Binance Data Engineer Interview Questions and Answers

Q1. What are joins of sql
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Q2. Explain about self join
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Q1. General Data Warehousing questions like explain your pipeline, how you implemented scd2?
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Q2. SQL questions like increment top 5th salary by 10k, last day of month, etc.
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Q1. Project question like how connected to s3 bucket through pyspark,HDFS basic commands likhe copy etc ,how and where created hive table (if used in your project).
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Q2. Share variables in pyspark like broadcast and accumulator..(i will suggest go through pyspark official documentation once)
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Q3. Sql joins- , how to read file in pyspark, job scheduling means resource allocation within and across spark..(ans- can go through job scheduling of pyspark documentaion )
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Basic aptitude test asking questions very basic

Coding questions based on dsa

Q1. Basic hr question
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Q1. Mostly on cloud tools
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Q1. What is the difference between supervised and unsupervised learning?
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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...read more
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Q2. Elaborate concepts of Object Oriented Programming in Python.
Ans. 
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...read more
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Q3. How to find delta between two tables in SQL?
Ans. 
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.
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Q4. Illustrate exception handling in python.
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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
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Q5. Give an example of decorators in Python?
Ans. 
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.
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Q1. What are examples of iaas,paas,saas
Ans. 
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
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Q2. Difference between Adf and ADB
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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...read more
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Q1. Architecture of Spark
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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.

• ...read more
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Q2. What is Lazy evaluation in spark
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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...read more
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Q3. Difference between Left join and inner join
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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...read more
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