Big Data for Beginners is the second continuously updated beginner series I’m starting, after Spring Cloud Microservices for Beginners. It covers data warehouse concepts and beginner tutorials for Hadoop, ZooKeeper, Hive, Flume, Kafka, Hbase, Sqoop, Oozie, Azkaban, Kylin, CDH, Impala, Hue, ClickHouse, Kettle, Ambari, ELK, Scala and Flink. All of it targets beginners and focuses on building and using a big data platform, without going deep into the individual technologies.
This series follows my own self-study, sharing notes and experience as I go. Corrections are welcome, and if you’d like to share your own experience and insights, join the discussion on the community forum: https://bbs.renfei.net/forum-50-1.html
This beginner series jumps straight into setting up Hadoop. Before that you’d normally learn the web basics, Java basics, Maven and Spring basics, plus Redis and MySQL and some Linux fundamentals — I already have those, so I won’t go back over them. I’ll assume you know them too and start from big data platform setup; otherwise there’d be no end to it.
Since the big data platform has so many components, this series may take a very long time to update, so I’m creating this post as a directory index first. I’ll update it as I publish, so bookmark this page as an index for later.
Here’s the index, updated in real time as the series progresses:
[ Data Warehouse Basics ] Data Warehouse Concepts (1): What a Data Warehouse Is and How It Differs from a Database Data Warehouse Concepts (2): Layered Data Warehouse Design Data Warehouse Concepts (3): Data Modeling — Fact Tables, Dimension Tables, Star and Snowflake Schemas Data Warehouse Concepts (4): Full, Incremental, Zipper, Transaction and Snapshot Tables
[ Hadoop for Beginners ] Hadoop for Beginners (1): What Hadoop Is and What It’s Made Of Hadoop for Beginners (2): Installing Hadoop Hadoop for Beginners (3): Single-Node Local and Pseudo-Distributed Mode Hadoop for Beginners (4): A Fully Distributed Hadoop Cluster Hadoop for Beginners (5): HDFS, the Distributed File System Hadoop for Beginners (6): Using the Hadoop API to Drive HDFS from Code Hadoop for Beginners (7): HDFS Data Read and Write Flow Hadoop for Beginners (8): How DataNode Works Hadoop for Beginners (9): Setting Up a Local Hadoop Development Environment Hadoop for Beginners (10): First Look at MapReduce Distributed Computing Hadoop for Beginners (11): Writing MapReduce in Code — a WordCount Example Hadoop for Beginners (12): Hadoop’s Writable Classes Hadoop for Beginners (13): MapReduce Input Splits and Parallelism Hadoop for Beginners (14): How MapReduce Shuffle Works
[ ZooKeeper for Beginners ] ZooKeeper for Beginners (1): Introduction and Installation ZooKeeper for Beginners (2): Programming with the ZooKeeper API ZooKeeper for Beginners (3): A Small Demo for Watching Node Changes ZooKeeper for Beginners (4): Inside ZooKeeper
[ Hive for Beginners ] Hive for Beginners (1): First Look at Hive Hive for Beginners (2): Installing and Deploying Hive Hive for Beginners (3): Hive Data Types
[ Flume for Beginners ] [None yet]
[ Kafka for Beginners ] [None yet]
[ Hbase for Beginners ] [None yet]
[ Sqoop for Beginners ] [None yet]
[ Oozie for Beginners ] [None yet]
[ Azkaban for Beginners ] [None yet]
[ Kylin for Beginners ] [None yet]
[ CDH for Beginners ] [None yet]
[ Impala for Beginners ] [None yet]
[ Hue for Beginners ] [None yet]
[ ClickHouse for Beginners ] [None yet]
[ Kettle for Beginners ] [None yet]
[ Ambari for Beginners ] [None yet]
[ ELK for Beginners ] [None yet]
[ Scala for Beginners ] [None yet]
[ Flink for Beginners ] [None yet]