Spark with Scala Training in Bangalore - ZekeLabs Best Spark with Scala Training Institute in Bangalore India
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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.
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Industry Level Projects
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Spark with Scala Course Curriculum



What Is Apache Spark?
Spark Core
Spark Streaming
GraphX
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
Actions
Passing Functions to Spark
Basic RDDs
Persistence (Caching)
Motivation
Transformations on Pair RDDs
Grouping Data
Sorting Data
Data Partitioning (Advanced)
Operations That Benefit from Partitioning
Example: PageRank
Motivation
Text Files
Comma-Separated Values and Tab-Separated Values
Object Files
File Compression
Local/“Regular” FS
HDFS
Apache Hive
Databases
Cassandra
Elasticsearch
Introduction
Accumulators and Fault Tolerance
Broadcast Variables
Working on a Per-Partition Basis
Numeric RDD Operations
Introduction
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
SchemaRDDs
Loading and Saving Data
Parquet
From RDDs
Working with Beeline
User-Defined Functions
Hive UDFs
Performance Tuning Options
A Simple Example
Transformations
Stateful Transformations
Input Sources
Additional Sources
Checkpointing
Worker Fault Tolerance
Processing Guarantees
Performance Considerations
Level of Parallelism
Overview
Machine Learning Basics
Data Types
Algorithms
Statistics
Clustering
Dimensionality Reduction
Tips and Performance Considerations
Configuring Algorithms
Caching RDDs to Reuse
Level of Parallelism

Frequently Asked Questions


We provide classroom-based as well as online training. Since this is a hand-on training so batches generally does not contain more than 4 people.

We will provide web services specific study material as the course progresses. You will have lifetime access to all the code and basic settings needed for these Spark with Scala through our github account and the study material that we share with you. You can use that for quick reference.

Feel free to drop a mail to us at support@zekelabs.com and we will get back to you at the earliest for your queries on Spark with Scala course

We have tie ups with various companies and placement organizations to whom we connect our learners. Each Spark with Scala training ends with career consulting

Minimum 2-3 projects of industry standards on Spark with Scala will be provided

Yes, we provide our own course completion certificate to all students. Each Spark with Scala training in bangalore ends with training and project completion certificate

You can pay by card (debit/credit), cash, cheque and net-banking. You can pay in two installments

We take immense pride to provide post training career consulting for Spark with Scala training



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