BigData Hadoop and PySpark full course in Telugu (తెలుగులో)

This course prepares you for a career change in Big Data Hadoop and Spark.

After watching it, you will understand Hadoop, HDFS, YARN, Map reduce, hive, sqoop, Linux, PySpark, Spark sql, PySpark streaming.

This is a one stop course. So don't worry and get started.

You will get all possible support from my side.

For any queries, feel free to message me here.

Note: All programs and materials are provided.

About Hadoop Ecosystem and Spark:

Hadoop and its Ecosystem: Hadoop is an open source framework for distributed storage and processing of large data sets. Its core components include the Hadoop Distributed File System (HDFS) for data storage and the MapReduce programming model for data processing. Hadoop's ecosystem consists of various tools and frameworks designed to enhance its capabilities. Important components include Apache Pig for data scripting, Apache Hive for data warehousing, Apache HBase for NoSQL database functionality, and Apache Spark for fast, in-memory data processing. These tools collectively form a robust ecosystem that enables organizations to efficiently tackle big data challenges, making Hadoop a cornerstone in the world of data analytics and processing.

Spark: Apache Spark is an open source, lightning-fast data processing framework designed for big data analytics. It provides in-memory processing that significantly speeds up data analysis and machine learning tasks. Spark supports a variety of programming languages, including Java, Scala, and Python, making it accessible to a wide range of developers. With the ability to process both batch and streaming data, Spark has become the preferred choice for organizations seeking high-performance data analytics and machine learning capabilities, outperforming traditional MapReduce-based solutions in many use cases.