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I applied via Internshala and was interviewed in Feb 2023. There were 3 interview rounds.
You are given an integer list coins representing coins of different denominations and an integer amount representing a total amount of money.
Return the fewest number of coins that you need to make up that amount. If that amount of money cannot be made up by any combination of the coins, return {}.
You may assume that you have an infinite number of each kind of coin.
Example 1: Input: coins = [1, 5, 6, 9, 15], amount = 31
Output: {15:2, 1:1}
Example 2: Input: coins = [1, 5, 6, 9, 15], amount = 100
Output: {15:6, 9:1, 1:1}
I am a data engineer with experience in designing and implementing data pipelines for large-scale projects.
Experienced in building and optimizing data pipelines using tools like Apache Spark and Hadoop
Proficient in programming languages like Python and SQL
Skilled in data modeling and database design
Familiar with cloud platforms like AWS and GCP
Strong problem-solving and analytical skills
Effective communicator and team
I applied via Recruitment Consulltant and was interviewed in Nov 2024. There were 2 interview rounds.
Different types of joins available in Databricks include inner join, outer join, left join, right join, and cross join.
Inner join: Returns only the rows that have matching values in both tables.
Outer join: Returns all rows when there is a match in either table.
Left join: Returns all rows from the left table and the matched rows from the right table.
Right join: Returns all rows from the right table and the matched rows ...
Implementing fault tolerance in a data pipeline involves redundancy, monitoring, and error handling.
Use redundant components to ensure continuous data flow
Implement monitoring tools to detect failures and bottlenecks
Set up automated alerts for immediate response to issues
Design error handling mechanisms to gracefully handle failures
Use checkpoints and retries to ensure data integrity
AutoLoader is a feature in data engineering that automatically loads data from various sources into a data warehouse or database.
Automates the process of loading data from different sources
Reduces manual effort and human error
Can be scheduled to run at specific intervals
Examples: Apache Nifi, AWS Glue
To connect to different services in Azure, you can use Azure SDKs, REST APIs, Azure Portal, Azure CLI, and Azure PowerShell.
Use Azure SDKs for programming languages like Python, Java, C#, etc.
Utilize REST APIs to interact with Azure services programmatically.
Access and manage services through the Azure Portal.
Leverage Azure CLI for command-line interface interactions.
Automate tasks using Azure PowerShell scripts.
Linked Services are connections to external data sources or destinations in Azure Data Factory.
Linked Services define the connection information needed to connect to external data sources or destinations.
They can be used in Data Factory pipelines to read from or write to external systems.
Examples of Linked Services include Azure Blob Storage, Azure SQL Database, and Amazon S3.
I applied via Recruitment Consulltant and was interviewed in Oct 2024. There was 1 interview round.
I applied via Recruitment Consulltant and was interviewed in May 2024. There was 1 interview round.
I applied via Company Website and was interviewed in Oct 2023. There was 1 interview round.
Supervised learning uses labeled data to train the model, while unsupervised learning uses unlabeled data.
Supervised learning requires a target variable to be predicted, while unsupervised learning does not.
In supervised learning, the model learns from labeled training data, whereas in unsupervised learning, the model finds patterns in unlabeled data.
Examples of supervised learning include regression and classification...
Object Oriented Programming in Python focuses on creating classes and objects to organize code and data.
Python supports classes, objects, inheritance, polymorphism, and encapsulation.
Classes are blueprints for creating objects, which are instances of classes.
Inheritance allows a class to inherit attributes and methods from another class.
Polymorphism enables objects to be treated as instances of their parent class.
Encap...
To find delta between two tables in SQL, use the EXCEPT or MINUS operator.
Use the EXCEPT operator in SQL to return rows from the first table that do not exist in the second table.
Use the MINUS operator in SQL to return distinct rows from the first table that do not exist in the second table.
Exception handling in Python allows for graceful handling of errors and preventing program crashes.
Use try-except blocks to catch and handle exceptions.
Multiple except blocks can be used to handle different types of exceptions.
Finally block can be used to execute code regardless of whether an exception was raised or not.
Custom exceptions can be defined by creating a new class that inherits from the built-in Exception c
Decorators in Python are functions that modify the behavior of other functions.
Decorators are defined using the @decorator_name syntax before the function definition.
They can be used for logging, timing, authentication, etc.
Example: @staticmethod decorator in Python makes a method static.
I applied via Naukri.com and was interviewed in Jan 2024. There was 1 interview round.
Examples of IaaS, PaaS, and SaaS include AWS (IaaS), Google App Engine (PaaS), and Salesforce (SaaS).
IaaS - Infrastructure as a Service: AWS, Microsoft Azure, Google Cloud Platform
PaaS - Platform as a Service: Google App Engine, Heroku, Microsoft Azure App Service
SaaS - Software as a Service: Salesforce, Google Workspace, Microsoft Office 365
ADF stands for Azure Data Factory, a cloud-based data integration service. ADB stands for Azure Databricks, an Apache Spark-based analytics platform.
ADF is used for data integration and orchestration, while ADB is used for big data analytics and machine learning.
ADF provides a visual interface for building data pipelines, while ADB offers collaborative notebooks for data exploration and analysis.
ADF supports various da...
Spark is a distributed computing system that provides an interface for programming clusters with implicit data parallelism.
Spark is built on the concept of Resilient Distributed Datasets (RDDs), which are fault-tolerant collections of objects.
It supports various programming languages such as Scala, Java, Python, and R.
Spark provides high-level APIs for distributed data processing, including transformations and actions.
...
Lazy evaluation is a strategy used by Spark to delay the execution of transformations until an action is called.
Lazy evaluation improves performance by optimizing the execution plan
Transformations in Spark are not executed immediately, but rather recorded as a lineage graph
Actions trigger the execution of the transformations and produce a result
Lazy evaluation allows Spark to optimize the execution plan by combining an...
Left join returns all records from the left table and the matching records from the right table.
Inner join returns only the matching records from both tables.
Left join includes all records from the left table, even if there are no matches in the right table.
Inner join excludes the non-matching records from both tables.
Left join is used to retrieve all records from one table and the matching records from another table.
I...
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