Introduction to Apache Hadoop
Apache Hadoop is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data.
Core Modules: HDFS, YARN, and MapReduce
Hadoop consists of three core components:
1.
HDFS (Hadoop Distributed File System): A distributed
storage layer that breaks large files into blocks and
replicates them across cluster nodes.
2.
MapReduce: The software framework that processes large
datasets in parallel across nodes.
3.
YARN (Yet Another Resource Negotiator): The cluster
operating system managing compute resources and job
scheduling.
Hadoop in the Era of Cloud Lakes
While modern data pipelines frequently use memory-centric frameworks like Spark or cloud services like Snowflake for processing, Hadoop HDFS remains highly relevant as a cost-effective, high-capacity distributed file system for storing massive historical datasets.
HDFS File Management Shell Operations
# Create a partitioned analytics folder structure on HDFS
hdfs dfs -mkdir -p /analytics/cacts/input
# Transfer local data lake CSV from local machine to Hadoop
hdfs dfs -put client_records.csv /analytics/cacts/input/
# Read files and verify HDFS directory structures
hdfs dfs -ls /analytics/cacts/input/Official Documentation
Access official code repositories and developer documentation.