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| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Associate Exam |
| Exam Number: | Databricks-Certified-Data-Engineer-Associate |
| Passing Score: | 70% |
| Exam Price: | $200 USD |
| Exam Duration: | 90 minutes |
| Available Languages: | English |
| Exam Format: | Multiple Select, Multiple Choice |
| Related Certifications: | Databricks Certified Data Analyst Associate |
| Real Exam Qty: | 60 |
| Certificate Validity Period: | 2 years |
| Sample Questions: | Databricks Databricks-Certified-Data-Engineer-Associate Sample Questions |
| Exam Way: | Online proctored or in-person testing center |
| Pre Condition: | Recommended: 6+ months of experience with Databricks and Apache Spark |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/data-engineer-associate |
>> Databricks-Certified-Data-Engineer-Associate Test Questions Answers <<
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Databricks Certified Data Engineer Associate Exam is designed for data engineers, software developers, and IT professionals who work with data on a regular basis. Databricks Certified Data Engineer Associate Exam certification program is ideal for individuals who want to demonstrate their expertise in designing and building data pipelines, working with big data, and developing data-driven applications using Databricks.
NEW QUESTION # 194
Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?
Answer: D
Explanation:
Delta Lake is the optimized storage layer that provides the foundation for storing data and tables in the Databricks lakehouse. Delta Lake is fully compatible with Apache Spark APIs, and was developed for tight integration with Structured Streaming, allowing you to easily use a single copy of data for both batch and streaming operations and providing incremental processing at scale1. Delta Lake supports upserts using the merge operation, which enables you to efficiently update existing data or insert new data into your Delta tables2. Delta Lake also provides time travel capabilities, which allow you to query previous versions of your data or roll back to a specific point in time3. References: 1: What is Delta Lake? | Databricks on AWS 2: Upsert into a table using merge | Databricks on AWS 3: [Query an older snapshot of a table (time travel) | Databricks on AWS] Learn more
1blob:https://www.bing.com/a746b4b4-48d0-4f44-9736-44d1ce0c4228
learn.microsoft.com2blob:https://www.bing.com/525fbb0f-e02f-4a70-8085-22c065fe0ca0 medium.com3blob:https://www.bing.com/5cb5bd07-1008-4cf7-9fa3-42a5a689c7d5 slideshare.net4blob:https://www.bing.com/9a7e8352-30c1-4356-a73f-a7253b607ef7 docs.databricks.com5blob:https://www.bing.com/3f65cc27-d573-4810-b272-01238a431c03 github.com6blob:https://www.bing.com/334f6880-dfeb-4e61-bd9a-76efae0a2d01 key2consulting.com
NEW QUESTION # 195
A data engineer runs CREATE TABLE gold.revenue AS SELECT * FROM silver.orders in Unity Catalog without specifying a LOCATION.
What is the result?
Answer: D
Explanation:
A CTAS statement without a LOCATION clause creates a Unity Catalog managed table in Delta format, stored in the managed storage location configured for the schema, catalog, or metastore.
Unity Catalog then controls the storage lifecycle, including file cleanup on drop.
NEW QUESTION # 196
A data engineer has manually created several Databricks jobs and dashboards using the workspace UI. The team now wants to manage these resources as code using Declarative Automation Bundles (formerly Databricks Asset Bundles), store the configuration in a Git repository, and deploy changes through CI/CD. Which approach converts the existing resources into a bundle project?
Answer: B
Explanation:
databricks bundle generate creates bundle configuration from each existing job or dashboard.
Using --bind links that configuration to the existing workspace resource, allowing subsequent bundle deployments to update it rather than create a duplicate.
NEW QUESTION # 197
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 approach can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?
Answer: B
Explanation:
To minimize the total running time of the SQL endpoint used in the refresh schedule of a dashboard in Databricks, the most effective approach is to utilize the Auto Stop feature. This feature allows the SQL endpoint to automatically stop after a period of inactivity, ensuring that it only runs when necessary, such as during the dashboard refresh or when actively queried. This minimizes resource usage and associated costs by ensuring the SQL endpoint is not running idle outside of these operations.
References:Databricks documentation on SQL endpoints: SQL Endpoints in Databricks
NEW QUESTION # 198
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The code block used by the data engineer is below:
If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?
Answer: E
NEW QUESTION # 199
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