Free Databricks Databricks-Certified-Data-Engineer-Associate Exam Actual Questions

The questions for Databricks-Certified-Data-Engineer-Associate were last updated On Dec 16, 2024

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Question No. 1

A data engineer needs access to a table new_table, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is.

Which of the following approaches can be used to identify the owner of new_table?

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Correct Answer: C

he approach that can be used to identify the owner of new_table is to review the Owner field in the table's page in Data Explorer.Data Explorer is a web-based interface that allows users to browse, create, and manage data objects such as tables, views, and functions in Databricks1.The table's page in Data Explorer provides various information about the table, such as its schema, partitions, statistics, history, and permissions2.The Owner field shows the name and email address of the user who created or owns the table3. The data engineer can use this information to contact the table owner and request for permission to access the table.

The other options are not correct or reliable for identifying the owner of new_table.Reviewing the Permissions tab in the table's page in Data Explorer can show the users and groups who have access to the table, but not necessarily the owner4.Reviewing the Owner field in the table's page in the cloud storage solution can be misleading, as the owner of the data files may not be the same as the owner of the table5. There is a way to identify the owner of the table, as explained above, so option E is false.


1:Data Explorer | Databricks on AWS

2:Table details | Databricks on AWS

3:Set owner when creating a view in databricks sql - Databricks - 9978

4:Table access control | Databricks on AWS

5:External tables | Databricks on AWS

Question No. 2

In which of the following file formats is data from Delta Lake tables primarily stored?

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Correct Answer: C

Delta Lake is an open source project that provides ACID transactions, time travel, and other features on top of Apache Parquet, a columnar file format that is widely used for big data analytics. Delta Lake uses versioned Parquet files to store your data in your cloud storage, along with JSON files as transaction logs and checkpoint files to track the changes and ensure data integrity. Delta Lake is compatible with any Apache Hive compatible file format, such as CSV, JSON, or AVRO, but it primarily stores data as Parquet files for better performance and compression.Reference:How to Create Delta Lake tables,5 reasons to choose Delta Lake format (on Databricks),Parquet vs Delta format in Azure Data Lake Gen 2 store,What is Delta Lake? - Azure Databricks,Lakehouse and Delta tables - Microsoft Fabric


Question No. 3

Which of the following data lakehouse features results in improved data quality over a traditional data lake?

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Correct Answer: B

: A data lakehouse is a data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data12.One of the key features of a data lakehouse is that it supports ACID-compliant transactions, which means that it ensures data integrity, consistency, and isolation across concurrent read and write operations3.This feature results in improved data quality over a traditional data lake, which does not support transactions and may suffer from data corruption, duplication, or inconsistency due to concurrent or streaming data ingestion and processing .Reference:1:What is a Data Lakehouse? - Databricks2:What is a Data Lakehouse? Definition, features & benefits. - Qlik3:ACID Transactions - Databricks: [Data Lake vs Data Warehouse: Key Differences] : [Data Lakehouse: The Future of Data Engineering]


Question No. 4

A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.

Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

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Correct Answer: A

The Auto Stop feature allows the SQL endpoint to automatically stop after a specified period of inactivity. This can help reduce the cost and resource consumption of the SQL endpoint, as it will only run when it is needed to refresh the dashboard or execute queries. The data engineer can configure the Auto Stop setting for the SQL endpoint from the SQL Endpoints UI, by selecting the desired idle time from the Auto Stop dropdown menu. The default idle time is 120 minutes, but it can be set to as low as 15 minutes or as high as 240 minutes. Alternatively, the data engineer can also use the SQL Endpoints REST API to set the Auto Stop setting programmatically.Reference:SQL Endpoints UI,SQL Endpoints REST API,Refreshing SQL Dashboard


Question No. 5

A single Job runs two notebooks as two separate tasks. A data engineer has noticed that one of the notebooks is running slowly in the Job's current run. The data engineer asks a tech lead for help in identifying why this might be the case.

Which of the following approaches can the tech lead use to identify why the notebook is running slowly as part of the Job?

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Correct Answer: B

The Tasks tab in the Jobs UI shows the list of tasks that are part of a job, and allows the user to view the details of each task, such as the notebook path, the cluster configuration, the run status, and the duration. By clicking on the active run of a task, the user can access the Spark UI, the notebook output, and the logs of the task. These can help the user to identify the performance bottlenecks and errors in the task. The Runs tab in the Jobs UI only shows the summary of the job runs, such as the start time, the end time, the trigger, and the status. It does not provide the details of the individual tasks within a job run.Reference:Jobs UI,Monitor running jobs with a Job Run dashboard,How to optimize jobs performance


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