Viral Industries Interview Questions and Answers

Handling service downtime in microservice architecture is crucial for maintaining system reliability.

• Implement circuit breakers to prevent cascading failures

• Use service discovery to automatically route traffic to healthy instances

• Implement retry mechanisms with exponential backoff to handle transient failures

• Monitor service health and performance metrics to proactively detect issues

• Implement graceful degradation to provide basic functionality when a service is down

Implement rate limiting, load balancing, and circuit breaking to handle too many requests in micro service architecture.

• Implement rate limiting to control the number of requests a service can handle within a specific time frame.

• Use load balancing to distribute incoming requests evenly across multiple instances of a service.

• Implement circuit breaking to prevent cascading failures and overload in case of high traffic.

• Consider using caching mechanisms to store frequently accesse...read more

Data shuffling in Spark is the process of redistributing data across partitions to optimize parallel processing.

• Data shuffling occurs when data needs to be moved across partitions, typically during operations like groupBy, join, or sortBy.

• It involves transferring data between executors, which can be a costly operation in terms of performance.

• Data shuffling can impact the performance of a Spark job, so it's important to minimize unnecessary shuffling.

• One way to reduce data shu...read more

Distribute candies among students based on their ratings, ensuring higher rated students get more candies.

• Create an array to store the ratings of each student

• Initialize another array to store the number of candies each student will receive

• Start by giving each student 1 candy

• Iterate over the ratings array from left to right, comparing each student's rating with the previous one and adjusting the candies accordingly

Data serialization is the process of converting data structures or objects into a format that can be stored or transmitted.

• Serialization involves converting data into a byte stream for storage or transmission.

• Common serialization formats include JSON, XML, and Protocol Buffers.

• Serialization allows data to be easily saved to a file or sent over a network.

• Deserialization is the reverse process of converting serialized data back into its original form.

Map-reduce is a programming model used for processing and generating large data sets in parallel.

• Map function processes input data and generates key-value pairs

• Reduce function takes the output of the map function and combines the values with the same key

• Example: Word count in a document - map function counts occurrences of each word, reduce function sums up the counts