10+ Hadoop Administrator Interview Questions and Answers

I will identify and delete unnecessary files, compress data, and optimize storage to free up space.

• Identify and delete unnecessary files and logs

• Compress data to save space

• Optimize storage by removing temporary files or old backups

I have 3 years of experience in Big Data Administration.

• I have worked with Hadoop, Spark, and Hive.

• I have experience in setting up and maintaining Hadoop clusters.

• I have worked with various Big Data tools and technologies.

• I have experience in troubleshooting and resolving issues related to Big Data systems.

We use JIRA as our ticketing tool.

• JIRA is a popular ticketing tool used for issue tracking and project management.

• It allows us to create, assign, and track issues and tasks.

• We can also set priorities, due dates, and add comments and attachments.

• JIRA integrates well with other tools like Confluence and Bitbucket.

• We use JIRA to manage our Hadoop cluster and track any issues or bugs.

• It helps us to prioritize and resolve issues quickly and efficiently.

Answers to common questions related to Hadoop administration.

• HS2 stands for HiveServer2, which is a service that enables clients to execute queries against Hive.

• Hive is a data warehousing tool that facilitates querying and managing large datasets stored in Hadoop.

• Checkpointing is a process of saving the current state of a running application to a stable storage.

• NameNode is the centerpiece of HDFS, which manages the file system namespace and regulates access to files.

• YARN is a...read more

The command for checking live processes on a local level is 'ps'

• Use the 'ps' command to display information about currently running processes

• Add options like 'aux' to show more detailed information

• Use 'grep' to filter the output for specific processes

Our project architecture follows a distributed model with Hadoop clusters for data storage and processing.

• We use Hadoop clusters for distributed storage and processing of large datasets.

• Our architecture includes multiple nodes with Hadoop Distributed File System (HDFS) for data storage.

• We use YARN for resource management and job scheduling.

• We also use Apache Spark for data processing and analysis.

• Our architecture is scalable and fault-tolerant, ensuring high availability of d...read more

Prioritize tickets based on severity and impact on business operations.

• Assess the severity of the issue reported in the ticket

• Determine the impact of the issue on business operations

• Prioritize tickets with high severity and high impact on business operations

• Ensure timely resolution of critical issues to minimize business impact

Big data refers to large volumes of structured and unstructured data that is too complex for traditional data processing applications.

• Big data is characterized by the 3 Vs - volume, velocity, and variety.

• Volume refers to the sheer amount of data being generated, often in terabytes or petabytes.

• Velocity refers to the speed at which data is being generated and processed, often in real-time.

• Variety refers to the different types of data sources and formats, such as text, images, ...read more

Hadoop Administrators are responsible for managing, maintaining, and optimizing Hadoop clusters.

• Install, configure, and maintain Hadoop clusters

• Monitor cluster performance and troubleshoot issues

• Implement security measures to protect data

• Manage and allocate resources within the cluster

• Backup and restore data as needed

Spark architecture is based on master-slave architecture with a cluster manager and worker nodes.

• Spark has a master node that manages the cluster and worker nodes that execute tasks.

• The cluster manager allocates resources to worker nodes and monitors their health.

• Spark uses a distributed file system like HDFS to store data and share it across the cluster.

• Spark applications are written in high-level languages like Scala, Java, or Python and compiled to run on the JVM.

• Spark sup...read more

Zookeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and group services.

• Zookeeper is used to manage distributed systems and ensure consistency across nodes.

• It provides a hierarchical key-value store, similar to a file system.

• Zookeeper is often used in conjunction with Hadoop for coordination and synchronization tasks.

• It helps in maintaining configuration information, naming, providing distributed synchron...read more

Configuration files in Hadoop

• Hadoop uses XML-based configuration files

• The main configuration file is core-site.xml

• Other important configuration files are hdfs-site.xml, yarn-site.xml, and mapred-site.xml

• Configuration files can be edited manually or through Hadoop's web UI

• Changes to configuration files require a restart of the affected Hadoop services