Eco Systeme Hadoop

The Hadoop ecosystem is a framework and a suite of tools that work together to provide various services. Here’s a brief overview:

1. Hadoop HDFS: Hadoop Distributed File System is the storage unit of Hadoop. It stores data across multiple machines and provides high availability and fault tolerance.

2. Hadoop MapReduce: This is the processing engine of Hadoop. It processes large datasets in parallel by dividing them into smaller chunks.

3. Hadoop YARN: Yet Another Resource Negotiator manages resources of the systems storing the data and running the analysis.

4. Hadoop Common: These are Java libraries and utilities needed by other Hadoop modules.

5. Pig: A platform used to analyze large data sets representing them as data flows.

6. Hive: A data warehousing and SQL-like query language that presents data in the form of tables.

7. HBase: A scalable and distributed database that supports structured data storage for large tables.

8. ZooKeeper: A centralized service for maintaining configuration information and providing distributed synchronization.

9. Sqoop: A tool designed to transfer data between Hadoop and relational databases.

10. Oozie: Workflow scheduler system to manage Hadoop jobs.

11. Flume: Used to gather and aggregate large amounts of streaming data, like logs, from various sources into Hadoop.

12. Mahout: Machine learning library that utilizes Hadoop to run distributed algorithms.

13. Spark: An open-source distributed computing system that can process data much faster than MapReduce.

14. Storm: Real-time computation system that works with Hadoop to process data as it comes in.

15. Tez: A framework that allows for a complex directed-acyclic-graph of tasks to process data.

The Hadoop ecosystem offers a powerful suite of tools for large scale data processing and analysis. It is widely used in various industries to handle big data challenges