This video on PySpark Tutorial 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 Subpackages 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? 00:31
2. PySpark Features 06:30
3. PySpark with Python and Scala 07:22
4. PySpark Contents 09:03
5. PySpark Subpackages 48:39
6. Companies using PySpark 49:45
7. Demo using PySpark 50:17
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This Apache Spark and Scala certification training is designed to advance your expertise working with the Big Data Hadoop Ecosystem. You will master essential skills of the Apache Spark open source framework and the Scala programming language, including Spark Streaming, Spark SQL, machine learning programming, GraphX programming, and Shell Scripting Spark. This Scala Certification course will give you vital skillsets and a competitive advantage for an exciting career as a Hadoop Developer.
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?
Simplilearn’s 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
Who should take this Scala course?
1. Professionals aspiring for a career in the field of real-time big data analytics
2. Analytics professionals
3. Research professionals
4. IT developers and testers
5. Data scientists
6. BI and reporting professionals
7. Students who wish to gain a thorough understanding of Apache Spark
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