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Databricks Certified Data Engineer Associate exam is a comprehensive exam that tests candidates on a range of topics related to data engineering on the Databricks platform. Databricks-Certified-Data-Engineer-Associate Exam covers topics such as data ingestion, data transformation, data storage, and data processing. Candidates are also tested on their knowledge of the Databricks platform, including its architecture, tools, and features.
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NEW QUESTION # 107
A new data engineering team has been assigned to work on a project. The team will need access to database customers in order to see what tables already exist. The team has its own group team.
Which of the following commands can be used to grant the necessary permission on the entire database to the new team?
Answer: E
Explanation:
1: The correct command to grant the necessary permission on the entire database to the new team is to use the GRANT USAGE command. The GRANT USAGE command grants the principal the ability to access the securable object, such as a database, schema, or table. In this case, the securable object is the database customers, and the principal is the group team. By granting usage on the database, the team will be able to see what tables already exist in the database. Option E is the only option that uses the correct syntax and the correct privilege type for this scenario. Option A uses the wrong privilege type (VIEW) and the wrong securable object (CATALOG). Option B uses the wrong privilege type (CREATE), which would allow the team to create new tables in the database, but not necessarily see the existing ones. Option C uses the wrong securable object (CATALOG) and the wrong principal (customers). Option D uses the wrong securable object (team) and the wrong principal (customers). Reference: GRANT, Privilege types, Securable objects, Principals
NEW QUESTION # 108
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.
Which of the following control flow statements should the data engineer use to begin this conditionally executed code block?
Answer: D
NEW QUESTION # 109
A new data engineering team team has been assigned to an ELT project. The new data engineering team will need full privileges on the table sales to fully manage the project.
Which of the following commands can be used to grant full permissions on the database to the new data engineering team?
Answer: A
NEW QUESTION # 110
A data engineering team has noticed that their Databricks SQL queries are running too slowly when they are submitted to a non-running SQL endpoint. The data engineering team wants this issue to be resolved.
Which of the following approaches can the team use to reduce the time it takes to return results in this scenario?
Answer: D
Explanation:
Explanation
Databricks SQL endpoints can run in two modes: Serverless and Dedicated. Serverless mode allows you to run queries without managing clusters, while Dedicated mode allows you to run queries on a specific cluster.
Serverless mode is faster and more cost-effective for ad-hoc queries, especially when the SQL endpoint is not running. Dedicated mode is more suitable for predictable and consistent performance, especially for long-running queries. By turning on the Serverless feature for the SQL endpoint, the data engineering team can reduce the time it takes to start the SQL endpoint and return results. The other options are not relevant or effective for this scenario. References: Databricks SQL endpoints, New Performance Improvements in Databricks SQL, Slowness when fetching results in Databricks SQL
NEW QUESTION # 111
A data analyst has developed a query that runs against Delta table. They want help from the data engineering team to implement a series of tests to ensure the data returned by the query is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following operations could the data engineering team use to run the query and operate with the results in PySpark?
Answer: E
Explanation:
The spark.sql operation allows the data engineering team to run a SQL query and return the result as a PySpark DataFrame. This way, the data engineering team can use the same query that the data analyst has developed and operate with the results in PySpark. For example, the data engineering team can use spark.sql("SELECT * FROM sales") to get a DataFrame of all the records from the sales Delta table, and then apply various tests or transformations using PySpark APIs. The other options are either not valid operations (A, D), not suitable for running a SQL query (B, E), or not returning a DataFrame (A). Reference: Databricks Documentation - Run SQL queries, Databricks Documentation - Spark SQL and DataFrames.
NEW QUESTION # 112
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