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800+ Java Interview Questions & Answers for 2 to 5 and 5 to 10+ years of experience & architects

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500+ Big Data Interview Questions & Answers for 2 to 5 and 5 to 10+ years of experience & architects

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11 Tips to have a rewarding career in Software & Data Engineering

A rewarding career should not only have a monetary reward, but also much needed non-monetary rewards like work life balance, sense of accomplishments, pride of building significant systems, progression, learning opportunities, building networks, making a difference, mentoring, etc.

The key take aways of this post are ….

1) Taking the road less travelled.
2) Prompting for a reality check.

#01 Balanced routine & consistency

Many so called influencers advice to work very hard and learn new technologies to earn 2x or 3x your salary.… Read more ...



29: NumPy Vs Pandas interview questions & answers – part 3

Q01. What is an index in Pandas? A01. An index is a series of labels that can uniquely identify each row of a DataFrame. The index can be of any datatype like integer, string, hash, etc. pandas_test.py

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28: NumPy Vs Pandas interview questions & answers – part 2

Q01. What is the difference between a Python List & NumPy? A01. Even though both superficially look the same with contents and indexes starting from 0 as shown below:

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22: PySpark Row object Interview Q&As with tutorials

This extends PySpark map vs flatMap Interview Q&As with tutorials. Q01. What is a Row object in PySpark? A01. Row can be used to create a row object by using named arguments. The previous example can be represented with a Row object. Given the below input, how will you concat…

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21: PySpark map vs flatMap Interview Q&As with tutorials

Q01. What is the difference between map and flatMap operations in Spark? A01. The map and flatMap are transformation operations in Spark. map transformation is applied to each element of RDD or a DataFrame and it returns the result as a new RDD or a DataFrame. Map takes N elements…

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20: PySpark Dataframe Vs Pandas Dataframe Interview Q&As with tutorials

This extends NumPy Vs Pandas interview questions & answers – part 1 Q: What is the difference between PySpark Dataframe & a Pandas Dataframe? A: PySpark is a library where the operations are quicker than Pandas Dataframe library because of its parallel execution over multiple CPU cores & distributed in…

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27: NumPy Vs Pandas interview questions & answers – part 1

Q01. What is the difference between NumPy & Pandas? A01. Firstly, pandas, which is a Python library for data wrangling is built on top of the NumPy python library. NumPy is short for Numerical Python, and used for scientific computing. This library is made up of multidimensional array objects and…

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19: PySpark on handling duplicates Interview Q&As with tutorials

Given the below data, where the record with the emp_name “Elliot” is repeated.

distinct(..)… Read more ...



18: PySpark problem solving Interview Q&As with tutorials – problem 2

Problem: Convert the below table

to

Step 1: Let’s create the sample data using PySpark.… Read more ...



17: PySpark problem solving Interview Q&As with tutorials – problem 1

This is based on the series of tutorials & interview Q&As at PySpark interview Q&As with tutorials

Problem: Convert the below table

to

Where each column is counted for its occurrence.… Read more ...



16: PySpark to read JSON files Interview Q&As with tutorials

Q51: How will you read the below JSON file employee.json into a Pyspark Dataframe?

A51: Here is the PySpark code with schema to read the above JSON file.… Read more ...



15: PySpark with Apache Kafka Interview Q&As with tutorials – part 3

This extends PySpark with Apache Kafka Interview Q&As with tutorials – part 1 and PySpark with Apache Kafka Interview Q&As with tutorials – part 2 Q46: How will you go about writing the streamed structured to a parquet file? A46: In the last tutorial we wrote a console sink, and…

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14: PySpark with Apache Kafka Interview Q&As with tutorials – part 2

This extends 13: PySpark with Apache Kafka Interview Q&As with tutorials – part 1 Q42: How would you go about displaying the array of JSON data in a tabular format? A42 In this post we will expand & explode the json data read via an Apache Kafka topic in the…

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13: PySpark with Apache Kafka Interview Q&As with tutorials – part 1

Q40: What is Spark streaming? What are the benefits of using Apache Kafka with PySpark? A40: Spark streaming is used for real time data processing, which allows you to process from various data sources like Apache Kafka, Amazon Kinesis Data Streams, etc. The source upstream applications like ERP systems, billing…

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12: PySpark working with SQL syntax Interview Q&As with tutorials

Q37: Can you use SQL in PySpark? A37: Yes, Spark supports both Dataframe APIs and also allows you to integrate SQL queries to work with structured data. The pyspark.sql is a module in PySpark that can be used to perform SQL like operations on the data stored in memory via…

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01: 13 Java low latency interview questions & answers

Have you seen job advertisements requiring Java candidates to work in low latency, high throughput, real-time and distributed systems with share-nothing architectures? Wondering what questions you will be asked? If you are an experienced Java developer targeting high paying skills then it pays to get a good handle on Java low latency interview questions & answers.

You will be quizzed on the low latency application you had recently worked on especially the outcomes in terms of the latencies, response times, and throughput along with the challenges you faced.… Read more ...



30+ Java Code Review Checklist Items

This Java code review checklist is not only useful during code reviews, but also to answer an important Java job interview question,

Q. How would you go about evaluating code quality of others’ work?

This can judge a candidate’s real experience & technical hows.

You also learn a lot from peer code reviews. What has been written well? Why was it done this way?… Read more ...



01: 30+ Java architect interview questions & answers – Part 1

One of the very frequently asked open-ended interview questions for anyone experienced is: Can you describe the high-level architecture of a recent application you had worked on? You can be asked:

1) to draw an architectural diagram on a white board and
2) to provide a brief description of the architecture, and
3) to elaborate on decisions, technologies & frameworks used, alternatives considered, pros, cons, challenges, risks, etc ….… Read more ...



18 Java scenarios based interview Q&As for the experienced – Part 1

Let’s look at scenarios or problem statements & how would you go about handling those scenarios in Java. These scenarios interview questions will judge your Java experience. Full list of Java scenarios based interview questions are covered at Judging your Java experience via scenarios based interview Q&As.

#1. Caching

Q01.Scenario: You need to load stock exchange security codes with price from a database and cache them for performance.… Read more ...



00: Top 50+ Core Java interview questions & answers for 1 to 3 years experience

Top 50 core Java interview questions covering core Java concepts with diagrams, code, examples, and scenarios. If you don’t get these Java interview questions right, you will not be getting an offer.

== Vs equals(…)

Q1. What is the difference between “==” and “equals(…)” in comparing Java String objects?
A1. When you use “==” (i.e. shallow comparison), you are actually comparing the two object references to see if they point to the same object.… Read more ...



27: 50+ SQL scenarios based interview Q&As – identifying consecutive records

The data analysts & engineers will often be faced with the below SQL scenario at work. It is also often asked in job interviews. This solution uses SQL analytical functions & you can learn more about them at SQL analytic functions interview questions – Part 1

Setup the data on db-fiddle MySQL V8.0 to practice.

Q. Given the below input:

How will you write SQL query to output the count of consecutive statuses of jobs?… Read more ...



01: Q01 – Q07 Spring framework core interview Q&As

Spring framework interview questions are very common for the Java programmer jobs. This covers Spring framework beginner interview questions on the Spring core and more advanced Spring framework interview questions at Java microservices interview questions.

Q1. What do you understand by the terms Dependency Inversion Principle (DIP), Dependency Injection (DI) and Inversion of Control (IoC) container?… Read more ...



15 Ice breaker interview Q&As asked 90% of the time

Most interviews start with these 15 open-ended questions. These are ice breaker interview questions with no right or wrong answers to ease nervousness, but the quality of the answers can make a good first impression. Your answer can reveal a lot about your experience & industry knowledge. Even though the answers provided here are Java focussed, the questions are generic.… Read more ...



16+ Tech Key Areas to go places as a Java, Big Data or any software engineer or architect

If you want to be a top-notch developer who goes places, then you must have a good handle on these 16+ technical key areas. Seasoned Java developers must have a solid understanding of these “transferrable skills“. These are transferrable skills that can be applied to any technology & programming by asking the right questions.

Inexperienced or rushed developers can create systems that work great in development, but have many problems in the test or production environments due to sheer load, concurrent access, locale or timezone settings, portability issues, hard coded values, not having proper service timeouts & retries, and the list goes on…NON Functional requirements are a must to build robust systems.
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15+ slacknesses or lack of experience that can come back & bite you as an architect, experienced programmer or data engineer

Production issues seek the attention of middle and top level management. Often these are intermittent issues that are harder to reproduce in lower environments without the right know-hows & tools. Some will shrug it off as “Cannot be reproduced“, whilst others will seize the opportunity to showcase their technical strengths & know hows to go places. Here are a few things that you must pay attention as a software developer, designer or architect to prevent any future embarrassments.… Read more ...



11: PySpark working with AVRO file format Interview Q&As with tutorials

This extends 10: PySpark working with parquet file format Interview Q&As with tutorials. Given the below employee.csv file in /tmp folder:

AVRO is a popular data serialization format used in big data processing systems such as Hadoop, Spark, and Kafka.… Read more ...



10: PySpark working with parquet file format Interview Q&As with tutorials

Given the below employee.csv file in /tmp folder:

Q26: How will you read the above file & calculate 10% bonus and write it as parquet file employee.parquet?… Read more ...



09: PySpark GroupBy & explode functions Interview Q&As with tutorials

Given the below file employee_by_prog_lanuguage.csv in a folder named /tmp.

Q24: Given the above file, how will display all prog_lang as a list against each emp_name?… Read more ...



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Java Developer & Architect Q&As

Big Data Engineer & Architect Q&As

16+ Key Areas & 13+ Techs to fast-track