TCS Hadoop and Spark Developer Interview Questions and Answers

Hive optimization techniques improve query performance by optimizing data storage and query execution.

• Partitioning tables based on commonly used columns to reduce data scanned during queries

• Using bucketing to evenly distribute data across files for faster query processing

• Using appropriate file formats like ORC or Parquet for efficient storage and retrieval

• Optimizing joins by broadcasting smaller tables or using map-sid...read more

Hive is a data warehousing tool built on top of Hadoop for querying and analyzing large datasets stored in Hadoop Distributed File System (HDFS).

• Hive uses a SQL-like query language called HiveQL to process data.

• It translates HiveQL queries into MapReduce jobs to execute on Hadoop.

• Hive organizes data into tables, partitions, and buckets for efficient querying.

• It supports external tables for data stored outside of HDFS.

• H...read more

HQL is used for querying data stored in Hadoop, while SQL is used for querying data stored in relational databases.

• HQL is used in Apache Hive for querying data stored in Hadoop Distributed File System (HDFS)

• SQL is used for querying data stored in relational databases like MySQL, PostgreSQL, etc.

• HQL supports complex data types like arrays and maps, which are not supported in SQL

• HQL queries are converted into MapReduce j...read more

I am a Hadoop Administrator with experience in managing and optimizing Hadoop clusters.

• Experienced Hadoop Administrator

• Proficient in managing and optimizing Hadoop clusters

• Skilled in troubleshooting and resolving Hadoop-related issues

• Knowledgeable in Hadoop ecosystem components like HDFS, MapReduce, YARN, Hive, Pig, etc.

• Familiar with Hadoop security and authentication mechanisms

• Experience in capacity planning and perfo

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.

My notice period is 30 days.

• I have a notice period of 30 days.

• I am required to give a 30-day notice before leaving my current position.

• I will be available to start a new job after the completion of my notice period.

As a Hadoop Administrator, my day-to-day activities involve managing and maintaining Hadoop clusters, monitoring system performance, troubleshooting issues, and implementing security measures.

• Managing and maintaining Hadoop clusters

• Monitoring system performance and resource utilization

• Troubleshooting and resolving issues related to Hadoop infrastructure

• Implementing security measures to protect data and ensure complianc...read more

The challenging aspects of a Hadoop Administrator job role

• Managing and troubleshooting large-scale Hadoop clusters

• Ensuring high availability and performance of the Hadoop ecosystem

• Implementing security measures to protect sensitive data

• Keeping up with the rapidly evolving Hadoop ecosystem and its related technologies

• Optimizing resource utilization and capacity planning

• Collaborating with cross-functional teams to addres...read more

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 sc...read more

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...read more

I handled a critical incident where a Hadoop cluster crashed due to a hardware failure.

• Identified the root cause of the hardware failure

• Coordinated with the hardware vendor to replace the faulty components

• Restored the Hadoop cluster from the latest backup

• Performed thorough testing to ensure data integrity and cluster stability

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 i

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

Yes, I have led a team.

• Led a team of 5 Hadoop administrators in managing and maintaining a large Hadoop cluster

• Assigned tasks, set goals, and provided guidance to team members

• Conducted regular team meetings to discuss progress, challenges, and improvements

• Implemented effective communication channels to ensure smooth collaboration within the team

• Successfully completed several projects on time and within budget with the