Databricks-Certified-Data-Engineer-Professional試験無料問題集（250題）「Databricks Certified Data Engineer Professional 認定」

出題：1

A data engineer is masking a column containing email addresses. The goal is to produce output strings of identical length for all rows, while generating different outputs for different email values.
Which SQL function should be used to achieve this?

A. sha2(email, 0)

B. mask(email, '?')

C. hash(email)

D. sha1(email)

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

When a new Databricks project starts, the central IP team provisions the required infrastructure using Terraform and a Service Principal. This includes creating a Databricks workspace, a Unity Catalog linked to an External Location, and a Databricks group containing all project team members. Project teams must store all assets - e.g., tables and volumes, as Managed assets in Unity Catalog. This model hides infrastructure complexity while giving teams autonomy within their catalog. They can create and manage schemas, tables, volumes, and related objects but cannot rename, delete, or change catalog permissions, those remain under IT's control. Which rights should the project group be granted to enable this model?

A. The group needs to have USE CATALOG and USE SCHEMA on the catalog.

B. The group needs to have ALL PRIVILEGES and the MANAGE on the catalog.

C. The group needs to have ALL PRIVILEGES on the catalog.

D. The group should be made OWNER of the catalog.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

A new data engineer notices that a critical field was omitted from an application that writes its Kafka source to Delta Lake. This happened even though the critical field was in the Kafka source.
That field was further missing from data written to dependent, long-term storage. The retention threshold on the Kafka service is seven days. The pipeline has been in production for three months.
Which describes how Delta Lake can help to avoid data loss of this nature in the future?

A. Ingestine all raw data and metadata from Kafka to a bronze Delta table creates a permanent, replayable history of the data state.

B. Data can never be permanently dropped or deleted from Delta Lake, so data loss is not possible under any circumstance.

C. Delta Lake schema evolution can retroactively calculate the correct value for newly added fields, as long as the data was in the original source.

D. The Delta log and Structured Streaming checkpoints record the full history of the Kafka producer.

E. Delta Lake automatically checks that all fields present in the source data are included in the ingestion layer.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

Which statement regarding stream-static joins and static Delta tables is correct?

A. Each microbatch of a stream-static join will use the most recent version of the static Delta table as of each microbatch.

B. The checkpoint directory will be used to track updates to the static Delta table.

C. Stream-static joins cannot use static Delta tables because of consistency issues.

D. Each microbatch of a stream-static join will use the most recent version of the static Delta table as of the job's initialization.

E. The checkpoint directory will be used to track state information for the unique keys present in the join.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

A data engineer and a platform engineer are working together to automate their system tasks. A script needs to be executed outside of Databricks only if a particular daily Databricks job finishes successfully for the day. Databricks CLI command was used to check the last execution of the job. What are the required command options for that task?

A. databricks jobs list-runs --job-id JOB_ID --start-time-from TODAY_MIDNIGHT_EPOCH_MS -- active-only

B. databricks jobs list-runs --job-id JOB_ID --start-time-to TODAY_MIDNIGHT_EPOCH_MS -- completed-only

C. databricks jobs list-runs --job-id JOB_ID --start-time-from TODAY_MIDNIGHT_EPOCH_MS -- completed-only

D. databricks jobs list-runs --job-id JOB_ID --start-time-to TODAY_MIDNIGHT_EPOCH_MS --active- only

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：6

The data governance team has instituted a requirement that all tables containing Personal Identifiable Information (PH) must be clearly annotated. This includes adding column comments, table comments, and setting the custom table property "contains_pii" = true.
The following SQL DDL statement is executed to create a new table:

Which command allows manual confirmation that these three requirements have been met?

A. DESCRIBE EXTENDED dev.pii test

B. SHOW TBLPROPERTIES dev.pii test

C. DESCRIBE DETAIL dev.pii test

D. DESCRIBE HISTORY dev.pii test

E. SHOW TABLES dev

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：7

A data engineering team uses Databricks Lakehouse Monitoring to track the percent_null metric for a critical column in their Delta table.
The profile metrics table (prod_catalog.prod_schema.customer_data_profile_metrics) stores hourly percent_null values.
The team wants to:
Trigger an alert when the daily average of percent_null exceeds 5% for
three consecutive days.
Ensure that notifications are not spammed during sustained issues.

A. SELECT SUM(CASE WHEN percent_null > 5 THEN 1 ELSE 0 END) AS violation_days FROM prod_catalog.prod_schema.customer_data_profile_metrics WHERE window.end >= CURRENT_TIMESTAMP - INTERVAL '3' DAY Alert Condition: violation_days >= 3 Notification Frequency: Just once

B. WITH daily_avg AS (
SELECT DATE_TRUNC('DAY', window.end) AS day,
AVG(percent_null) AS avg_null
FROM prod_catalog.prod_schema.customer_data_profile_metrics
GROUP BY DATE_TRUNC('DAY', window.end)
)
SELECT day, avg_null
FROM daily_avg
ORDER BY day DESC
LIMIT 3
Alert Condition: ALL avg_null > 5 for the latest 3 rows
Notification Frequency: Just once

C. SELECT AVG(percent_null) AS daily_avg
FROM prod_catalog.prod_schema.customer_data_profile_metrics
WHERE window.end >= CURRENT_TIMESTAMP - INTERVAL '3' DAY
Alert Condition: daily_avg > 5
Notification Frequency: Each time alert is evaluated

D. SELECT percent_null
FROM prod_catalog.prod_schema.customer_data_profile_metrics
WHERE window.end >= CURRENT_TIMESTAMP - INTERVAL '1' DAY
Alert Condition: percent_null > 5
Notification Frequency: At most every 24 hours

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：8

What is the first line of a Databricks Python notebook when viewed in a text editor?

A. %python

B. # MAGIC %python

C. // Databricks notebook source

D. # Databricks notebook source

E. -- Databricks notebook source

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：9

A member of the data engineering team has submitted a short notebook that they wish to schedule as part of a larger data pipeline. Assume that the commands provided below produce the logically correct results when run as presented.

Which command should be removed from the notebook before scheduling it as a job?

A. Cmd 3

B. Cmd 5

C. Cmd 6

D. Cmd 4

E. Cmd 2

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：10

Which statement describes integration testing?

A. Validates interactions between subsystems of your application

B. Requires an automated testing framework

C. Requires manual intervention

D. Validates an application use case

E. Validates behavior of individual elements of your application

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

Databricks-Certified-Data-Engineer-Professional試験無料問題集「Databricks Certified Data Engineer Professional 認定」