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1. A Data engineer wants to run unit's tests using common Python testing frameworks on python functions defined across several Databricks notebooks currently used in production. How can the data engineer run unit tests against function that work with data in production?

A) Run unit tests against non-production data that closely mirrors production
B) Define units test and functions within the same notebook
C) Define and import unit test functions from a separate Databricks notebook
D) Define and unit test functions using Files in Repos

2. A production cluster has 3 executor nodes and uses the same virtual machine type for the driver and executor.
When evaluating the Ganglia Metrics for this cluster, which indicator would signal a bottleneck caused by code executing on the driver?

A) Network I/O never spikes
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
B) Bytes Received never exceeds 80 million bytes per second
C) Overall cluster CPU utilization is around 25%
D) Total Disk Space remains constant
E) The five Minute Load Average remains consistent/flat

3. Which distribution does Databricks support for installing custom Python code packages?

A) nom
B) CRAN
C) Wheels
D) sbt
E) CRAM
F) jars

4. The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.
Which approach will ensure that this requirement is met?

A) When a database is being created, make sure that the LOCATION keyword is used.
B) When data is saved to a table, make sure that a full file path is specified alongside the Delta format.
C) When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.
D) When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.
E) When the workspace is being configured, make sure that external cloud object storage has been mounted.

5. Which statement characterizes the general programming model used by Spark Structured Streaming?

A) Structured Streaming relies on a distributed network of nodes that hold incremental state values for cached stages.
B) Structured Streaming is implemented as a messaging bus and is derived from Apache Kafka.
C) Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.
D) Structured Streaming leverages the parallel processing of GPUs to achieve highly parallel data throughput.
E) Structured Streaming uses specialized hardware and I/O streams to achieve sub-second latency for data transfer.

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