Functions and OOP in Python | Functions in Python | Spark Training | Edureka | Apache Spark Live -

?PySpark Certification Training: https://www.edureka.co/pyspark-certification-training

This Edureka "Functions and OOP in Python ?" video will help you to understand the Functions and OOPs required in Spark in depth. It includes an example where we Understand what is Python and Apache Spark.

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About the Course

Edureka’s PySpark Certification Training is designed to provide you the knowledge and skills that are required to become a successful Spark Developer using Python and prepare you for the Cloudera Hadoop and Spark Developer Certification Exam (CCA175). Throughout the PySpark Training, you will get an in-depth knowledge of Apache Spark and the Spark Ecosystem, which includes Spark RDD, Spark SQL, Spark MLlib and Spark Streaming. You will also get comprehensive knowledge of Python Programming language, HDFS, Sqoop, Flume, Spark GraphX and Messaging System such as Kafka.

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Spark Certification Training is designed by industry experts to make you a Certified Spark Developer. The PySpark Course offers:
Overview of Big Data & Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator)
Comprehensive knowledge of various tools that falls in Spark Ecosystem like Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming
The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
The power of handling real time data feeds through a publish-subscribe messaging system like Kafka
The exposure to many real-life industry-based projects which will be executed using Edureka’s CloudLab

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Who should go for this course?

Developers and Architects
BI /ETL/DW Professionals
Senior IT Professionals
Mainframe Professionals
Freshers
Big Data Architects, Engineers and Developers
Data Scientists and Analytics Professionals

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There are no such prerequisites for Edureka’s PySpark Training Course. However, prior knowledge of Python Programming and SQL will be helpful but is not at all mandatory.

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For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free)