60+ Appitsimple Infotek Interview Questions and Answers

Java 8 Garbage collector follows the algorithm called G1 (Garbage-First).

• G1 divides the heap into regions and collects garbage in small portions called 'garbage-first' regions.

• It uses multiple parallel threads for garbage collection.

• G1 aims to minimize pause times by dynamically adjusting the amount of garbage collected in each region.

• It uses a combination of young and old generation collection to achieve better performance.

• G1 also supports concurrent garbage collection, allo...read more

HTTP request passes through multiple network layers before reaching the server.

• HTTP request is first sent from client to local network router.

• Router forwards request to Internet Service Provider's network.

• Request then passes through multiple routers and switches in the internet backbone.

• Finally, request reaches the server hosting the requested website or service.

• Each network layer adds its own headers and metadata to the request.

Our project architecture follows a microservices approach with containerization using Docker and orchestration with Kubernetes.

• We have divided our application into smaller, independent services that communicate with each other through APIs.

• Each service is containerized using Docker, allowing for easy deployment and scaling.

• We use Kubernetes for orchestration, which automates the deployment, scaling, and management of our containers.

• Our services are written in different langua...read more

Forwards are customized contracts between two parties while futures are standardized contracts traded on exchanges.

• Forwards are traded over-the-counter while futures are traded on exchanges

• Forwards are customizable in terms of contract size, delivery date, and delivery location while futures are standardized

• Forwards have higher counterparty risk while futures have lower counterparty risk due to the involvement of a clearinghouse

• Forwards require a higher initial investment whi...read more

SOLID is a set of principles for object-oriented programming. L stands for Liskov Substitution Principle.

• SOLID principles help in creating maintainable and scalable software.

• Liskov Substitution Principle states that objects of a superclass should be replaceable with objects of its subclasses without affecting the correctness of the program.

• This principle ensures that the behavior of the program remains consistent even when objects are replaced with their subtypes.

• For example,...read more

I have worked with huge data sets in the past.

• I have experience working with data sets ranging from a few gigabytes to several terabytes.

• One of the toughest problems I faced was optimizing a query that was taking too long to execute.

• I resolved it by analyzing the query plan and identifying the bottleneck, then optimizing the query accordingly.

• Another challenge I faced was dealing with data inconsistencies, which I resolved by implementing data validation and cleaning processe...read more

Calculating time complexity of contains method in Java 8

• Time complexity of contains method in Java 8 is O(n)

• It depends on the size of the collection and the type of collection used

• For example, for ArrayList, it is O(n), for HashSet, it is O(1)

• Java 8 introduced a new method called contains(Object o, Predicate filter) which has a time complexity of O(n)

• The contains method is used to check if a collection contains a specific element

Use caching, minimize data transfer, optimize server-side code.

• Implement caching to reduce server requests

• Minimize data transfer by sending only necessary data

• Optimize server-side code for faster response time

Java 8 introduced several new features such as lambda expressions, functional interfaces, streams, and default methods.

• Lambda expressions: Allow you to pass functions as arguments to methods, making your code more concise and readable.

• Functional interfaces: Interfaces with a single abstract method, used to implement lambda expressions.

• Streams: Provide a way to work with sequences of elements and perform operations such as filter, map, and reduce.

• Default methods: Allow interfa...read more

Optimisation techniques in Pyspark and sample code for SCD type 2

• Use broadcast variables to reduce data shuffling

• Partition data based on key columns to improve performance

• Use cache() or persist() to avoid recomputing data

• Use coalesce() or repartition() to reduce the number of partitions

• For SCD type 2, use merge() function to update or insert new records

• Example code for SCD type 2: https://github.com/awantik/pyspark-101/blob/master/11-SCD2.ipynb

Sum of distinct elements from two arrays

• Create a set to store distinct elements from both arrays

• Iterate through each array and add elements to the set

• Calculate the sum of elements in the set

Murex front end office is a user interface for traders to manage trades and risk in real-time.

• Provides real-time market data and analytics

• Allows traders to execute trades and manage risk

• Customizable user interface to fit specific needs

• Integrates with other Murex modules such as back office and risk management

• Examples: Murex MX.3, Murex Mx.2

Creating a simple Jenkins job with required parameters

• Log in to Jenkins and click on 'New Item'

• Enter a name for the job and select 'Freestyle project'

• Add build steps, post-build actions, and configure parameters as needed

• Save the job and run it to test

WAP to count Duplicate String using Java 8

• Use Java 8 Stream API to group and count duplicate strings

• Create a Map to store the count of each string

• Filter the map to get only the strings with count > 1

• Return the size of the filtered map as the number of duplicate strings

Yes, I have been involved in binary upgrade testing of Murex.

• I have experience in testing Murex upgrades from version 2.11 to 3.1

• I have worked on testing the compatibility of Murex with different operating systems and databases

• I have also tested the integration of Murex with other systems such as Bloomberg and Reuters

• I have experience in creating test cases, executing tests, and reporting defects

• I am familiar with Murex testing tools such as MXTest and MXVerify

Workflows in Murex are a series of steps that automate business processes.

• Workflows can be used to automate trade processing, risk management, and settlement processes.

• They can be customized to fit the specific needs of a business.

• Workflows can be triggered by events such as trade creation or modification.

• They can also be used to send notifications and alerts to users.

• Murex provides a graphical interface for designing and managing workflows.

Explanation of protocols, call by value/reference, structures, unions, and arrays.

• Protocols are a set of rules for communication between devices or software components.

• Call by value passes a copy of the value to a function, while call by reference passes a reference to the value.

• Structures are user-defined data types that group related data together.

• Unions are similar to structures, but they share the same memory location for all their members.

• Arrays are a collection of eleme...read more

Custom annotations can be created using @interface in Java.

• Create a new interface with @interface keyword

• Add required elements and default values

• Use the annotation by adding @ followed by the annotation name

• Example: @CustomAnnotation(value = "example")

• Annotations can be used for compile-time checks or runtime behavior

Static storage class is used to declare variables that have a lifetime throughout the program execution.

• Variables declared with static storage class are initialized only once and retain their value between function calls.

• They have a default value of 0 if not initialized explicitly.

• Static functions and variables are only visible within the file they are declared in.

• Static variables can be used to count the number of times a function is called or to cache values for future use.

An ongoing sprint can be stopped if the team realizes that the sprint goal is no longer achievable or if there are external factors impacting the project.

• An ongoing sprint can be stopped if the team realizes that the sprint goal is no longer achievable due to unforeseen challenges or changes in requirements.

• External factors such as budget constraints, resource limitations, or changes in business priorities may also lead to the stoppage of an ongoing sprint.

• It is important for...read more

Capital markets refer to financial markets where long-term securities such as stocks, bonds, and derivatives are traded.

• Capital markets are where companies and governments raise funds by issuing securities.

• These markets are also used for trading existing securities between investors.

• Examples of capital markets include stock exchanges, bond markets, and commodity markets.

• Capital markets play a crucial role in the global economy by facilitating the flow of capital between inves...read more

Yes, it is possible to connect to a database using JavaScript.

• JavaScript can connect to databases using APIs such as Web SQL, IndexedDB, and MongoDB.

• It is also possible to use Node.js to connect to databases using JavaScript.

• However, it is not recommended to connect to a database directly from client-side JavaScript due to security concerns.

HTTP is stateless because it does not retain information about previous requests.

• HTTP treats each request as an independent transaction without any knowledge of previous requests.

• This design simplifies implementation and improves scalability.

• State information can be managed using cookies or session tokens.

• Example: When a user logs into a website, the server may create a session token to track the user's activity.

Memory leaks can be resolved by identifying the source of the leak and freeing up the allocated memory.

• Use memory profiling tools to identify the source of the leak

• Analyze the code to find any unnecessary memory allocations

• Ensure all allocated memory is freed up after use

• Use smart pointers or garbage collection to automate memory management

• Test thoroughly to ensure the issue is resolved

Java 8 uses automatic memory management through garbage collection.

• Java 8 uses a garbage collector to automatically manage memory.

• The garbage collector frees up memory by removing objects that are no longer in use.

• Java 8 introduced the G1 garbage collector which is designed to reduce pause times.

• Developers can also use tools like jmap and jstat to monitor memory usage.

A transaction in a database is a sequence of operations that are treated as a single unit of work.

• Transactions ensure data consistency and integrity.

• They allow multiple operations to be grouped together and either all succeed or all fail.

• ACID properties (Atomicity, Consistency, Isolation, Durability) are maintained in transactions.

• Examples of transactions include transferring money between bank accounts or updating inventory levels in an e-commerce website.

Garbage collection is an automatic memory management process that frees up memory occupied by objects that are no longer in use.

• Garbage collection is performed by the JVM.

• It helps prevent memory leaks and improves application performance.

• There are different types of garbage collectors such as serial, parallel, CMS, and G1.

• Garbage collection can cause pauses in the application, which can be minimized by tuning the JVM parameters.

• It is important to write efficient and optimized...read more

Hash collusion is when two different inputs produce the same hash value.

• It is a security vulnerability in hash functions.

• Attackers can exploit this vulnerability to create a collision attack.

• For example, an attacker can create a malicious file with the same hash value as a legitimate file to bypass security checks.

To merge 2 dataframes of different schema, use join operations or data transformation techniques.

• Use join operations like inner join, outer join, left join, or right join based on the requirement.

• Perform data transformation to align the schemas before merging.

• Use tools like Apache Spark, Pandas, or SQL to merge dataframes with different schemas.

Saga design pattern is used to manage long-lived transactions between microservices.

• It ensures that all services involved in a transaction are either committed or rolled back together.

• It uses a sequence of local transactions to achieve global consistency.

• It can be implemented using either choreography or orchestration.

• Example: A customer places an order, which involves multiple microservices such as inventory, payment, and shipping. Saga pattern ensures that if any of these s...read more

Memory issues can be resolved by identifying and fixing memory leaks, optimizing memory usage, and using appropriate data structures.

• Identify and fix memory leaks using tools like Valgrind or AddressSanitizer

• Optimize memory usage by reducing unnecessary allocations and deallocations

• Use appropriate data structures like arrays, linked lists, and hash tables

• Avoid using global variables and excessive recursion

• Consider using garbage collection or smart pointers in certain cases

Backend office in Murex is a module that handles post-trade processing and risk management.

• Backend office is responsible for trade confirmation, settlement, and accounting

• It also handles risk management tasks such as limit monitoring and collateral management

• The module integrates with other Murex modules such as Front Office and Risk Management

• Backend office can be customized to meet specific business requirements

Sessions in Hibernate are used to manage the interaction between the application and the database.

• A session is a single-threaded object that represents a connection between the application and the database.

• It is responsible for managing the persistence of objects, executing queries, and providing transactional support.

• A session can be obtained from a session factory and should be closed when no longer needed.

• Example: Session session = sessionFactory.openSession();

• Example: ses...read more

Microservices design pattern is an architectural approach to building software applications as a collection of small, independent services.

• Microservices are independently deployable and scalable

• Each microservice focuses on a specific business capability

• Communication between microservices is done through APIs

• Microservices can be developed using different programming languages and technologies

• Examples of companies using microservices include Netflix, Amazon, and Uber

Car propertymanager is a component in AOSP that manages properties related to car-specific features.

• Car propertymanager is used to handle properties like car make, model, year, etc.

• It is mostly used in Android Automotive OS for managing car-specific settings and configurations.

• Developers can use car propertymanager to access and modify car-related properties in their apps.

Streams in Java 11 provide a concise and efficient way to handle collections.

• Streams allow for functional-style operations on collections.

• They can be used to filter, map, and reduce data.

• Parallel streams can improve performance on large collections.

• Example: List names = Arrays.asList("John", "Jane", "Bob"); long count = names.stream().filter(name -> name.startsWith("J")).count();

• Example: List numbers = Arrays.asList(1, 2, 3, 4, 5); int sum = numbers.stream().reduce(0, Integer...read more

Pyspark streaming is a scalable and fault-tolerant stream processing engine built on top of Apache Spark.

• Pyspark streaming allows for real-time processing of streaming data.

• It provides high-level APIs in Python for creating streaming applications.

• Pyspark streaming supports various data sources like Kafka, Flume, Kinesis, etc.

• It enables windowed computations and stateful processing for handling streaming data.

• Example: Creating a streaming application to process incoming data f...read more

Spark architecture includes driver, cluster manager, and worker nodes for distributed processing.

• Spark architecture consists of a driver program that manages the execution of tasks on worker nodes.

• Cluster manager is responsible for allocating resources and scheduling tasks across worker nodes.

• Worker nodes execute the tasks and store data in memory or disk for processing.

• Example: In a Spark application, the driver program sends tasks to worker nodes for parallel processing of ...read more

ConcurrentSkipListMap is a concurrent, sorted map implementation in Java.

• ConcurrentSkipListMap is a concurrent version of SkipListMap, which is a sorted map implementation based on skip list data structure.

• It allows multiple threads to access and modify the map concurrently.

• It provides logarithmic time complexity for most operations, making it efficient for concurrent access.

• Example: ConcurrentSkipListMap map = new ConcurrentSkipListMap<>();

Catalyst optimizer is a query optimizer in Apache Spark that leverages advanced techniques to optimize and improve the performance of Spark SQL queries.

• Catalyst optimizer uses a rule-based and cost-based optimization approach to generate an optimized query plan.

• It performs various optimizations such as constant folding, predicate pushdown, and projection pruning to improve query performance.

• Catalyst optimizer also leverages advanced techniques like query plan caching and code...read more

Pyspark is a Python API for Apache Spark, a powerful open-source distributed computing system.

• Pyspark is used for processing large datasets in parallel across a cluster of computers.

• It provides high-level APIs in Python for Spark programming.

• Pyspark allows seamless integration with other Python libraries like Pandas and NumPy.

• Example: Using Pyspark to perform data analysis and machine learning tasks on big data sets.

Pyspark SQL is a module in Apache Spark that provides a SQL interface for working with structured data.

• Pyspark SQL allows users to run SQL queries on Spark dataframes.

• It provides a more concise and user-friendly way to interact with data compared to traditional Spark RDDs.

• Users can leverage the power of SQL for data manipulation and analysis within the Spark ecosystem.

Annotations in Java provide metadata about a program that can be used by the compiler or at runtime.

• Annotations start with the @ symbol.

• Annotations can be used to provide information to the compiler or to runtime environments.

• Annotations can be used to define custom metadata for classes, methods, fields, etc.

• Annotations can also be used for code generation, documentation, and validation.

• Examples of annotations in Java include @Override, @Deprecated, and @SuppressWarnings.

A binary upgrade is a software upgrade that involves replacing the existing version with a new version without changing the data format or structure.

• Binary upgrades are typically faster and easier to implement compared to non-binary upgrades.

• They are commonly used in software applications to ensure compatibility with existing data and configurations.

• An example of a binary upgrade is updating a software application from version 1.0 to version 2.0 without requiring any changes ...read more

Review and explain/correct provided code

• Understand the purpose of the code

• Check for any syntax errors or logical mistakes

• Explain the code step by step

• Suggest improvements if necessary

Mistakes in embedded software code

• Check for buffer overflows and memory leaks

• Ensure proper error handling and exception handling

• Verify correct usage of pointers and memory allocation

• Check for race conditions and synchronization issues

• Ensure compliance with coding standards and best practices

I have experience with Spring, Hibernate, and Apache Struts frameworks in Java development.

• Used Spring framework for dependency injection and MVC architecture

• Utilized Hibernate for ORM mapping and database interaction

• Worked with Apache Struts for building web applications

Handling ADF pipelines involves designing, building, and monitoring data pipelines in Azure Data Factory.

• Designing data pipelines using ADF UI or code

• Building pipelines with activities like copy data, data flow, and custom activities

• Monitoring pipeline runs and debugging issues

• Optimizing pipeline performance and scheduling triggers

Static and global are storage classes in C programming language.

• Static variables have a local scope but retain their value between function calls.

• Global variables have a file scope and can be accessed from any function within the file.

• Static functions have a file scope and can only be called within the file.

Explode function is used in Apache Spark to split an array into multiple rows.

• Used in Apache Spark to split an array into multiple rows

• Creates a new row for each element in the array

• Commonly used in data processing and transformation tasks

Data can be sent from JCL to COBOL using parameters, files, or shared memory.

• Passing parameters through JCL PROC statement

• Writing data to a file in JCL and reading it in COBOL program

• Using shared memory to communicate between JCL and COBOL

RDD stands for Resilient Distributed Dataset, a fundamental data structure in Apache Spark.

• RDD is a fault-tolerant collection of elements that can be operated on in parallel.

• RDDs are immutable, meaning they cannot be changed once created.

• RDDs support two types of operations: transformations (creating a new RDD from an existing one) and actions (returning a value to the driver program).

Types of clusters in Databricks include Standard, High Concurrency, and Single Node clusters.

• Standard clusters are used for general-purpose workloads

• High Concurrency clusters are optimized for concurrent workloads

• Single Node clusters are used for development and testing purposes

Tosca is a software testing tool that automates end-to-end testing of applications.

• Tosca uses model-based test automation to create and execute test cases.

• It supports a wide range of technologies and platforms.

• Buffer and xBuffer are Tosca's built-in data storage and manipulation functions.

• Buffer is used to store and retrieve data, while xBuffer is used to manipulate data.

• Tosca is commonly used in industries such as finance, healthcare, and manufacturing.

Cursors are database objects used to retrieve data from result sets one row at a time.

• Cursors are used in database management systems to navigate through a result set.

• They allow for processing individual rows of a result set instead of fetching the entire set at once.

• Cursors can be used in SQL queries to perform operations on each row of a result set.

Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications.

• Kubernetes follows a master-slave architecture with a master node that controls multiple worker nodes.

• Master node components include API server, scheduler, controller manager, and etcd.

• Worker node components include kubelet, kube-proxy, and container runtime (e.g. Docker).

• Kubernetes uses Pods as the smallest deployable units, which...read more

Blending combines data from different data sources in a single view, while joins combine data from the same data source based on a common field.

• Blending is used when data comes from different sources and cannot be joined together directly.

• Joins are used when data comes from the same source and can be combined based on a common field.

• Blending allows for combining data at different levels of granularity.

• Joins require a common field to match records from different tables.

• Example...read more

Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads.

• Delta Lake provides ACID transactions, schema enforcement, and time travel capabilities on top of data lakes.

• Data lakes are a storage repository that holds a vast amount of raw data in its native format until it is needed.

• Delta Lake is optimized for big data workloads and provides reliability and performance improvements over traditional data lakes.

• Data lakes can st...read more

Code of conduct is a set of rules and guidelines that outline the ethical and professional behavior expected from individuals in a particular organization or profession.

• Code of conduct sets standards for behavior and interactions within an organization.

• It outlines expectations for ethical decision-making and professionalism.

• Violation of the code of conduct can result in disciplinary action.

• Examples include rules on confidentiality, honesty, respect, and integrity.

To create a Spark DataFrame, use the createDataFrame() method.

• Import the necessary libraries

• Create a list of tuples or a dictionary containing the data

• Create a schema for the DataFrame

• Use the createDataFrame() method to create the DataFrame