---
title: "Short note: Oozie"
subject: "Big Data Technologies"
chapter: 6
key: "semester_8/big_data_technologies:short-note-oozie"
source: https://www.bctengineer.com/q/semester_8/big_data_technologies/short-note-oozie
site: BCT Engineering
---

# Short note: Oozie

Big Data Technologies · Chapter 6: Case Study: Hadoop

- Asked in: 2075 Bhadra, 5 marks
- Video: [Apache Oozie   Hadoop Ecosystem - Big Data Analytics Tutorial by Mahesh Huddar](https://www.youtube.com/watch?v=RexvKZHWw3s) — Mahesh Huddar
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_8/big_data_technologies/short-note-oozie
- Whole chapter: https://www.bctengineer.com/md/semester_8/big_data_technologies/chapter-6

## Question

Write a short note on Oozie.

## Short answer

Oozie is a workflow scheduler for Hadoop jobs, defining workflows as DAGs in XML with control and action nodes. It supports coordinator jobs for time or data triggers and bundles for multiple coordinators, and can rerun failed workflows.

## Answer

**Apache Oozie** is a workflow scheduler system for managing Hadoop jobs. It lets users define a series of dependent jobs (MapReduce, Pig, Hive, Sqoop, shell, Java) as a single unit and run them in order, on a schedule or on data availability. It is a Java web application integrated with the Hadoop stack, and works with YARN.

#### Types of Oozie jobs

1. **Workflow job:** a Directed Acyclic Graph (DAG) of actions defined in an XML file (`workflow.xml`). It has control nodes (start, end, kill, decision, fork, join) and action nodes.
2. **Coordinator job:** triggers workflows at regular times (e.g. daily) or when input data becomes available.
3. **Bundle:** a package of several coordinator jobs managed together.

```text
 start -> Sqoop import -> fork -> Hive job
                            \---> Pig job
                                 join -> MapReduce -> end
                    (any failure -> kill)
```

#### Features

- Workflows are written in XML (hPDL); a job runs as a MapReduce launcher on the cluster.
- Supports fork/join for parallel actions and decision nodes for conditions.
- Sends email notifications and provides callbacks and a web UI/CLI for monitoring.
- Scalable and reliable: it can rerun failed workflows.

#### Use

For example, a daily pipeline: import sales data from MySQL with Sqoop, clean it with Pig, aggregate with Hive, and export results, all in one Oozie workflow.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What is Apache Oozie?
   A. A workflow scheduler that runs dependent Hadoop jobs as a single unit
   B. A column database on HDFS
   C. A tool for streaming log collection
   D. A SQL engine
   Answer: A. Oozie defines a series of dependent jobs (MapReduce, Pig, Hive, Sqoop, etc.) and runs them in order or on schedule. (Key point: Purpose of Oozie)

2. What is an Oozie workflow job?
   A. A list of cron entries only
   B. A DAG of action and control nodes (start, end, kill, decision, fork, join) defined in XML
   C. A bundle of coordinator jobs
   D. A Java class with no configuration
   Answer: B. Workflows are Directed Acyclic Graphs written in workflow.xml. (Key point: Workflow job structure)

3. What does a coordinator job do, and what is a bundle?
   A. Coordinator groups many workflows; bundle runs a single action
   B. Coordinator is a kind of action node; bundle is a control node
   C. Coordinator triggers workflows at set times or when input data is available; a bundle packages several coordinators
   D. Both only restart failed jobs
   Answer: C. Coordinators add time and data triggers; bundles manage multiple coordinators together. (Key point: Coordinator and bundle)