Top 5 Interview Questions on Apache Oozie

Shikha Sharma 14 Feb, 2023
5 min read

Introduction

Today we have an abundance of Hadoop jobs that are running in a constant plane, but we can’t schedule these jobs manually, we need some kind of scheduler to handle this flow. Apache Oozie is one such job scheduler that allows users to run, schedule, and manage Hadoop jobs in a distributed environment.

 https://informationit27.medium.com/job-scheduling-using-apache-oozie-e18aff73f2c6

Source: informationit27.medium.com

Oozie is a scalable, extensible, and reliable system that allows users to execute multiple jobs parallelly so that more than one job can be executed simultaneously, and we can accomplish a more significant task. Oozie is famous for its smooth integration with the Hadoop stack, which allows the execution of various Hadoop-related jobs like Pig, Hive, and Sqoop.

In this blog, I discussed five interview-winning questions that will help you to set a pace for Apache Oozie and ace your upcoming interview!

Learning Objectives

Below is what we’ll learn after reading this blog thoroughly:

  1. A common understanding of what an Apache Oozie is and its role in the technical era.
  2. Knowledge of Apache Oozie workflow along with different states of a workflow job.
  3. An understanding of the Oozie security.
  4. An understanding of pipeline workflows in Apache Oozie.
  5. Insights into some frequently used Oozie commands

Overall, by reading this guide, we will gain a comprehensive understanding of Oozie to schedule the jobs.

This article was published as a part of the Data Science Blogathon.

Table of Contents

Q1. Why do we Need Apache Oozie if we Cascade Jobs One After Another?

By cascading the jobs one after another, we can perform the job scheduling, but whenever there is a job failure for any reason, we’re not allowed to restart that job from the failure. Rather, we have to restart the entire process, which is a very inefficient and time-consuming. Also, we lack flexibility like starting, stopping, suspending, or re-running a job.

The purpose of using Apache Oozie is to manage multiple types of jobs that are being efficiently processed in the Hadoop system.

Oozie is a Java Web Application that runs in a Java servlet container, allows us to execute multiple independent jobs simultaneously, run the jobs back to back following a specific sequence, run the jobs on a defined time, or can control the jobs from anywhere.

Users define their jobs as a Directed Acyclic Graph(DAG) with multiple dependencies in-between and then, Oozie takes this information to perform the assigned task in a particular order as available in the workflow. That’s how Ooozie will save our time and energy by managing the entire workflow, which is not available in normal job cascading.

Special Features of Oozie
1. Email Notification: Oozie facilities us with Email notification features that can be sent upon the completion of jobs.

2. Web Services API: Oozie supports web services API, enabling us to control jobs from anywhere.

3. Client API: Oozie supports us with a command-line interface to launch, control, and monitor a job from the Java application.

4. Periodic Run: Oozie allows us to execute the scheduled jobs periodically.

Q2. Explain the Apache Oozie Workflow in Detail.

The workflow of Apache Oozie is a collection/group of actions arranged in a control dependency DAG (Direct Acyclic Graph). The DAG can control how and when an action can be run. “hPDL”(an XML Process Definition Language) is used to write the Oozie workflow definitions.

Major components of Apache Oozie Workflow

The two key components of Apache Oozie Workflow include:

Control Flow Nodes: Control flow nodes are the mechanisms that play a significant role in defining the start and end of the workflow i.e., start, end, and fail. Apart from that control glow node also offers a mechanism to control and handle the execution path of the workflow (decision, fork, and join).

Action Nodes: Action nodes are used to trigger the execution of a computation or processing task. It is a mechanism by which Oozie offers support for different types of Hadoop actions, including Hadoop MapReduce, Hadoop file system, Pig, etc. Oozie also offers support for system-defined jobs like SSH, HTTP, email, etc.

 https://aws.amazon.com/blogs/big-data/use-apache-oozie-workflows-to-automate-apache-spark-jobs-and-more-on-amazon-emr/

Source: aws.amazon.com

Apache Oozie Workflow Job States

Below are the various states defined in an Oozie workflow job:-

1. PREP: It is the initial state of the workflow job where the user only creates the job, and it’s still just defined.

2. RUNNING: It is the main execution state where the job begins to run and stays there until it reaches the end state, an error occurs, or the job is suspended due to some conditions.

3. SUSPENDED: A job reaches the suspended state if there is any issue occurring in the running time or someone explicitly suspends the job. A job can move from the suspended state to the running or killed state.

4. SUCCEEDED: As soon as the job hits the end node, the workflow job becomes successful.

5. KILLED: As soon as the administrator kills any workflow job in the prep, running, or suspend state, it moves to the killed state.

6. FAILED: When any workflow job fails due to an unexpected error in the running state, it reaches the failed state.

 https://www.cloudduggu.com/oozie/coordinator/

Source: www.cloudduggu.com

Q3. Why is There a Concept of Oozie Security?

Oozie facilitates security features because the customer/user is not allowed to modify the job of any other user, and Hadoop does not authenticate the end user. That’s why Oozie does the task of user verification and then passes the jobs to Hadoop.

Q4. Explain how the Pipeline Works in Apache Oozie.

The role of the pipeline in Oozie is to connect the various jobs in a workflow that executes routinely but during different time intervals. A joined chain of workflows where the output of multiple executions of workflow becomes the input of the next scheduled job in the workflow and gets executed one after another in the pipeline creates the Oozie pipeline of jobs.

Q5. Write the Oozie Commands for the Following Tasks.

  • Command to run the Oozie
$ oozie job -oozie http://172.20.95.107:11000(oozie_server_node)/oozie 
-config job.properties -run
  • Command to check the status of coordinator or bundle action in Oozie
$ oozie job -oozie http://172.20.95.107:11000(oozie_server_node)/oozie 
-info <job id>
  • Command to specify oozie start, end, and error nodes
<start to=“[START-NODE-­NAME]” />

<end name=“[END-NODE-­NAME]”/>

<error

<message>“[Any custom message]”</message>

</error>
  • Command to get the status of all running Oozie workflow
$ oozie job -oozie http://172.20.95.107:11000(oozie_server_node)/oozie 
-start <job-name or job-id>
  • Command to submit a coordinator or bundle job in Oozie
$ oozie job -oozie http://172.20.95.107:11000(oozie_server_node)/oozie
 -config job.properties -submit <job-name or job-id>

Conclusion

This blog covers some of the frequently asked Apache Oozie interview questions that could be asked in data science and big data developer interviews. Using these interview questions as a reference, you can better understand the concept of Apache Oozie and start formulating effective answers for upcoming interviews. The key takeaways from this Oozie blog are:-

  1. Apache Oozie is a scalable, extensible, and reliable scheduler that allows users to run, schedule, and manage Hadoop jobs.
  2. Oozie is always better than any cascading solutions due to its special features like Email notification, Client API, web API, etc.
  3. We discussed the complete workflow of Oozie with its main components.
  4. At last, we ended this blog by discussing some frequently used Oozie commands.

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Shikha Sharma 14 Feb, 2023

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