Senior Software Engineer 4 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

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

Reverse a linked list by changing the next pointers of each node to point to the previous node.

• Start with three pointers: current, previous, and next.

• Iterate through the linked list, updating the next pointer of each node to point to the previous node.

• Update the previous, current, and next pointers for each iteration.

Reverse a string by iterating through the characters and swapping them

• Create a function that takes a string as input

• Initialize two pointers, one at the beginning and one at the end of the string

• Swap the characters at the two pointers and move them towards the center until they meet