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Databricks Certified Data Engineer Professional Exam Reliable Exam Papers & Databricks-Certified-Data-Engineer-Professional Study Pdf Vce & Databricks Certified Data Engineer Professional Exam Online Practice Test

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q123-Q128):

NEW QUESTION # 123
A data engineer is troubleshooting a slow-running Delta Lake query on Databricks SQL involves complex joins and large datasets. They need to identify whether the root cause is related to poor data skipping, inefficient join strategies, or excessive data shuffling. Which approach should identify the specific bottlenecks using native Databricks tools?

A. Check the query's execution time in the Jobs UI and correlate it with cluster resource utilization metrics.
B. Analyze the Top Operators panel in the Query Profile to identify high-cost operations like BroadcastNestedLoopJoin
C. Use the LIMIT clause to run a subset of the query and compare execution times with the full dataset.
D. Enable the EXPLAIN command to review the parsed logical plan and manually estimate shuffle sizes.

Answer: B

Explanation:
The Query Profile's Top Operators panel surfaces the most expensive operators in the query execution, making it possible to directly identify bottlenecks such as inefficient join strategies, poor data skipping, or excessive shuffling. This native visualization highlights where time and resources are spent, enabling precise root-cause analysis for slow-running queries.

NEW QUESTION # 124
A faulty IoT sensor in a factory reports a temperature of -500, causing the LDP pipeline to fail the expectation, which only allows values between -100 and 200 degrees Celsius. The data engineer would like to further analyze the faulty data to better understand the reason behind this. How should the data engineer resolve the faulty data while ensuring data quality standards are maintained?

A. Fix the pipeline code and implement a quarantine logic to isolate the faulty data before re-running the pipeline.
B. Ignore the error and simply re-run the pipeline, as Databricks will automatically skip the problematic record on the next run.
C. Remove all expectations form the pipeline to prevent any future failures, regardless of data quality.
D. Change the expectation action from fail to warn so that invalid records are included in the output and the pipeline does not fail.

Answer: A

Explanation:
Implementing quarantine logic allows invalid records to be isolated for further analysis while keeping them out of trusted datasets. Fixing the pipeline and re-running it ensures the expectation continues to enforce data quality standards, prevents future failures, and enables root-cause analysis of the faulty sensor data without compromising downstream consumers.

NEW QUESTION # 125
What is the first line of a Databricks Python notebook when viewed in a text editor?

A. // Databricks notebook source
B. -- Databricks notebook source
C. %python
D. # Databricks notebook source
E. # MAGIC %python

Answer: D

Explanation:
https://docs.databricks.com/en/notebooks/notebook-export-import.html#import-a-file-and-convert- it-to-a-notebook

NEW QUESTION # 126
All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion.
However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?

A. Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
B. Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.
C. Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
D. Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.
E. All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.

Answer: D

Explanation:
By default partitionning by a column will create a separate folder for each subset data linked to the partition.

NEW QUESTION # 127
The view updates represents an incremental batch of all newly ingested data to be inserted or updated in the customers table.
The following logic is used to process these records.
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

Which statement describes this implementation?

A. The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
B. The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.
C. The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.
D. The customers table is implemented as a Type 3 table; old values are maintained as a new column alongside the current value.
E. The customers table is implemented as a Type 2 table; old values are maintained but marked as no longer current and new values are inserted.

Answer: E

NEW QUESTION # 128
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