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

Section	Weight	Objectives
Topic 1: Data Sharing and Federation	5%	- Implement Lakehouse Federation - Manage cross-platform data access - Use Delta Sharing for secure data sharing
Topic 2: Data Modelling	6%	- Design Medallion Architecture - Optimize table design and partitioning - Implement dimensional and relational models
Topic 3: Debugging and Deploying	10%	- Implement CI/CD and DevOps practices - Troubleshoot and debug pipelines - Deploy using Asset Bundles, CLI, and APIs
Topic 4: Monitoring and Alerting	10%	- Track data lineage and metrics - Monitor pipeline performance and health - Set up alerts and notifications
Topic 5: Data Governance	7%	- Enforce data policies and standards - Manage data assets and metadata - Use Unity Catalog for governance
Topic 6: Cost & Performance Optimisation	13%	- Apply cost management best practices - Improve query and pipeline performance - Optimize compute and storage resources
Topic 7: Data Ingestion & Acquisition	7%	- Use Auto Loader and structured streaming - Ingest data from diverse sources - Handle incremental and batch data loads
Topic 8: Developing Code for Data Processing using Python and SQL	22%	- Implement complex data processing logic - Write efficient and maintainable code - Use Databricks-specific libraries and APIs
Topic 9: Data Transformation, Cleansing, and Quality	10%	- Enforce data quality standards - Apply data cleansing and validation rules - Implement schema evolution and management
Topic 10: Ensuring Data Security and Compliance	10%	- Secure data at rest and in transit - Ensure data privacy and compliance - Implement access control and permissions

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Databricks Certified Data Engineer Professional Exam 認定 Databricks-Certified-Data-Engineer-Professional 試験問題 (Q30-Q35):

質問 # 30
A data engineering team needs to implement a tagging system for their tables as part of an automated ETL process, and needs to apply tags programmatically to tables in Unity Catalog.
Which SQL command adds tags to a table programmatically?

A. APPLY TAGS ON table_name VALUES ('key1' = 'value1', 'key2' = 'value2');
B. COMMENT ON TABLE table_name TAGS ('key1' = 'value1', 'key2' = 'value2');
C. SET TAGS FOR table_name AS ('key1' = 'value1', 'key2' = 'value2');
D. ALTER TABLE table_name SET TAGS ('key1' = 'value1', 'key2' = 'value2');

正解：D

解説：
Unity Catalog supports programmatic tagging through the ALTER TABLE statement. Using SET TAGS allows tags to be added or updated directly on a table as part of automated ETL workflows, making it the correct and supported SQL command for managing table tags.

質問 # 31
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. Events are recorded once per minute per device.
Streaming DataFrame df has the following schema:
"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"
Code block:
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Choose the response that correctly fills in the blank within the code block to complete this task.

A. lag("event_time", "10 minutes").alias("time")
B. "event_time"
C. window("event_time", "5 minutes").alias("time")
D. to_interval("event_time", "5 minutes").alias("time")
E. window("event_time", "10 minutes").alias("time")

正解：C

解説：
This is the correct answer because the window function is used to group streaming data by time intervals. The window function takes two arguments: a time column and a window duration. The window duration specifies how long each window is, and must be a multiple of 1 second. In this case, the window duration is "5 minutes", which means each window will cover a non-overlapping five- minute interval. The window function also returns a struct column with two fields: start and end, which represent the start and end time of each window. The alias function is used to rename the struct column as "time".

質問 # 32
An upstream source writes Parquet data as hourly batches to directories named with the current date. A nightly batch job runs the following code to ingest all data from the previous day as indicated by the date variable:
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Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order.
If the upstream system is known to occasionally produce duplicate entries for a single order hours apart, which statement is correct?

A. Each write to the orders table will only contain unique records, but newly written records may have duplicates already present in the target table.
B. Each write to the orders table will only contain unique records, and only those records without duplicates in the target table will be written.
C. Each write to the orders table will only contain unique records; if existing records with the same key are present in the target table, the operation will tail.
D. Each write to the orders table will only contain unique records; if existing records with the same key are present in the target table, these records will be overwritten.
E. Each write to the orders table will run deduplication over the union of new and existing records, ensuring no duplicate records are present.

正解：A

解説：
This is the correct answer because the code uses the dropDuplicates method to remove any duplicate records within each batch of data before writing to the orders table. However, this method does not check for duplicates across different batches or in the target table, so it is possible that newly written records may have duplicates already present in the target table. To avoid this, a better approach would be to use Delta Lake and perform an upsert operation using mergeInto.

質問 # 33
The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).

Which statement describes what will happen when the above code is executed?

A. The connection to the external table will succeed; the string value of password will be printed in plain text.
B. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
C. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.
D. The connection to the external table will succeed; the string "redacted" will be printed.
E. The connection to the external table will fail; the string "redacted" will be printed.

正解：D

解説：
This is the correct answer because the code is using the dbutils.secrets.get method to retrieve the password from the secrets module and store it in a variable. The secrets module allows users to securely store and access sensitive information such as passwords, tokens, or API keys. The connection to the external table will succeed because the password variable will contain the actual password value. However, when printing the password variable, the string "redacted" will be displayed instead of the plain text password, as a security measure to prevent exposing sensitive information in notebooks.

質問 # 34
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 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;
B. 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;
C. 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;
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;

正解：B

解説：
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.

質問 # 35
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