Databricks-DE-Assoc Practice Test 5 — 10 Questions

Question 1

A data engineer needs to create a Delta table in Unity Catalog that will be used by multiple teams. The engineer wants to ensure that the table is governed by Unity Catalog and that access can be controlled using SQL GRANT statements. What is the correct way to create the table?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

CREATE TABLE my_catalog.my_schema.my_table (id INT, name STRING) USING DELTA;. To create a managed Delta table in Unity Catalog, use the CREATE TABLE statement with a three-part name (catalog.schema.table) and specify USING DELTA. This ensures the table is governed by Unity Catalog and can be secured with GRANT statements.

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CREATE EXTERNAL TABLE my_catalog.my_schema.my_table (id INT, name STRING) USING DELTA LOCATION '/mnt/data/my_table';

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CREATE TABLE my_catalog.my_schema.my_table AS SELECT * FROM parquet.`/mnt/data/my_table`;

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CREATE TABLE my_table (id INT, name STRING) USING DELTA LOCATION '/mnt/data/my_table';

Question 2

Refer to the exhibit. A data engineer is deploying an automated job. Based on the provided configuration, what is the primary benefit of using the 'autoscale' attribute in this cluster definition?

Accepted Answer

It enables the cluster to adjust resources dynamically based on current job load.. The 'autoscale' configuration allows the Databricks Intelligence Platform to dynamically adjust the number of worker nodes based on the workload demands. By setting a minimum and maximum range, the cluster automatically adds nodes during intensive processing and removes them during idle periods. This is critical for optimizing costs and performance, ensuring that compute resources are consumed only when necessary without requiring manual intervention by the engineer.

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It forces the cluster to always use 8 nodes to ensure maximum performance.

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It ensures that the cluster uses specific instance types defined in the policy.

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It mandates the use of Spot Instances to reduce total cost of ownership.

Question 3

When a data engineer needs to automate a recurring ETL job, which Databricks tool is most appropriate for orchestrating tasks and handling dependencies?

Accepted Answer

Databricks Workflows. Databricks Workflows allows engineers to create, run, and monitor multi-task jobs. It supports dependencies, retries, and notifications, making it the standard choice for orchestrating complex data pipelines. By using Workflows, engineers can ensure that data transformation tasks occur in the correct sequence, with robust error handling and monitoring, which is critical for maintaining reliable production data pipelines in the Databricks Intelligence Platform.

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Databricks Notebooks

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Delta Live Tables

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MLflow Models

Question 4

A Databricks job is failing due to 'Out of Memory' (OOM) errors during a join operation on two large datasets. Which TWO actions could help mitigate this issue?

Accepted Answer

Increase the cluster's worker node instance type with more memory.. OOM errors during joins often occur because the driver or worker nodes lack enough memory to handle the shuffle or broadcast operations. Increasing the cluster memory allows for larger data partitions to reside in memory, while adjusting the broadcast join threshold prevents the optimizer from attempting to broadcast datasets that exceed available node capacity. These configurations are essential for stabilizing large-scale ETL pipelines that process high-volume data.

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Decrease the number of partitions in the Spark cluster.

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Enable dynamic allocation for the cluster.

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Use the cache() method on every DataFrame in the pipeline.

Question 5

A data engineer needs to share a Delta table managed by Unity Catalog with external partners who do not have access to the Databricks workspace. Which feature should be used to securely grant read-only access to this table without replicating the data?

Accepted Answer

Create a Delta Sharing share, add the table to the share, and grant access to a recipient object configured for the partners.. Delta Sharing is an open protocol for secure data sharing that allows organizations to share data directly from cloud storage without copying files. Unity Catalog integrates natively with Delta Sharing, enabling governance teams to manage access for external recipients securely using tokens and activation links, making it the ideal solution for cross-organization data collaboration.

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Configure cross-account IAM role assumption to grant direct AWS S3 bucket read permissions to the external partners.

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Set up a Databricks SQL endpoint and create individual workspace user accounts for every external partner.

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Export the Delta table to CSV format and upload the files to an external SFTP server on a nightly schedule.

Question 6

A data engineer needs to configure a Databricks Job containing multiple tasks where downstream tasks should only execute if all upstream parent tasks complete successfully. Which task dependency setting should be configured?

Accepted Answer

Add the upstream tasks as parents of the downstream task directly within the job configuration graph.. To ensure tasks execute conditionally based on the success of parent tasks, you configure task dependencies within the Databricks Jobs UI or JSON definition. By default, adding a parent task creates a strict dependency where downstream tasks trigger only upon successful completion. This mechanism orchestrates complex directed acyclic graphs for robust, reliable data pipelines.

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Configure a retry policy with exponential backoff on the parent task to guarantee eventual success.

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Set up a global workspace webhook to trigger downstream tasks manually after the parent completes.

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Enable concurrent run suppression on the job level to prevent overlapping workflow executions.

Question 7

A data engineering team must implement dynamic row-level filtering on a customer analytics table in Unity Catalog so that regional analysts only view records corresponding to their assigned territory. Which TWO steps are required to achieve this using Unity Catalog features? (Choose 2)

Accepted Answer

Create a SQL user-defined function (UDF) that returns a boolean expression evaluating user identity and territory.. Implementing row-level security in Unity Catalog requires creating a SQL user-defined function that evaluates the current user's identity or group membership against a territory mapping table, and then applying that function to the target table using an ALTER TABLE command.

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Modify the underlying cloud storage bucket IAM policy to restrict read access based on user session tags.

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Create separate physical views for each regional analyst group and grant SELECT privileges exclusively on those views.

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Configure cluster-level Spark configurations to automatically inject WHERE clauses into user queries.

Question 8

Which Databricks command should you use to recover storage space by removing files that are no longer referenced by a Delta table and are older than the retention period?

Accepted Answer

VACUUM table_name RETAIN 30 DAYS;. VACUUM is the standard tool for cleaning up orphan files in Delta Lake. Because Delta Lake uses versioning, old files are kept for 'Time Travel' functionality until specifically vacuumed. Managing this storage is essential for cost control and compliance with data retention policies. Engineers must understand that once VACUUM is run, the history of the table is permanently pruned, making point-in-time recovery to those older versions impossible.

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DELETE FROM table_name WHERE date < current_date() - 30;

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TRUNCATE TABLE table_name;

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DROP TABLE table_name;

Question 9

Refer to the exhibit. A data engineer receives this error when collecting data from a large transformation back to the driver node. Which approach should be used to fix this issue?

Accepted Answer

Rewrite the job to write the results to a Delta table.. The error occurs because the result set being pulled to the driver exceeds the configured limit. Collecting massive data to the driver is an anti-pattern in distributed computing as it bypasses the cluster's parallel processing capabilities. Instead of forcing data into the driver's memory, the engineer should write the output to cloud storage or a Delta table, allowing downstream processes to handle the data in a distributed, scalable manner without memory pressure.

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Increase the spark.driver.maxResultSize setting.

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Reduce the number of tasks in the Spark job.

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Enable Spark dynamic allocation.

Question 10

Which TWO of the following statements accurately describe the functionality of Unity Catalog within the Databricks Intelligence Platform?

Accepted Answer

It provides centralized access control, auditing, and lineage for all data and AI assets.. Unity Catalog provides a unified governance layer for data and AI assets across a Databricks account. It simplifies security by providing a single place to define access control policies, and it enables cross-workspace data sharing. Understanding this is essential for engineers responsible for managing multi-workspace environments, as it replaces the older, workspace-specific Hive Metastore with a centralized, cloud-agnostic governance model for better auditability and compliance.

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It requires a separate Hive Metastore for each individual Databricks workspace.

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It is an execution engine used to run heavy machine learning training jobs.

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It only supports files stored in Amazon S3 buckets.