Distributed System Characteristics in Hadoop Assignment Help from Experts
Security and Law Enforcement: The national security agency of the USA uses Hadoop to prevent terrorist attacks. It is used to detect and prevent cyber-attacks. Customer’s Requirements Understanding: Many companies like financial, telecom use this technology to find out the customer’s requirement by analyzing the big amount of data. Social media also uses this technology and keeps posting an advertisement on various social media sites to the target customer whenever the user opens their social media on the browser. Cities and Countries Improvement: Used to development of the country, state, cities by analyzing of data, example traffic jams can be controlled by uses of Hadoop. It used in the development of a smart city, It used to improve the transport of the city. It gives proper guidelines for the buses, train, and other ways of transportation.
Financial Trading and Forecasting: Hadoop is used in the trading field. It has a complex algorithm that scan markets with predefined condition and criteria to find out trading opportunities. It is designed in a way that it can work without human interaction in case nobody present to monitor the things according to end-users needs this works. Understanding and Optimizing Business Processes: Retailer can customize their stocks by predicting came from various source like social media google search, various other platforms. A company can make the best decision to improve its business and maximize its profits. Improving Healthcare and Public Health: Hadoop is used in the medical field to improve public health. Many health-related applications are based on Hadoop only, where they monitor day-to-day activities.
HDFS Basic Concepts
NameNode: The centralized piece of the HDFS, known as the Master and designed to store the MetaData. Name Node is responsible
for monitoring the Health Status of the Slave Nodes and to assign Tasks to the Data Nodes.
Tasks of HDFS NameNode:
– Manage file system namespace.
DataNode: The actual unit which stores the data, known as the Slave, and responds to the Name Node about its Health Status and the task status in the form of a Heartbeat. If the Data Node fails to respond to the Name Node, then the Name Node considers the Slave Node to be Dead and reassigns the task to the Next available Data Node.
Tasks of HDFS DataNode: DataNode performs operations like block replica creation, deletion, and replication according to the instruction of NameNode. DataNode manages the data storage of the system.
Secondary NameNode: The Secondary Name Node is not a backup of the name node. It acts as a Buffer to the Name Node. It stores the intermediate updates of the FS-image of the Name Node in the Edit-log and updates the information to the Final FS-image when the name node is inactive.
Map: It takes data and set then divides it into chunks such that they are converted into a new format which would be in the form of a key-value pair.
Reduce: It is the second part where the Key/Value pairs are reduced to tuples.
The MapReduce process enables us to perform various operations over the big data such as Filtering and Sorting and many such similar ones.
– Reads data as key/value pairs
– Outputs zero or more key/value pairs
– Output from the mapper is sorted by key
– All values with the same key are guaranteed to go to the same machine
– Called once for each unique key
– Gets a list of all values associated with a key as input
– The reducer outputs zero or more final key/value pairs
– Usually just one output per input key
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