Company: Linkedin Learning Author: Lynn Langit Full Title: Cloud Hadoop: Scaling Apache Spark Year: 2020 Language: English Genre: Educational: Big Data Skill Level: Beginner Price: €24.99 - Files: MP4 (+ Exercise Files, Subtitles .SRT) Time: 03:13:26 Video: AVC, 1280 x 720 (1.778) at 15.000 fps, 200 kbps Audio: AAC at 160 Kbps, 2 channels, 48.0 KHz Apache Hadoop and Spark make it possible to generate genuine business insights from big data. The Amazon cloud is natural home for this powerful toolset, providing a variety of services for running large-scale data-processing workflows. Learn to implement your own Apache Hadoop and Spark workflows on AWS in this course with big data architect Lynn Langit. Explore deployment options for production-scaled jobs using virtual machines with EC2, managed Spark clusters with EMR, or containers with EKS. Learn how to configure and manage Hadoop clusters and Spark jobs with Databricks, and use Python or the programming language of your choice to import data and execute jobs. Plus, learn how to use Spark libraries for machine learning, genomics, and streaming. Each lesson helps you understand which deployment option is best for your workload. Topics include: 01. File systems for Hadoop and Spark 02. Working with Databricks 03. Loading data into tables 04. Setting up Hadoop and Spark clusters on the cloud 05. Running Spark jobs 06. Importing and exporting Python notebooks 07. Executing Spark jobs in Databricks using Python and Scala 08. Importing data into Spark clusters 09. Coding and executing Spark transformations and actions 10. Data caching 11. Spark libraries: Spark SQL, SparkR, Spark ML, and more 12. Spark streaming 13. Scaling Spark with AWS and GCP Our members see more. Join us! ------------- Our members see more. Join us!
