Exam Databricks-Certified-Data-Engineer-Professional Success & Databricks-Certified-Data-Engineer-Professional Test Preparation

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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Section	Weight	Objectives
Data Modeling and Storage	20%	- File Formats - Data Modeling - Storage Optimization
Data Quality and Governance	12%	- Data Quality - Governance - Data Lineage
Data Processing	28%	- Structured Streaming - Data Transformation - ETL Pipelines - Spark SQL
Monitoring and Troubleshooting	16%	- Monitoring - Troubleshooting - Performance Optimization
Databricks Lakehouse Platform	24%	- Unity Catalog - Lakehouse Architecture - Delta Lake - Data Management

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q55-Q60):

NEW QUESTION # 55
What statement is true regarding the retention of job run history?

A. It is retained for 60 days, after which logs are archived
B. It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3
C. It is retained for 90 days or until the run-id is re-used through custom run configuration
D. It is retained until you export or delete job run logs
E. It is retained for 60 days, during which you can export notebook run results to HTML

Answer: E

NEW QUESTION # 56
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 jo to execute the pipeline once and hour on a dedicated interactive cluster.
C. Schedule a job to execute the pipeline once hour on a new job cluster.
D. Configure a job that executes every time new data lands in a given directory.

Answer: C

Explanation:
Scheduling a job to execute the data processing pipeline once an hour on a new job cluster is the most cost-effective solution given the scenario. Job clusters are ephemeral in nature; they are spun up just before the job execution and terminated upon completion, which means you only incur costs for the time the cluster is active. Since the total processing time is only 10 minutes, a new job cluster created for each hourly execution minimizes the running time and thus the cost, while also fulfilling the requirement for hourly data updates for the business reporting team's dashboards.

NEW QUESTION # 57
A data engineer needs to provide access to a group named manufacturing-team. The team needs privileges to create tables in the quality schema. Which set of SQL commands will grant a group named manufacturing-team to create tables in a schema named production with the parent catalog named manufacturing with the least privileges?

A. GRANT USE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
B. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE CATALOG ON CATALOG manufacturing TO manufacturing-team;
C. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
D. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;

Answer: C

Explanation:
To create a table within a schema, a principal must have CREATE TABLE on the schema, USE SCHEMA on that schema, and USE CATALOG on the parent catalog. This combination ensures the group has just enough privileges to create objects in that schema without excessive permissions like CREATE SCHEMA or CREATE CATALOG.

NEW QUESTION # 58
A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:
SELECT COUNT (*) FROM table
Which of the following describes how results are generated each time the dashboard is updated?

A. The total count of records is calculated from the Delta transaction logs
B. The total count of records is calculated from the parquet file metadata
C. The total count of records is calculated from the Hive metastore
D. The total count of rows will be returned from cached results unless REFRESH is run
E. The total count of rows is calculated by scanning all data files

Answer: A

Explanation:
Delta Lake maintains a transaction log that records details about every change made to a table.
When you execute a count operation on a Delta table, Delta Lake can use the information in the transaction log to calculate the total number of records without having to scan all the data files.
This is because the transaction log includes information about the number of records in each file, allowing for an efficient aggregation of these counts to get the total number of records in the table.

NEW QUESTION # 59
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. withWatermark("event_time", "10 minutes")
B. await("event_time + `10 minutes'")
C. slidingWindow("event_time", "10 minutes")
D. delayWrite("event_time", "10 minutes")
E. awaitArrival("event_time", "10 minutes")

Answer: A

Explanation:
This is because the question asks for incremental state information to be maintained for 10 minutes for late-arriving data. The withWatermark method is used to define the watermark for late data. The watermark is a timestamp column and a threshold that tells the system how long to wait for late data. In this case, the watermark is set to 10 minutes. The other options are incorrect because they are not valid methods or syntax for watermarking in Structured Streaming.

NEW QUESTION # 60
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