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HADOOP DEV + SPARK & SCALA
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4.7 (2092 Ratings)
The solution for Big Data is built on open-source platforms and offers a comprehensive ETL data processing framework. It includes various tools for efficient data processing across distributed environments. Unlike SQL-based tools, it processes data without requiring centralized storage. This ensures scalability and flexibility in handling large datasets.
Overview
The Syllabus
Curriculum Designed by Experts
Big Data
• Distributed computing
• Data management – Industry challenges
• Overview of Big Data
• Characteristics of Big Data
• Types of data
• Sources of Big Data
• Big Data examples
• What is streaming data?
• Batch vs Streaming data processing
• Overview of Analytics
• Big data Hadoop opportunities
Hadoop
- Why we need Hadoop
- Data centers and Hadoop Cluster overview
- Overview of Hadoop Daemons
- Hadoop Cluster and Racks
- Learning Linux required for Hadoop
- Hadoop ecosystem tools overview
- Understanding the Hadoop configurations and Installation
HDFS (Storage)
- HDFS
- HDFS Daemons – Namenode, Datanode, Secondary Namenode
- Hadoop FS and Processing Environment’s UIs
- Fault Tolerant
- High Availability
- Block Replication
- How to read and write files
- Hadoop FS shell commands
YARN (Hadoop Processing Framework)
- YARN
- YARN Daemons – Resource Manager, Node Manager, etc.
- Job assignment & Execution flow
MapReduce using Java (Processing Data)
- Introduction to MapReduce
- MapReduce Architecture
- Data flow in MapReduce
- Difference Between Block and InputSplit
- Role of RecordReader
- Basic Configuration of MapReduce
- MapReduce life cycle
- How MapReduce Works
- Writing and Executing Basic MapReduce Program using Java
- Submission & Initialization of MapReduce Job
- File Input/Output Formats in MapReduce Jobs (Text, Key Value, Sequence File, NLine Input Formats)
- Joins (Map-side, Reducer-side Joins)
- Word Count Example / Election Vote Count
- Real-time MapReduce examples (5-10)
Apache Hive
- Data warehouse basics
- OLTP vs OLAP Concepts
- Hive Architecture
- Metastore DB and Metastore Service
- Hive Query Language (HQL)
- Managed and External Tables
- Partitioning & Bucketing
- Query Optimization
- Hiveserver2 (Thrift server)
- JDBC, ODBC connection to Hive
- Hive Transactions
- Hive UDFs
- Working with Avro Schema and AVRO file format
- Real-time datasets
Apache Pig
- Apache Pig Overview
- Advantage of Pig over MapReduce
- Pig Latin (Scripting language for Pig)
- Schema and Schema-less data in Pig
- Structured and Semi-Structure data processing in Pig
- Pig UDFs
- HCatalog
- Pig vs. Hive Use case
- Hands-On examples of daily data analysis
HBASE (Real NoSQL)
- Introduction to HBASE
- Basic Configurations of HBASE
- HBase Data Model (Table, Row, Column Family, Column Qualifier, Cell Versioning)
- Categories of NoSQL Databases (Key-Value, Document, Column Family)
- HBase Architecture (HMaster, Region Servers, Regions, MemStore, Store)
- SQL vs. NOSQL
- HDFS vs. HBase
- Client-side buffering or bulk uploads
- Designing Tables in HBase
- HBase Operations (Get, Scan, Put, Delete)
- Live Dataset
Sqoop
- Sqoop Commands
- Practical implementation of Sqoop
- Importing data to HDFS & Hive
- Exporting data to RDBMS
- Sqoop connectors
Flume
- Flume Commands
- Source, Channel, and Sink configuration
- Fan-out flume agents
- Loading data from web server or storage into Hadoop
- Loading streaming data from Twitter into HDFS
Oozie
- Oozie Overview
- Action Node and Control Flow Node
- Designing Workflow Jobs
- Scheduling time-based jobs with Oozie
- Oozie Configuration file
Scala
- Scala Syntax, Datatypes, Variables
- Classes, Objects, Functional Objects
- Control Structures, Functions, Closures
- Inheritance, Traits, Packages, Imports
- Lists, Collections, Abstract Members
- Implicit Conversions and Parameters
- Modular Programming
Spark
- Spark Architecture and APIs
- Spark components (Master, Driver, Executor, Worker)
- Resilient Distributed Datasets (RDDs)
- RDD Transformations and Actions
- Loading data in Spark Shell
- Spark application lifecycle and job scheduling
- Persistence levels for RDD caching
- Web UI and application monitoring
- Spark SQL, SchemaRDD, DataFrames, Filtering, Sorting
- Spark SQL program demo
Kafka With ZooKeeper
- Kafka Overview and Cluster architecture
- Kafka basic operations
- Integration with Spark, Camel
- Kafka with Spring Boot Integration
- Security, Authentication
Apache Splunk
- Introduction & Installing Splunk
- Data ingestion and feeding
- Searching & Reporting
- Data Visualization
- Advanced Splunk Concepts
Cassandra + MongoDB
- Introduction to NoSQL (Data Types, CAP Theorem)
- MongoDB Installation and CRUD Operations
- JSON vs. XML
- Cassandra Data Model, Architecture, Installation
- Tables creation and schema in Cassandra
- Cassandra Operations (Insert, Update, Delete, etc.)
- Bulk file uploads, collections handling
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Why Radical Technologies
Live Online Training
Highly practical oriented training
Installation of Software On your System
24/7 Email and Phone Support
100% Placement Assistance until you get placed
Global Certification Preparation
Trainer Student Interactive Portal
Assignments and Projects Guided by Mentors
And Many More Features
Course completion certificate and Global Certifications are part of our all Master Program
Live Classroom Training
Weekend / Weekdays / Morning / Evening Batches
80:20 Practical and Theory Ratio
Real-life Case Studies
Easy Coverup if you missed any sessions
PSI | Kryterion | Redhat Test Centers
Life Time Video Classroom Access ( coming soon )
Resume Preparations and Mock Interviews
And Many More Features
Course completion certificate and Global Certifications are part of our all Master Program
Self Paced Training
Self Paced Learning
Learn 300+ Courses at Your Own Time
50000+ Satisfied Learners
Course Completion Certificate
Practical Labs Available
Mentor Support Available
Doubt Clearing Session Available
Attend Our Virtual Job Fair
10% Discounted Global Certification
Course completion certificate and Global Certifications are part of our all Master Program
Skills Covered
Like the Curriculum ? Let's Get Started
Why Enroll for Hadoop Developer + Spark & Scala ?
In-Demand Skills
Enhance your career with Hadoop Dev + Spark & Scala training! Gain expertise in big data tools like Hadoop, Spark, and Scala to manage large datasets and optimize data processing. Enroll today to gain these highly sought-after abilities and unlock doors to rewarding data engineering employment prospects.
Career Opportunities
Hadoop Dev + Spark & Scala training opens doors to top tech roles like Big Data Engineer, Data Analyst, and Machine Learning Expert. These in-demand skills are sought by leading companies worldwide. Enroll now to boost your career and stay competitive in the data-driven industry!
Cloud Adoption
As cloud adoption accelerates, Hadoop Dev + Spark & Scala training prepares you to handle vast amounts of data on platforms like AWS, Azure, and Google Cloud. Master these tools for efficient data processing, analytics, and scalability. Enroll today to thrive in this cloud-dominated tech landscape!
Scalability and Flexibility
Hadoop Dev + Spark & Scala training offers the scalability and flexibility needed for managing large datasets. These tools enable seamless expansion and adaptability for diverse data-processing needs.Enroll now to gain expertise in scalable big data solutions and stay ahead in your career!
Cost Management
Managing costs effectively in Hadoop Dev, Spark, and Scala training is key to maximizing your ROI. By enrolling, you gain expert knowledge on optimizing Big Data processes, reducing infrastructure expenses, and improving performance. Invest in your skills to unlock the full potential of data-driven insights.
Security and Compliance
Ensure security and compliance with Hadoop Dev, Spark, and Scala training.Learn to safeguard data, follow regulatory standards, and secure Big Data pipelines.By enrolling, you’ll gain vital skills to protect sensitive information and stay compliant in today’s fast-evolving tech landscape.
Course benefits
Who Can Apply for Red Hat Linux
- Information Architects and Statisticians
- Developers looking to master Machine Learning and Predictive Analytics
- Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
- Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
- Anyone who wants to learn machine learning, artificial intelligence, data visualization, data analytics, data structures, and algorithms (DSA).
Why Hadoop Developer + Spark & Scala ?
Scalability
Boost your career with our HADOOP DEV + SPARK & SCALA TRAINING. This course is designed to ensure scalability, handling vast data with ease. Learn Hadoop development, Spark’s real-time processing, and Scala's versatility, preparing you for high-demand big data roles across industries.
Flexibility
Our HADOOP DEV + SPARK & SCALA TRAINING offers unmatched flexibility, enabling you to handle structured and unstructured data with ease. Master Hadoop's storage power, Spark's processing speed, and Scala's adaptability, making you industry-ready for diverse big data challenges.
Hybrid Capabilities
Our HADOOP DEV + SPARK & SCALA TRAINING combines the best of both worlds—Hadoop’s storage and data management with Spark’s lightning-fast processing, powered by Scala's functional programming. This hybrid approach equips you with dynamic skills for handling modern big data challenges efficiently.
Security and Compliance
Our HADOOP DEV + SPARK & SCALA TRAINING ensures you master security and compliance in big data environments. Learn how to safeguard data with Hadoop’s robust security features, Spark’s encryption, and Scala’s secure coding, ensuring compliance with industry standards and regulations.
Cost-Effectiveness:
Our HADOOP DEV + SPARK & SCALA TRAINING is designed for cost-effectiveness, offering powerful tools for big data at a fraction of the cost. Hadoop's open-source framework, paired with Spark’s efficiency and Scala’s concise coding, optimizes resources while reducing infrastructure expenses.
Innovation
Our HADOOP DEV + SPARK & SCALA TRAINING drives innovation by combining cutting-edge technologies. Hadoop’s robust data management, Spark’s real-time processing, and Scala’s advanced programming enable you to create groundbreaking solutions and stay ahead in the rapidly evolving big data landscape.
Global Certification
Online Classroom PREFERRED
- Live Classes from IIT Faculty & Industry Experts
- Certification from IHUB IIT Roorkee
- Career Services (Mock Interviews, Resume Preparation)
- Placement Assistance upon clearing PRT
- Dedicated Learning Manage
Hadoop Dev Spark Scala Training & Certification In Bangalore
Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry
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career services
At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalized resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career. Join us and let your journey to a successful future begin with the right support.
At Radical Technologies, we ensure you’re ready to shine in any interview. Our comprehensive Interview Preparation program includes mock interviews, expert feedback, and tailored coaching sessions to build your confidence. Learn how to effectively communicate your skills, handle technical questions, and make a lasting impression on potential employers. With our guidance, you’ll walk into your interviews prepared and poised for success.
At Radical Technologies, we believe that a strong professional profile is key to standing out in the competitive IT industry. Our Profile Building services are designed to highlight your unique skills and experiences, crafting a resume and LinkedIn profile that resonate with employers. From tailored advice on showcasing your strengths to tips on optimizing your online presence, we provide the tools you need to make a lasting impression. Let us help you build a profile that opens doors to your dream career.
Red Hat Linux Course Projects
Infrastructure Provisioning
And Configuration Management
Implementing automated infrastructure provisioning and configuration management using Ansible. This may include setting up servers, networking devices, and other infrastructure components using playbooks and roles.
Applications Deployment
And Orchestration
Automating the deployment and orchestration of applications across development, testing, and production environments. This could involve deploying web servers, databases. middleware, and other application components using Ansible
Continuous Integration
And Continuous Deployment
Integrating Ansible into CI/CD pipelines to automate software. build, test, and deployment processes. This may include automating the creation of build artifacts, running tests, and deploying applications to various environments.
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