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Category: Bigdata Fundamentals
Apache Hive Overview Hive is a data warehouse infrastructure built on top of Hadoop and SQL-like language called HiveQL for querying data stored in various databases and file systems that integrate with Hadoop. Hive allows users to read, write, and manage large datasets residing in distributed storage using SQL. It simplifies the process of data…
What is Hadoop? Hadoop is an open-source, distributed computing framework that allows for the processing and storage of large datasets across a cluster of computers. It was created by Doug Cutting and Mike Cafarella and is now maintained by the Apache Software Foundation. History of Hadoop Hadoop was inspired by Google’s MapReduce and Google File…
Big Data Lake: Data Storage HDFS is a scalable storage solution designed to handle massive datasets across clusters of machines. Hive tables provide a structured approach for querying and analyzing data stored in HDFS. Understanding how these components work together is essential for effectively managing data in your BDL ecosystem. HDFS – Hadoop Distributed File…
Big data and big data lakes are complementary concepts. Big data refers to the characteristics of the data itself, while a big data lake provides a storage solution for that data. Organizations often leverage big data lakes to store and manage their big data, enabling further analysis and exploration. Here’s an analogy: Think of big…