Learn Spark Programming: A Comprehensive Introduction Course

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Introduction to Spark Programming Course Overview

The Introduction to Spark Programming certification is a recognition of an individual's proficiency in Apache Spark, one of the most renowned open-source distributed computing systems built for big data processing and analytics. Primely, the certificate validates the individual's capability to leverage Spark in processing large data sets across clusters with rapid processing speed and user-friendly interfaces. Industries use Spark programming widely in machine learning, interactive querying, and stream processing. Basic concepts include Spark architecture, Spark Shell, Spark applications, and Resilient Distributed Datasets. With the certification, professionals can handle tasks such as data ingestion, queries, machine learning algorithms, and data visualization more efficiently, providing valuable insights for their companies.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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The 1-on-1 Advantage

Get 1-on-1 session with our expert trainers at a date & time of your convenience.
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Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
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4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.
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Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

Module 1: Scala Ramp Up
  • Scala Introduction, Variables, Data Types, Control Flow
  • The Scala Interpreter
  • Collections and their Standard Methods (e.g. map())
  • Functions, Methods, Function Literals
  • Class, Object, Trait, case Class
  • Overview, Motivations, Spark Systems
  • Spark Ecosystem
  • Spark vs. Hadoop
  • Acquiring and Installing Spark
  • The Spark Shell, SparkContext
  • RDD Concepts, Lifecycle, Lazy Evaluation
  • RDD Partitioning and Transformations
  • Working with RDDs - Creating and Transforming (map, filter, etc.)
  • Overview
  • SparkSession, Loading/Saving Data, Data Formats (JSON, CSV, Parquet, text ...)
  • Introducing DataFrames and DataSets (Creation and Schema Inference)
  • Supported Data Formats (JSON, Text, CSV, Parquet)
  • Working with the DataFrame (untyped) Query DSL (Column, Filtering, Grouping, Aggregation)
  • SQL-based Queries
  • Working with the DataSet (typed) API
  • Mapping and Splitting (flatMap(), explode(), and split())
  • DataSets vs. DataFrames vs. RDDs
  • Grouping, Reducing, Joining
  • Shuffling, Narrow vs. Wide Dependencies, and Performance Implications
  • Exploring the Catalyst Query Optimizer (explain(), Query Plans, Issues with lambdas)
  • The Tungsten Optimizer (Binary Format, Cache Awareness, Whole-Stage Code Gen)
  • Caching - Concepts, Storage Type, Guidelines
  • Minimizing Shuffling for Increased Performance
  • Using Broadcast Variables and Accumulators
  • General Performance Guidelines
  • Core API, SparkSession.Builder
  • Configuring and Creating a SparkSession
  • Building and Running Applications - sbt/build.sbt and spark-submit
  • Application Lifecycle (Driver, Executors, and Tasks)
  • Cluster Managers (Standalone, YARN, Mesos)
  • Logging and Debugging
  • Introduction and Streaming Basics
  • Spark Streaming (Spark 1.0+)
  • DStreams, Receivers, Batching
  • Stateless Transformation
  • Windowed Transformation
  • Stateful Transformation
  • Structured Streaming (Spark 2+)
  • Continuous Applications
  • Table Paradigm, Result Table
  • Steps for Structured Streaming
  • Sources and Sinks
  • Consuming Kafka Data
  • Kafka Overview
  • Structured Streaming - 'kafka' format
  • Processing the Stream
Live Online Training (Duration : 32 Hours) Fee On Request
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
Date On Request
Course Prerequisites
- Basic knowledge of the Scala programming language
- Understanding of SQL Language
- Familiarity with Java, Python or R Programming
- Basic knowledge of Big Data concepts and Distributed Computing.
- Familiarity with Linux or Unix-based systems is beneficial but not mandatory.

Introduction to Spark Programming Certification Training Overview

Spark Programming certification training is designed to provide knowledge and skills to become a successful Spark Developer. The course covers core concepts such as Spark architecture, Spark components like Spark Streaming and Mllib, and Spark RDD, along with coding exercises in Scala and Python. The training also explores real-time data processing, machine learning, and graph processing with Spark. Through this course, participants can gain expertise in SparK SQL, creating Spark applications, and employing Spark with Hadoop clusters.

Why Should You Learn Introduction to Spark Programming?

Learning Introduction to Spark Programming course in stats can greatly enhance your data processing skills. It enables efficient data analysis on large datasets, offering real-time processing capabilities. The course also provides knowledge on Spark’s MLlib, enhancing machine learning proficiency. With increased demand for professionals in big data analytics, this course can boost your career prospects.

Target Audience for Introduction to Spark Programming Certification Training

- Professionals involved in Big Data Analysis
- Data Scientists and statisticians
- Technology Architects
- Software Engineers and Programmers
- Aspiring Data Engineers
- Individuals interested in learning Spark
- IT and analytics managers

Why Choose Koenig for Introduction to Spark Programming Certification Training?

- Access to Certified Instructors who provide expert guidance and thorough understanding of Spark Programming.
- Opportunities to Boost Your Career by learning in-demand Spark Programming skills.
- Customized Training Programs designed to suit individual learning requirements and pace.
- Unique Destination Training that offers chances to explore new cultures, environments, and networking opportunities.
- Affordable Pricing system, ensuring value for money without compromising on the quality of training.
- Recognition as a Top Training Institute offering trusted and reliable training services.
- Flexibility in choosing training dates according to personal schedule availability.
- Interactive Instructor-Led Online Training that offers real-time education and communication.
- Wide Range of Courses, providing the option to choose from a vast array of relevant courses.
- Accredited Training ensures your qualifications are recognized and respected globally.

Introduction to Spark Programming Skills Measured

After completing the Introduction to Spark Programming certification training, an individual can learn essential skills like understanding the basics of Apache Spark and its Ecosystem, working with RDD in Spark, understanding Spark Streaming, Machine Learning Libraries (MLlib) and Graph Processing. Additionally, they can gain knowledge on Hadoop Distributed File System (HDFS) and learn the architecture of Spark SQL and context. Further, capabilities to develop Spark applications using real-time use cases will also be honed.

Top Companies Hiring Introduction to Spark Programming Certified Professionals

Top companies hiring professionals certified in Introduction to Spark Programming include leading tech and data-focused organizations like IBM, Amazon, Microsoft, Google, Databricks and Oracle. These companies value Spark's ability to process large datasets, and seek certified professionals to harness the power of this big data tool in developing innovative solutions.

Learning Objectives - What you will Learn in this Introduction to Spark Programming Course?

By the end of the Introduction to Spark Programming course, students should be able to comprehend the fundamentals of Apache Spark, a vital tool in the Big Data ecosystem. They should acquire proficiency in using Spark's interactive APIs for big data processing and understand how to integrate it with various data sources. The learners will also gain knowledge in Spark SQL for structured data manipulation and will be able to implement broadcast and accumulator concepts. Finally, they will understand how to configure, manage, and monitor Spark applications and should be capable of developing proficient Spark applications using RDD transformations and actions.

FAQ's


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1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, fee excludes local taxes.
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Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).

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