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20+ Lumens Technologies Interview Questions and Answers

Updated 18 Feb 2025
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Q1. design pattern mule 4

Ans.

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.

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Q2. mule 4 design api test

Ans.

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

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Q3. mule 4 vs mule 3

Ans.

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

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Q4. writing code using java8

Ans.

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

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Q5. print the count of words in a list

Ans.

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

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Q6. what is execution context?

Ans.

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.

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Q7. Stream Based Problems

Ans.

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

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Q8. What is closure?

Ans.

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

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Q9. check if strings are anagrams

Ans.

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

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Q10. Working of LRU cache

Ans.

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

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Q11. Dataflow vs Dataproc, layering processing and curated environments in gcp , Data cleaning

Ans.

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

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Q12. delete duplicates from table in spark and sql

Ans.

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

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Q13. types of transformations,no of jobs,tasks,actions

Ans.

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

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Q14. optimisation in spark,sql,bigquery,airflow

Ans.

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.

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Q15. architecture of spark,airflow,bigquery,

Ans.

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

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Q16. in a array move zeros to end

Ans.

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.

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Q17. What's difference between stack memory and heap memory

Ans.

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

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Q18. Test ng annotations attributes parallel execution

Ans.

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

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Q19. Methods in collections and their uses.

Ans.

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

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Q20. Deep dive in Exceptional Handling

Ans.

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

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Q21. AWS concepts services used architecture for Kubernetes

Ans.

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

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Q22. Write an extended method, which will accept locator and timeout, if method is visible before timeout, return success else return failure

Ans.

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

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Q23. Generic project duscussion and salary

Ans.

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

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Q24. What is the roal you applied to?

Ans.

I applied for the role of Marketing Intern.

  • I have experience in social media marketing and content creation.

  • I am familiar with SEO and Google Analytics.

  • I have completed relevant coursework in marketing strategies.

  • I have previously interned at a marketing agency.

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