Apache Hadoop Training by
Laliwala IT is designed for data engineers,
developers, and IT professionals who want to
master the industry's leading big data platform.
Based in Ahmedabad, Gujarat,
India, we deliver live,
interactive, project-based training covering
everything from HDFS and MapReduce to YARN,
cluster setup, and the complete Hadoop
ecosystem.
Our online Apache Hadoop course features
real-time instructor-led classes,
hands-on projects, flexible schedules, and
career guidance. Whether you're a
beginner or looking to upgrade your big data
skills, this training will turn you into a
job-ready Hadoop professional.
Course Modules — Comprehensive Apache Hadoop
Training (6-7 Weeks | 45+ Hours)
- Module 1: Big Data & Hadoop
Fundamentals – What is
Big Data? 5Vs, Hadoop history,
architecture, ecosystem overview,
use cases
- Module 2: HDFS (Hadoop
Distributed File
System) – HDFS
architecture, NameNode, DataNode,
block storage, replication,
read/write pipeline
- Module 3: HDFS Operations &
Commands – HDFS shell
commands, file permissions,
snapshots, quotas, balancer, data
recovery
- Module 4: MapReduce
Framework – MapReduce
paradigm, Mapper, Reducer, Combiner,
Partitioners, Shuffle & Sort phase
- Module 5: MapReduce
Programming (Java) –
Writing MR jobs, InputFormats,
OutputFormats, Counters, custom data
types, Writable
- Module 6: YARN (Yet Another
Resource Negotiator) –
ResourceManager, NodeManager,
ApplicationMaster, Schedulers (FIFO,
Capacity, Fair)
- Module 7: Hadoop Cluster
Setup – Single node,
pseudo-distributed, fully
distributed cluster, configuration
files, AWS EMR setup
- Module 8: Hadoop Ecosystem
Tools – Hive, Pig,
HBase, Sqoop, Flume, Oozie,
ZooKeeper, Hue – introduction &
integration
- Module 9: Data Ingestion
(Sqoop & Flume) –
Import/export between RDBMS and
HDFS, incremental imports, Flume
agents, sources, sinks
- Module 10: Workflow &
Orchestration – Oozie
workflows, coordinators, bundles,
scheduling MapReduce, Hive, Pig jobs
- Module 11: Hadoop Security &
High Availability –
Kerberos authentication, ACLs, HDFS
HA (QJM, NFS), ResourceManager HA
- Module 12: Real-World
Capstone Project –
Build end-to-end batch processing
pipeline for log analytics or
clickstream data
What's Included in Apache Hadoop Training?
- Live
Instructor-led classes
(real-time Q&A, screen sharing, doubt
clearing)
-
Recorded sessions for
revision anytime
-
Hands-on assignments &
industry-level big data projects
-
Study materials (PDFs,
MapReduce code examples, cluster configs)
-
Certificate of completion
(recognized by industry partners)
-
Placement assistance –
resume & interview prep, freelance guidance
-
Lifetime access to course
updates and student community
Detailed Curriculum Highlights
Week 1-2: HDFS & MapReduce Core
- Introduction to distributed
computing and Hadoop design
principles
- HDFS architecture deep dive:
block placement, rack awareness,
heartbeats
- Hands-on HDFS commands: put,
get, copyToLocal, cat, du,
dfsadmin
- Understanding NameNode metadata
(fsimage, edits log) & Secondary
NameNode
- MapReduce data flow: input
splits, mapping, shuffling,
sorting, reducing
- Writing custom MapReduce jobs
for word count, log analysis,
join operations
- Using Counters for job metrics
and debugging
- Custom Writable and
WritableComparable
implementations
Week 3-4: YARN, Cluster Setup &
Ecosystem
- YARN architecture:
ResourceManager, NodeManager,
ApplicationMaster lifecycle
- Configuring CapacityScheduler
and FairScheduler for
multi-tenancy
- Setting up Hadoop cluster on AWS
EMR / Google Dataproc / Local VM
- Ecosystem introduction: Hive
(warehousing), Pig (data flow),
HBase (NoSQL)
- Using Sqoop to import/export
data between MySQL/Oracle and
HDFS
- Flume for streaming log
collection from sources to HDFS
- ZooKeeper for distributed
coordination and configuration
management
- Hue web interface for browsing
HDFS, Hive queries, job
management
Week 5-6: Advanced Operations,
Security & Capstone
- Oozie workflows: creating job
DAGs for complex ETL pipelines
- HDFS High Availability (HA) with
Quorum Journal Manager (QJM)
- ResourceManager HA setup and
failover configuration
- Kerberos authentication for
secure Hadoop clusters
- HDFS encryption at rest and data
masking
- Performance tuning: MapReduce
parameters, speculative
execution, JVM reuse
- Monitoring tools: Hadoop Admin
UI, YARN ResourceManager UI,
Ganglia, Ambari
- Capstone: Build complete batch
processing pipeline for
e-commerce clickstream analytics
Tools & Technologies Covered
- Apache Hadoop 3.x, HDFS,
MapReduce, YARN
- Languages: Java (primary),
Python (streaming), Shell
scripting
- Ecosystem: Hive, Pig, HBase,
Sqoop, Flume, Oozie, ZooKeeper,
Hue
- Cluster: AWS EMR, Google
Dataproc, Cloudera CDH,
Hortonworks HDP
- Monitoring: Ambari, Ganglia,
Prometheus, Grafana
- Orchestration: Apache Oozie,
Apache Airflow (overview)
Why Choose Laliwala IT for Apache Hadoop Online
Training?
- Industry Expert
Trainers: 10+ years of
Big Data & Hadoop experience
- Live Project
Experience: Build at
least 3 real-world big data
pipelines + final portfolio
- Flexible Batches:
Weekday & weekend options, recorded
backup for missed classes
- Small Batch Size:
Max 10-12 students for personalized
attention
- Affordable Fees:
High-quality training at competitive
rates from Ahmedabad hub
- Job Assistance:
Regular tie-ups with IT companies &
placement cell
- Certification: ISO
& Govt recognized certificate after
successful completion
- 24/7 Lab Access:
Online Hadoop clusters & learning
management system
- Global Recognition:
Trained students from India, USA,
UK, Canada, Australia, UAE
- Post-training
Support: Doubt clearing
via dedicated forum & email for 6
months
Who Should Join?
- Data engineers & developers wanting
to start Big Data career
- Java/Python professionals moving to
Hadoop ecosystem
- Database administrators exploring
distributed storage solutions
- System administrators managing
Hadoop clusters
- Data scientists requiring big data
processing skills
- College students seeking job-ready
Hadoop skills
- Working professionals aiming for
Cloudera/Hortonworks certification