Spark with Scala-training-in-bangalore-by-zekelabs

Spark with Scala Training

Spark with Scala Course:

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance.

Spark with Scala-training-in-bangalore-by-zekelabs
Spark with Scala-training-in-bangalore-by-zekelabs
Industry Level Projects
Spark with Scala-training-in-bangalore-by-zekelabs

Spark with Scala Course Curriculum

What Is Apache Spark?
Spark Core
Spark Streaming
Who Uses Spark, and for What?
Data Processing Applications
Spark Versions and Releases
Downloading Spark
Introduction to Core Spark Concepts
Initializing a SparkContext
RDD Basics
RDD Operations
Passing Functions to Spark
Basic RDDs
Persistence (Caching)
Transformations on Pair RDDs
Grouping Data
Sorting Data
Data Partitioning (Advanced)
Operations That Benefit from Partitioning
Example: PageRank
Text Files
Comma-Separated Values and Tab-Separated Values
Object Files
File Compression
Local/“Regular” FS
Apache Hive
Accumulators and Fault Tolerance
Broadcast Variables
Working on a Per-Partition Basis
Numeric RDD Operations
The Driver
Cluster Manager
Packaging Your Code and Dependencies
A Scala Spark Application Built with sbt
Scheduling Within and Between Spark Applications
Standalone Cluster Manager
Apache Mesos
Which Cluster Manager to Use?
Configuring Spark with SparkConf
Finding Information
Driver and Executor Logs
Level of Parallelism
Memory Management
Linking with Spark SQL
Initializing Spark SQL
Loading and Saving Data
From RDDs
Working with Beeline
User-Defined Functions
Hive UDFs
Performance Tuning Options
A Simple Example
Stateful Transformations
Input Sources
Additional Sources
Worker Fault Tolerance
Processing Guarantees
Performance Considerations
Level of Parallelism
Machine Learning Basics
Data Types
Dimensionality Reduction
Tips and Performance Considerations
Configuring Algorithms
Caching RDDs to Reuse
Level of Parallelism

Frequently Asked Questions

This "Spark with Scala" course is an instructor-led training (ILT). The trainer travels to your office location and delivers the training within your office premises. If you need training space for the training we can provide a fully-equipped lab with all the required facilities. The online instructor-led training is also available if required. Online training is live and the instructor's screen will be visible and voice will be audible. Participants screen will also be visible and participants can ask queries during the live session.

Participants will be provided "Spark with Scala"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Spark with Scala". Our public GitHub repository and the study material will also be shared with the participants.

All the courses from zekeLabs are hands-on courses. The code/document used in the class will be provided to the participants. Cloud-lab and Virtual Machines are provided to every participant during the "Spark with Scala" training.

The "Spark with Scala" training varies several factors. Including the prior knowledge of the team on the subject, the objective of the team learning from the program, customization in the course is needed among others. Contact us to know more about "Spark with Scala" course duration.

The "Spark with Scala" training is organised at the client's premises. We have delivered and continue to deliver "Spark with Scala" training in India, USA, Singapore, Hong Kong, and Indonesia. We also have state-of-art training facilities based on client requirement.

Our Subject matter experts (SMEs) have more than ten years of industry experience. This ensures that the learning program is a 360-degree holistic knowledge and learning experience. The course program has been designed in close collaboration with the experts working in esteemed organizations such as Google, Microsoft, Amazon, and similar others.

Yes, absolutely. For every training, we conduct a technical call with our Subject Matter Expert (SME) and the technical lead of the team that undergoes training. The course is tailored based on the current expertise of the participants, objectives of the team undergoing the training program and short term and long term objectives of the organisation.

Drop a mail to us at [email protected] or call us at +91 8041690175 and we will get back to you at the earliest for your queries on "Spark with Scala" course.

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