Apache Spark 3 - Beyond Basics and Cracking Job Interviews

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Offered byUDEMY

Apache Spark 3 - Beyond Basics and Cracking Job Interviews
at
UDEMY
Overview

Learn PySpark Advanced Skills and Prepare for Certification and Job Interviews

Duration	4 hours
Total fee	₹649
Mode of learning	Online
Credential	Certificate

Apache Spark 3 - Beyond Basics and Cracking Job Interviews
at
UDEMY
Highlights

Earn a certificate of completion from Udemy
Get full lifetime access of the course material
Comes with 30 days money back guarantee

Apache Spark 3 - Beyond Basics and Cracking Job Interviews
at
UDEMY
Course details

Skills you will learn

Spark Apache

Who should do this course?

For Anyone who wants to learn and develop Advanced Skills in Apache Spark
For Those wo are preparing for Job Interviews and want to learn advanced skills

What are the course deliverables?

Apache Spark 3 Advanced Topics and Concept
Deep Dive in to Spark 3 Architecture and Memory Management
Learn AQE, DPP, Broadcast, Accumulators, and Multithreading in Spark 3

More about this course

In this course, you will learn some advanced Spark skills that we have already collected as feedback from various students and professionals
This course also covers some advanced topics and concepts that are asked in the Databricks Spark certification exam
It is also possible that you are working on some project, and you faced some scenarios which you couldn't solve or fix, come back here and share them with me

Apache Spark 3 - Beyond Basics and Cracking Job Interviews
at
UDEMY
Curriculum

Before you begin

Course Introduction

Spark Architecture

Spark Cluster and Runtime Architecture

Spark Submit and Important Options

Deploy Modes - Client and Cluster mode

Spark Jobs - Stage, Shuffle, Task, Slots

Spark SQL Engine and Query Planning

Lets Practice - Quiz 1 Solution Video

Lets Practice - Quiz 2 Solution Video

Performance and Applied Understanding

Spark Memory Allocation

Spark Memory Management

Spark Adaptive Query Execution

Spark AQE Dynamic Join Optimization

Handling Data Skew in Spark Joins

Spark Dynamic Partition Pruning

Data Caching in Spark

Repartition and Coalesce

Dataframe Hints

Broadcast Variables

Accumulators

Speculative Execution

Dynamic Resource Allocation

Spark Schedulers

Lets Practice - Quiz 3 Solution Video

Lets Practice - Quiz 4 Solution Video

Open Ended Topics

Help me add more content - Demand for more

Apache Spark 3 - Beyond Basics and Cracking Job Interviews
at
UDEMY
Faculty details

Prashant Kumar Pandey

Prashant Kumar Pandey is passionate about helping people to learn and grow in their career by bridging the gap between their existing and required skills. In his quest to fulfill this mission, he is authoring books, publishing technical articles, and creating training videos to help IT professionals and students succeed in the industry.