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Category: Bigdata Fundamentals
Below is the Hive Deep Dive Series, delivered inline, one module at a time with real-world relevance, use cases, syntax, and interview insights. ✅ Module 1: 📘 Hive Basics & Architecture 🔹 What is Hive? Apache Hive is a data warehouse system built on top of Hadoop for querying and analyzing structured data using a…
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…
Ordered Guide to Big Data, Data Lakes, Data Warehouses & Lakehouses 1  The Modern Data Landscape — Bird’s‑Eye View Every storage paradigm slots into this flow at the Storage layer, but each optimises different trade‑offs for the rest of the pipeline. 2  Foundations: What Is Big Data? 5 Vs Meaning Volume Petabytes+ generated continuously Velocity Milliseconds‑level arrival & processing Variety Structured, semi‑structured, unstructured Veracity Data quality…