20+ EPAM Systems Interview Questions and Answers for Freshers

Design patterns in Mule 4 help in structuring and organizing code for better maintainability and scalability.

• Mule 4 supports various design patterns such as scatter-gather, choice, splitter, aggregator, etc.

• Design patterns help in solving common integration challenges and promoting best practices.

• For example, using scatter-gather pattern to send a request to multiple services in parallel and aggregate the responses.

Designing API tests for Mule 4

• Use MUnit for testing Mule 4 APIs

• Write test cases to cover all possible scenarios

• Mock external dependencies for isolated testing

• Use assertions to validate API responses

Mule 4 offers improved performance, enhanced error handling, and better support for modern integration patterns compared to Mule 3.

• Mule 4 has a more streamlined and efficient runtime engine.

• Mule 4 provides better error handling capabilities with the introduction of Try scope.

• Mule 4 supports more modern integration patterns like reactive programming.

• Mule 4 offers improved dataweave capabilities for data transformation.

• Mule 4 has a more modular architecture, making it easier to...read more

Using Java 8 features to write efficient and concise code.

• Utilize lambda expressions for functional programming

• Use streams for processing collections in a more declarative way

• Leverage default methods in interfaces for backward compatibility

• Explore the new Date and Time API for improved handling of dates and times

Count the number of words in a list of strings

• Iterate through the list of strings

• Split each string by spaces to get individual words

• Increment a counter for each word encountered

Execution context refers to the environment in which a piece of code is executed, including variables, scope, and this keyword.

• Execution context includes variables, scope chain, and the value of the this keyword.

• There are three types of execution contexts: global, function, and eval.

• Each function call creates a new execution context, which is pushed onto the call stack.

• Lexical environment and variable environment are part of the execution context.

Stream based problems involve processing data in a continuous flow rather than all at once.

• Use stream processing libraries like Apache Kafka or Apache Flink

• Consider factors like data volume, velocity, and variety

• Implement backpressure mechanisms to handle high data loads

Closure is a function that captures the environment in which it was created, allowing it to access variables from its outer scope even after the outer function has finished executing.

• Closure allows a function to access variables from its outer scope even after the outer function has finished executing.

• It 'closes over' the variables in its lexical scope, preserving their values.

• Closure is commonly used in event handlers, callbacks, and asynchronous code.

• Example: function outer...read more

Check if strings are anagrams by sorting characters and comparing

• Sort characters in each string and compare if they are equal

• Use a hashmap to count characters in each string and compare the counts

• Example: 'listen' and 'silent' are anagrams

LRU cache is a data structure that stores the most recently used items and discards the least recently used items.

• LRU stands for Least Recently Used

• It has a fixed size and when it reaches its limit, the least recently used item is removed to make space for a new item

• It uses a doubly linked list and a hash map to achieve O(1) time complexity for both insertion and deletion

• Example: A web browser caching the most recently visited web pages to improve performance

Dataflow and Dataproc are both processing services in GCP, but with different approaches and use cases.

• Dataflow is a fully managed service for executing batch and streaming data processing pipelines.

• Dataproc is a managed Spark and Hadoop service for running big data processing and analytics workloads.

• Dataflow provides a serverless and auto-scaling environment, while Dataproc offers more control and flexibility.

• Dataflow is suitable for real-time streaming and complex data tran...read more

To delete duplicates from a table in Spark and SQL, you can use the DISTINCT keyword or the dropDuplicates() function.

• In SQL, you can use the DISTINCT keyword in a SELECT statement to retrieve unique rows from a table.

• In Spark, you can use the dropDuplicates() function on a DataFrame to remove duplicate rows.

• Both methods compare all columns by default, but you can specify specific columns to consider for duplicates.

• You can also use the partitionBy() function in Spark to remov...read more

The question is asking about types of transformations, number of jobs, tasks, and actions in the context of a Senior Data Engineer role.

• Types of transformations: Extract, Transform, Load (ETL), MapReduce, Spark transformations, SQL transformations

• Number of jobs: Depends on the complexity and scale of the data engineering projects

• Number of tasks: Varies based on the number of data sources, data transformations, and data destinations

• Actions: Data ingestion, data cleaning, data ...read more

Optimization techniques in Spark, SQL, BigQuery, and Airflow.

• Use partitioning and bucketing in Spark to optimize data processing.

• Optimize SQL queries by using indexes, query rewriting, and query optimization techniques.

• In BigQuery, use partitioning and clustering to improve query performance.

• Leverage Airflow's task parallelism and resource allocation to optimize workflow execution.

Spark is a distributed processing engine, Airflow is a workflow management system, and BigQuery is a fully managed data warehouse.

• Spark is designed for big data processing and provides in-memory computation capabilities.

• Airflow is used for orchestrating and scheduling data pipelines.

• BigQuery is a serverless data warehouse that allows for fast and scalable analytics.

• Spark can be integrated with Airflow to schedule and monitor Spark jobs.

• BigQuery can be used as a data source or...read more

Move all zeros in an array of strings to the end.

• Iterate through the array and keep track of the count of zeros encountered.

• Remove each zero encountered and append it to the end of the array.

• Continue this process until all zeros are moved to the end.

Stack memory is used for static memory allocation while heap memory is used for dynamic memory allocation.

• Stack memory is allocated at compile-time while heap memory is allocated at runtime.

• Stack memory is limited in size while heap memory can grow dynamically.

• Stack memory is automatically managed by the system while heap memory must be manually managed.

• Examples of stack memory include function call stack and local variables while examples of heap memory include objects creat...read more

TestNG annotations allow for parallel execution of test methods using attributes like 'parallel' and 'thread-count'.

• TestNG annotations like @Test, @BeforeTest, @AfterTest can be used with attributes like 'parallel' to specify parallel execution of test methods.

• The 'parallel' attribute can have values like 'methods', 'tests', 'classes', 'instances' to define the scope of parallel execution.

• The 'thread-count' attribute can be used to specify the number of threads to be used for...read more

Methods in collections are used to manipulate and retrieve data from collections in programming.

• Some common methods include add(), remove(), contains(), size(), and clear().

• For example, the add() method is used to add an element to a collection, while remove() is used to remove an element.

• The contains() method is used to check if a collection contains a specific element, while size() returns the number of elements in the collection.

• Finally, the clear() method is used to remov...read more

Exceptional handling is the process of identifying, catching, and responding to errors in software applications.

• Exception handling is used to prevent application crashes and provide a graceful way to handle errors.

• It involves using try-catch blocks to catch exceptions and handle them appropriately.

• Logging and reporting exceptions is also important for debugging and improving application performance.

• Best practices include using specific exception types, avoiding catching gener...read more

AWS provides various services that can be used to build a scalable and reliable architecture for Kubernetes.

• AWS Elastic Kubernetes Service (EKS) is a managed Kubernetes service that simplifies the deployment, management, and scaling of Kubernetes clusters.

• AWS CloudFormation can be used to automate the provisioning of infrastructure resources for Kubernetes clusters.

• AWS Identity and Access Management (IAM) can be used to manage access control and permissions for Kubernetes res...read more

Create a method to check if element is visible within a specified timeout

• Create a method that accepts a locator and timeout as parameters

• Use a loop to check if the element is visible within the specified timeout

• Return success if the element is visible before timeout, else return failure

Discussing project details and negotiating salary for Senior Developer position.

• Highlighting past project successes and challenges

• Discussing technical skills and experience relevant to the role

• Negotiating salary based on market rates and personal expectations