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PySpark Tutorial | PySpark Tutorial For Beginners | Apache Spark With Python Tutorial | Simplilearn

PySpark Tutorial | PySpark Tutorial For Beginners | Apache Spark With Python Tutorial | Simplilearn

This presentation about PySpark will help you understand what PySpark is, the different features of PySpark, and the comparison of Spark with Python and Scala. Then, you will learn the various PySpark contents - SparkConf, SparkContext, SparkFiles, RDD, StorageLevel, DataFrames, Broadcast and Accumulator. You will get an idea about the various Sub packages in PySpark. Finally, you will look at a demo using PySpark SQL to analyze Walmart Stocks data. Now, let's dive into learning PySpark in detail. 1. What is PySpark? 2. PySpark Features 3. PySpark with Python and Scala 4. PySpark Contents 5. PySpark Sub packages 6. Companies using PySpark 7. Demo using PySpark What is this Big Data Hadoop training course about? The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. What are the course objectives? Simplilearnu2019s Apache Spark and Scala certification training are designed to: 1. Advance your expertise in the Big Data Hadoop Ecosystem 2. Help you master essential Apache and Spark skills, such as Spark Streaming, Spark SQL, machine learning programming, GraphX programming and Shell Scripting Spark 3. Help you land a Hadoop developer job requiring Apache Spark expertise by giving you a real-life industry project coupled with 30 demos What skills will you learn? By completing this Apache Spark and Scala course you will be able to: 1. Understand the limitations of MapReduce and the role of Spark in overcoming these limitations 2. Understand the fundamentals of the Scala programming language and its features 3. Explain and master the process of installing Spark as a standalone cluster 4. Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark 5. Master Structured Query Language (SQL) using SparkSQL 6. Gain a thorough understanding of Spark streaming features 7. Master and describe the features of Spark ML programming and GraphX programming Learn more at https://www.simplilearn.com/big-data-and-analytics/apache-spark-scala-certification-training

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