How does Photon contribute to cost efficiency in Databricks?

By eliminating the need for compute resources.

By automatically pausing clusters when not in use.

By enabling faster query completion, which can reduce compute time and associated costs.

By reducing the amount of data stored in Delta Lake.

A team is evaluating whether to enable Photon on their cluster. They run a variety of workloads: SQL dashboards, Python pandas code, and machine learning training with Spark MLlib. Which workload will benefit most from Photon?

SQL dashboards that aggregate large Delta tables.

All workloads will benefit equally.

Machine learning training with Spark MLlib.

Python pandas code that runs on the driver.

What is Photon in the context of Databricks?

A cluster manager that allocates resources for concurrent workloads

A vectorized query engine that accelerates SQL and DataFrame operations

A data catalog service for managing metadata and schema evolution

A proprietary file format optimized for columnar storage

A data analyst is about to create a new cluster for running SQL analytics on Delta Lake. They want to use Photon to speed up queries. What is the correct way to enable Photon?

Run a SQL command to enable Photon on the cluster after it starts.

Install Photon as a library on the cluster.

Select the Photon option in the cluster configuration before creating the cluster.

Enable Photon in the notebook settings.

A data analyst is writing a complex SQL query that uses window functions, subqueries, and joins on Delta tables. They want to ensure the query runs as fast as possible and are considering enabling Photon. Which consideration is most important?

Photon only supports basic SELECT queries, so complex SQL will fail.

Photon only works with Parquet files, not Delta Lake.

Photon requires the query to be rewritten in PySpark to work.

Photon supports ANSI SQL and Delta Lake, so the query will run without modification.

DatabricksCertified Data Analyst Associate

Domain 5Objective 1

Understand the Features, Benefits, and Supported Workloads of Photon. DATA-ANALYST-ASSOCIATE Practice Questions (Page 2)

Part of the Section 5: Analyzing Queries domain, which makes up ~17% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~6–10 in this domain), expect 1–2 from this objective — we provide 21 practice questions to prepare you well beyond it. (estimate)

21questions here

5free pages

5concepts

Questions 6–10

6foundation · easy
How does Photon contribute to cost efficiency in Databricks?
Select an answer first
7application · medium
A team is evaluating whether to enable Photon on their cluster. They run a variety of workloads: SQL dashboards, Python pandas code, and machine learning training with Spark MLlib. Which workload will benefit most from Photon?
Select an answer first
8foundation · easy
What is Photon in the context of Databricks?
Select an answer first
9application · medium
A data analyst is about to create a new cluster for running SQL analytics on Delta Lake. They want to use Photon to speed up queries. What is the correct way to enable Photon?
Select an answer first
10application · medium
A data analyst is writing a complex SQL query that uses window functions, subqueries, and joins on Delta tables. They want to ensure the query runs as fast as possible and are considering enabling Photon. Which consideration is most important?
Select an answer first

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