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I applied via Recruitment Consulltant and was interviewed in Nov 2024. There was 1 interview round.
Use distributed computing framework like Apache Spark to efficiently load and transform the large CSV file.
Use Apache Spark to distribute the workload across multiple nodes for faster processing.
Utilize Spark's DataFrame API to read the CSV file and apply transformations.
Consider partitioning the data to optimize performance.
Use Spark SQL for complex transformations and aggregations.
Leverage in-memory processing capabi
I applied via Recruitment Consulltant and was interviewed in Apr 2024. There were 3 interview rounds.
They gave a regular problem like using sqllite in the code and using it to get data from a csv file and parse it. I was allowed to use google. They wanted to see how I approach a problem.
I applied via LinkedIn and was interviewed in Sep 2023. There were 4 interview rounds.
General Aptitude and behaviour test
Data wrangling and processing using python data structures
Presentation test, describe previous work and motivation
Top trending discussions
I applied via Recruitment Consulltant and was interviewed before Nov 2021. There were 2 interview rounds.
Window functions in SQL are used to perform calculations across a set of rows that are related to the current row.
Window functions are used to calculate running totals, moving averages, and rank values.
They are applied to a set of rows defined by an OVER clause.
Examples of window functions include ROW_NUMBER, RANK, DENSE_RANK, and NTILE.
CTE stands for Common Table Expression, a temporary named result set that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement.
CTE is defined using the WITH keyword followed by a name and a SELECT statement.
It can be used to simplify complex queries, improve readability, and reduce code duplication.
CTE can also be recursive, allowing for hierarchical queries.
Example: WITH sales AS (SELECT * FROM order...
I applied via Walk-in and was interviewed in Apr 2021. There was 1 interview round.
I applied via Naukri.com and was interviewed in Nov 2023. There was 1 interview round.
Developed a predictive model to forecast sales based on historical data
Used machine learning algorithms to analyze sales trends
Incorporated external factors like seasonality and promotions into the model
Validated the model using cross-validation techniques
Python, sql was asked
I applied via Approached by Company and was interviewed in Sep 2021. There were 3 interview rounds.
I applied via Referral and was interviewed before Jan 2024. There was 1 interview round.
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