we could configure even
49+
lower auto-terminate times on the endpoint, savings us even more on
50+
unproductive and idle cluster costs.
51+
52+
On the Looker side there really wasn’t any difference in the connection
53+
configuration other than a URL change. In the end, after some preparation work
54+
a simple 5 minute change in Looker, and a simple 5 minute change in Terraform
55+
switched everything over to Databricks SQL Serverless, and we were ready to
56+
rock! Our BI team is very happy with the performance, especially on cold start
57+
queries. Our CFO is happy about reducing infrastructure costs. And I’m happy
58+
about simpler infrastructure!

0 commit comments

Comments
 (0)