Tag: big_data_interview
Optimizing data queries with AWS Glue and Amazon Athena
AWS Glue, a serverless data integration service, and Amazon Athena, an interactive query service, together offer a seamless solution for…
Mastering data partitioning in AWS Glue
This article explores how AWS Glue handles data partitioning during processing, supplemented by a real-world example. Understanding data partitioning in…
Ensuring data integrity with AWS Glue: A practical guide to data validation
In the world of big data, ensuring the accuracy and integrity of data during ingestion is paramount. AWS Glue, a…
Replacing NaN (Not a Number) values with a specified value in a column : nanvl
The nanvl function in PySpark is used to replace NaN (Not a Number) values with a specified value in a…
Computing the average value of a numeric column in PySpark
The mean function in PySpark is used to compute the average value of a numeric column. This function is part…
Concatenating two or more maps into a single map : map_concat
The map_concat function in PySpark is designed to concatenate two or more maps into a single map. It merges key-value…
Removing leading spaces (spaces on the left side) from a string in PySpark
PySpark, a leading tool in big data processing, provides several functions for string manipulation, one of which is ltrim. This…
Adding a new column to a DataFrame with a constant value
The lit function in PySpark is a straightforward yet powerful tool for adding constant values as new columns in a…
Finding the position of a substring within a string using PySpark
pyspark.sql.functions.locate PySpark, a tool for handling large-scale data processing, offers a plethora of functions for string manipulation, one of which…
Adding a specified character to the left of a string until it reaches a certain length in PySpark
LPAD, or Left Padding, is a string function in PySpark that adds a specified character to the left of a…
