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Databricks Databricks-Certified-Data-Engineer-Associate 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Production Pipelines: It focuses on identifying the advantages of using multiple tasks in Jobs, a suitable scenario where predecessor task should be set up, CRON as an opportunity for scheduling opportunity, and how an alert can be sent via email. The topic also discusses setting up a predecessor task in Jobs, reviewing a task's execution history, and debugging a failed task. Lastly, it delves into setting up a retry policy in case of failure and creating an alert in the case of a failed task.
トピック 2	Databricks Lakehouse Platform: This topic covers the relationship between the data lakehouse and the data warehouse, the improvement in data quality, comparing and contrasting silver and gold tables, elements of the Databricks Platform Architecture, and differentiating between all-purpose clusters and jobs clusters. Moreover, it identifies how cluster software is versioned, how clusters can be filtered, how to use multiple languages, how to run one notebook, how notebooks can be shared, Git operations, and limitations in Databricks Notebooks. Lastly, the topic describes how clusters are terminated, how to use multiple languages, and how Databricks Repos enables CI CD workflows.
トピック 3	ELT with Apache Spark: It focuses on extracting data, identifying the prefix, creating a view, duplicating rows, creating a new table, utilizing the dot, parsing JSON, and defining a SQL UDF. Moreover, the topic delves into describing the security model, identifying the location of a function, and identifying the PIVOT.
トピック 4	Data Governance: It identifies one of the four areas of data governance, Unity Catalog securables, and the cluster security modes. It also discusses how to create a UC-enabled all-purpose cluster and a DBSQL warehouse. The topic explains how to implement data object access control, create a DBSQL warehouse, and e a UC-enabled all-purpose cluster.
トピック 5	Incremental Data Processing: In this topic questions about identifying Delta Lake, benefits of ACID transactions, a scenario to use an external table, location of a table, the benefits of Zordering, the kind of files, CTAS as a solution, the impact of ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATE, and the necessary component to create a new DLT pipeline. Moreover, the topic also discusses directory structure of Delta Lake files, generated column, adding a table comment, and the benefits of the MERGE command.

参照：https://www.databricks.com/learn/certification/data-engineer-associate

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Databricks Certified Data Engineer Associate 認定 Databricks-Certified-Data-Engineer-Associate 試験問題：

問題 #1
A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE.
Three datasets are defined against Delta Lake table sources using LIVE TABLE.
The table is configured to run in Production mode using the Continuous Pipeline Mode.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?

A. All datasets will be updated once and the pipeline will persist without any processing. The compute resources will persist but go unused.
B. All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated.
C. All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.
D. All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will be deployed for the update and terminated when the pipeline is stopped.
E. All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing.

問題 #2
A data engineer works for an organization that must meet a stringent Service Level Agreement (SLA) that demands minimal runtime errors and high availability for its data processing pipelines.
The data engineer wants to avoid the operational overhead of managing and tuning clusters.
Which architectural solution will meet the requirements?

A. Deploy a dedicated, manually managed cluster optimized by in-house IT staff.
B. Utilize Databricks serverless compute that automatically optimizes resources and abstracts cluster management.
C. Use an auto-scaling cluster configured and monitored by the user.
D. Implement a hybrid approach with scheduled batch jobs on custom cloud VMs.

問題 #3
A data engineer has finished developing a new Declarative Automation Bundle (formerly Databricks Asset Bundle) for a streaming pipeline. They need to ensure the configuration is syntactically correct, push the code to the workspace, and finally trigger the pipeline to verify it runs as expected. Which sequence of Databricks CLI commands should the engineer use to perform these steps in the correct order?

A. databricks bundle init -> databricks bundle deploy -> databricks bundle run
B. databricks bundle validate -> databricks bundle sync -> databricks bundle execute
C. databricks bundle check -> databricks bundle upload -> databricks bundle start
D. databricks bundle validate -> databricks bundle deploy -> databricks bundle run

問題 #4
A data engineer needs to audit who made changes to a Delta table in the last 7 days. Which SQL statement returns the record of past operations, including timestamps, users, and operation types?

A. SHOW TBLPROPERTIES my_table
B. DESCRIBE HISTORY my_table
C. SELECT * FROM 'delta.my_table/_delta_log/'
D. DESCRIBE DETAIL my_table

問題 #5
What Databricks feature can be used to check the data sources and tables used in a workspace?

A. Use the lineage feature to visualize a graph that shows all dependencies, including where the table is used in notebooks, other tables, and reports.
B. Do not use the lineage feature as it only tracks activity from the last 3 months and will not provide full details on dependencies.
C. Use the lineage feature to visualize a graph that highlights where the table is used only in reports.
D. Use the lineage feature to visualize a graph that highlights where the table is used only in notebooks.

解説：

問題 #1
正解： D

問題 #2
正解： B

問題 #3
正解： D

問題 #4
正解： B

問題 #5
正解： A