Category: Tutorials
-
Regular expressions (regex) are a powerful tool for matching patterns in text. Python’s re module provides functions and tools for working with regular expressions. Here’s…
-
1.Exploratory Data Analysis (EDA) with Pandas in Banking – Converted in Pyspark While searching for A free Pandas Project on Google Found this link –Exploratory…
-
String manipulation is a common task in data processing. PySpark provides a variety of built-in functions for manipulating string columns in DataFrames. Below, we explore…
-
Window functions in PySpark allow you to perform operations on a subset of your data using a “window” that defines a range of rows. These…
-
PySpark provides a powerful API for data manipulation, similar to pandas, but optimized for big data processing. Below is a comprehensive overview of DataFrame operations,…
-
Let us go through the Project requirement:- 1.Let us create One or Multiple dynamic lists of variables and save it in dictionary or Array or…
-
I wrote a Python code or I created a Python script, and it executed successfully So what does it Mean? This will be the most…
-
Spark SQL supports several types of joins, each suited to different use cases. Below is a detailed explanation of each join type, including syntax examples…
-
Temporary functions allow users to define functions that are session-specific and used to encapsulate reusable logic within a database session. While both PL/SQL and Spark…
-
Apache Spark, including PySpark, automatically optimizes job execution by breaking it down into stages and tasks based on data dependencies. This process is facilitated by…
-
explain a typical Pyspark execution Logs A typical PySpark execution log provides detailed information about the various stages and tasks of a Spark job. These…
-
RDD (Resilient Distributed Dataset) is the fundamental data structure in Apache Spark. It is an immutable, distributed collection of objects that can be processed in…
-
Yes, DataFrames in PySpark are lazily evaluated, similar to RDDs. Lazy evaluation is a key feature of Spark’s processing model, which helps optimize the execution…
-
Big Data Lake: Data Storage HDFS is a scalable storage solution designed to handle massive datasets across clusters of machines. Hive tables provide a structured…
-
Big data and big data lakes are complementary concepts. Big data refers to the characteristics of the data itself, while a big data lake provides…
-
Window functions, also known as analytic functions, perform calculations across a set of table rows that are somehow related to the current row. This is…
-
Common Table Expressions (CTEs) are a useful feature in SQL for simplifying complex queries and improving readability. Both Oracle PL/SQL and Apache Hive support CTEs,…
-
Function Name Description Example Usage Result CONCAT Concatenates two strings. SELECT CONCAT(‘Oracle’, ‘PL/SQL’) FROM dual; OraclePL/SQL ` ` (Concatenation) Concatenates two strings. LENGTH Returns the…
-
Date and Time manipulation in Oracle SQL In Oracle SQL, date and time manipulation is essential for many database operations, ranging from basic date arithmetic…
-
The input() function in Python is primarily used to take input from the user through the command line. While its most common use is to…