Tag: Spark_Interview
PySpark : Returning the input values, pivoted into an ARRAY
To pivot data in PySpark into an array, you can use a combination of groupBy, pivot, and collect_list functions. The…
PySpark : Extract values from JSON strings within a DataFrame in PySpark [json_tuple]
pyspark.sql.functions.json_tuple PySpark provides a powerful function called json_tuple that allows you to extract values from JSON strings within a DataFrame….
PySpark : Finding the cube root of the given value using PySpark
The pyspark.sql.functions.cbrt(col) function in PySpark computes the cube root of the given value. It takes a column as input and…
PySpark : Identify the grouping level in data after performing a group by operation with cube or rollup in PySpark [grouping_id]
pyspark.sql.functions.grouping_id(*cols) This function is valuable when you need to identify the grouping level in data after performing a group by…
PySpark : Calculating the exponential of a given column in PySpark [exp]
PySpark offers the exp function in its pyspark.sql.functions module, which calculates the exponential of a given column. In this article,…
PySpark : An Introduction to the PySpark encode Function
PySpark provides the encode function in its pyspark.sql.functions module, which is useful for encoding a column of strings into a…
PySpark : Subtracting a specified number of days from a given date in PySpark [date_sub]
In this article, we will delve into the date_sub function in PySpark. This versatile function allows us to subtract a…
PySpark : A Comprehensive Guide to PySpark’s current_date and current_timestamp Functions
PySpark enables data engineers and data scientists to perform distributed data processing tasks efficiently. In this article, we will explore…
PySpark : Understanding the ‘take’ Action in PySpark with Examples. [Retrieves a specified number of elements from the beginning of an RDD or DataFrame]
In this article, we will focus on the ‘take’ action, which is commonly used in PySpark operations. We’ll provide a…
PySpark : Exploring PySpark’s joinByKey on DataFrames: [combining data from two different DataFrames] – A Comprehensive Guide
In PySpark, join operations are a fundamental technique for combining data from two different DataFrames based on a common key….
