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Hadoop stands out as a leading Big Data processing system. So, what exactly is Hadoop? What makes the Hadoop structure unique?
1. What is Hadoop?
Apache Hadoop is an open-source software framework used to develop applications for processing data in a Distributed Computing Environment (DCE).
Applications built on Hadoop run on distributed clusters of computers, handling large datasets.
Similar to data residing in local file systems on personal computers, in Hadoop, data resides in a distributed file system called Hadoop Distributed File System (HDFS).
A processing model based on the concept of 'Data Locality,' where computational logic is sent to nodes (servers) containing the data. Essentially, the computational logic is just a compiled version of a program written in a high-level language like Java.
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2. Hadoop Ecosystem and its Components
Components in the Hadoop ecosystem include: HDFS and HDFS, MapReduce, YARN, Hive, Apache Pig, Apache HBase, and components like HBase, HCatalog, Avro, Thrift, Drill, Apache Mahout, Sqoop, Apache Flume, Ambari, Zookeeper, and Apache Oozie.
Apache Hadoop comprises two sub-projects, namely:
- Hadoop MapReduce: It is a computational model and framework used to write applications that run on Hadoop. These MapReduce programs can handle parallel processing of massive data blocks across large computing node clusters.
- HDFS (Hadoop Distributed File System): HDFS plays a role in storing Hadoop applications. MapReduce applications use data from HDFS. HDFS creates multiple copies of data blocks and distributes them across computing nodes in the cluster.
Additionally, there are other related projects in the Hadoop ecosystem such as Hive, HBase, Mahout, Sqoop, Flume, and ZooKeeper.
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3. Hadoop Architecture
The Master-Slave architecture on Hadoop stores and processes distributed data using MapReduce and HDFS.
NameNode: represents files and directories used in the Namespace.
DataNode: manages the state of HDFS nodes and allows users to interact with blocks.
MasterNode: enables parallel data processing with Hadoop MapReduce.
Slave node: essentially, Slave nodes are supplementary machines in the Hadoop cluster, enabling users to store data for performing complex computations.
Additionally, all Slave nodes are integrated with Task Tracker and DataNode, enabling synchronization of processes with the corresponding NameNode and Job Tracker.
In Hadoop, the master/slave system can be configured on-premises or in the cloud.
4. Features of Hadoop
Some notable features of Hadoop include:
4.1. Big Data Analysis Solution
The nature of Big Data is unstructured and tends to be distributed, making Hadoop clusters an ideal choice for analyzing this type of data. As the computational nodes handle logical processing (not actual data), it consumes less bandwidth. This concept is known as Data Locality, enhancing the efficiency of Hadoop-based applications.
4.2. Scalability
By adding node clusters to expand Hadoop clusters. This allows you to process larger volumes of data without modifying application logic.
4.3. Fault Tolerance
The Hadoop ecosystem has the ability to replicate input data to other node clusters. This way, in case of any issues with a node cluster, the data processing can still continue using the data stored on another node cluster.
5. Network Topology in Hadoop
Topology, or network structure, affects the performance of Hadoop clusters as their size increases. In addition to performance, users also care about availability and the ability to handle incidents.
To form this Hadoop cluster, Network Topology (network structure) is utilized.
Typically, bandwidth is a crucial factor when forming any network. However, in Hadoop, measuring bandwidth is more intricate; the network is represented as a tree, and the distance between nodes of the tree is considered a vital factor in the formation of Hadoop clusters.
A Hadoop cluster includes a data center, racks, and nodes. Specifically, the data center comprises racks, and each rack consists of nodes. Network bandwidth is available for different processes, depending on the location of the processes.
This article by Mytour has just introduced you to What is Hadoop? Its components and Hadoop ecosystem? If you have any more questions or queries, feel free to leave your comments below the article.
