Why Hadoop was created for big data - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to show the main reason Hadoop was created.

Hadoop

Hadoop was created to handle [1] data volumes that traditional systems could not manage.

Drag options to blanks, or click blank then click option'

Alarge

Bsmall

Cstructured

Dsimple

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'small' because it sounds easier

Confusing data type with data size

Hadoop was created to handle large data volumes that traditional systems could not manage.

2fill in blank

medium

Complete the code to explain what Hadoop uses to store big data.

Hadoop

Hadoop uses [1] to store data across many computers.

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ACloud storage

BSQL databases

CHDFS

DLocal files

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'SQL databases' because of familiarity

Choosing 'Cloud storage' which is different technology

Hadoop uses HDFS (Hadoop Distributed File System) to store data across many computers.

3fill in blank

hard

Fix the error in the sentence about Hadoop's processing model.

Hadoop

Hadoop processes data using the [1] model, which breaks tasks into small parts.

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AMapReduce

BBatch

CStream

DReal-time

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'Batch' which is a general term

Choosing 'Stream' or 'Real-time' which Hadoop does not primarily use

Hadoop processes data using the MapReduce model, which breaks tasks into small parts to run in parallel.

4fill in blank

hard

Fill both blanks to describe Hadoop's fault tolerance and scalability.

Hadoop

Hadoop achieves fault tolerance by [1] data and scales by adding [2] to the cluster.

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Areplicating

Bremoving nodes

Cnodes

Dcompressing

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'removing nodes' which reduces capacity

Choosing 'compressing' which is unrelated to fault tolerance

Hadoop achieves fault tolerance by replicating data and scales by adding nodes to the cluster.

5fill in blank

hard

Fill all three blanks to complete the explanation of Hadoop's design principles.

Hadoop

Hadoop was designed to handle [1] data by distributing storage with [2] and processing with [3].

Drag options to blanks, or click blank then click option'

Asmall

BHDFS

CMapReduce

Dlarge

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'small' instead of 'large'

Mixing up HDFS and MapReduce roles

Hadoop was designed to handle large data by distributing storage with HDFS and processing with MapReduce.