Hadoop and Big Data Concepts

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Questions and Answers

What is the primary function of the Namenode in HDFS?

To perform read-write operations on the data blocks

To manage the data storage of the system

To manage the file system namespace and regulate client access (correct)

To create replicas of blocks for fault tolerance

What is the default block size in HDFS?

128MB

256MB

32MB

64MB (correct)

What is the purpose of the Blockreport sent by the DataNode to the Namenode?

To request a new block size

To report the availability of the DataNode

To provide a list of all blocks on the DataNode (correct)

To request replication of blocks

What is the main goal of the replica placement policy in HDFS?

To ensure data reliability and availability Signup and view all the answers

What is the function of the DataNode in HDFS?

To manage the data storage of the system and perform read-write operations Signup and view all the answers

What is the purpose of the Heartbeat sent by the DataNode to the Namenode?

To report the availability of the DataNode Signup and view all the answers

What is the minimum unit of data that can be read or written in HDFS?

Block Signup and view all the answers

What is the replication factor in HDFS?

The number of replicas of a block Signup and view all the answers

What is the primary purpose of Hadoop?

To manage and process huge volumes of structured and unstructured data Signup and view all the answers

What is the core component of Hadoop's processing layer?

MapReduce Signup and view all the answers

What is the primary feature of HDFS that enables it to handle large datasets?

Support for Petabyte size of data Signup and view all the answers

What is the purpose of the Namenode in a Hadoop cluster?

To manage the cluster Signup and view all the answers

What is the coherency model of HDFS?

Write-once-read-many Signup and view all the answers

What is the main advantage of Hadoop's distributed computing platform?

It allows for moving computation to the data Signup and view all the answers

What is the primary benefit of HDFS's fault-tolerance feature?

It ensures data availability in case of node failures Signup and view all the answers

What is the key characteristic of Hadoop's data processing approach?

It divides the task into small parts and assigns them to many computers Signup and view all the answers

What is the primary benefit of HDFS's replication policy?

Preventing data loss in case of rack failure Signup and view all the answers

What is the purpose of data locality in Hadoop?

To minimize overall network congestion Signup and view all the answers

What is the role of the JobTracker in the MapReduce framework?

To schedule the jobs' component tasks on the slaves Signup and view all the answers

How does HDFS's replication policy affect the cost of writes?

It increases the cost of writes Signup and view all the answers

What is the typical output of a MapReduce job?

A file stored in a file-system Signup and view all the answers

What is the role of the TaskTracker in the MapReduce framework?

To execute the tasks as directed by the master Signup and view all the answers

What is the primary function of the map tasks in a MapReduce job?

To process the input data-set in a parallel manner Signup and view all the answers

What is the purpose of the job configuration in a MapReduce job?

To specify the input/output locations and supply map and reduce functions Signup and view all the answers

Study Notes

Big Data and Hadoop

Big Data is a collection of large datasets that cannot be processed using traditional computing techniques.
It involves many areas of business and technology and requires an infrastructure to manage and process huge volumes of structured and unstructured data in real-time.
Hadoop is an Apache open-source framework written in Java that allows distributed processing of large datasets across clusters of computers using the MapReduce algorithm.

Hadoop Distributed File System (HDFS)

HDFS is a Distributed File System (DFS) that allows files from multiple hosts to share via a computer network.
It supports concurrency and includes facilities for transparent replication and fault tolerance.
HDFS is based on the Google File System (GFS).
Key features of HDFS:
- Supports Petabyte size of data
- Heterogeneous - can be deployed on different hardware
- Streaming data access via batch processing
- Coherency model - Write-once-read-many
- Data locality - "Moving Computation is Cheaper than Moving Data"
- Fault-tolerance

Hadoop Architecture

Namenode:
- Each cluster has one Namenode
- Contains the GNU/Linux operating system and the Namenode software
- Prevents data loss when an entire rack fails and allows use of bandwidth from multiple racks when reading data
Data locality:
- Moves computation close to where the actual data resides
- Minimizes overall network congestion
- Increases the overall throughput of the system

MapReduce

MapReduce workflow:
- Splits input data-set into independent chunks
- Processed by map tasks in a completely parallel manner
- Outputs are sorted and input to reduce tasks
- Framework takes care of scheduling tasks, monitoring, and re-executing failed tasks
MapReduce framework:
- Consists of a single master JobTracker and one slave TaskTracker per cluster-node
- Master is responsible for scheduling jobs, monitoring, and re-executing failed tasks
- Slaves execute tasks as directed by the master

Namenode and Datanode

Namenode:
- Manages the file system namespace
- Regulates client's access to files
- Executes file system operations
Datanode:
- Same hardware as Namenode but runs the Datanode software
- Manages data storage of their system
- Performs read-write operations and block creation, deletion, and replication

Blocks and Replication

Blocks:
- Files in HDFS are divided into one or more blocks
- Default block size is 64MB but can be changed via configuration
Replication:
- Blocks of a file are replicated for fault tolerance
- Block size and replication factor are configurable per file
- Namenode makes all decisions regarding replication of blocks
- Replica placement policy follows Rack-aware replica placement for data reliability, availability, and network bandwidth utilization

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Description

Learn about Big Data, its definition, and the importance of infrastructure in handling large datasets. Explore Hadoop's role in managing and processing structured and unstructured data.