Livy Hadoop

Livy is not directly related to Hadoop but rather to Apache Spark, which is often used in conjunction with Hadoop in big data processing. Livy is an open-source REST service for Apache Spark that allows you to interact with and submit Spark jobs remotely via a REST API. While it’s not specifically a Hadoop component, it can be used alongside Hadoop to manage and submit Spark jobs within a Hadoop cluster.

Here are some key points about Livy and its relationship with Hadoop:

1. Apache Spark Integration: Livy is designed to work with Apache Spark, which is commonly used for data processing, analytics, and machine learning tasks in the Hadoop ecosystem. Spark can be used alongside Hadoop’s HDFS for distributed data storage and processing.

2. Remote Spark Job Submission: Livy provides a RESTful API for submitting Spark jobs to a Spark cluster, which can be running on a Hadoop cluster. This allows you to submit Spark jobs from remote clients or applications without direct access to the cluster’s Spark master.

3. Job Management: Livy not only enables job submission but also provides job management capabilities. You can monitor job progress, retrieve job results, and perform various job-related operations using the Livy API.

4. Interactive Sessions: Livy supports interactive Spark sessions, where you can run Spark commands or code snippets interactively. This is useful for data exploration and experimentation.

5. Multi-User Support: Livy is designed to support multiple users, allowing different users or applications to submit and manage their Spark jobs concurrently.

6. Hadoop Cluster Usage: Livy can be deployed on a Hadoop cluster or alongside Hadoop components. This enables seamless integration of Spark job execution with data stored in HDFS and other Hadoop ecosystem tools.