phData Hadoop Administrator Interview Questions and Answers

Basic Logical Reasoning, Maths questions

Q1. Basic sql, python, past projects, guesstimates
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Q1. Why Axtria? What you know about Axtria?
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Q1. Code any program in 2 languages
Ans. 
I can code a program in Python and Java.
• I am proficient in both Python and Java programming languages.

• I have experience in developing web applications using Python and Java frameworks.

• I can write efficient and optimized code in both languages.

• I can develop programs for data analysis, machine learning, and automation using Python.

• I can develop enterprise-level applications using Java.

• Examples: Python - a program to scra...read more
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Q2. Behavioral questions on why you want to join?
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General aptitude test on an online platform with camera and mic monitoring.

Q1. One on one round with manager and senior manager. Basic questions about day to day responsibilities and tech stack.
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Aptitude test was on hirepro having logical,quat,verbal, technical questions

Q1. About project and basics of sql
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Logical, statistics, Aptitude, Data science and analytics

Q1. Difference between Delete and Truncate in SQL
Ans. 
Delete removes specific rows from a table, while Truncate removes all rows from a table.
• Delete is a DML command, while Truncate is a DDL command.

• Delete can be rolled back, while Truncate cannot be rolled back.

• Delete maintains the table structure and indexes, while Truncate resets the table structure and indexes.

• Delete triggers delete triggers and delete constraints, while Truncate does not trigger any triggers or const...read more
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Q2. Assumptions of regression
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Assumptions of regression
• Linearity: The relationship between the independent and dependent variables is linear.

• Independence: The residuals are independent of each other.

• Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.

• Normality: The residuals are normally distributed.

• No multicollinearity: The independent variables are not highly correlated with each other.
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Q1. Ridge and lasso regression difference
Ans. 
Ridge and lasso regression are both regularization techniques used in linear regression to prevent overfitting by adding penalty terms to the cost function.
• Ridge regression adds a penalty term equivalent to the square of the magnitude of coefficients, while lasso regression adds a penalty term equivalent to the absolute value of the magnitude of coefficients.

• Ridge regression tends to shrink the coefficients towards zer...read more
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Q2. Random forest vs decision tree vs xg boost
Ans. 
Random forest is an ensemble method using multiple decision trees, XGBoost is a gradient boosting algorithm that builds trees sequentially.
• Random forest is an ensemble learning method that builds multiple decision trees and combines their predictions.

• Decision tree is a single tree model that makes decisions based on features to predict outcomes.

• XGBoost is a gradient boosting algorithm that builds trees sequentially, op...read more
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Q1. Why do you not want to opt for higher studies
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Q2. What to do when a team member is not collaborating
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