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10+ Interview Questions and Answers

Updated 27 Sep 2024
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Q1. What is the best approach to finding whether the data frame is empty or not?

Ans.

Use the len() function to check the length of the data frame.

  • Use len() function to get the number of rows in the data frame.

  • If the length is 0, then the data frame is empty.

  • Example: if len(df) == 0: print('Data frame is empty')

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Q2. What is the difference between repartition and Coelsce?

Ans.

Repartition increases or decreases the number of partitions in a DataFrame, while Coalesce only decreases the number of partitions.

  • Repartition can increase or decrease the number of partitions in a DataFrame, leading to a shuffle of data across the cluster.

  • Coalesce only decreases the number of partitions in a DataFrame without performing a full shuffle, making it more efficient than repartition.

  • Repartition is typically used when there is a need to increase the number of parti...read more

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Q3. Two SQL Codes and Two Python codes like reverse a string ?

Ans.

Reverse a string using SQL and Python codes.

  • In SQL, use the REVERSE function to reverse a string.

  • In Python, use slicing with a step of -1 to reverse a string.

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Q4. How do you decide on cores and worker nodes?

Ans.

Cores and worker nodes are decided based on the workload requirements and scalability needs of the data processing system.

  • Consider the size and complexity of the data being processed

  • Evaluate the processing speed and memory requirements of the tasks

  • Take into account the parallelism and concurrency needed for efficient data processing

  • Monitor the system performance and adjust cores and worker nodes as needed

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Q5. Find top 5 countries with highest population in Spark and SQL

Ans.

Use Spark and SQL to find the top 5 countries with the highest population.

  • Use Spark to load the data and perform data processing.

  • Use SQL queries to group by country and sum the population.

  • Order the results in descending order and limit to top 5.

  • Example: SELECT country, SUM(population) AS total_population FROM table_name GROUP BY country ORDER BY total_population DESC LIMIT 5

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Q6. What is shuffling? How to Handle Shuffling?

Ans.

Shuffling is the process of redistributing data across partitions in a distributed computing environment.

  • Shuffling is necessary when data needs to be grouped or aggregated across different partitions.

  • It can be handled efficiently by minimizing the amount of data being shuffled and optimizing the partitioning strategy.

  • Techniques like partitioning, combiners, and reducers can help reduce the amount of shuffling in MapReduce jobs.

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Q7. What is a catalyst optimiser? How it works?

Ans.

A catalyst optimizer is a query optimization tool used in Apache Spark to improve performance by generating an optimal query plan.

  • Catalyst optimizer is a rule-based query optimization framework in Apache Spark.

  • It leverages rules to transform the logical query plan into a more optimized physical plan.

  • The optimizer applies various optimization techniques like predicate pushdown, constant folding, and join reordering.

  • By optimizing the query plan, it reduces the overall execution...read more

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Q8. How do you handle Incremental data?

Ans.

Incremental data is handled by identifying new data since the last update and merging it with existing data.

  • Identify new data since last update

  • Merge new data with existing data

  • Update data warehouse or database with incremental changes

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Q9. Using two tables find the different records for different joins

Ans.

To find different records for different joins using two tables

  • Use the SQL query to perform different joins like INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

  • Identify the key columns in both tables to join on

  • Select the columns from both tables and use WHERE clause to filter out the different records

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Q10. What happens when we enforce schema ?

Ans.

Enforcing schema ensures that data conforms to a predefined structure and rules.

  • Ensures data integrity by validating incoming data against predefined schema

  • Helps in maintaining consistency and accuracy of data

  • Prevents data corruption and errors in data processing

  • Can lead to rejection of data that does not adhere to the schema

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Q11. How DAG handle Fault tolerance?

Ans.

DAGs handle fault tolerance by rerunning failed tasks and maintaining task dependencies.

  • DAGs rerun failed tasks automatically to ensure completion.

  • DAGs maintain task dependencies to ensure proper sequencing.

  • DAGs can be configured to retry failed tasks a certain number of times before marking them as failed.

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Q12. When we use ssis packages? Difference between union merge

Ans.

SSIS packages are used for ETL processes in SQL Server. Union combines datasets vertically, while merge combines them horizontally.

  • SSIS packages are used for Extract, Transform, Load (ETL) processes in SQL Server.

  • Union in SSIS combines datasets vertically, stacking rows on top of each other.

  • Merge in SSIS combines datasets horizontally, matching rows based on specified columns.

  • Union All in SSIS combines datasets vertically without removing duplicates.

  • Merge Join in SSIS combine...read more

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Q13. What is SCD ??

Ans.

SCD stands for Slowly Changing Dimension, a concept in data warehousing to track changes in data over time.

  • SCD is used to maintain historical data in a data warehouse.

  • There are three types of SCD - Type 1, Type 2, and Type 3.

  • Type 1 SCD overwrites old data with new data.

  • Type 2 SCD creates a new record for each change, preserving history.

  • Type 3 SCD maintains both old and new values in the same record.

  • SCD is important for tracking changes in dimensions like customer information ...read more

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Q14. What is ssis? How we use

Ans.

SSIS stands for SQL Server Integration Services, a tool provided by Microsoft for data integration and workflow applications.

  • SSIS is a platform for building high-performance data integration and workflow solutions.

  • It allows you to create packages that move data from various sources to destinations.

  • SSIS includes a visual design interface for creating, monitoring, and managing data integration processes.

  • You can use SSIS to automate tasks such as data extraction, transformation,...read more

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