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I applied via Walk-in and was interviewed in Nov 2023. There were 2 interview rounds.
IDFC offers various benefits and opportunities for growth, making it a compelling choice to join.
IDFC provides a competitive salary and benefits package.
There are ample opportunities for career growth and development within the organization.
IDFC has a strong reputation and is a leading financial institution in the industry.
The company values work-life balance and promotes a positive work environment.
IDFC offers challen...
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I applied via Walk-in and was interviewed in Apr 2024. There were 3 interview rounds.
Lazy evaluation in Spark delays the execution of transformations until an action is called.
Lazy evaluation allows Spark to optimize the execution plan by combining multiple transformations into a single stage.
Transformations are not executed immediately, but are stored as a directed acyclic graph (DAG) of operations.
Actions trigger the execution of the DAG and produce results.
Example: map() and filter() are transformat...
MapReduce is a programming model and processing technique for parallel and distributed computing.
MapReduce is used to process large datasets in parallel across a distributed cluster of computers.
It consists of two main functions - Map function for processing key/value pairs and Reduce function for aggregating the results.
Popularly used in big data processing frameworks like Hadoop for tasks like data sorting, searching...
Skewness is a measure of asymmetry in a distribution. Skewed tables are tables with imbalanced data distribution.
Skewness is a statistical measure that describes the asymmetry of the data distribution around the mean.
Positive skewness indicates a longer tail on the right side of the distribution, while negative skewness indicates a longer tail on the left side.
Skewed tables in data engineering refer to tables with imba...
Spark is a distributed computing framework designed for big data processing.
Spark is built around the concept of Resilient Distributed Datasets (RDDs) which allow for fault-tolerant parallel processing of data.
It provides high-level APIs in Java, Scala, Python, and R for ease of use.
Spark can run on top of Hadoop, Mesos, Kubernetes, or in standalone mode.
It includes modules for SQL, streaming, machine learning, and gra...
I applied via Naukri.com and was interviewed in Mar 2024. There were 3 interview rounds.
Error handling in PySpark involves using try-except blocks and logging to handle exceptions and errors.
Use try-except blocks to catch and handle exceptions in PySpark code
Utilize logging to record errors and exceptions for debugging purposes
Consider using the .option('mode', 'PERMISSIVE') method to handle corrupt records in data processing
I applied via LinkedIn and was interviewed in Mar 2024. There were 2 interview rounds.
Coding questions on sql python and spark
Implement a function to pair elements of an array based on a given sum.
Iterate through the array and check if the current element plus any other element equals the given sum.
Use a hash set to store elements already visited to avoid duplicate pairs.
Return an array of arrays containing the pairs that sum up to the given value.
2 questions based on Algorithm and logic
I applied via Recruitment Consulltant and was interviewed before Jul 2023. There were 2 interview rounds.
Technical problem comprised of searching google and then using api call and performing parallel execution
I applied via Naukri.com and was interviewed in Mar 2024. There was 1 interview round.
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