Log management and troubleshooting in Hadoop - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of log management in Hadoop?

Log management helps collect, store, and analyze logs from Hadoop components to monitor system health and troubleshoot issues.

beginner

Name two common Hadoop logs used for troubleshooting.

Two common logs are the Namenode log and the Datanode log. They record important events and errors for their respective services.

intermediate

How can you access Hadoop logs on a cluster?

You can access logs via the Hadoop web UI or by checking log files directly on the cluster nodes, usually under the /var/log/hadoop directory.

beginner

What is a common first step when troubleshooting a failed Hadoop job using logs?

The first step is to check the job's logs for error messages or exceptions that indicate what went wrong.

intermediate

Why is it important to monitor Hadoop logs continuously?

Continuous monitoring helps detect problems early, prevent failures, and maintain cluster performance and reliability.

Which Hadoop component's log would you check first if the file system is not accessible?

A Datanode log

B Namenode log

C ResourceManager log

D JobHistory log

The Namenode manages the file system namespace, so its logs are key for file system access issues.

Where are Hadoop logs typically stored on cluster nodes?

A /var/log/hadoop

B /usr/local/hadoop/logs

C /etc/hadoop/logs

D /home/hadoop/logs

Hadoop logs are usually stored in /var/log/hadoop on cluster nodes.

What is the best way to find the cause of a failed MapReduce job?

A Check the job's logs for errors

B Restart the cluster

C Increase memory allocation

D Run the job again without changes

Checking the job's logs helps identify specific errors causing failure.

Which tool can help you view Hadoop logs through a web interface?

A YARN ResourceManager

B SSH terminal

C Hadoop Web UI

D HDFS command line

The Hadoop Web UI provides access to logs in a user-friendly way.

Why is continuous log monitoring important in Hadoop?

A To avoid writing logs

B To reduce disk space usage

C To speed up job execution

D To detect issues early and maintain cluster health

Continuous monitoring helps catch problems early and keep the cluster running smoothly.

Explain how you would use Hadoop logs to troubleshoot a job failure.

Think about the steps from finding logs to understanding errors.

Describe why log management is critical for maintaining a healthy Hadoop cluster.

Consider the benefits of logs beyond just error messages.