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最新的 Databricks Certification Databricks-Certified-Data-Engineer-Professional 免費考試真題:

1. A Data engineer wants to run unit's tests using common Python testing frameworks on python functions defined across several Databricks notebooks currently used in production. How can the data engineer run unit tests against function that work with data in production?

A) Run unit tests against non-production data that closely mirrors production
B) Define units test and functions within the same notebook
C) Define and import unit test functions from a separate Databricks notebook
D) Define and unit test functions using Files in Repos

2. A junior data engineer is working to implement logic for a Lakehouse table named silver_device_recordings. The source data contains 100 unique fields in a highly nested JSON Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from structure.
The silver_device_recordings table will be used downstream for highly selective joins on a number of fields, and will also be leveraged by the machine learning team to filter on a handful of relevant fields, in total, 15 fields have been identified that will often be used for filter and join logic.
The data engineer is trying to determine the best approach for dealing with these nested fields before declaring the table schema.
Which of the following accurately presents information about Delta Lake and Databricks that may Impact their decision-making process?

A) By default Delta Lake collects statistics on the first 32 columns in a table; these statistics are leveraged for data skipping when executing selective queries.
B) Because Delta Lake uses Parquet for data storage, Dremel encoding information for nesting can be directly referenced by the Delta transaction log.
C) Tungsten encoding used by Databricks is optimized for storing string data: newly-added native support for querying JSON strings means that string types are always most efficient.
D) Schema inference and evolution on Databricks ensure that inferred types will always accurately match the data types used by downstream systems.

3. A junior data engineer has been asked to develop a streaming data pipeline with a grouped aggregation using DataFrame df. The pipeline needs to calculate the average humidity and average temperature for each non-overlapping five-minute interval. Incremental state information should be maintained for 10 minutes for late-arriving data.
Streaming DataFrame df has the following schema:
"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"
Code block:

Choose the response that correctly fills in the blank within the code block to complete this task.

A) slidingWindow("event_time", "10 minutes")
B) await("event_time + `10 minutes'")
C) withWatermark("event_time", "10 minutes")
D) delayWrite("event_time", "10 minutes")
E) awaitArrival("event_time", "10 minutes")

4. A Databricks job has been configured with 3 tasks, each of which is a Databricks notebook. Task A does not depend on other tasks. Tasks B and C run in parallel, with each having a serial dependency on Task A.
If task A fails during a scheduled run, which statement describes the results of this run?

A) Tasks B and C will attempt to run as configured; any changes made in task A will be rolled back due to task failure.
B) Unless all tasks complete successfully, no changes will be committed to the Lakehouse; because task A failed, all commits will be rolled back automatically.
C) Tasks B and C will be skipped; task A will not commit any changes because of stage failure.
D) Because all tasks are managed as a dependency graph, no changes will be committed to the Lakehouse until all tasks have successfully been completed.
E) Tasks B and C will be skipped; some logic expressed in task A may have been committed before task failure.

5. The business reporting tem requires that data for their dashboards be updated every hour. The total processing time for the pipeline that extracts transforms and load the data for their pipeline runs in 10 minutes.
Assuming normal operating conditions, which configuration will meet their service-level agreement requirements with the lowest cost?

A) Schedule a Structured Streaming job with a trigger interval of 60 minutes.
B) Schedule a job to execute the pipeline once hour on a new job cluster.
C) Schedule a jo to execute the pipeline once and hour on a dedicated interactive cluster.
D) Configure a job that executes every time new data lands in a given directory.

問題與答案：