PySpark
Big Data with Apache Spark PySpark: Hands on PySpark, Python
Classes : 20 Days : 2 months Duration : Weekdays / Weekends
This tutorial presents effective, time-saving techniques on how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Apache Spark architecture and how to set up a Python environment for Spark.
You`ll learn about different techniques for collecting data, and distinguish between (and understand) techniques for processing data. Next, we provide an in-depth review of RDDs and contrast them with DataFrames. We provide examples of how to read data from files and from HDFS and how to specify schemas using reflection or programmatically (in the case of DataFrames).The concept of lazy execution is described and we outline various transformations and actions specific to RDDs and DataFrames.
Finally, we show you how to use SQL to interact with DataFrames. By the end of this tutorial, you will have learned how to process data using Spark DataFrames and mastered data collection techniques by distributed data processing.
Who this course is for:
If you are a Python developer keen to master hands-on techniques using the Apache Spark 2.x ecosystem in the best possible manner, this course is for you.
You`ll learn about different techniques for collecting data, and distinguish between (and understand) techniques for processing data. Next, we provide an in-depth review of RDDs and contrast them with DataFrames. We provide examples of how to read data from files and from HDFS and how to specify schemas using reflection or programmatically (in the case of DataFrames).The concept of lazy execution is described and we outline various transformations and actions specific to RDDs and DataFrames.
Finally, we show you how to use SQL to interact with DataFrames. By the end of this tutorial, you will have learned how to process data using Spark DataFrames and mastered data collection techniques by distributed data processing.
Who this course is for:
If you are a Python developer keen to master hands-on techniques using the Apache Spark 2.x ecosystem in the best possible manner, this course is for you.
-A firm understanding of Python is expected to get the best out of the course. Familiarity with Spark would also be helpful.
A Brief Primer on PySpark
Resilient Distributed Datasets
Resilient Distributed Datasets and Actions
DataFrames and Transformations
Data Processing with Spark DataFrames
Resilient Distributed Datasets
Resilient Distributed Datasets and Actions
DataFrames and Transformations
Data Processing with Spark DataFrames
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Student Reviews
Bhawana
Fabulous NLP + ML course
I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.
Harish
Excellent ML course!
The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.