HBase vs HDFS comparison in Hadoop - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Primary difference between HBase and HDFS

Which statement best describes the primary difference between HBase and HDFS?

A HBase stores data as files, while HDFS stores data in tables with rows and columns.

B HBase is designed for batch processing, while HDFS supports real-time queries.

C HBase is a NoSQL database for real-time read/write access, while HDFS is a distributed file system for batch processing.

D HBase and HDFS are both relational databases used for structured data storage.

💡 Hint

Think about how each system handles data access and storage format.

HBase is a NoSQL database built on top of HDFS to provide fast random access to large datasets. HDFS is a distributed file system optimized for storing large files and batch processing.

❓ data_output

intermediate

HBase data retrieval example output

Given the following HBase table snapshot, what will be the output of retrieving the value for row key 'user1' and column 'info:name'?

Hadoop

Row key: user1
Column Family: info
Columns:
  name: Alice
  age: 30
Row key: user2
Column Family: info
Columns:
  name: Bob
  age: 25

A "Alice"

B "user1"

C "info:name"

D "30"

💡 Hint

Focus on the value stored at the specified row and column.

The value stored at row 'user1' and column 'info:name' is 'Alice'.

❓ Predict Output

advanced

HDFS file replication factor effect

What will be the output of the following command showing the replication factor of a file in HDFS?

Hadoop

hdfs dfs -stat %r /user/data/file1.txt

A 0

B 1

C Error: command not found

D 3

💡 Hint

By default, what is the replication factor for files in HDFS?

The default replication factor in HDFS is 3, meaning each file block is stored on three different nodes for fault tolerance.

🧠 Conceptual

advanced

Use case best suited for HBase over HDFS

Which use case is best suited for HBase rather than HDFS?

A Running MapReduce jobs on large datasets.

B Real-time querying of user profile data with frequent updates.

C Archiving large video files for long-term storage.

D Storing large log files for batch analysis.

💡 Hint

Consider which system supports fast random reads and writes.

HBase supports real-time read/write access and is ideal for use cases requiring frequent updates and quick queries, such as user profiles.

🔧 Debug

expert

Identifying error in HBase data insertion code

What error will the following Python code produce when trying to insert data into HBase using the HappyBase library?

Hadoop

import happybase
connection = happybase.Connection('localhost')
table = connection.table('users')
table.put('user1', {'info:name': 'Alice', 'info:age': b'30'})

A TypeError: expected bytes, int found

B ConnectionError: Could not connect to HBase

C SyntaxError: invalid syntax

D No error, data inserted successfully

💡 Hint

Check the data types required by HappyBase for values.

HappyBase requires values to be bytes, but the age value is an integer, causing a TypeError.