What is this course about?This course covers all the fundamentals about Apache Spark streamingwith Python and teaches you everything you need to know about developing Spark streamingapplications using PySpark, the PythonAPI for Spark. At the end of this course, you will gain in-depth knowledge about Spark streamingand general big datamanipulationskills to help your company to adapt Spark Streaming for building big data processing pipelines and data analytics applications.This course will be absolutely critical to anyone trying to make it in data science today.What will you learn from this ApacheSpark streaming cour?In this ApacheSpark streaming course, you’ll learn the following:An overview of the architecture of Apache Spark.How to develop Apache Spark streaming applications with PySparkusing RDD transformations and actions and Spark SQL.How to work with Spark’s primary abstraction, resilient distributed datasets(RDDs), to process and analyze large data sets.Advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.Analyzing structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Spark SQL.How to scale up Spark Streaming applications for both bandwidth and processing speedHow to integrate Spark Streaming with cluster computing tools like Apache KafkaHow to connect your Spark Stream to a data source like Amazon WebServices (AWS)KinesisBest practices of working with Apache Spark streaming in the field.Big data ecosystem overview.Why should you learn Apache Spark streaming?Spark streaming is becoming incredibly popular, and with good reason.According to IBM, Ninety percent of the datain the world today has been created in the last two years alone. Our current output of datais roughly 2.5 quintillion bytes per day. The world is being immersed in data, moreso each and every day. As such, analyzing static dataframes of non-dynamic data becomes the less practical approach to more and more problems. This is where data streaming comes in, the ability to process data almost as soon as its produced, recognizing the time-dependency of the data.ApacheSpark streaming gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world.Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks.Spark also is a powerful engine for streaming data as well as processing it. The synergy between them makes Spark an ideal tool for processing gargantuan data firehoses.Tons of companies, including Fortune 500 companies, are adapting ApacheSpark streaming to extract meaning from massive data streams, today you have access to that same big data technology right on your desktop.What programming language is this ApacheSpark streaming course taught in?This ApacheSpark streamingcourse is taught in Python. Python is currently one of the most popular programming languages in the world! It’s rich data community, offering vast amounts of toolkits and features, makes it a powerful tool for data processing. Using PySpark (thePythonAPI forSpark) you will be able to interact with Apache Spark Streaming’s main abstraction, RDDs, as well as other Spark components, such as Spark SQL and much more!Let’s learn how to write ApacheSpark streaming programs with PySpark Streamingto process big data sources today!30-day Money-back Guarantee!You will get 30-day money-back guarantee from Udemy for this ApacheSpark streaming course.If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked.Are you ready to take your big data analysis skills and career to the next level, take this course now!You will go fromzero to Spark streaming heroin 4 hours.