Why to learn Apache Spark using Scala
In this era of Artificial intelligence, machine learning, and data science, algorithms that run on Distributed Iterative computation make the task of distributing and computing huge volumes of data easy. Spark is a lightning fast, in-memory, cluster computing framework that can be used for a variety of purposes. This JVM based open source framework can be used for processing and analyzing huge volumes of data and at the same time can be used to distribute data over a cluster of machines. It is designed in such a way that it can perform batch and stream processing and hence is known as a cluster computing platform. Scala is the language in which Spark is developed. Scala is a powerful and dynamic programming language that doesn’t compromise on type safety.
Do you know the secret behind Uber’s flawless map functioning? Here’s a hint, the images gathered by the Map Data Collection Team are accessed by the downstream Apache Spark team and are assessed by operators responsible for map edits. A number of file formats are supported by Apache Spark which allows multiple records to be stored in a single file.
According to a recent survey by DataBricks, 71% of Spark users use Scala for programming. Spark with Scala is a perfect combination to stay grounded in the Big Data world. 9 out of 10 companies have this successful combination running in their organizations. Spark has over 1000 contributors across 250+ organizations making it the most popular open source project ever. The Apache Spark Market is expected to grow at a CAGR of 67% between 2019 and 2022 jostling a high demand for trained professionals.
Benefits of Apache Spark with Scala:
Apache Spark with Scala is used by 9 out of 10 organizations for their big data needs. Let’s take a look at its benefits at the individual and organizational level:
Individual Benefits:
- Learn Apache Spark to have increased access to Big Data
- There’s a huge demand for Spark Developers across organizations
- With an Apache Spark with Scala certification, you will earn a minimum salary of $100,000.
- As Apache Spark is deployed by every industry to extract huge volumes of data, you get an opportunity to be in demand across various industries
Organization Benefits:
- It supports multiple languages like Java, R, Scala, Python
- Easier integration with Hadoop as Spark is built on the Hadoop Distributed File System
- It enables faster processing of data streams in real-time with accuracy
- Spark code can be used for batch processing, join stream against historical data, and run ad-hoc queries on stream state
According to Databricks - "The adoption of Apache Spark by businesses large and small is growing at an incredible rate across a wide range of industries, and the demand for developers with certified expertise is quickly following suit".
WHAT YOU WILL LEARN
1. Big Data Introduction
Understand Big Data, its components and the frameworks, Hadoop Cluster architecture and its modes.
2. Introduction on Scala
Understand Scala programming, its implementation, basic constructs required for Apache Spark.
3. Spark Introduction
Gain an understanding of the concepts of Apache Spark and learn how to develop Spark applications.
4. Spark Framework & Methodologies
Master the concepts of the Apache Spark framework and its associated deployment methodologies.
5. Spark Data Structure
Learn Spark Internals RDD and use of Spark’s API and Scala functions to create and transform RDDs.
6. Spark Ecosystem
Master the RDD and various Combiners, SparkSQL, Spark Context, Spark Streaming, MLlib, and GraphX.
Prerequisites
- Basic understanding of SQL, any database, and query language for databases.
- It is not mandatory, but helpful for you to have working knowledge of Linux or Unix-based systems.
- Also, it is recommended to have a certification training on Big Data Hadoop Development.