Cluster planning and sizing in Hadoop - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of cluster planning in Hadoop?

The main goal is to design a cluster that meets performance, storage, and cost needs by choosing the right number and type of nodes.

beginner

Name two key factors to consider when sizing a Hadoop cluster.

Data volume (how much data you have) and workload type (batch processing, streaming, etc.) are key factors.

intermediate

Why is it important to consider network bandwidth in cluster sizing?

Because data moves between nodes during processing, insufficient bandwidth can slow down jobs and reduce cluster efficiency.

intermediate

What role does memory play in Hadoop cluster sizing?

Memory affects how much data can be processed in memory, impacting speed and the ability to run multiple tasks simultaneously.

beginner

Explain the difference between compute nodes and storage nodes in a Hadoop cluster.

Compute nodes handle data processing tasks, while storage nodes focus on storing data. Some clusters combine both roles in the same nodes.

What is the first step in Hadoop cluster planning?

A Buying hardware

B Estimating data size and growth

C Installing Hadoop software

D Running sample jobs

Estimating data size helps decide how big the cluster needs to be.

Which resource is most critical for fast data processing in Hadoop?

A Disk space

B Network bandwidth

C Monitor size

D CPU and memory

CPU and memory directly affect processing speed and task handling.

In cluster sizing, what does 'scalability' mean?

A Ability to add more nodes easily

B Faster network cables

C More storage disks per node

D Using cheaper hardware

Scalability means you can grow the cluster by adding nodes without big changes.

Which Hadoop component stores data across the cluster?

A HDFS

B YARN

C MapReduce

D Hive

HDFS (Hadoop Distributed File System) stores data across nodes.

Why might you separate compute and storage nodes in a cluster?

A To reduce network traffic

B To make the cluster smaller

C To optimize resource use for specific tasks

D To avoid using memory

Separating roles helps optimize hardware for processing or storage needs.

Describe the key steps involved in planning and sizing a Hadoop cluster.

Think about what you need to know before buying and setting up the cluster.

Explain how memory and network bandwidth affect Hadoop cluster performance.

Consider how data moves and is processed inside the cluster.

Practice

1. What is the main goal of cluster planning in Hadoop?

easy

A. To increase network speed only

B. To write complex MapReduce code

C. To ensure enough resources for big data tasks

D. To reduce the size of data stored

Solution

1. Step 1: Understand cluster planning purpose

   Cluster planning is about preparing resources like CPU, memory, and storage to handle big data jobs efficiently.

2. Step 2: Identify the main goal

   The main goal is to ensure the cluster has enough resources to process and store data reliably.

3. Final Answer:

   To ensure enough resources for big data tasks -> Option C

4. Quick Check:

   Cluster planning = resource readiness [OK]

Hint: Think about what cluster planning prepares for [OK]

Common Mistakes:

• Confusing cluster planning with coding tasks
• Thinking it only improves network speed
• Assuming it reduces data size

2. Which of the following is the correct way to calculate total storage needed for a Hadoop cluster with 10 TB data and replication factor 3?

easy

A. 10 TB * 3 = 30 TB

B. 10 TB / 3 = 3.33 TB

C. 10 TB + 3 = 13 TB

D. 10 TB - 3 = 7 TB

Solution

1. Step 1: Understand replication factor meaning

   Replication factor 3 means each data block is stored 3 times for fault tolerance.

2. Step 2: Calculate total storage

   Total storage = original data size * replication factor = 10 TB * 3 = 30 TB.

3. Final Answer:

   10 TB * 3 = 30 TB -> Option A

4. Quick Check:

   Storage needed = data size x replication factor [OK]

Hint: Multiply data size by replication factor [OK]

Common Mistakes:

• Dividing instead of multiplying
• Adding or subtracting replication factor incorrectly
• Ignoring replication factor

3. Given a Hadoop cluster with 5 nodes, each having 16 CPU cores and 64 GB RAM, what is the total CPU cores and RAM available?

medium

A. 80 CPU cores and 320 GB RAM

B. 16 CPU cores and 64 GB RAM

C. 5 CPU cores and 5 GB RAM

D. 320 CPU cores and 80 GB RAM

Solution

1. Step 1: Calculate total CPU cores

   Total CPU cores = number of nodes * CPU cores per node = 5 * 16 = 80 cores.

2. Step 2: Calculate total RAM

   Total RAM = number of nodes * RAM per node = 5 * 64 GB = 320 GB.

3. Final Answer:

   80 CPU cores and 320 GB RAM -> Option A

4. Quick Check:

   Total CPU = 5x16, Total RAM = 5x64 [OK]

Hint: Multiply nodes by cores and RAM per node [OK]

Common Mistakes:

• Adding CPU cores and RAM instead of multiplying
• Mixing CPU cores with RAM units
• Using per node values as total

4. Identify the error in this cluster sizing calculation: A cluster has 8 nodes, each with 32 GB RAM. The total RAM is calculated as 8 + 32 = 40 GB. What is wrong?

medium

A. Ignoring CPU cores

B. Multiplying nodes and RAM correctly

C. Using wrong units for RAM

D. Adding nodes and RAM instead of multiplying

Solution

1. Step 1: Understand total RAM calculation

   Total RAM should be number of nodes multiplied by RAM per node, not added.

2. Step 2: Identify the mistake

   The calculation 8 + 32 = 40 GB is incorrect; it should be 8 * 32 = 256 GB.

3. Final Answer:

   Adding nodes and RAM instead of multiplying -> Option D

4. Quick Check:

   Total RAM = nodes x RAM per node [OK]

Hint: Multiply nodes by RAM, don't add [OK]

Common Mistakes:

• Adding node count and RAM size
• Confusing units of measurement
• Ignoring multiplication for totals

5. You have 20 TB of raw data with replication factor 3 and want to plan a Hadoop cluster. Each node has 4 TB usable storage. How many nodes are needed at minimum to store the data?

hard

A. 20 nodes

B. 15 nodes

C. 60 nodes

D. 5 nodes

Solution

1. Step 1: Calculate total storage needed with replication

   Total storage = raw data x replication factor = 20 TB x 3 = 60 TB.

2. Step 2: Calculate number of nodes needed

   Nodes needed = total storage / storage per node = 60 TB / 4 TB = 15 nodes.

3. Final Answer:

   15 nodes -> Option B

4. Quick Check:

   Nodes = (data x replication) ÷ node storage [OK]

Hint: Divide total replicated data by node storage [OK]

Common Mistakes:

• Ignoring replication factor
• Dividing raw data by node storage only
• Rounding nodes incorrectly