Databricks-Certified-Data-Engineer-Associate模擬トレーリング & Databricks-Certified-Data-Engineer-Associateトレーニング費用

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GAQM Databricks-Certified-Data-Engineer-Associate（Databricks認定データエンジニアアソシエイト）試験は、Databricksプラットフォームを使用したデータエンジニアリングのスキルをマスターすることを目的とした認定試験です。この認定試験は、グローバルに認められ、Databricksで作業するために必要な知識とスキルを持っていることを証明するため、雇用主から高く評価されています。

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Databricks Certified Data Engineer Associate認定は、業界で高く評価され、多くの雇用主にとってデータエンジニアリングの卓越性の証として認められています。認定試験は挑戦的に設計されており、候補者はDatabricksおよびそのさまざまなコンポーネントについて深い理解を持っている必要があります。試験に合格した候補者は、潜在的な雇用主に自分のスキルと知識を証明し、求職市場で競争力を持つことができます。

Databricks Certified Data Engineer Associate Exam 認定 Databricks-Certified-Data-Engineer-Associate 試験問題 (Q158-Q163):

質問 # 158
An organization has implemented a data pipeline in Databricks and needs to ensure it can scale automatically based on varying workloads without manual cluster management. The goal is to meet the company's Service Level Agreements (SLAs), which require high availability and minimal downtime, while Databricks automatically handles resource allocation and optimization.
Which approach fulfills these requirements?

A. Use interactive clusters in Databricks, adjusting cluster sizes manually based on workload demands
B. Deploy job clusters with fixed configurations, dedicated to specific tasks, without automatic scaling
C. Use spot instances to allocate resources dynamically while minimizing costs, with potential interruptions
D. Use Serverless compute in Databricks to automatically scale and provision resources with minimal manual intervention

正解：D

解説：
Databricks documentation recommends serverless compute as the simplest and most reliable compute option when the workload is supported. Serverless compute is designed to automatically provision resources, scale with demand, reduce infrastructure management, and apply platform optimizations without requiring users to configure clusters manually. This directly supports the requirement for automatic scaling, reduced operational overhead, and better alignment with strict SLAs. Databricks also states that serverless compute is always available and scales according to workload, making it a strong fit for organizations seeking high availability and minimal downtime. Fixed-configuration job clusters in option B still require manual sizing decisions and do not meet the "no manual cluster management" requirement. Spot instances in option C may reduce costs but can be interrupted, which makes them a poor choice when reliability is a top requirement. Interactive clusters in option D are intended more for development and exploration and still need manual management. Based on Databricks guidance, serverless compute is the correct choice.
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質問 # 159
A departing platform owner currently holds ownership of multiple catalogs and controls storage credentials and external locations. The data engineer wants to ensure continuity: transfer catalog ownership to the platform team group, delegate ongoing privilege management, and retain the ability to receive and share data via Delta Sharing.
Which role must be in place to perform these actions across the metastore?

A. Workspace Admin, because workspace admins can transfer ownership of any Unity Catalog object.
B. Catalog Owner, because catalog owners can transfer any object in any catalog in the metastore.
C. Account Admin, because account admins can only create metastores but cannot change ownership of catalogs.
D. Metastore Admin, because metastore admins can transfer ownership and manage privileges across all metastore objects, including shares and recipients.

正解：D

質問 # 160
A data engineer ingests semi-structured JSON logs into a Delta table using Auto Loader with schema evolution enabled. A new string field userAgent appears in the JSON. What happens to the new userAgent field?

A. The new userAgent field is added as a new nullable column in the Delta table, populated for new data.
B. The new userAgent field is silently ignored, and its data is dropped for all new files.
C. All existing data is backfilled with a default value for userAgent and made non-nullable.
D. Ingestion fails with a schema-mismatch error until the table is altered.

正解：A

解説：
With schema evolution enabled, Auto Loader adds userAgent as a nullable column. Existing rows have NULL, while new records populate the field when present.

質問 # 161
A data analyst has a series of queries in a SQL program. The data analyst wants this program to run every day. They only want the final query in the program to run on Sundays. They ask for help from the data engineering team to complete this task.
Which of the following approaches could be used by the data engineering team to complete this task?

A. They could submit a feature request with Databricks to add this functionality.
B. They could only run the entire program on Sundays.
C. They could wrap the queries using PySpark and use Python's control flow system to determine when to run the final query.
D. They could automatically restrict access to the source table in the final query so that it is only accessible on Sundays.
E. They could redesign the data model to separate the data used in the final query into a new table.

正解：C

解説：
This approach would allow the data engineering team to use the existing SQL program and add some logic to control the execution of the final query based on the day of the week. They could use the datetime module in Python to get the current date and check if it is a Sunday. If so, they could run the final query, otherwise they could skip it. This way, they could schedule the program to run every day without changing the data model or the source table. References: PySpark SQL Module, Python datetime Module, Databricks Jobs

質問 # 162
A data architect has determined that a table of the following format is necessary:

Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above format regardless of whether a table already exists with this name?

A. Option B
B. Option A
C. Option D
D. Option E
E. Option C

正解：D

解説：
References: Create a table using SQL | Databricks on AWS, Create a table using SQL - Azure Databricks, Delta Lake Quickstart - Azure Databricks

質問 # 163
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