Apache Spark is a powerful open-source monitoring and distributed general-purpose in-memory computing engine which is written in the Scala programming language. Apache Spark and Scala provide fault-tolerant in-memory data parallelism at a very fast, standard interface and ease of use. Most of the big data developers choosing Scala programming language in the Apache Spark framework to build big data applications with faster data analysis.
Scope of Apache Spark and Scala is immense because of its demandable key features like less complexity, fast memory computations, dynamic programming, inbuilt machine learning libraries, data streaming, real-time analysis, graphs libraries, high productivity, and performance.
Hachion Apache Spark and Scala Online training curated by industry experts from scratch. Our Spark and scala tutorial covers all basic fundamental concepts to updated advanced topics in the course content. Enhance full knowledge with the course that includes Scala programming language, Spark architecture, RDD for creating apps in Apache Spark, SparkSQL, streaming, batch processing, ML programming, and graph analytics. Master your skills and get hands-on experience with given real-time projects to become a big data developer.
What Is Apache Spark?
A Unified Stack
Who Uses Spark, and for What?
Data Science Tasks
Data Processing Applications
A Brief History of Spark
Spark Versions and Releases
Storage Layers for Spark
Introduction to Spark’s Python and Scala Shells
Introduction to Core Spark Concepts
Initializing a SparkContext
Passing Functions to Spark
Common Transformations and Actions
Converting Between RDD Types
Creating Pair RDDs
Transformations on Pair RDDs
Actions Available on Pair RDDs
Data Partitioning (Advanced)
Determining an RDD’s Partitioner
Operations That Benefit from Partitioning
Operations That Affect Partitioning
Comma-Separated Values and Tab-Separated Values
Hadoop Input and Output Formats
Structured Data with Spark SQL
Java Database Connectivity
Accumulators and Fault Tolerance
Working on a Per-Partition Basis
Piping to External Programs
Numeric RDD Operations
Spark Runtime Architecture
Launching a Program
Packaging Your Code and Dependencies
A Java Spark Application Built with Maven
A Scala Spark Application Built with sbt
Scheduling Within and Between Spark Applications
Standalone Cluster Manager
Which Cluster Manager to Use?
Configuring Spark with SparkConf
Components of Execution: Jobs, Tasks, and Stages
Spark Web UI
Driver and Executor Logs
Key Performance Considerations
Level of Parallelism
Linking with Spark SQL
Using Spark SQL in Applications
Initializing Spark SQL
Basic Query Example
Loading and Saving Data
Working with Beeline
Long-Lived Tables and Queries
Spark SQL UDFs
Spark SQL Performance
Performance Tuning Options
A Simple Example
Architecture and Abstraction
Multiple Sources and Cluster Sizing / Operation
Driver Fault Tolerance
Worker Fault Tolerance
Receiver Fault Tolerance
Batch and Window Sizes
Level of Parallelism
Garbage Collection and Memory Usage
Machine Learning Basics
Example: Spam Classification
Working with Vectors
Classification and Regression
Collaborative Filtering and Recommendation
Tips and Performance Considerations
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Caching RDDs to Reuse
Level of Parallelism
Apache Spark is an open-source cluster computing framework that was initially developed at UC Berkeley in the AMPLab.As compared to the disk-based, two-stage MapReduce of Hadoop, Spark provides up to 100 times faster performance for a few applications with in-memory primitives. Scala is a modern and multi-paradigm programming language. It has been designed for expressing general programming patterns in an elegant, precise, and type-safe way. One of the prime features is that it integrates the features of both object-oriented and functional languages smoothly.
Although there are many spark classroom training Portals. Hachion is one of the best Spark classroom training Institutes, with the expert instructors who provide great support at the time of learning. As the course, is all about learning to manage and process volumes of data, it is recommended for those who work upon managing big data. Also, for the matter of fact that, Apache spark technology is the foundation to understand the architecture and functionalities of software technology like big data.
Hachion's Spark & Scala training program covers from basic to advanced concepts in Spark and Scala. Our course curriculum is designed by industry experts in the IT industry. We provide 100% job assistance with certification guidance.
We provide 100% job assistance to the Hachion students, once they complete the course. We also provide resume writing, mock interviews and resume marketing services as part of our job assistance program.
We offer three modes of training in the Spark and Scala online training program.
The basic prerequisite of the Apache Spark and Scala Tutorial is a fundamental knowledge of any programming language is a prerequisite for the tutorial. Participants are expected to have a basic understanding of any database, SQL, and query language for databases. Working knowledge of Linux or Unix based systems, while not mandatory, is an added advantage for this tutorial.
The average salary for "big data scala spark" ranges from approximately $92,445 per year for Developer to $138,252 per year for Machine Learning Engineer.
After completion of the Spark and Scala online training program, candidates will get a course completion certificate