Tags
Language
Tags
October 2025
Su Mo Tu We Th Fr Sa
28 29 30 1 2 3 4
5 6 7 8 9 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30 31 1
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

    [NEW]Hands-on Big Data & Spark Tuning Practices with PySpark

    Posted By: BlackDove
    [NEW]Hands-on Big Data & Spark Tuning Practices with PySpark

    [NEW]Hands-on Big Data & Spark Tuning Practices with PySpark
    Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 5.14 GB | Duration: 17 lectures • 9h 31m


    Best Hands-on PySpark practices on Semi-Structured (JSON), Structured, and Unstructured Data using RDD, DF and SQL

    What you'll learn
    Understand Apache Spark’s framework, execution and programming model for the development of Big Data Systems
    Learn how to work with a free Cloud-based and a Desktop machine for Spark setup and configuration
    Build Advanced Big Data applications for different types of data (volume, variety, veracity) through real case studies
    Learn Advanced hands-on PySpark practices on structured, unstructured and semi-structured data using RDD, DataFrame and SQL

    Requirements
    Basic Python and Spark skill
    Description
    In this course, students will be provided with hands-on PySpark practices using real case studies from academia and industry to be able to work interactively with massive data. We designed this course for anyone seeking to master Spark/PySpark and Spread the knowledge of Big Data Analytics using real and challenging use cases.

    We will work with Spark RDD, DF, and SQL to process huge sized of data in the format of semi-structured, structured, and unstructured data. The learning outcomes and the teaching approach in this course will accelerate the learning through Identifying the most critical required skills in industry and understanding the demands of Big Data analytics content.

    We will not only cover the details of the Spark engine for large-scale data processing, but also we will drill down big data problems that allow users to instantly shift from an overview of large scale data to a more detailed and granular view using RDD, DF and SQL in real-life examples. We will walk through the Big Data case studies step by step to achieve the aim of this course.

    By the end of the course, you will be able to build advanced Big Data applications for different types of data (volume, variety, veracity) and you will get acquainted with best-in-class examples of Big Data problems using PySpark.

    Who this course is for
    Beginner/Junior Big Data developers who want to master Spark/PySpark and Spread the knowledge of Big Data Analytics using Advanced use cases