Databricks-Certified-Professional-Data-Engineer更新 & Databricks-Certified-Professional-Data-Engineer考試指南

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成為Databricks認證的數據工程師專業人員，候選人必須通過一項涵蓋數據工程相關廣泛主題的嚴格考試。該考試旨在測試候選人使用Databricks工具和技術設計、建立和維護數據流水線的能力。它還測試了候選人對數據建模、數據倉儲和數據集成的理解。

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認證考試涵蓋廣泛的主題，包括使用Spark進行數據處理，使用Delta Lake進行數據工程，使用MLflow進行機器學習以及使用AWS和Azure的雲基礎架構等。試驗旨在測試考生對這些主題的了解和他們在現實情況下應用這些知識的能力。試驗還旨在測試考生設計和實施可擴展數據管線和機器學習工作流程的能力，並使用Databricks。

最新的 Databricks Certification Databricks-Certified-Professional-Data-Engineer 免費考試真題 (Q147-Q152):

問題 #147
An hourly batch job is configured to ingest data files from a cloud object storage container where each batch represent all records produced by the source system in a given hour. The batch job to process these records into the Lakehouse is sufficiently delayed to ensure no late-arriving data is missed. Theuser_idfield represents a unique key for the data, which has the following schema:
user_id BIGINT, username STRING, user_utc STRING, user_region STRING, last_login BIGINT, auto_pay BOOLEAN, last_updated BIGINT New records are all ingested into a table namedaccount_historywhich maintains a full record of all data in the same schema as the source. The next table in the system is namedaccount_currentand is implemented as a Type 1 table representing the most recent value for each uniqueuser_id.
Assuming there are millions of user accounts and tens of thousands of records processed hourly, which implementation can be used to efficiently update the describedaccount_currenttable as part of each hourly batch job?

A. Filter records in account history using the last updated field and the most recent hour processed, making sure to deduplicate on username; write a merge statement to update or insert the most recent value for each username.
B. Use Delta Lake version history to get the difference between the latest version of account history and one version prior, then write these records to account current.
C. Overwrite the account current table with each batch using the results of a query against the account history table grouping by user id and filtering for the max value of last updated.
D. Filter records in account history using the last updated field and the most recent hour processed, as well as the max last iogin by user id write a merge statement to update or insert the most recent value for each user id.
E. Use Auto Loader to subscribe to new files in the account history directory; configure a Structured Streaminq trigger once job to batch update newly detected files into the account current table.

答案：D

解題說明：
This is the correct answer because it efficiently updates the account current table with only the most recent value for each user id. The code filters records in account history using the last updated field and the most recent hour processed, which means it will only process the latest batch of data. It also filters by the max last login by user id, which means it will only keep the most recent record for each user id within that batch. Then, it writes a merge statement to update or insert the most recent value for each user id into account current, which means it will perform an upsert operation based on the user id column. Verified References:
[Databricks Certified Data Engineer Professional], under "Delta Lake" section; Databricks Documentation, under "Upsert into a table using merge" section.

問題 #148
You are working to set up two notebooks to run on a schedule, the second notebook is dependent on the first notebook but both notebooks need different types of compute to run in an optimal fashion, what is the best way to set up these notebooks as jobs?

A. Use a very large cluster to run both the tasks in a single job
B. A Job can only use single cluster, setup job for each notebook and use job dependency to link both jobs together
C. Each task can use different cluster, add these two notebooks as two tasks in a single job with linear dependency and modify the cluster as needed for each of the tasks
D. Use DELTA LIVE PIPELINES instead of notebook tasks
E. Use a single job to setup both notebooks as individual tasks, but use the cluster API to setup the second cluster before the start of second task

答案：C

解題說明：
Explanation
Tasks in Jobs support different clusters for each task in the same job.

問題 #149
A table is registered with the following code:

Bothusersandordersare Delta Lake tables. Which statement describes the results of queryingrecent_orders?

A. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
B. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
C. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
D. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
E. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.

答案：A

問題 #150
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 have full permissions on the prod database and can also assign permissions to other users or groups.
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 list all tables in the prod database but are not able to see the results of any queries on those tables.
E. Group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database.

答案：E

解題說明：
The GRANT USAGE ON DATABASE prod TO eng command grants the eng group the permission to use the prod database, which means they can list and access the tables and views in the database. The GRANT SELECT ON DATABASE prod TO eng command grants the eng group the permission to select data from the tables and views in the prod database, which means they can query the data using SQL or DataFrame API.
However, these commands do not grant the eng group any other permissions, such as creating, modifying, or deleting tables and views, or defining custom functions. Therefore, the eng group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database. References:
* Grant privileges on a database:
https://docs.databricks.com/en/security/auth-authz/table-acls/grant-privileges-database.html
* Privileges you can grant on Hive metastore objects:
https://docs.databricks.com/en/security/auth-authz/table-acls/privileges.html

問題 #151
The downstream consumers of a Delta Lake table have been complaining about data quality issues impacting performance in their applications. Specifically, they have complained that invalid latitude and longitude values in the activity_details table have been breaking their ability to use other geolocation processes.
A junior engineer has written the following code to add CHECK constraints to the Delta Lake table:

A senior engineer has confirmed the above logic is correct and the valid ranges for latitude and longitude are provided, but the code fails when executed.
Which statement explains the cause of this failure?

A. The activity details table already exists; CHECK constraints can only be added during initial table creation.
B. Because another team uses this table to support a frequently running application, two-phase locking is preventing the operation from committing.
C. The current table schema does not contain the field valid coordinates; schema evolution will need to be enabled before altering the table to add a constraint.
D. The activity details table already contains records that violate the constraints; all existing data must pass CHECK constraints in order to add them to an existing table.
E. The activity details table already contains records; CHECK constraints can only be added prior to inserting values into a table.

答案：D

解題說明：
The failure is that the code to add CHECK constraints to the Delta Lake table fails when executed. The code uses ALTER TABLE ADD CONSTRAINT commands to add two CHECK constraints to a table named activity_details. The first constraint checks if the latitude value is between -90 and 90, and the second constraint checks if the longitude value is between -180 and 180. The cause of this failure is that the activity_details table already contains records that violate these constraints, meaning that they have invalid latitude or longitude values outside of these ranges. When adding CHECK constraints to an existing table, Delta Lake verifies that all existing data satisfies the constraints before adding them to the table. If any record violates the constraints, Delta Lake throws an exception and aborts the operation. Verified Reference: [Databricks Certified Data Engineer Professional], under "Delta Lake" section; Databricks Documentation, under "Add a CHECK constraint to an existing table" section.
https://docs.databricks.com/en/sql/language-manual/sql-ref-syntax-ddl-alter-table.html#add-constraint

問題 #152
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Databricks-Certified-Professional-Data-Engineer考試指南: https://tw.fast2test.com/Databricks-Certified-Professional-Data-Engineer-premium-file.html

此外，這些Fast2test Databricks-Certified-Professional-Data-Engineer考試題庫的部分內容現在是免費的：https://drive.google.com/open?id=1ofxk3Z4E0VxJ2gM7qBGtNlFOrAgt_iXh