MapReduce Job History Server
The MapReduce Job History Server in Apache Hadoop is a web-based service that provides detailed information about the execution of past MapReduce jobs. This server is particularly useful for tracking, debugging, and monitoring historical job data after the job has completed.
Key Components:
The following section describes the key components of the MapReduce Job History Server:
- Job History Files:
- The Job History Server retrieves completed job information from the job history logs, which are stored in a designated directory in HDFS.
- These files include details such as job configuration, task-level metrics, counters, logs, and other metadata.
- Server UI
- The Job History Server provides a web interface (often available on port 19888 by default) where users can view job-specific details.
- The UI includes a dashboard with lists of completed jobs, allowing users to drill down into each job to view individual tasks, map/reduce counters, and logs.
- Job Summary and Details:
- Each completed job in the UI shows a summary that includes, Job start and end times, Duration and the Final status (successful or failed)
- Number of tasks, task types (map/reduce), and completion statistics
- Detailed task views are available, including information on data read/write, task attempts, execution time, and error messages if applicable.
- Error Analysis and Logs:
- The Job History Server enables users to review logs and error messages for failed tasks.
- Logs help with troubleshooting and identifying performance bottlenecks.
- Counters and Metrics:
- Job and task-level counters offer insights into resource usage, such as data processed, time spent, and custom counters defined in the job.
