In this article i am gone to share Coursera Course: Microsoft Azure Databricks for Data Engineering Week 1 | Test prep Quiz Answers with you..

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Microsoft Azure Databricks for Data Engineering Week 1 | Test prep Quiz Answers

Test prep Quiz Answers

Question 1)
Azure Databricks Runtime adds several key capabilities to Apache Spark workloads that can increase performance and reduce costs. Which of the following are features of Azure Databricks? Select all that apply.

• Auto-scaling and auto-termination
• Indexing
• Caching
• Parallel Cluster Drivers
• High-speed connectors to Azure storage services

Question 2)
Apache Spark supports which of the following languages? Select all that apply.

• ORC
• Scala
• Java
• Python

Question 3)
Which of the following statements are True Select all that apply.

• To use your Azure Databricks notebook to run code, you must attach it to a cluster
• You can detach a notebook from a cluster and attach it to another cluster.
• To use your Azure Databricks notebook to run code you do not require a cluster
• Once created a notebook can only be connected to the original cluster.

Question 4)
Which of the following Databricks features are not Open-Source Spark?

• MLFlow
• Databricks Workflows
• Databricks Runtime
• Databricks Workspace

Question 5)
How many drivers does a Cluster have?

• Configurable between one and eight
• Two, running in parallel
• Only one

Question 6)
What type of process are the driver and the executors?

• C++ processes
• Java processes
• Python processes

Question 7)
You work with Big Data as a data engineer, and you must process real-time data. This is referred to as having which of the following characteristics?

• Variety
• High volume
• High velocity

Question 8)
Spark’s performance is based on parallelism. Which of the following Scalability methods is limited to a finite amount of RAM, Threads and CPU speeds?

• Diagonal Scaling
• Vertical Scaling
• Horizontal Scaling

Question 9)
Spark Cluster use two levels of parallelization. Which of the following are levels of parallelization?

• Executor
• Slot
• Partition
• Job

Question 10)
In an Apache Spark Cluster jobs are divided into which of the following?

• Executors
• Tasks
• Slots
• Drivers