Abjayon Senior Quality Engineer Interview Questions and Answers

Bigdata systems architecture involves distributed storage, processing, and analysis of large volumes of data.

• Utilize distributed file systems like HDFS for storage

• Use parallel processing frameworks like Apache Spark or Hadoop for data processing

• Implement data pipelines for ETL processes

• Leverage NoSQL databases like Cassandra or MongoDB for real-time data querying

• Consider data partitioning and replication for fault tole

Big data system distribution for storage and compute involves partitioning data across multiple nodes for efficient processing.

• Data is partitioned across multiple nodes to distribute storage and processing load.

• Hadoop Distributed File System (HDFS) is commonly used for storage distribution.

• Apache Spark utilizes a cluster computing framework for distributed computing.

• Data locality is important to minimize data transfer ...read more

Use two threads to print odd and even numbers in sync

• Create two threads, one for printing odd numbers and one for printing even numbers

• Use synchronization mechanisms like mutex or semaphore to ensure output is in sync

• Example: Thread 1 prints odd numbers (1, 3, 5, ...) and Thread 2 prints even numbers (2, 4, 6, ...)

Find the largest common prefix among an array of strings.

• Iterate through the characters of the first string and compare with the corresponding characters of other strings.

• Stop when a mismatch is found or when reaching the end of any string.

• Return the prefix found so far.

Saga pattern is a design pattern used in microservices architecture to manage distributed transactions.

• Saga pattern breaks down a transaction into a series of smaller, independent steps.

• Each step in the saga is a separate transaction that can be rolled back if needed.

• If one step fails, compensating transactions can be executed to undo the changes made by previous steps.

• Saga pattern helps maintain data consistency in a ...read more

Hash map and hash set are data structures that use hashing to store key-value pairs and unique values respectively.

• Hash map uses key-value pairs where keys are hashed to find the corresponding value

• Hash set stores unique values using hashing to quickly check for duplicates

• Example: HashMap map = new HashMap<>(); HashSet set = new HashSet<>();