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Databricks Certified Professional Data Engineer Exam Sample Questions (Q68-Q73):

NEW QUESTION # 68
The data architect has mandated that all tables in the Lakehouse should be configured as external Delta Lake tables.
Which approach will ensure that this requirement is met?

A. Whenever a table is being created, make sure that the location keyword is used.
B. When the workspace is being configured, make sure that external cloud object storage has been mounted.
C. When configuring an external data warehouse for all table storage. leverage Databricks for all ELT.
D. When tables are created, make sure that the external keyword is used in the create table statement.
E. Whenever a database is being created, make sure that the location keyword is used

Answer: A

Explanation:
This is the correct answer because it ensures that this requirement is met. The requirement is that all tables in the Lakehouse should be configured as external Delta Lake tables. An external table is a table that is stored outside of the default warehouse directory and whose metadata is not managed by Databricks. An external table can be created by using the location keyword to specify the path to an existing directory in a cloud storage system, such as DBFS or S3. By creating external tables, the data engineering team can avoid losing data if they drop or overwrite the table, as well as leverage existing data without moving or copying it. Verified Reference: [Databricks Certified Data Engineer Professional], under "Delta Lake" section; Databricks Documentation, under "Create an external table" section.

NEW QUESTION # 69
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. A Job can only use single cluster, setup job for each notebook and use job dependency to link both jobs together
B. Use DELTA LIVE PIPELINES instead of notebook tasks
C. Use a very large cluster to run both the tasks in a single job
D. 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
E. 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

Answer: E

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

NEW QUESTION # 70
Which of the following scenarios is the best fit for the AUTO LOADER solution?

A. Incrementally process new streaming data from Apache Kafa into delta lake
B. Efficiently copy data from data lake location to another data lake location
C. Efficiently move data incrementally from one delta table to another delta table
D. Incrementally process new data from relational databases like MySQL
E. Efficiently process new data incrementally from cloud object storage

Answer: E

Explanation:
Explanation
The answer is, Efficiently process new data incrementally from cloud object storage.
Please note: AUTO LOADER only works on data/files located in cloud object storage like S3 or Azure Blob Storage it does not have the ability to read other data sources, although AU-TO LOADER is built on top of structured streaming it only supports files in the cloud object stor-age. If you want to use Apache Kafka then you can just use structured streaming.
Diagram Description automatically generated

Auto Loader and Cloud Storage Integration
Auto Loader supports a couple of ways to ingest data incrementally
1.Directory listing - List Directory and maintain the state in RocksDB, supports incremental file listing
2.File notification - Uses a trigger+queue to store the file notification which can be later used to retrieve the file, unlike Directory listing File notification can scale up to millions of files per day.
[OPTIONAL]
Auto Loader vs COPY INTO?
Auto Loader
Auto Loader incrementally and efficiently processes new data files as they arrive in cloud storage without any additional setup. Auto Loader provides a new Structured Streaming source called cloudFiles. Given an input directory path on the cloud file storage, the cloudFiles source automatically processes new files as they arrive, with the option of also processing existing files in that directory.
When to use Auto Loader instead of the COPY INTO?
*You want to load data from a file location that contains files in the order of millions or higher. Auto Loader can discover files more efficiently than the COPY INTO SQL command and can split file processing into multiple batches.
*You do not plan to load subsets of previously uploaded files. With Auto Loader, it can be more difficult to reprocess subsets of files. However, you can use the COPY INTO SQL command to reload subsets of files while an Auto Loader stream is simultaneously running.
Refer to more documentation here,
https://docs.microsoft.com/en-us/azure/databricks/ingestion/auto-loader

NEW QUESTION # 71
John Smith is a newly joined team member in the Marketing team who currently has access read access to sales tables but does not have access to delete rows from the table, which of the following commands help you accomplish this?

A. GRANT DELETE TO TABLE table_name ON [email protected]
B. GRANT USAGE ON TABLE table_name TO [email protected]
C. GRANT DELETE ON TABLE table_name TO [email protected]
D. GRANT MODIFY TO TABLE table_name ON [email protected]
E. GRANT MODIFY ON TABLE table_name TO [email protected]

Answer: E

Explanation:
Explanation
The answer is GRANT MODIFY ON TABLE table_name TO [email protected] , please note INSERT, UPDATE, and DELETE are combined into one role called MODIFY.
Below are the list of privileges that can be granted to a user or a group, SELECT: gives read access to an object.
CREATE: gives the ability to create an object (for example, a table in a schema).
MODIFY: gives the ability to add, delete, and modify data to or from an object.
USAGE: does not give any abilities, but is an additional requirement to perform any action on a schema object.
READ_METADATA: gives the ability to view an object and its metadata.
CREATE_NAMED_FUNCTION: gives the ability to create a named UDF in an existing catalog or schema.
MODIFY_CLASSPATH: gives the ability to add files to the Spark classpath.
ALL PRIVILEGES: gives all privileges (is translated into all the above privileges

NEW QUESTION # 72
A CHECK constraint has been successfully added to the Delta table named activity_details using the following logic:

A batch job is attempting to insert new records to the table, including a record where latitude = 45.50 and longitude = 212.67.
Which statement describes the outcome of this batch insert?

A. The write will include all records in the target table; any violations will be indicated in the boolean column named valid_coordinates.
B. The write will insert all records except those that violate the table constraints; the violating records will be recorded to a quarantine table.
C. The write will fail completely because of the constraint violation and no records will be inserted into the target table.
D. The write will insert all records except those that violate the table constraints; the violating records will be reported in a warning log.
E. The write will fail when the violating record is reached; any records previously processed will be recorded to the target table.

Answer: C

Explanation:
Explanation
The CHECK constraint is used to ensure that the data inserted into the table meets the specified conditions. In this case, the CHECK constraint is used to ensure that the latitude and longitude values are within the specified range. If the data does not meet the specified conditions, the write operation will fail completely and no records will be inserted into the target table. This is because Delta Lake supports ACID transactions, which means that either all the data is written or none of it is written. Therefore, the batch insert will fail when it encounters a record that violates the constraint, and the target table will not be updated. References:
Constraints: https://docs.delta.io/latest/delta-constraints.html
ACID Transactions: https://docs.delta.io/latest/delta-intro.html#acid-transactions

NEW QUESTION # 73
......

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Databricks Certified Professional Data Engineer Exam Sample Questions (Q68-Q73):

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