Explore the Complete Hadoop Ecosystem: 20+ Projects and Learning Roadmap

Since 2011, China has entered the era of big data, with Hadoop and its family dominating data processing. The Hadoop ecosystem now includes over 20 open‑source projects such as Hadoop, Hive, Pig, HBase, Sqoop, Mahout, Zookeeper, Avro, Ambari, and many newer components like YARN, HCatalog, Oozie, Cassandra, Hama, Whirr, Flume, Bigtop, Crunch, Hue.

Below is a concise overview of each project and a suggested learning roadmap.

1. Hadoop Family Projects

Apache Hadoop – distributed computing framework with HDFS and MapReduce.

Apache Hive – data‑warehouse tool that maps structured files to tables and provides SQL‑like queries.

Apache Pig – large‑scale data analysis with Pig Latin language compiled to MapReduce.

Apache HBase – column‑oriented, scalable, high‑reliability storage system.

Apache Sqoop – tool for transferring data between Hadoop and relational databases.

Apache Zookeeper – coordination service for distributed applications.

Apache Mahout – machine‑learning and data‑mining library built on MapReduce.

Apache Cassandra – open‑source distributed NoSQL database.

Apache Avro – data serialization system for high‑volume data exchange.

Apache Ambari – web‑based management and monitoring of Hadoop clusters.

Apache Chukwa – data collection system for large distributed systems.

Apache Hama – BSP‑based parallel computing framework for graphs, matrices, networks.

Apache Flume – reliable, high‑availability service for massive log aggregation.

Apache Giraph – scalable iterative graph processing system.

Apache Oozie – workflow engine for coordinating Hadoop jobs.

Apache Crunch – Java library for building MapReduce pipelines.

Apache Whirr – library for running Hadoop and other services on cloud platforms.

Apache Bigtop – packaging, distribution, and testing tool for Hadoop ecosystem.

Apache HCatalog – metadata and schema management across Hadoop and RDBMS.

Cloudera Hue – web UI for monitoring and managing HDFS, MapReduce/YARN, HBase, Hive, Pig.

2. Hadoop Family Learning Roadmap

The author proposes a personal learning path, covering installation, configuration, and practical projects for each component.

Hadoop

Hadoop learning roadmap

YARN learning roadmap

Build Hadoop projects with Maven

Install historical Hadoop versions

Programmatic HDFS access

Massive web‑log analysis for KPI extraction

Movie recommendation system with Hadoop

Create Hadoop base virtual machine

Clone VM to add Hadoop nodes

Integrate R with Hadoop (RHadoop)

RHadoop practice series – environment setup

Implement matrix multiplication with MapReduce

Parallel PageRank algorithm

PeopleRank for social‑network value discovery

Hive

Hive learning roadmap

Hive installation and usage guide

Hive test importing 10 GB data

R‑based NoSQL series – Hive

Extract reverse‑repo information with RHive

Pig

Pig learning roadmap

Zookeeper

Zookeeper learning roadmap

Step‑by‑step cluster installation and usage

Implement distributed queue with Zookeeper

Implement FIFO queue with Zookeeper

Case study of queue system integration based on Zookeeper

HBase

HBase learning roadmap

Install HBase on Ubuntu

RHadoop practice series – rhbase installation and usage

Mahout

Mahout learning roadmap

R analysis of Mahout collaborative filtering

RHadoop practice – MapReduce collaborative filtering

Build Mahout projects with Maven

Mahout recommendation API details

Source‑code dissection of Mahout engine

Item‑based collaborative filtering development

K‑means clustering

Job recommendation engine with Mahout

Book recommendation system with Mahout

Sqoop

Sqoop learning roadmap

Cassandra

Cassandra learning roadmap

Two‑node Cassandra cluster experiment

R‑based NoSQL series – Cassandra

Additional components to explore later include Avro, Ambari, Chukwa, Hama, Flume, Giraph, Oozie, Crunch, Whirr, Bigtop, HCatalog, and Hue.