Databricks Databricks-Certified-Professional-Data-Engineer関連復習問題集、Databricks-Certified-Professional-Data-Engineer英語版

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Databricksは、さまざまな業界で広く使用されている強力なデータエンジニアリングおよび機械学習プラットフォームです。専門家がDatabricksと協力するために必要なスキルと専門知識を確保するために、同社は認証プログラムを提供しています。提供されている認定の1つは、DataBricks Databricks認定のプロフェッショナルData-Engineer試験としても知られるDatabricks Certified Professional Data Engineer Examです。

>> Databricks Databricks-Certified-Professional-Data-Engineer関連復習問題集 <<

Databricks-Certified-Professional-Data-Engineer英語版、Databricks-Certified-Professional-Data-Engineerトレーニング

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Databricks認定プロフェッショナルデータエンジニア試験は、Databricksを使用してデータエンジニアリングソリューションを構築、展開、および維持する専門知識を証明したいデータ専門家向けの認定プログラムです。この試験では、データエンジニアリングに関連する広範なトピックをカバーし、Databricksデータエンジニアリングの概念と技術に対する徹底的な理解が必要です。試験は難しく、候補者はDatabricksを使用して特定のタスクを実行する能力を証明する必要があります。

Databricks Certified Professional Data Engineer Exam 認定 Databricks-Certified-Professional-Data-Engineer 試験問題 (Q65-Q70):

質問 # 65
A Delta Lake table was created with the below query:

Consider the following query:
DROP TABLE prod.sales_by_store -
If this statement is executed by a workspace admin, which result will occur?

A. The table will be removed from the catalog and the data will be deleted.
B. An error will occur because Delta Lake prevents the deletion of production data.
C. Nothing will occur until a COMMIT command is executed.
D. The table will be removed from the catalog but the data will remain in storage.
E. Data will be marked as deleted but still recoverable with Time Travel.

正解：A

解説：
When a table is dropped in Delta Lake, the table is removed from the catalog and the data is deleted. This is because Delta Lake is a transactional storage layer that provides ACID guarantees. When a table is dropped, the transaction log is updated to reflect the deletion of the table and the data is deleted from the underlying storage. References:
* https://docs.databricks.com/delta/quick-start.html#drop-a-table
* https://docs.databricks.com/delta/delta-batch.html#drop-table

質問 # 66
Data science team members are using a single cluster to perform data analysis, although cluster size was chosen to handle multiple users and auto-scaling was enabled, the team realized queries are still running slow, what would be the suggested fix for this?

A. Disable the auto-scaling feature
B. Increase the size of the driver node
C. Use High concurrency mode instead of the standard mode
D. Setup multiple clusters so each team member has their own cluster

正解：C

解説：
Explanation
The answer is Use High concurrency mode instead of the standard mode,
https://docs.databricks.com/clusters/cluster-config-best-practices.html#cluster-mode High Concurrency clusters are ideal for groups of users who need to share resources or run ad-hoc jobs.
Databricks recommends enabling autoscaling for High Concurrency clusters.

質問 # 67
Which of the following type of tasks cannot setup through a job?

A. DELTA LIVE PIPELINE
B. Spark Submit
C. Python
D. Notebook
E. Databricks SQL Dashboard refresh

正解：E

質問 # 68
You are noticing job cluster is taking 6 to 8 mins to start which is delaying your job to finish on time, what steps you can take to reduce the amount of time cluster startup time

A. Use SQL endpoints to reduce the startup time
B. Use All purpose cluster instead to reduce cluster start up time
C. Use cluster pools to reduce the startup time of the jobs
D. Setup a second job ahead of first job to start the cluster, so the cluster is ready with re-sources when the job starts
E. Reduce the size of the cluster, smaller the cluster size shorter it takes to start the clus-ter

正解：C

解説：
Explanation
The answer is, Use cluster pools to reduce the startup time of the jobs.
Cluster pools allow us to reserve VM's ahead of time, when a new job cluster is created VM are grabbed from the pool. Note: when the VM's are waiting to be used by the cluster only cost incurred is Azure. Databricks run time cost is only billed once VM is allocated to a cluster.
Here is a demo of how to setup and follow some best practices,
https://www.youtube.com/watch?v=FVtITxOabxg&ab_channel=DatabricksAcademy

質問 # 69
Delete records from the transactions Delta table where transactionDate is greater than current timestamp?

A. DELETE FROM transactions where transactionDate > current_timestamp() KEEP_HISTORY
B. DELET FROM transactions where transactionDate GE current_timestamp()
C. DELETE FROM transactions FORMAT DELTA where transactionDate > cur-renct_timestmap()
D. DELETE FROM transactions if transctionDate > current_timestamp()
E. DELETE FROM transactions where transactionDate > current_timestamp()

正解：E

質問 # 70
......

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