Question 1

A junior data engineer seeks to leverage Delta Lake's Change Data Feed functionality to create a Type 1 table representing all of the values that have ever been valid for all rows in a bronze table created with the property delta.enableChangeDataFeed = true. They plan to execute the following code as a daily job:

Databricks-Certified-Professional-Data-Engineer-page61-image24

Which statement describes the execution and results of running the above query multiple times?

Options :

A :

Each time the job is executed, newly updated records will be merged into the target table, overwriting previous values with the same primary keys.

B :

Each time the job is executed, the entire available history of inserted or updated records will be appended to the target table, resulting in many duplicate entries.

C :

Each time the job is executed, the target table will be overwritten using the entire history of inserted or updated records, giving the desired result.

D :

Each time the job is executed, the differences between the original and current versions are calculated; this may result in duplicate entries for some records.

E :

Each time the job is executed, only those records that have been inserted or updated since the last execution will be appended to the target table, giving the desired result.

Answer: B

Question 2

A data engineering team is migrating off its legacy Hadoop platform. As part of the process, they are evaluating storage formats for performance comparison. The legacy platform uses ORC and RCFile formats. After converting a subset of data to Delta Lake, they noticed significantly better query performance. Upon investigation, they discovered that queries reading from Delta tables leveraged a Shuffle Hash Join, whereas queries on legacy formats used Sort Merge Joins. The queries reading Delta Lake data also scanned less data. Which reason could be attributed to the difference in query performance?

Options :

A : Delta Lake enables data skipping and file pruning using a vectorized Parquet reader.

B : The queries against the Delta Lake tables were able to leverage the dynamic file pruning optimization.

C : Shuffle Hash Joins are always more efficient than Sort Merge Joins.

D : The queries against the ORC tables leveraged the dynamic data skipping optimization but not the dynamic file pruning optimization.

Answer: A

Question 3

A data architect has designed a system in which two Structured Streaming jobs will concurrently write to a single bronze Delta table. Each job is subscribing to a different topic from an Apache Kafka source, but they will write data with the same schema. To keep the directory structure simple, a data engineer has decided to nest a checkpoint directory to be shared by both streams. The proposed directory structure is displayed below:

Databricks-Certified-Professional-Data-Engineer-page61-image5

Which statement describes whether this checkpoint directory structure is valid for the given scenario and why?

Options :

A : No; Delta Lake manages streaming checkpoints in the transaction log.

B : Yes; both of the streams can share a single checkpoint directory.

C : No; only one stream can write to a Delta Lake table

D : Yes; Delta Lake supports infinite concurrent writers.

E : No; each of the streams needs to have its own checkpoint directory.

Answer: E

Question 4

A data engineer, User A, has promoted a pipeline to production by using the REST API to programmatically create several jobs. A DevOps engineer, User B, has configured an external orchestration tool to trigger job runs through the REST API. Both users authorized the REST API calls using their personal access tokens.

A workspace admin, User C, inherits responsibility for managing this pipeline. User C uses the Databricks Jobs UI to take "Owner" privileges of each job. Jobs continue to be triggered using the credentials and tooling configured by User B.

An application has been configured to collect and parse run information returned by the REST API. Which statement describes the value returned in the creator_user_name field?

Options :

A : Once User C takes "Owner" privileges, their email address will appear in this field; prior to this, User A’s email address will appear in this field.

B : User B’s email address will always appear in this field, as their credentials are always used to trigger the run.

C : User A’s email address will always appear in this field, as they still own the underlying notebooks.

D : Once User C takes "Owner" privileges, their email address will appear in this field; prior to this, User B’s email address will appear in this field.

E : User C will only ever appear in this field if they manually trigger the job, otherwise it will indicate User B.

Answer: C

Question 5

The data engineering team has a Silver table called ‘sales_cleaned’ where new sales data is appended in near real-time.

They want to create a new Gold-layer entity against the ‘sales_cleaned’ table to calculate the year-to-date (YTD) of the sales amount. The new entity will have the following schema:

country_code STRING, category STRING, ytd_total_sales FLOAT, updated TIMESTAMP

It’s enough for these metrics to be recalculated once daily. But since they will be queried very frequently by several business teams, the data engineering team wants to cut down the potential costs and latency associated with materializing the results.

Which of the following solutions meets these requirements?

Options :

A : Define the new entity as a view to avoid persisting the results each time the metrics are recalculated

B : Define the new entity as a global temporary view since it can be shared between notebooks or jobs that share computing resources.

C : Configuring a nightly batch job to recalculate the metrics and store them as a table overwritten with each update

D : Create multiple tables, one per business team so the metrics can be queried quickly and efficiently.

E : All the above solutions meet the required requirements since Databricks uses the Delta Caching feature

Answer: C

Free Databricks-Certified-Professional-Data-Engineer Mock Exam – Practice Online Confidently

Buying Options: