Databricks Databricks-Certified-Data-Engineer-Associate日本語 Exam Syllabus Topics:

Topic	Details
Topic 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.
Topic 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.
Topic 3	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.
Topic 4	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.
Topic 5	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.

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

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Databricks Certified Data Engineer Associate Exam (Databricks-Certified-Data-Engineer-Associate日本語版) Sample Questions:

Question #1
オートローダーのストリームは、受信するJSONファイルに新しい列が出現すると失敗します。チームは、ストリームが永続的に失敗するのではなく、必要に応じて再起動しながら、新しい列を自動的に追加するようにしたいと考えています。
どの cloudFiles.schemaEvolutionMode 設定を使用すべきですか？

A. addNewColumns
B. failOnNewColumns
C. なし
D. レスキュー

Question #2
データエンジニアリングチームは、ノートブックのバージョン管理を行い、プルリクエストを通じて変更内容をレビューし、同じコードを開発環境、ステージング環境、本番環境にデプロイする必要があります。
このワークフローをサポートするDatabricksの機能はどれですか？

A. ノートブックの改訂履歴を有効にし、必要に応じてスナップショットを復元する
B. ノートブックのソースファイルをDBFS/FileStoreに保存し、手動でコピーする
C. ノートブックをDBCアーカイブとしてエクスポートし、ワークスペース間でメールで送信する
D. リモートGitプロバイダーと統合されたDatabricks Gitフォルダー(リポジトリ)

Question #3
開発者がDatabricks Connectを設定し、ローカルでPySparkコードの実行を開始しました。すると、データフレームの操作はリモートクラスター上で実行されるものの、.show()などのアクションの結果はローカルコンソールに直接表示されることに気づきました。この動作は、Databricks Connectの使用方法について何を示しているでしょうか？

A. ローカルクライアントからリモートクラスタへのSparkコマンドのプロキシとして機能します。
B. クラスターからの結果の手動同期が必要です
C. 開発者のマシン上にクラスタ環境全体をミラーリングします
D. Sparkの計算処理はすべてローカルで実行され、リモートファイルの読み取りのみを行います。

Question #4
次のコマンドのうち、データベース customer360 の場所を返すものはどれですか?

A. データベース customer360 の説明を記述します。
B. データベース customer360 を削除します。
C. ALTER DATABASE customer360 SET DBPROPERTIES ('location' = '/user'};
D. 場所を説明します customer360;
E. データベース customer360 を使用します。

Question #5
ワークスペースで使用されているデータソースとテーブルを確認するには、Databricksのどの機能を使用できますか？

A. データオブジェクト間の依存関係を視覚化する代わりに、監査ログ機能を使用して、誰がテーブルを照会または変更したかなどのユーザーアクティビティを確認します。
B. 系統機能を使用して、ノートブック内でのみテーブルが使用されている箇所を強調表示するグラフを視覚化します。
C. 系統機能を使用して、レポートでのみテーブルが使用されている箇所を強調表示するグラフを視覚化します。
D. リネージ機能を使用して、ノートブック、他のテーブル、レポートでテーブルが使用されている場所など、すべての依存関係を示すグラフを視覚化します。

Solutions:

Question #1
Correct Answer: A

Question #2
Correct Answer: D

Question #3
Correct Answer: A

Question #4
Correct Answer: A

Question #5
Correct Answer: D

Databricks Databricks-Certified-Data-Engineer-Associate日本語

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