Scala course syllabus

Introduction

We teach you with a comprehensive and updated Scala course syllabus that would equip you with the knowledge and expertise required to thrive in data processing and functional programming. We teach you with a detailed Scala course syllabus that covers core concepts like Scala’s syntax, OOP features, error handling, functional programming paradigms, concurrency and parallelism, pattern matching, case classes etc.

Our Scala course syllabus also includes real-world applications with frameworks like Apache Spark that would enable you to effectively process vast amounts of data sets. Our Scala course syllabus is specially formulated to meet the needs of both beginners and seasoned professionals looking to level up their skills in Scala. Visit https://www.ficusoft.in/ to know more.

Scala course syllabus

Module 1 – Introduction to Scala Programming

• Overview of Scala and its abilities
• Basic syntax and information kinds in Scala
• Functional programming ideas in Scala
• Scala’s interoperability with Java
• Setting up the Scala improvement environment

Module 2 – Scala Language Fundamentals

• Variables, records structures, and operators in Scala
• Control structures: if, else, suit expressions
• Functions and techniques in Scala
• Pattern matching and case training
• Exception dealing with in Scala

Module 3 – Object-Oriented Programming in Scala

• Classes and gadgets in Scala
• Inheritance and polymorphism
• Traits and summary lessons
• Companion gadgets and case objects
• Type hierarchy in Scala

Module 4 – Functional Programming in Scala

• First-beauty capabilities and higher-order capabilities
• Immutability and persistent statistics systems
• Closures and currying
• Monads and choice types
• Lazy assessment and movement processing

Module 5 – Concurrency and Parallelism in Scala

• Basics of concurrency in Scala
• Futures and Promises
• Actors model for concurrent programming
• Parallel collections in Scala
• Handling synchronization and thread safety

Module 6 – Scala Tools and Libraries

• Build system: SBT and Maven
• Testing frameworks in Scala
• Scala’s significant library
• Popular Scala libraries (Akka, Play Framework)
• Scala IDEs and development environments

Module 7 – Scala for Big Data and Reactive Programming

• Introduction to Apache Spark and Scala
• Reactive programming with Scala
• Handling streaming records with Akka Streams
• Integrating Scala with NoSQL databases
• Real-worldwide obligations and case studies in Scala applications

Module 8 – Scala Programming

• Introduction to Scala
• Feature of Scala
• Scala vs Java Comparison
• Data types
• Data Structure
• Arrays
• Literals
• Logical Operators
• Mutable & Immutable variables
• Type interface

Module 9 – Scala Functions

• Oops  vs Functions
• Anonymous 
• Recursive 
• Call-by-name
• Currying
• Conditional statement

Module 10 – Scala Collections

• List
• Map
• Sets
• Options
• Tuples
• Mutable collection
• Immutable collection
• Iterating
• Filtering and counting 
• Group By
• Flat Map
• Word count
• File Access

Module 11 – Scala Distributed File System (HDFS)

• HDFS Design & Concepts
• Blocks, Name nodes and Data nodes
• HDFS High-Availability and HDFS Federation
• Scala DFS The Command-Line Interface
• Basic File System Operations
• Anatomy of File Read, File Write
• Block Placement Policy and Modes
• More detailed explanation about Configuration files
• Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
• How to add New Data Node dynamically, decommission a Data Node dynamically (Without stopping cluster)
• FSCK Utility. (Block report)
• How to override default configuration at system level and Programming level
• HDFS Federation
• ZOOKEEPER Leader Election Algorithm
• Exercise and small use case on HDFS

Module 12 – Map Reduce

• Map Reduce Functional Programming Basics
• Map and Reduce Basics
• How Map Reduce Works
• Anatomy of a Map Reduce Job Run
• Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
• Job Completion, Failures
• Shuffling and Sorting
• Splits, Record reader, Partition, Types of partitions & Combiner
• Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
• Types of Schedulers and Counters
• Comparisons between Old and New API at code and Architecture Level
• Getting the data from RDBMS into HDFS using Custom data types
• Distributed Cache and Scala Streaming (Python, Ruby and R)
• YARN
• Sequential Files and Map Files
• Enabling Compression Codec’s
• Map side Join with distributed Cache
• Types of I/O Formats: Multiple outputs, NLINEinputformat
• Handling small files using CombineFileInputFormat

Module 13 – Map Reduce Programming – Java Programming

• Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
• Sorting files using Scala Configuration API discussion
• Emulating “grep” for searching inside a file in Scala
• DBInput Format
• Job Dependency API discussion
• Input Format API discussion,Split API discussion
• Custom Data type creation in Scala

Module 14 – NOSQL

• ACID in RDBMS and BASE in NoSQL
• CAP Theorem and Types of Consistency
• Types of NoSQL Databases in detail
• Columnar Databases in Detail (HBASE and CASSANDRA)
• TTL, Bloom Filters and Compensation

Module 15 – HBase

• HBase Installation, Concepts
• HBase Data Model and Comparison between RDBMS and NOSQL
• Master & Region Servers
• HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
• Catalog Tables
• Block Cache and sharding
• SPLITS
• DATA Modeling (Sequential, Salted, Promoted and Random Keys)
• Java API’s and Rest Interface
• Client Side Buffering and Process 1 million records using Client side Buffering
• HBase Counters
• Enabling Replication and HBase RAW Scans
• HBase Filters
• Bulk Loading and Co processors (Endpoints and Observers with programs)
• Real world use case consisting of HDFS,MR and HBASE

Module 16 – Hive

• Hive Installation, Introduction and Architecture
• Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
• Meta store, Hive QL
• OLTP vs. OLAP
• Working with Tables
• Primitive data types and complex data types
• Working with Partitions
• User Defined Functions
• Hive Bucketed Tables and Sampling
• External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
• Dynamic Partition
• Differences between ORDER BY, DISTRIBUTE BY and SORT BY
• Bucketing and Sorted Bucketing with Dynamic partition
• RC File
• INDEXES and VIEWS
• MAPSIDE JOINS
• Compression on hive tables and Migrating Hive tables
• Dynamic substation of Hive and Different ways of running Hive
• How to enable Update in HIVE
• Log Analysis on Hive
• Access HBASE tables using Hive
• Hands on Exercises

Module 17 – Pig

• Pig Installation
• Execution Types
• Grunt Shell
• Pig Latin
• Data Processing
• Schema on read
• Primitive data types and complex data types
• Tuple schema, BAG Schema and MAP Schema
• Loading and Storing
• Filtering, Grouping and Joining
• Debugging commands (Illustrate and Explain)
• Validations,Type casting in PIG
• Working with Functions
• User Defined Functions
• Types of JOINS in pig and Replicated Join in detail
• SPLITS and Multiquery execution
• Error Handling, FLATTEN and ORDER BY
• Parameter Substitution
• Nested For Each
• User Defined Functions, Dynamic Invokers and Macros
• How to access HBASE using PIG, Load and Write JSON DATA using PIG
• Piggy Bank
• Hands on Exercises

Module 18 – SQOOP

• Sqoop Installation
• Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV, Compressing, Control Parallelism, All tables Import)
• Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
• Free Form Query Import
• Export data to RDBMS,HIVE and HBASE
• Hands on Exercises

Module 19 – HCatalog

• HCatalog Installation
• Introduction to HCatalog
• About Hcatalog with PIG,HIVE and MR
• Hands on Exercises

Module 20 – Flume

• Flume Installation
• Introduction to Flume
• Flume Agents: Sources, Channels and Sinks
• Log User information using Java program in to HDFS using LOG4J and Avro Source, Tail Source
• Log User information using Java program in to HBASE using LOG4J and Avro Source, Tail Source
• Flume Commands
• Use case of Flume: Flume the data from twitter in to HDFS and HBASE. Do some analysis using HIVE and PIG

Module 21 – More Ecosystems

• HUE.(Hortonworks and Cloudera)

Module 22 – Oozie

• Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG
• Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour
• Zoo Keeper
• HBASE Integration with HIVE and PIG
• Phoenix
• Proof of concept (POC)

Conclusion

Our top Scala course syllabus will provide an excellent opportunity for aspiring developers and data professionals to get ahead in their chosen career. Our Scala course syllabus integrates theoretical knowledge with practical applications, helping you master the complexities of Scala.

Our Scala course syllabus not only covers basic concepts, but also helps you go deep into advanced frameworks like Akka and Play to equip you with the knowledge and skills to build scalable, maintainable, and high performance applications.

Learning our Scala course syllabus from A – Z will help you gain the necessary skills for handling real-world challenges in web development and data analysis. Learn our Scala course syllabus and accelerate your career in the tech landscape! Catch our training programs and webinars live through https://www.facebook.com/ficusofttechnologies/.