Apache Spark is an open-source, distributed computing system that provides a fast and flexible framework for large-scale data processing and analytics. It was developed to address the limitations of the Hadoop MapReduce model and is designed to handle a wide range of data processing tasks, including batch processing, real-time streaming, machine learning, graph processing, and […]

Apache Hadoop is an open-source framework designed for distributed storage and processing of large sets of data across clusters of computers. It provides a scalable and reliable platform for storing, managing, and analyzing vast amounts of data, including structured, semi-structured, and unstructured data. Key components of the Hadoop ecosystem include: Hadoop Distributed File System (HDFS): […]

Apache Parquet is a popular columnar storage format for data that is optimized for analytics workloads. It is designed to efficiently store and process large amounts of data, making it well-suited for big data processing frameworks like Apache Hadoop (more about Apache Hadoop HERE) and Apache Spark (more about Apache Spark HERE). Parquet datasets refer […]

Making Changes to Production Environments A change to a production environment refers to any modification, addition, or removal of hardware, software, configurations, or processes within a live or operational system that may impact its functionality, performance, security, or stability. It is a deliberate action taken to improve, update, or enhance the production system. Changes can […]

C# Explained C# (pronounced “C sharp”) is a modern, general-purpose programming language developed by Microsoft. It is part of the Microsoft .NET platform and is commonly used for developing various types of applications, including Windows desktop applications, web applications, mobile apps, cloud services, and more. C# is known for its simplicity, type safety, and object-oriented […]