Welcome to the Future – AI Hints Today
Keyword is AI– This is your go-to space to ask questions, share programming tips, and engage with fellow coding enthusiasts. Whether you’re a beginner or an expert, our community is here to support your journey in coding. Dive into discussions on various programming languages, solve challenges, and exchange knowledge to enhance your skills.
Date and Time Functions- Pyspark Dataframes & Pyspark Sql Queries
PySpark Date Function Cheat Sheet (with Input-Output Types & Examples) This one-pager covers all core PySpark date and timestamp functions, their input/output types, and example usage. Suitable for data engineers and interview prep. 🔄 Date Conversion & Parsing FunctionInputOutputExampleto_date(col, fmt)StringDateto_date(‘2025-06-14’, ‘yyyy-MM-dd’) → 2025-06-14to_timestamp(col, fmt)StringTimestampto_timestamp(‘2025-06-14 12:01’, ‘yyyy-MM-dd HH:mm’)unix_timestamp(col, fmt)StringLong (seconds since epoch)unix_timestamp(‘2025-06-14’, ‘yyyy-MM-dd’)from_unixtime(col)LongString (formatted time)from_unixtime(1718342400) 🕒…
Apache Spark RDDs: Comprehensive Tutorial
#Define a function to apply to each row def process_row(row):print(f”Name: {row[‘name’]}, Score: {row[‘score’]}”) #Apply the function using foreach df.foreach(process_row).. My question is- the process function for each element gets applied at driver side, is there a way that this loop will execute on distributed side You’re absolutely right — and this is a key concept…
DataBricks Tutorial for Beginner to Advanced
Here’s Post 5: Medallion Architecture with Delta Lake — the heart of scalable Lakehouse pipelines. This post is written in a tutorial/blog format with clear steps, diagrams, and hands-on examples for Databricks. 🪙 Post 5: Medallion Architecture with Delta Lake (Bronze → Silver → Gold) The Medallion Architecture is a layered data engineering design that…
Complete crisp PySpark Interview Q&A Cheat Sheet
Q1.Default Sizes for Broadcast in PySpark In PySpark, broadcasting is used to efficiently share a small DataFrame or variable with all worker nodes to avoid shuffling during joins. 🔹 Default Sizes for Broadcast in PySpark The default maximum size for broadcasting is: This means: 🔧 Configurable Setting You can change this threshold via Spark config:…
Python Lists- how it is created, stored in memory, and how inbuilt methods work — including internal implementation details
In Python, a list is a mutable, ordered collection of items. Let’s break down how it is created, stored in memory, and how inbuilt methods work — including internal implementation details. 🔹 1. Creating a List 🔹 2. How Python List is Stored in Memory Python lists are implemented as dynamic arrays (not linked lists…
Data Engineer Interview Questions Set1
1.Tell us about Hadoop Components, Architecture, Data Processing 2.Tell us about Apache Hive Components, Architecture, Step by Step Execution 3.In How many ways pyspark script can be executed? Detailed explanation 4.Adaptive Query Execution (AQE) in Apache Spark- Explain with example 5.DAG Scheduler in Spark: Detailed Explanation, How it is involved at architecture Level 6.Differences between…
PySpark SQL API Programming- How To, Approaches, Optimization
🔍 Understanding cache() in PySpark: Functionality, Optimization & Best Use Cases 🔹 What is cache() in PySpark? 🔧 How Does cache() Work Internally? 🔹 How Does cache() Optimize Performance? ✅ Avoids Recomputations: ✅ Reduces IO Load & Network Latency: ✅ Speeds Up Iterative Jobs (ML, Graph Processing, Multiple Queries on Same Data): ✅ Optimizes Joins…
How the Python interpreter reads and processes a Python script and Memory Management in Python
I believe you read our Post https://www.hintstoday.com/i-did-python-coding-or-i-wrote-a-python-script-and-got-it-exected-so-what-it-means/. Before starting here kindly go through the Link. How the Python interpreter reads and processes a Python script The Python interpreter processes a script through several stages, each of which involves different components of the interpreter working together to execute the code. Here’s a detailed look at how…
Lists and Tuples in Python – List and Tuple Comprehension, Usecases
Python Lists: A Comprehensive Guide What is a List? Lists are a fundamental data structure in Python used to store collections of items. They are: Example: Accessing Elements in a List Positive Indexing Negative Indexing (Access elements from the end) Slicing List Operations Modifying Elements Adding Elements Removing Elements Sorting and Reversing List Comprehensions Basic…
Python ALL Eyes on Strings- String Data Type & For Loop Combined
String functions for revision in Python: Let us Revise what we did learn!! Essential String Functions in Python: