Spark Programming in Python for Beginners - Apache Spark 3

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SKILL CURB

2:21:23

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1. Introduction

1. Introduction to Apache Spark.mp4

05:13

2. Demo Installing and Running Apache Spark in local mode using cmd.mp4

06:07

3. Demo Configuring Apche Spark in IDE-PyCharm.mp4

08:50

4. Demo Apache Spark in cloud-Databricks.mp4

05:08

2. Spark Architecture and Execution Model

1. Spark Execution Methods.mp4

02:26

2. Distributed Processing Model of Spark.mp4

01:50

3. Demo Working with PySpark Shell.mp4

04:31

4. Demo Creating a Multi-Node Spark Cluster using GCP.mp4

05:14

5. Demo Working with Zeppelin Notebook in cluster.mp4

03:56

3. Spark Programming Model

1. Introduction to DataFrame.mp4

02:10

2. Demo Creating Spark Project Build Configuration.mp4

04:14

3. Demo Configuration Spark Project Application Logs.mp4

06:39

4. Demo Creating and Configuring Spark Session.mp4

13:11

4. Spark Data Sources and Sinks

1. Spark APIs.mp4

03:13

2. Demo Reading CSV, JSON and Parquet Files.mp4

05:16

3. Demo Creating Spark DataFrame Schema.mp4

02:50

4. Demo Writing data using DataFrame Writer and Managing Layouts.mp4

06:52

5. Demo Working with Spark SQL Tables.mp4

07:33

5. Spark DataFrame and DataSets Transformation

1. Demo Working with DataFrame Rows.mp4

03:44

2. Demo DataFrame Rows and Unit Testing.mp4

05:23

3. Demo Working with DataFrame Columns.mp4

07:57

4. Demo Creating and using user-defined Functions.mp4

06:46

6. Aggregations in Apache Spark

1. Demo Simple Aggregations.mp4

03:23

2. Demo Grouping Aggregations.mp4

04:04

3. Demo Windowing Aggregations.mp4

03:22

7. Spark DataFrame Joins

1. Demo Inner Join.mp4

06:48

2. Demo Outer Join.mp4

04:43

Description

Unlock the Power of Apache Spark 3

What You'll Learn?

Basic knowledge of Apache Spark
Apache Spark installation and configuration on local machine as well as on cloud
How to use Spar-shell
Installation of multi-node cluster on Google Cloud Platform
Using clusters in notebooks
Creating and configuring spark session
Creating Spark project Build Configuration
Configuring spark application logs
How to load different file formats in Dataframe
Dataframe and Data sets transformations
Aggregations in spark
Spark Dataframe Joins

Who is this for?

Software Engineers and Architects who are willing to design and develop a Big data Engineering Projects using Apache Spark

Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

What You Need to Know?

Basic Programming Knowledge Using Python Language

A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM

More details

Description
Get ready for the Apache Spark with Python complete course. Gain familiarity with the course details and topics designed to help you succeed.

Apache Sparkâ„¢ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. This course is designed for students, professionals, and people in non-technical roles who are willing to develop a Data Engineering pipeline and application using Apache Spark. The managers and architects, who are not directly involved in the Spark implementation process, are another group of people. Still, they collaborate with those who really put Apache Spark into practice.

Learn Apache Spark with Hands-On Labs
The Spark Programming in Python course is a hands-on practice course designed to teach you the basic and intermediate concepts of spark via practical demonstration through hands-on labs. The course comprises approximately 22 labs starting from the basics and moving to high levels in terms of complexity.

Who should take this course?
The course is intended for software developers who want to build an Apache Spark-based data engineering pipeline and application. The data architects and data engineers who are in charge of creating the data-centric architecture for the company can also benefit from it. The managers and architects, who are not directly involved in the Spark implementation process, are another group of people. Still, they collaborate with those who really put Apache Spark into practice.

Requirements
â— Basic Programming Knowledge Using Python Language
â— A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM
Who this course is for:
â— Software Engineers and Architects who are willing to design and develop Big data Engineering Projects using Apache Spark
â— Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

What youâ€™ll learn
â— Basic knowledge of Apache Spark
â— Apache Spark installation and configuration on the local machine as well as on the cloud
â— How to use Spar-shell
â— Installation of the multi-node cluster on the Google Cloud Platform
â— Using clusters in notebooks
â— Creating and configuring spark session
â— Creating Spark project Build Configuration
â— Configuring spark application logs
â— How to load different file formats in a dataframe
â— Dataframe and Data set transformations
â— Aggregations in spark
â— Spark dataframe Joins

Are there any course requirements or prerequisites?
â— Basic Programming Knowledge Using Python Language
â— A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM

Who this course is for:
â— Software Engineers and Architects who are willing to design and develop Big data Engineering Projects using Apache Spark
â— Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark
Who this course is for:
Software Engineers and Architects who are willing to design and develop a Big data Engineering Projects using Apache Spark
Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

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SkillCurb is in the business of making an impact through creating easy to understand cutting edge technology courses at affordable prices. We are proud to have our co-instructors from around the world that are certified and have years of practical experience working for the fortune 500 companies build quality courses for our students.We focus on the next generation of technology platforms that will prepare our workforce for what's next to come in the future and secure a job in this competitive market.One of our goals is to set aside part of our revenues to charitable causes that focus on providing education to under-privileged students.Some of the key differentiators of our online courses:1: Our instructors are passionate about technology and have been teaching on average for more than 10 years individually.2: We make sure that our Practical Labs in the courses are the center of focus where students can learn to implement real-life use cases necessary to succeed at work.3: All our courses have Capstone projects in the end where students can apply the skills learnt during the course and create awesome projects which can be showcased on their resumes and interviews.4: All our lectures have Quizzes in the end which forces the student to start applying the key principles learnt.5: We make sure that all complex ideas are broken down and Visually Explained for the students rather than showing them long winded text which at times is hard to conceptualize.6: We make sure that our instructors communicate clearly and are highly proficient in delivering lectures in English.7: We also try to add bonus reference material for the students that they can use for future reference i.e interview questions with answers and additional coding challenges with solutions.

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