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Apache Spark and Scala Training Overview
Apache Spark and Scala Training Course outline
Module 1: Introduction to Scala
- Introduction to Scala and Development of Scala for Big Data Applications
- Apache Spark
Module 2: Pattern Matching
- Introduction to Pattern Matching
- Uses of Scala
- Concept of REPL (Read Evaluate Print Loop)
- Deep Drive into Scala Pattern Matching
- Type Interface and Higher-Order Function
- Currying and Traits
Module 3: Executing the Scala Code
- Introduction to Scala Interpreter
- Creating Static Members with Companion Objects
- Implicit Classes in Scala
- Different Classes in Scala
Module 4: Classes Concepts in Scala
- Understanding the Constructor Overloading
- Different Abstract Classes
- Hierarchy Types in Scala
- Concept of Object Equality and Val and Var Methods in Scala
Module 5: Concepts of Traits with Example
- Introduction to Traits in Scala
- When to Use Traits?
- Linearisation of Traits and the Java Equivalent
- Boilerplate Code
Module 6: Scala Java Interoperability and Scala Collection
- Implementation of Traits in Scala and Java
- Handling of Multiple Traits Extending
- Introduction to Scala Collections
- Classification of Collections
- Difference Between Iterator and Iterable in Scale
- List and Sequence in Scala
Module 7: Mutable Collections vs Immutable Collections
- Types of Collections in Scala
- Lists and Arrays in Scala
- List Buffer and Array Buffer
- Queue in Scala
- Stacks and Sets
- Maps and Tuples in Scala
Module 8: Introduction to Spark
- What are Spark and Spark Stack?
- Ways to Resolve Hadoop Drawbacks
- Interactive Operations on Map Reduce
- Spark Hadoop YARN
- HDFS and YARN Revision
- How it is Better Hadoop?
- Deploying Spark Without Hadoop
- Spark History Server
- Cloudera Distribution
Module 9: Spark Basics
- Spark Installation
- Memory Management
- Concept of Resilient Distributed Datasets (RDD)
- Functional Programming in Spark
Module 10: Working with RDDs in Spark
- Creating RDDs
- Operations and Transformation in RDD
- RDD Partitioning
- FlatMap Method
- Scala Map Count
- Saveastextfiles
- Pair RDD Functions
Module 11: Aggregating Data with Pair RDDs
- Introduction to Key-Value Pair in RDDs
- How Spark Makes Map-Reduce Operations Faster?
Module 12: Writing and Deploying Spark Applications
- Difference Between Spark and Scala
- Set and Set Operations
- List and Tuple
- Concatenating List
- Install Apache Maven
Module 13: Parallel Processing
- Spark Parallel Processing
- Setup Spark Master Code
- Introduction to Spark Partitions
- Data Locality in Hadoop
- Comparing Repartition and Coalesce
- Actions of Spark
Module 14: Spark RDD Persistence
- Execution Flow in Spark
- RDD Persistence Overview
- Spark Terminology
- Distribution Shared Memory vs RDD
- ReduceByKey and SortByKey and AggregateByKey
Module 15: Spark Streaming and Mila
- Introduction to Spark Streaming
- What is Spark Streaming?
- Aspects of Spark Streaming
- How does Spark Streaming Work?
- Broadcast Variables
- Accumulator
Module 16: Spark Variables and RDD Operations
- Variables in Spark
- Numeric RDD Operations
Module 17: Scheduling or Partitioning
- Partitioning in Spark
- Hash Partition and Range Partition
- Scheduling within and Around Applications
- Map Partition with Index
- GroupByKey
- Spark Master High Availability
- Standby Masters with Zookeeper
Who should attend this Apache Spark and Scala Training Course?
The Apache Spark and Scala Training Course is a specialised that helps professionals to gain expertise in the Big Data Analytics and Distributed Computing sector. This course can be beneficial for a wide range of professionals, including:
- Software Developer
- Data Scientists
- Data Engineers
- Business Analysts
- Systems Architects
- Database Administrators
- Data Journalists
- Project Managers
Prerequisites of the Apache Spark and Scala Training Course
For attending this Apache Spark and Scala Training Course, a basic knowledge of Java, Database, Query Language, and SQL would be beneficial for delegates.
Apache Spark and Scala Training Course Overview
Apache Spark and Scala have emerged as pivotal tools in the world of Big Data Processing and Analytics. Apache Spark is a robust open-source data processing framework combined with Scala, a high-performance programming language that offers a scalable solution. This course is designed for software developers and IT professionals who can benefit from understanding these technologies to build efficient data processing pipelines.
Proficiency in Apache Spark and Scala is crucial in today's data-driven landscape. It empowers data engineers, data scientists, and analysts to process and analyse large datasets swiftly, enabling data-driven decision-making. For professionals in fields like data science, machine learning, and big data analytics, mastering Spark and Scala is essential.
This intensive 2-day training is designed to provide delegates with a solid foundation in Apache Spark and Scala. Delegates will gain hands-on experience in working with these technologies, learning to develop efficient data processing pipelines, working with distributed datasets, and applying advanced analytics techniques. The course combines theoretical knowledge with practical exercises, ensuring that delegates can immediately apply what they learn in their professional roles.
Course Objectives
- To learn how to work with distributed data using Spark RDDs
- To explore Spark's DataFrame and Dataset APIs for structured data processing
- To master the art of data manipulation, transformation, and analysis with Spark
- To develop Spark applications and perform data processing tasks
- To discover the integration of Spark with popular data sources and tools
- To implement real-world use cases and best practices for Spark and Scala
Upon completing this course, delegates will benefit from a solid foundation in Apache Spark and Scala. They will possess the practical skills and knowledge required to handle and analyse big data effectively, enabling them to excel in their data analytics roles. This course is a valuable investment in their professional development and opens doors to various opportunities in the world of big data analytics.
What’s included in this Apache Spark and Scala Training Course?
- World-Class Training Sessions from Experienced Instructors
- Apache Spark and Scala Certificate
- Digital Delegate Pack
Why choose us
Ways to take this course
Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Apache Spark and Scala Training. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.
Live classes
Join a scheduled class with a live instructor and other delegates.
Interactive
Engage in activities, and communicate with your trainer and peers.
Global Pool of the Best Trainers
We handpick from a global pool of expert trainers for our Online Instructor-led courses.
Expertise
With 10+ years of quality, instructor-led training, we equip professionals with lasting skills for success.
Global Reach
With classes running in all timezones, access any of our courses and course material from anywhere, anytime.
Unlock your potential with The Knowledge Academy's Apache Spark and Scala Training, accessible anytime, anywhere on any device. Enjoy 90 days of online course access, extendable upon request, and benefit from the support of our expert trainers. Elevate your skills at your own pace with our Online Self-paced sessions.
What our customers are saying
Apache Spark and Scala Training FAQs
The Apache Spark and Scala Training at The Knowledge Academy focuses on equipping learners with the skills to efficiently process big data using Apache Spark, a fast and general-purpose cluster computing system. The training also covers Scala, a powerful programming language used to develop Spark applications, making it ideal for data analysis and processing.
This training is ideal for Data Professionals, Developers, and IT specialists who want to enhance their skills in big data processing. Whether you are an aspiring data engineer or an experienced software developer, this course will help you advance your career with cutting-edge knowledge.
The course covers key topics such as Spark Core, Spark SQL, Spark Streaming, and MLlib for machine learning, as well as an introduction to Scala. You’ll learn how to build real-time data processing pipelines, work with large datasets, and create scalable applications.
There are no formal prerequisites to attend this course. However, a basic knowledge of programming languages like Python or Java, and familiarity with data processing concepts, will be helpful.
Apache Spark is known for its speed, ease of use, and support for a wide range of applications, from batch processing to real-time data streaming. It also integrates well with popular big data tools, making it a versatile platform for data engineers and analysts.
While both Scala and Spark are important, it's recommended to start with Scala, as it provides the programming foundation to build Spark applications. Learning Scala first will help you understand the syntax and functional programming concepts essential for Spark development.
The best way to learn Apache Spark is through hands-on practice and guided training. At The Knowledge Academy, our practical, real-world exercises and expert instruction ensure you gain both theoretical knowledge and applied skills to work effectively with Spark.
Online training offers flexibility and convenience, allowing you to learn at your own pace and from anywhere. You'll have access to expert trainers, interactive sessions, and real-world projects that will help you apply your knowledge effectively.
You'll need a basic understanding of programming and data processing concepts. Familiarity with distributed computing and cloud services will also be beneficial, though our course covers the essential skills needed to master Spark and Scala.
No, this training is suitable for both beginners and experienced professionals. Whether you're new to big data or looking to enhance your existing skill set, the course content is designed to accommodate learners of various levels.
The course includes comprehensive study materials, hands-on projects, access to expert instructors, and real-world case studies. You’ll also gain access to interactive sessions and practice exercises to reinforce your learning.
The Apache Spark and Scala Training course spans 2 days.
Yes, The Knowledge Academy provides continuous access to a wide range of resources, including recorded sessions, study materials, and expert support. Additionally, you can join our community of professionals to stay updated with the latest trends.
You will learn how to efficiently process large-scale data using Apache Spark, build real-time applications, and develop Spark projects using Scala. The training will also cover data manipulation, machine learning, and stream processing techniques.
After completing the training, you can pursue advanced certifications in data science or big data engineering. You may also consider gaining practical experience by applying your newly acquired skills to real-world projects or contributing to open-source platforms.
This training opens doors to numerous career opportunities in big data, data engineering, and machine learning. Apache Spark is in high demand across various industries, and this course will give you the skills to excel in these growing fields.
Yes, you will have continued access to all course materials, recorded sessions, and other valuable resources even after the training is completed, allowing you to revisit the content whenever you need to.
Upon successful completion of the course, you will receive a globally recognised certification from The Knowledge Academy, validating your expertise in Apache Spark and Scala.
You can attend the Apache Spark and Scala Training by visiting The Knowledge Academy’s website, selecting your preferred course option, and completing the registration process. Our support team is always available to assist you.
Completing this course can lead to roles such as Big Data Engineer, Data Analyst, Spark Developer, and Machine Learning Engineer. These positions are in high demand in industries such as technology, finance, and healthcare, offering excellent career prospects.
The Knowledge Academy stands out as a prestigious training provider known for its extensive course offerings, expert instructors, adaptable learning formats, and industry recognition.
The training fees for Apache Spark and Scala Trainingin Canada starts from CAD4295
The Knowledge Academy is the Leading global training provider for Apache Spark and Scala Training.
Please see our Big Data and Analytics Training courses available in Canada
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Best price in the industry
You won't find better value in the marketplace. If you do find a lower price, we will beat it.
Many delivery methods
Flexible delivery methods are available depending on your learning style.
High quality resources
Resources are included for a comprehensive learning experience.
"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"
Joshua Davies, Thames Water
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