PySpark Installation | Configure Jupyter Notebook with PySpark | PySpark Tutorial | Edureka




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** PySpark Certification Training: https://www.edureka.co/pyspark-certification-training **
This Edureka video on PySpark Installation will provide you with step by step installation of PySpark on a Linux Environment. This video is on CentOs but the steps are the same for Ubuntu as well. It will also provide you with the hardware as well as the software requirements for the installation. This video covers the following topics:

1.Hardware Requirements
2. Software Requirements
3. Installation Process
4. PySpark Demo

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About the Course

Edureka’s PySpark Certification Training is designed to provide you with 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 fall 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
Projects which are diverse in nature covering banking, telecommunication, social media, and government domains
Rigorous involvement of an SME throughout the Spark Training to learn industry standards and best practices

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Who should go for this course?

The market for Big Data Analytics is growing tremendously across the world and such a strong growth pattern followed by market demand is a great opportunity for all IT Professionals. Here are a few Professional IT groups, who are continuously enjoying the benefits and perks of moving into the Big Data domain.

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 sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free).

Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

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Comment List

  • edureka!
    November 25, 2020

    Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka PySpark Certification Training Curriculum, Visit the website: http://bit.ly/2GLH4nk

  • edureka!
    November 25, 2020

    helpful video. Thanks

  • edureka!
    November 25, 2020

    excellent

  • edureka!
    November 25, 2020

    sudo yum install pip is not working

  • edureka!
    November 25, 2020

    nice quick video i have a question:
    i have vm already running on mmy machine for sas. when i created another vm (say test-spark) it gave me an error: fatal: no bootable medium found! system halted. what am i getting wrong?

  • edureka!
    November 25, 2020

    You can deploy instance in GCP(google cloud platform) for free where there no need of this hardware.

  • edureka!
    November 25, 2020

    how to install pyspark (jupyter) in windows or cloudera ?
    please help !

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