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Apache Spark and Scala Certification Training Course
Apache Spark and Scala Certification Training Course
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Why enroll for Apache Spark and Scala Training?
Apache Spark and Scala Training Benefits
There are several industries making significant investments in big data analytics, including banking, retail, manufacturing, finance, healthcare, and government to make more informed business decisions. That translates into a range of jobs being created within each sector, for which individuals with this expertise will be needed. It is also being forecasted that the rise in demand for these roles far outweighs the current supply. Spark and Scala certification will certainly enhance your chance of landing a good job with handsome salary.
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Why Apache Spark and Scala Training from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your Apache Spark and Scala Training
Skills Covered
Tools Covered
Spark and Scala Certification Training Course Curriculum
Curriculum Designed by Experts
Introduction to Big Data Hadoop and Spark
18 Topics
Topics:
- What is Big Data?
- Big Data Customer Scenarios
- Limitations and Solutions of Existing Data Analytics Architecture with Uber Use Case
- How Hadoop Solves the Big Data Problem?
- What is Hadoop?
- Hadoop’s Key Characteristics
- Hadoop Ecosystem and HDFS
- Hadoop Core Components
- Rack Awareness and Block Replication
- YARN and its Advantage
- Hadoop Cluster and its Architecture
- Hadoop: Different Cluster Modes
- Hadoop Terminal Commands
- Big Data Analytics with Batch & Real-time Processing
- Why Spark is needed?
- What is Spark?
- How Spark differs from other frameworks?
- Spark at Yahoo!
![skill]( "Hands On Experience")
- Hadoop terminal commands
![skill]( "skill you will learn")
- Hadoop components and its architecture
- Storing data in HDFS
- Working with HDFS commands
Introduction to Scala for Apache Spark
10 Topics
Topics:
- What is Scala?
- Why Scala for Spark?
- Scala in other Frameworks
- Introduction to Scala REPL
- Basic Scala Operations
- Variable Types in Scala
- Control Structures in Scala
- Foreach loop, Functions and Procedures
- Collections in Scala- Array
- ArrayBuffer, Map, Tuples, Lists, and more
![skill]( "Hands On Experience")
- Control structures in Scala
- Working with various looping statements
- Implementing collections in Scala
![skill]( "skill you will learn")
- Writing Basic Scala Programs
- Working with Collections in Scala
Functional Programming and OOPs Concepts in Scala
12 Topics
Topics:
- Functional Programming
- Higher Order Functions
- Anonymous Functions
- Class in Scala
- Getters and Setters
- Custom Getters and Setters
- Properties with only Getters
- Auxiliary Constructor and Primary Constructor
- Singletons
- Extending a Class
- Overriding Methods
- Traits as Interfaces and Layered Traits
![skill]( "Hands On Experience")
- Creating objects and classes
- Working with higher order functions
- Creating constructors in Scala
![skill]( "skill you will learn")
- Implementing OOPs Concepts
- Functional Programming
Deep Dive into Apache Spark Framework
8 Topics
Topics:
- Spark’s Place in Hadoop Ecosystem
- Spark Components & its Architecture
- Spark Deployment Modes
- Introduction to Spark Shell
- Writing your first Spark Job Using SBT
- Submitting Spark Job
- Spark Web UI
- Data Ingestion using Sqoop
![skill]( "Hands On Experience")
- Building and Running Spark Application
- Spark Application Web UI
- Configuring Spark Properties
- Data ingestion using Sqoop
![skill]( "skill you will learn")
- Writing basic Sprk application
- Spark architecture and its components
- Ingesting structured data into HDFS
Playing with Spark RDDs
11 Topics
Topics:
- Challenges in Existing Computing Methods
- Probable Solution & How RDD Solves the Problem
- What is RDD, It’s Operations, Transformations & Actions
- Data Loading and Saving Through RDDs
- Key-Value Pair RDDs
- Other Pair RDDs, Two Pair RDDs
- RDD Lineage
- RDD Persistence
- WordCount Program Using RDD Concepts
- RDD Partitioning & How It Helps Achieve Parallelization
- Passing Functions to Spark
![skill]( "Hands On Experience")
- Loading data in RDDs
- Saving data through RDDs
- RDD Transformations
- RDD Actions and Functions
- RDD Partitions
- WordCount through RDDs
![skill]( "skill you will learn")
- Transformations and actions in Spark
- Implementing RDDs in Spark
DataFrames and Spark SQL
10 Topics
Topics:
- Need for Spark SQL
- What is Spark SQL?
- Spark SQL Architecture
- SQL Context in Spark SQL
- User Defined Functions
- Data Frames & Datasets
- Interoperating with RDDs
- JSON and Parquet File Formats
- Loading Data through Different Sources
- Spark – Hive Integration
![skill]( "Hands On Experience")
- Spark SQL – Creating Data Frames
- Loading and Transforming Data through Different Sources
- Stock Market Analysis
- Spark-Hive Integration
![skill]( "skill you will learn")
- Working with DataFrame API
- Querying structured data using Spark SQL
- Integrating Spark with Hive
Machine Learning using Spark MLlib
8 Topics
Topics:
- Why Machine Learning?
- What is Machine Learning?
- Where Machine Learning is Used?
- Face Detection: USE CASE
- Different Types of Machine Learning Techniques
- Introduction to MLlib
- Features of MLlib and MLlib Tools
- Various ML algorithms supported by MLlib
![skill]( "Hands On Experience")
- Face detection use case
![skill]( "skill you will learn")
- Understanding machine learning
- Functions and features of MLlib
Deep Dive into Spark MLlib
3 Topics
Topics:
- Supervised Learning - Linear Regression, Logistic Regression, Decision Tree, Random Forest
- Unsupervised Learning - K-Means Clustering & How It Works with MLlib
- Analysis on US Election Data using MLlib (K-Means)
![skill]( "Hands On Experience")
- Machine Learning MLlib
- K- Means Clustering
- Linear Regression
- Logistic Regression
- Decision Tree
- Random Forest
![skill]( "skill you will learn")
- Working with machine learning algorithms
- Implementing Spark MLlib
Understanding Apache Kafka and Apache Flume
16 Topics
Topics:
- Need for Kafka
- What is Kafka?
- Core Concepts of Kafka
- Kafka Architecture
- Where is Kafka Used?
- Understanding the Components of Kafka Cluster
- Configuring Kafka Cluster
- Kafka Producer and Consumer Java API
- Need of Apache Flume
- What is Apache Flume?
- Basic Flume Architecture
- Flume Sources
- Flume Sinks
- Flume Channels
- Flume Configuration
- Integrating Apache Flume and Apache Kafka
![skill]( "Hands On Experience")
- Configuring Single Node Single Broker Cluster
- Configuring Single Node Multi Broker Cluster
- Producing and consuming messages
- Flume Commands
- Setting up Flume Agent
- Streaming Twitter Data into HDFS
![skill]( "skill you will learn")
- Ingesting unstructured data into HDFS
- Working with Kafka command line tools
Apache Spark Streaming - Processing Multiple Batches
12 Topics
Topics:
- Drawbacks in Existing Computing Methods
- Why Streaming is Necessary?
- What is Spark Streaming?
- Spark Streaming Features
- Spark Streaming Workflow
- How Uber Uses Streaming Data
- Streaming Context & DStreams
- Transformations on DStreams
- Describe Windowed Operators and Why it is Useful
- Important Windowed Operators
- Slice, Window and ReduceByWindow Operators
- Stateful Operators
![skill]( "Hands On Experience")
- Creating a DStream
- Transformation on DStreans
- Creating streaming context
![skill]( "skill you will learn")
- Working with DStream API
Apache Spark Streaming - Data Sources
5 Topics
Topics:
- Apache Spark Streaming: Data Sources
- Streaming Data Source Overview
- Apache Flume and Apache Kafka Data Sources
- Example: Using a Kafka Direct Data Source
- Perform Twitter Sentimental Analysis Using Spark Streaming
![skill]( "Hands On Experience")
- Different Streaming Data Sources
- Integrating Spark with Kafka and Flume
- Twitter Sentimental Analysis
![skill]( "skill you will learn")
- Real time data processing
- Building data pipelines
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Apache Spark Course Description
About the Apache Spark and Scala Online Course
The Apache Spark Certification Training Course is designed to provide you with the knowledge and skills to become a successful Big Data & Spark Developer. This training will help you clear the CCA Spark and Hadoop Developer (CCA175) Examination. You will understand the basics of Big Data and Hadoop, along with how Spark enables in-memory data processing and runs much faster than Hadoop MapReduce. This course also covers RDDs, Spark SQL for structured processing, and different APIs offered by Spark, such as Spark Streaming and Spark MLlib. This Scala online course is an integral part of a Big Data Developer’s career path. It will also encompass fundamental concepts such as data capturing using Flume, data loading using Sqoop, and messaging systems like Kafka, etc.
What are the prerequisites for our Spark and Scala Certification Training?
There are no specific prerequisites for our Spark Scala Certification Training. However, prior knowledge of Java Programming and SQL will be helpful but not mandatory.
What are the objectives of our Online Spark Training Course?
The Spark Certification Training is designed by industry experts to make you a Certified Spark Developer. The Spark Scala Course offers:
- An overview of Big Data & Hadoop, including HDFS (Hadoop Distributed File System) and YARN (Yet Another Resource Negotiator).
- Comprehensive knowledge of various tools that fall in the Spark Ecosystem, such as Spark SQL, Spark MlLib, Sqoop, Kafka, Flume, and Spark Streaming.
- The capability to ingest data in HDFS using Sqoop & Flume and analyze those large datasets stored in the HDFS.
- The power to handle real-time data feeds through a publish-subscribe messaging system like Kafka.
- Exposure to many real-life industry-based projects that will be executed using Edureka’s CloudLab.
- Projects that are diverse in nature, covering banking, telecommunications, social media, and government domains.
- Rigorous involvement of an SME throughout the Spark Training to learn industry standards and best practices.
Why should you go for Online Spark Training?
Spark is one of the fastest-growing and widely used tools for Big Data & Analytics. It has been adopted by multiple companies in various domains around the globe and, therefore, offers promising career opportunities. To take part in these kinds of opportunities, you need structured training that is aligned with Cloudera Hadoop and Spark Developer Certification (CCA175) and current industry requirements and best practices. Besides strong theoretical understanding, it is essential to have strong hands-on experience. Hence, during Edureka’s Spark and Scala course, you will be working on various industry-based use cases and projects incorporating big data and Spark tools as part of the solution strategy. Additionally, all your doubts will be addressed by industry professionals currently working on real-life big data and analytics projects.
What are the skills that you will be learning with our Spark Certification Training?
Edureka’s Spark Training is designed to help you become a successful Spark developer. During this course, our expert instructors will train you to:
- Write Scala Programs to build Spark Application
- Master the concepts of HDFS
- Understand Hadoop 2.x Architecture
- Understand Spark and its Ecosystem
- Implement Spark operations on Spark Shell
- Implement Spark applications on YARN (Hadoop)
- Write Spark Applications using Spark RDD concepts
- Learn data ingestion using Sqoop
- Perform SQL queries using Spark SQL
- Implement various machine learning algorithms using Spark MLlib API
- Explain Kafka and its components
- Understand Flume and its components
- Integrate Kafka with real time streaming systems like Flume
- Use Kafka to produce and consume messages
- Build Spark Streaming Application
- Process Multiple Batches in Spark Streaming
- Implement different streaming data sources
Who should take this Apache Spark Certification Course?
The market for Big Data Analytics is growing tremendously across the world, and the strong growth pattern followed by market demand is a great opportunity for all IT Professionals. Here are a few professional IT groups who are continuously enjoying the benefits and perks of moving into the Big Data domain:
- Developers and Architects
- BI /ETL/DW Professionals
- Senior IT Professionals
- Testing Professionals
- Mainframe Professionals
- Freshers
- Big Data Enthusiasts
- Software Architects, Engineers, and Developers
- Data Scientists and Analytics Professionals
How will Apache Spark Certification Training help your career?
The statistics provided below will give you a glimpse of the growing popularity and adoption rate of Big Data tools like Spark in the current and upcoming years:
- 56% of Enterprises Will Increase Their Investment in Big Data over the Next Three Years" - Forbes
- McKinsey predicts that by 2018, there will be a shortage of 1.5 million data experts.
- The average salary of Spark Developers is $113k.
- According to a McKinsey report, the US alone will face a shortage of nearly 190,000 data scientists and 1.5 million data analysts and Big Data managers by 2025.
As you know, nowadays many organizations are showing interest in Big Data and adopting Spark as part of their solution strategy. The demand for jobs in Big Data and Spark is rising rapidly. So, it is high time to pursue a career in the field of Big Data & Analytics with our Spark and Scala Certification Training Course.
How will I execute the practicals in this Spark Certification Training?
You will execute all your Spark and Scala course assignments and case studies in the Cloud LAB environment provided by Edureka. You will access the Cloud LAB via a browser. In case of any doubts, Edureka’s support team will be available 24/7 for prompt assistance.
What is CloudLab?
CloudLab is a cloud-based Spark and Hadoop environment that Edureka offers with the Spark Course. It allows you to execute all the in-class demos and work on real-life Spark case studies seamlessly. This not only saves you from the trouble of installing and maintaining Spark and Scala on a virtual machine but also provides you with an experience of a real big data and Spark production cluster. You can access the Spark Training CloudLab via your browser, which requires minimal hardware configuration. In case you get stuck at any step, our support team is ready to assist 24/7.
What are the system requirements for our Apache Spark Certification Training?
You don't have to worry about the system requirements as you will be executing your practicals in a Cloud LAB, which is a pre-configured environment. This environment already contains all the necessary tools and services required for Edureka's course.
Apache Spark Certification Training Course Projects
Industry: Finance
A leading financial bank is trying to broaden the financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure thi....Industry: Transportation
With the spike in pollution levels and the fuel prices, many Bicycle Sharing Programs are running around the world. Bicycle sharing systems are a means of renting bicycles where ....Apache Spark Certification
To unlock Edureka’s Apache Spark and Scala Training course completion certificate, you must ensure the following:
- Fully participate in this Apache Spark Certification Training Course.
- Complete the assessments and projects listed.
- Successfully complete the course and achieve a minimum score of 80% in the assessment.
Big Data is omnipresent, and there is an urgent need to collect and preserve the generated data to avoid missing out on important insights. That's why Big Data Analytics is at the forefront of IT and has become crucial for improving businesses, decision-making, and gaining a competitive edge. Technology professionals experienced in Analytics are in high demand as organizations seek ways to leverage the power of Big Data. The number of job postings related to Analytics has significantly increased in the last 12 months. This surge is due to the growing number of organizations implementing Analytics and therefore searching for Big Data Analytics professionals. Despite the high demand, there is still a large number of unfilled jobs globally due to a shortage of required skills. Choosing a career in the field of Big Data and Analytics can be a fantastic move, offering the type of role you have been seeking.
Beginners can easily familiarize themselves with Apache Spark as it is a user-friendly framework. To learn its capabilities and functionalities, proper guidance and a well-structured training path are required. Beginners interested in a career in Big Data Analytics can sign up for our training program and earn certificates to demonstrate their expertise in this domain.
Apache Spark is a globally popular framework for real-time data analysis and processing. The demand for Apache Spark training is increasing, and there are numerous lucrative employment opportunities in tech organizations. This makes it an ideal time for candidates to enroll in the training and earn certification. Learning Apache Spark and Scala skills and starting to work immediately are highly recommended due to the wide range of job options and prospects available.
Our Apache Spark certification course is designed to develop skills and evaluate candidates' knowledge. Apache Spark is currently the most advanced technology globally, opening doors to many possibilities for professionals seeking growth in the Big Data Analytics field. After completing this certification, you will have access to a wide range of job opportunities and be prepared for roles such as Big Data Developer, Big Data Engineer, Big Data Analyst, and many more.
Please visit the page that provides a comprehensive guide to the top Apache Spark Interview questions and answers.
John Doe
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Apache Spark Training FAQs
What if I miss a class of Apache Spark training?
"You will never miss a lecture at Edureka! You have two options:
- View the recorded session of the class available in your LMS.
- Attend the missed session in any other live batch."
What if I have queries after completing this Apache Spark online course?
Your access to the Support Team is for a lifetime and will be available 24/7. The team will help you resolve queries during and after the course.
How soon after signing up will I get access to the learning content?
Post-enrollment, the LMS access will be provided to you instantly and will be available for a lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, and assignments. Moreover, access to our 24x7 support team will be granted instantly as well. You can start learning right away.
Is the Apache Spark Certification Course material accessible to students even after the course training is over?
Yes, access to the course material will be available for a lifetime once you have enrolled in the Apache Spark online course.
Can I attend a demo session before enrollment?
We have a limited number of participants in a live session to maintain quality standards. Therefore, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording, which will give you a clear insight into how the classes are conducted, the quality of instructors, and the level of interaction in a class.
Who are the instructors of Apache Spark online training?
All the instructors at Edureka are practitioners from the industry with a minimum of 10-12 years of relevant IT experience. They are subject matter experts and are trained by Edureka to provide an excellent learning experience to the participants.
What if I have more queries?
You can give us a CALL at +91 90660 20867/1844 230 6362 (US Tollfree Number) OR email at sales@edureka.co
Why learn Apache Spark? What are the career benefits?
Apache Spark is one of the leading Big Data frameworks in demand today. Spark is the next evolutionary change in big data processing environments as it provides both batch and streaming capabilities. This makes it the ideal framework for anyone seeking fast data analysis. With companies eager to adopt Spark in their systems, learning this framework can help you climb the career ladder.
How to learn Scala for Spark?
Scala stands for Scalable Language. If you want to master Spark with Scala, Edureka's training program is what you need. Our course module starts from the basics and covers all necessary modules. With our instructor-led sessions and 24x7 support system, we ensure that you achieve your learning objectives.
How to learn Apache Spark?
Edureka offers a vast repository of guides, tutorials, and comprehensive courses that will help you understand and master Spark. You can start by checking out our blogs to get started with Spark and gain basic foundational knowledge. Our tutorials will then guide you to dive deeper and understand the underlying concepts. Finally, our training program will help you truly master the technology through instructor-led sessions and real-world hands-on experience.
How much time does it take to learn Spark?
Edureka's Spark and Scala training is a 6-week structured training program designed to help learners master Spark with Scala. In these 6 weeks, you will attend live instructor-led sessions and work on various assignments and projects to develop a strong understanding of the Spark ecosystem.
How long will it take to complete the course?
Edureka's Spark and Scala Certification Training offers a flexible batch schedule to suit everyone's needs. Weekend batches run for 6 weeks of live instructor-led sessions, followed by a real-time project for better hands-on experience. The accelerated program or weekday batches can be completed in a much shorter time with rigorous training sessions and a final live project to work on.
Why take an online Spark and Scala course? How is it better than an offline course?
Learning pedagogy has evolved with the advancement of technology. Online training adds convenience and quality to the learning module. With our 24x7 support system, online learners have assistance even after the class ends. This ensures that learners can achieve their learning objectives. Additionally, we provide lifetime access to our updated course material for all our learners.
How can a beginner learn Spark and Scala?
Big data technology is dominating the job market, and for complete beginners, we have compiled an extensive list of blogs and tutorials on our blogging and YouTube channel. These resources can be a great help if you are looking to start out. Once you are clear with the basic concepts, you can consider taking up Edureka's Apache Spark and Scala Certification Training to truly master the technology.
What are the top Apache Spark certifications that I can pursue?
Here are the top 5 certifications:
- Cloudera Spark and Hadoop Developer
- HDP Certified Apache Spark Developer
- MapR Certified Spark Developer
- Databricks Apache Spark Certifications
- O’Reilly Developer Apache Spark Certifications
Top Reasons why one should become a certified Spark Developer?
If you are considering a career in big data, obtaining Spark certification is the first step towards achieving it. This certification will give you a boost in your career and validate your Spark skills. It is highly sought-after by almost all companies, providing you with a competitive edge in the job market.
It is easy to obtain Spark certification preparation. There are many ways to get certified. The best reason to get certified is that it will give you an edge over your peers. Because there is fierce competition outside.
Do you have samples of Scala interview questions?
Please visit the Scala Interview Questions page, which will guide you through the top 45+ Interview questions.
What do you need to know about Databricks Certified Associate Developer for Apache Spark 3.0?
The Databricks Certified Associate Developer for Apache Spark 3.0 certification tests your understanding of the Spark DataFrame API. It assesses your ability to use the Spark DataFrame API to perform basic data manipulation tasks within a Spark session. These tasks include manipulating, filtering, dropping, and sorting columns, handling missing data, and combining, reading, and writing DataFrames with schemas. The exam also covers working with UDFs or Spark SQL functions. Additionally, the exam assesses fundamental aspects of Apache Spark architecture, such as execution/deployment mode, execution hierarchy, fault tolerance, and garbage collection.
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