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.
All major PySpark data structures and types Discussed
🔍 What Does collect_list() Do in Spark SQL? collect_list() is an aggregation function in Spark SQL and PySpark. It: Collects all values of a column (within a group, if grouped) into a single array, preserving duplicates and order (non-deterministically). ✅ Syntax In PySpark: 🧾 Example Input table: categoryvalueAxAyAxBzBy Query: Output: categoryvalue_listA[x, y, x]B[z, y] 🔄…
PySpark Control Statements Vs Python Control Statements- Conditional, Loop, Exception Handling, UDFs
understanding when and why to use UDFs (User-Defined Functions) in PySpark is key for both real-world development and interviews. Let’s break it down clearly: ✅ What is a PySpark UDF? A UDF (User-Defined Function) lets you write custom logic in Python (or Java/Scala), which can then be applied to DataFrames just like native Spark functions.…
Partition & Join Strategy in Pyspark- Scenario Based Questions
Great question — PySpark joins are a core interview topic, and understanding how they work, how to optimize them, and which join strategy is used by default shows your depth as a Spark developer. ✅ 1. Join Methods in PySpark PySpark provides the following join types: Join Type Description inner Only matching rows from both…
Data Engineer Interview Questions Set5
Here’s a detailed and interview-optimized answer sheet for each of your 8 questions (Q1–Q8), covering PySpark coding, Data Quality (DQ), SCD, optimization, and Spark architecture (AQE) — exactly how you’d want to respond in a technical interview: ✅ Q1. Extract dates from lines using string methods (not regex) and return those with year > 2018…
SQL Tricky Conceptual Interview Questions
Perfect—now I understand! You’re looking for tricky, high-quality SQL interview questions like: “What’s the difference between DELETE, DROP, and TRUNCATE?” These are concept-based, real-world, and interview-style—not just syntax exercises. 🔥 Top Tricky SQL Interview Questions (with Answers) Below is a carefully curated list covering real-world understanding, edge cases, performance, and design: ✅ 1. What is…
Data Engineer Interview Questions Set4
Perfect! Here’s everything inline, right in this window: ✅ Part 1: Spark Cluster Simulation Notebook (Inline Code) This Jupyter/Databricks notebook simulates how Spark behaves across cluster components: 🧠 Use .explain(True) at any step to inspect execution plan. ✅ Part 2: Spark Execution Flow — Mindmap Style Summary (Inline) ✅ Optional: Mindmap Format You Can Copy…
Data Engineer Interview Questions Set3
Let’s visualize how Spark schedules tasks when reading files (like CSV, Parquet, or from Hive), based on: ⚙️ Step-by-Step: How Spark Schedules Tasks from Files 🔹 Step 1: Spark reads file metadata When you call: 🔹 Step 2: Input Splits → Tasks File Size Block Size Input Splits Resulting Tasks 1 file, 1 GB 128…
Data Engineer Interview Questions Set2
Here’s the full code from the Databricks notebook, followed by a handy Join Optimization Cheatsheet. 📓 Azure Databricks PySpark Notebook Code 🔗 Broadcast Join vs Sort-Merge Join + Partitioning vs Bucketing ✅ Notes on Optimization 📘 Join Optimization Cheatsheet Aspect Broadcast Join Sort-Merge Join Partitioning Bucketing Trigger Small table < threshold (10MB) Default fallback User-defined…
How SQL queries execute in a database, using a real query example.
We should combine both perspectives—the logical flow (SQL-level) and the system-level architecture (engine internals)—into a comprehensive, step-by-step guide on how SQL queries execute in a database, using a real query example. 🧠 How a SQL Query Executes (Combined Explanation) ✅ Example Query: This query goes through the following four high-level stages, each containing deeper substeps.…
Comprehensive guide to important Points and tricky conceptual issues in SQL
Let me explain why NOT IN can give incorrect results in SQL/Spark SQL when NULL is involved, and why LEFT ANTI JOIN is preferred in such cases—with an example. 🔥 Problem: NOT IN + NULL = Unexpected behavior In SQL, when you write: This behaves differently if any value in last_week.user_id is NULL. ❌ What…
RDD and Dataframes in PySpark- Code Snipppets
Where to Use Python Traditional Coding in PySpark Scripts Using traditional Python coding in a PySpark script is common and beneficial for handling tasks that are not inherently distributed or do not involve large-scale data processing. Integrating Python with a PySpark script in a modular way ensures that different responsibilities are clearly separated and the…
Azure Databricks tutorial roadmap (Beginner → Advanced), tailored for Data Engineering interviews in India
Here’s a crisp explanation of core technical terms in Azure Databricks, tailored for interviews and hands-on clarity: 🚀 Databricks Key Technical Terms 🧭 Workspace UI and environment where users organize notebooks, jobs, data, repos, and libraries. ⚙️ Cluster A Spark compute environment managed by Databricks. 🧱 DBFS (Databricks File System) Databricks-managed distributed storage layer on…
Spark SQL Join Types- Syntax examples, Comparision
Here are Spark SQL join questions that are complex, interview-oriented, and hands-on — each with sample data and expected output to test real-world logic. ✅ Setup: Sample DataFrames 🔹 Employee Table (emp) 🔹 Department Table (dept) 🧠 1. Find all employees, including those without a department. Show department name as Unknown if not available. 🧩…
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 is Post 4: Delta Lake Deep Dive — a complete, hands-on guide perfect for your Databricks tutorial series. 💎 Post 4: Delta Lake Deep Dive in Databricks Powerful Features to Scale Your Data Engineering Projects Delta Lake is at the heart of the Lakehouse architecture. If you’ve already started exploring Spark and saved your…