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Databricks Databricks-Certified-Data-Engineer-Professional 考試大綱主題:

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

1. A company processes semi-structured JSON files from an external source using Auto Loader in a classic Databricks job. Occasionally, records arrive with null critical fields, invalid types, or unexpected nested schema variations. The engineer must ensure that malformed or non- conforming records are not dropped silently and are captured in a separate quarantine table. The pipeline should continue processing good records into the Bronze layer without failing the job, and the approach must support both batch and streaming ingestion.
The data engineer needs to build a robust ingestion pattern that automatically routes bad records to a quarantine Delta table, while still ingesting good records into the Bronze layer for further processing.
Which approach fulfills the quarantine mechanism in this ingestion architecture?

A) Create a notebook job with inferSchema=True, write a streaming query with .foreachBatch() and catch exceptions using try/except to redirect failed batches to quarantine.
B) Use Lakeflow Spark Declarative Pipelines with a SQL pipeline; configure it to drop rows with nulls using where critical_fields is not null, and rely on audit logs for malformed data.
C) Use Auto Loader with LDP and implement an EXPECT () constraint with a record audit logic to route bad records.
D) Use Auto Loader with failFast mode to set to false, and enable schema evolution; invalid records will be silently ignored during ingestion.

2. Although the Databricks Utilities Secrets module provides tools to store sensitive credentials and avoid accidentally displaying them in plain text users should still be careful with which credentials are stored here and which users have access to using these secrets.
Which statement describes a limitation of Databricks Secrets?

A) Because the SHA256 hash is used to obfuscate stored secrets, reversing this hash will display the value in plain text.
B) Account administrators can see all secrets in plain text by logging on to the Databricks Accounts console.
C) Iterating through a stored secret and printing each character will display secret contents in plain text.
D) The Databricks REST API can be used to list secrets in plain text if the personal access token has proper credentials.
E) Secrets are stored in an administrators-only table within the Hive Metastore; database administrators have permission to query this table by default.

3. Which approach demonstrates a modular and testable way to use DataFrame transform for ETL code in PySpark?

A)

B)

C)

D)

4. The data architect has decided that once data has been ingested from external sources into the Databricks Lakehouse, table access controls will be leveraged to manage permissions for all production tables and views.
The following logic was executed to grant privileges for interactive queries on a production database to the core engineering group.
GRANT USAGE ON DATABASE prod TO eng;
GRANT SELECT ON DATABASE prod TO eng;
Assuming these are the only privileges that have been granted to the eng group and that these users are not workspace administrators, which statement describes their privileges?

A) Group members are able to query and modify all tables and views in the prod database, but cannot create new tables or views.
B) Group members are able to list all tables in the prod database but are not able to see the results of any queries on those tables.
C) Group members are able to create, query, and modify all tables and views in the prod database, but cannot define custom functions.
D) Group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database.
E) Group members have full permissions on the prod database and can also assign permissions to other users or groups.

5. Which statement describes Delta Lake Auto Compaction?

A) Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.
B) An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 1 GB.
C) An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 128 MB.
D) Before a Jobs cluster terminates, optimize is executed on all tables modified during the most recent job.
E) Data is queued in a messaging bus instead of committing data directly to memory; all data is committed from the messaging bus in one batch once the job is complete.

問題與答案：