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Introduction to Hadoop:)
- Hadoop is an open-source software framework designed to handle and process large volumes of data across distributed computing environments.
- It is designed to be scalable, fault-tolerant, and capable of handling vast amounts of data efficiently.
- Hadoop Distributed File System (HDFS) is the storage layer of Hadoop, designed to store large files across multiple machines.
- MapReduce is the processing layer of Hadoop. It allows for parallel processing of data across a cluster, which speeds up the data processing tasks.
- Yet Another Resource Negotiator (YARN) is the resource management and job scheduling layer of Hadoop. It manages and schedules resources and job execution across the Hadoop cluster.
- In addition to these core components, the Hadoop ecosystem includes various tools and frameworks that enhance its capabilities: HBase, Hive, Pig, Sqoop, Flume, and Oozie.
- Hadoop Streaming JAR file is a key component in Hadoop’s MapReduce ecosystem that facilitates the use of non-Java languages for writing MapReduce jobs.
- Data stream refers to a continuous flow of data elements that are generated and transmitted in real-time.
- Types of queries on data streams include Standard Queries and Ad-hoc Queries.
- Bloom Filter is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set.
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