HintsToday
Hints and Answers for Everything
recent posts
- What is Hive? Important Points, Interview Questions
- How SQL queries execute in a database, using a real query example.
- Comprehensive guide to important Points and tricky conceptual issues in SQL
- RDD and Dataframes in PySpark- Code Snipppets
- Azure Databricks tutorial roadmap (Beginner → Advanced), tailored for Data Engineering interviews in India
about
Author: lochan2014
Hive a Data warehouse infra Hive is an open-source data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. It allows users to query and manage large datasets residing in distributed storage using a SQL-like language called HiveQL. Here’s an overview of Hive: Features of Hive: Components of Hive: Use…
Understanding how an SQL query executes in a database is essential for performance tuning and system design. Here’s a step-by-step breakdown of what happens under the hood when you run an SQL query like: 🧭 0. Query Input (Your SQL) You submit the SQL query via: ⚙️ Step-by-Step SQL Query Execution 🧩 Step 1: Parsing…
Here’s a comprehensive guide to important and tricky conceptual issues in SQL, including NULL behavior, joins, filters, grouping, ordering, and subqueries. ✅ 1. NULLs: The #1 source of confusion a. NULL ≠ NULL b. NOT IN with NULL c. Arithmetic with NULL ✅ 2. JOIN Issues a. INNER JOIN drops unmatched rows. b. LEFT JOIN…
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…
Here’s a complete Azure Databricks tutorial roadmap (Beginner → Advanced), tailored for Data Engineering interviews in India, including key concepts, technical terms, use cases, and interview Q&A: ✅ What is Azure Databricks? Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for the Microsoft Azure cloud. 🔗 How Azure Databricks integrates…
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 and comparisons. Types of Joins in Spark SQL 1. Inner Join An inner join returns only the rows that have matching values in both tables. Syntax: Example: 2. Left (Outer)…
A quick reference for date manipulation in PySpark:– Function Description Works On Example (Spark SQL) Example (DataFrame API) to_date Converts string to date. String TO_DATE(‘2024-01-15’, ‘yyyy-MM-dd’) to_date(col(“date_str”), “yyyy-MM-dd”) to_timestamp Converts string to timestamp. String TO_TIMESTAMP(‘2024-01-15 12:34:56’, ‘yyyy-MM-dd HH:mm:ss’) to_timestamp(col(“timestamp_str”), “yyyy-MM-dd HH:mm:ss”) date_format Formats date or timestamp as a string. Date, Timestamp DATE_FORMAT(CURRENT_DATE, ‘dd-MM-yyyy’) date_format(col(“date_col”), “dd-MM-yyyy”)…
Apache Spark RDDs: Comprehensive Tutorial Table of Contents Introduction to RDDs Resilient Distributed Datasets (RDDs) are the fundamental data structure of Spark. They are: Key Characteristics: RDD Lineage RDD lineage is a graph of all the parent RDDs of an RDD. It’s built as a result of applying transformations to the RDD. Output would show…
Absolutely! Let’s break down Data Lake, Data Warehouse, and then show how they combine into a Data Lakehouse Architecture—with key differences and when to use what. 🧊 1. Data Lake vs Data Warehouse Feature 🪣 Data Lake 🏛️ Data Warehouse Type of Data Raw, unstructured, semi-structured, structured (e.g., logs, images, JSON, CSV, Parquet) Structured data…
Certainly! Here’s the complete crisp PySpark Interview Q&A Cheat Sheet with all your questions so far, formatted consistently for flashcards, Excel, or cheat sheet use: Question Answer How do you handle schema mismatch when reading multiple JSON/Parquet files with different structures? Use .option(“mergeSchema”, “true”) when reading Parquet files; for JSON, unify schemas by selecting common…