Spark & Scala
Humble beginnings
Redprism came a long way intending to ‘Transform the Career and Lives’ of the individuals in the competitive world and up skilling their career, and creating a balance between the learning and implementing the real-time cases in education and achieve the dreams.
Spark & Scala
What is Spark?
Apache Spark is a highly developed engine for data processing on large scale over thousands of compute engines in parallel. This allows maximizing processor capability over these compute engines. Spark has the capability to handle multiple data processing tasks including complex data analytics, streaming analytics, graph analytics as well as scalable machine learning on huge amount of data in the order of Terabytes, Zettabytes and much more.
It is based on Hadoop MapReduce and it extends the MapReduce model to efficiently use it for more types of computations, which includes interactive queries and stream processing. The main feature of Spark is its in-memory cluster computing that increases the processing speed of an application.
Spark is designed to cover a wide range of workloads such as batch applications, iterative algorithms, interactive queries and streaming. Apart from supporting all these workload in a respective system, it reduces the management burden of maintaining separate tools.
What is Scala?
Scala is a highly scalable programming language devised to the programming expressions in a precise and safe manner. It is named after its feature of ‘scalability’ which separates it from other programming languages. In a nutshell, Scala is a pure-bred object-oriented programming language inculcating the features of functional languages.
Why should you learn Spark and Scala?
ü Ideal for implementing IOT
ü Helps in optimizing business decision making
ü Complex workflows can be created with ease
ü Versatile Framework
ü Faster than Hadoop
ü Proficiency Enhancer
ü Helps in decentralized processing of data
ü Prototyping solutions becomes easier
Exclusive Redprism Key Factors
Redprism is the best Spark & Scala training institute in Noida that provides 100% placement assistance and world class environment. In this training period, candidates will undergo complete real time experience through practical examples and live projects, in this program, candidate get support for resume preparation, interview preparation and mock interviews. Now the demand for Spark and Scala is increasing day to day. So come and join us to achieve what you really deserve.
Prime Features why to Join Red Prism?-
· Industry Expert Trainers with 10-15 years of experience.
· Course content is curated by best Subject Matter Experts.
· Practical Assignments.
· Real Time Projects.
· Video recording of each and every session.
· Yours doubts are clarified with 24*7 assistance by our experts.
· We conduct regular Mock tests and certifications at the end of course.
· Certification Guidance.
· Recognized training complete certificate.
· 100% Placement Assistance.
· Less fees as compared to other institutes.
· Flexi payment options
· Scholarship Available
Course Content:-
- Why Scala?
- What is Scala?
- Introducing Scala
- Installing Scala
- Journey – Java to Scala
- First Dive – Interactive Scala
- Writing Scala Scripts – Compiling Scala Programs
- Scala Basics
- Scala Basic Types
- Defining Functions
- IDE for Scala, Scala Community
- Immutability in Scala – Semicolons
- Method Declaration, Literals
- Lists
- Tuples
- Options
- Maps
- Reserved Words
- Operators
- Precedence Rules
- If statements
- Scala for Comprehensions
- While Loops
- Do-While Loops
- Conditional Operators
- Pattern Matching
- Enumerations
- Traits Intro – Traits as Mixins
- Stackable Traits
- Creating Traits Basic OOPS – Class and Object Basics
- Scala Constructors
- Nested Classes
- Visibility Rules
- What is Functional Programming?
- Functional Literals and Closures
- Recursion
- Tail Calls
- Functional Data Structures
- Implicit Function Parameters
- Call by Name
- Call by Value
- Introduction to Big Data
- Challenges with Big Data
- Batch Vs. Real Time Big Data Analytics
- Batch Analytics – Hadoop Ecosystem Overview
- Real Time Analytics Options, Streaming Data – Storm
- In Memory Data – Spark
- What is Spark?
- Modes of Spark
- Spark Installation Demo
- Overview of Spark on a cluster
- Spark Standalone Cluster
- Invoking Spark Shell
- Loading a File in Shell
- Performing Some Basic Operations on Files in Spark Shell
- Building a Spark Project with sbt, Building and Running Spark Project with sbt
- Caching Overview, Distributed Persistence
- Spark Streaming Overview
- Example: Streaming Word Count
- Spark & Distributed Systems
- Spark for Scalable Systems
- Spark Execution Context
- What is RDD
- RDD Deep Dive and Dependencies
- RDD Lineage
- Spark Application In Depth and Spark Deployment
- Parallelism in Spark
- Caching in Spark
- Why Shark?
- Installing Shark
- Running Shark
- Loading of Data
- Hive Queries through Spark
- Testing Tips in Scala
- Performance Tuning Tips in Spark
- Shared Variables: Broadcast Variables
- Shared Variables: Accumulators
- Features of Spark Streaming
- Micro Batch
- Dstreams
- Transformations on Dstreams
- Spark Streaming Use Case
- Spark MIB
- Classification Algorithm
- Clustering Algorithm
- Sequence Mining Algorithm
- Collbrative filtering
- Graph analysis with Spark
- GraphX for graphs
- Graph-parallel computation
