Spark architecture (driver, executors, cluster manager) in Apache Spark - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the role of the Driver in Spark architecture?

The Driver is the main program that controls the Spark application. It converts user code into tasks, schedules them, and collects results.

beginner

What do Executors do in Spark?

Executors run on worker nodes and execute the tasks assigned by the Driver. They also store data in memory or disk for fast access.

beginner

What is the purpose of the Cluster Manager in Spark?

The Cluster Manager allocates resources across the cluster. It manages where Executors run and how many resources they get.

intermediate

How do Driver, Executors, and Cluster Manager work together in Spark?

The Driver sends tasks to Executors. The Cluster Manager assigns resources and starts Executors on worker nodes. Executors run tasks and send results back to the Driver.

beginner

Name two popular Cluster Managers used with Spark.

Two popular Cluster Managers are YARN (Yet Another Resource Negotiator) and Apache Mesos.

What component in Spark is responsible for scheduling tasks?

A Driver

B Executor

C Cluster Manager

D Worker Node

The Driver schedules tasks and coordinates the execution.

Where do Executors run in a Spark cluster?

A On the Cluster Manager node

B On the Driver node

C On worker nodes

D On the client machine

Executors run on worker nodes to execute tasks.

Which Spark component manages resource allocation?

A Cluster Manager

B Executor

C Task Scheduler

D Driver

The Cluster Manager handles resource allocation across the cluster.

What happens if the Driver fails during a Spark job?

A Executors continue running tasks

B The job stops because the Driver coordinates the job

C Cluster Manager restarts the job automatically

D Nothing, the job finishes normally

The Driver controls the job; if it fails, the job stops.

Which of these is NOT a Cluster Manager for Spark?

A YARN

B Apache Mesos

C Kubernetes

D HDFS

HDFS is a storage system, not a Cluster Manager.

Explain the roles of Driver, Executors, and Cluster Manager in Spark architecture.

Think about who plans, who works, and who manages resources.

Describe how Spark components interact during a job execution.

Focus on the flow of tasks and resource management.

Practice

1. Which component in Spark is responsible for planning the tasks and controlling the job execution?

easy

A. Task Scheduler

B. Executor

C. Cluster Manager

D. Driver

Solution

1. Step 1: Understand the role of the Driver

   The Driver is the main program that creates the SparkContext and plans the tasks to run.

2. Step 2: Compare with other components

   Executors run the tasks, and the Cluster Manager manages resources, but only the Driver plans and controls the job.

3. Final Answer:

   Driver -> Option D

4. Quick Check:

   Driver = plans tasks [OK]

Hint: Driver plans tasks; executors run them [OK]

Common Mistakes:

• Confusing executors with driver
• Thinking cluster manager plans tasks
• Mixing driver with resource manager

2. Which of the following is the correct way to describe the role of executors in Spark?

easy

A. They manage cluster resources and allocate executors

B. They plan the job and schedule tasks

C. They run tasks and store data for the application

D. They submit jobs to the cluster manager

Solution

1. Step 1: Identify executor responsibilities

   Executors run the tasks assigned by the driver and store data in memory or disk during processing.

2. Step 2: Eliminate other options

   Cluster manager manages resources, driver plans jobs, and job submission is done by the driver, not executors.

3. Final Answer:

   They run tasks and store data for the application -> Option C

4. Quick Check:

   Executors = run tasks + store data [OK]

Hint: Executors run tasks and keep data [OK]

Common Mistakes:

• Confusing executors with cluster manager
• Thinking executors plan jobs
• Mixing driver and executor roles

3. Consider a Spark application running on a cluster. Which component is responsible for requesting resources from the cluster manager?

medium

A. Driver

B. Executor

C. Cluster Manager

D. Task Scheduler

Solution

1. Step 1: Understand resource request flow

   The Driver requests resources (executors) from the Cluster Manager to run tasks.

2. Step 2: Clarify roles of other components

   Executors run tasks, Cluster Manager allocates resources, but Driver initiates the request.

3. Final Answer:

   Driver -> Option A

4. Quick Check:

   Driver requests resources [OK]

Hint: Driver asks cluster manager for executors [OK]

Common Mistakes:

• Thinking executors request resources
• Confusing cluster manager with driver
• Assuming task scheduler requests resources

4. You see a Spark application failing because no executors are allocated. Which component should you check first to fix this issue?

medium

A. Cluster Manager configuration

B. Executor logs

C. Driver program code

D. Task Scheduler settings

Solution

1. Step 1: Identify the cause of no executors

   No executors means the cluster manager did not allocate resources.

2. Step 2: Check cluster manager setup

   Cluster Manager manages resource allocation; misconfiguration here can block executors.

3. Final Answer:

   Cluster Manager configuration -> Option A

4. Quick Check:

   Cluster Manager controls executors allocation [OK]

Hint: Check cluster manager if no executors start [OK]

Common Mistakes:

• Checking driver code first instead of cluster manager
• Looking at executor logs when none exist
• Confusing task scheduler with resource manager

5. In a Spark cluster, if the driver fails but executors continue running, what is the expected behavior and why?

hard

A. Executors keep running tasks independently without driver

B. Executors stop working because driver controls task scheduling

C. Cluster manager automatically restarts executors without driver

D. Driver failure does not affect executors as they are independent

Solution

1. Step 1: Understand driver role in task scheduling

   The driver plans and schedules tasks; executors depend on it for instructions.

2. Step 2: Analyze executor behavior on driver failure

   Without the driver, executors cannot receive new tasks and will stop processing.

3. Final Answer:

   Executors stop working because driver controls task scheduling -> Option B

4. Quick Check:

   Driver failure stops executors [OK]

Hint: Executors need driver to schedule tasks [OK]

Common Mistakes:

• Assuming executors run independently
• Thinking cluster manager restarts executors automatically
• Believing driver failure has no impact