if your #dataengineering experience grows more than 5 years you expect these questions in your interviews.....1. Explain me the architecture of spark?2. How does internals job execution happens?3. what will happen when you fire the Spark Job?4. How did you tune your jobs?5. Explain optimizations you have used in your project?6. How did you connected... Continue Reading →
Chatgpt for Interviews
ChatGPT can help you land your dream job twice as fast.Here are 10 powerful ChatGPT prompts will 10X your interview chances.1. Customizing Your ResumeChatGPT prompt: "Can you make changes to my resume to fit the [Job Title] role at [Company]?Here's the job description: [Paste Job Description], and resume: [Paste Resume]."2. Creating a Professional SummaryChatGPT prompt:... Continue Reading →
Database Indexes
Spend 2 minutes on this post, and you'll gain a good understanding of Database Indexing, which might take much longer to learn otherwise!Imagine managing a large-scale database:Database Size: ๐ฑ๐ฌ๐ฌ ๐๐Average Query Search Time Without Index: ๐ฑ ๐๐ฒ๐ฐ๐ผ๐ป๐ฑ๐Number of Records: ๐ฑ๐ฌ ๐บ๐ถ๐น๐น๐ถ๐ผ๐ป๐๐ฒ๐'๐ ๐ฑ๐ถ๐๐ฒ ๐ถ๐ป๐๐ผ ๐๐ต๐ฒ ๐๐ผ๐ฟ๐น๐ฑ ๐ผ๐ณ ๐๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ ๐๐ป๐ฑ๐ฒ๐ ๐ถ๐ป๐ด:1๏ธโฃ ๐ช๐ต๐ฎ๐ ๐ถ๐ ๐๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ ๐๐ป๐ฑ๐ฒ๐ ๐ถ๐ป๐ด?A database index is... Continue Reading →
Data Masking in Pyspark
Hide Credit card number:Accept 16 digit credit card number from user and display only last 4 characters of card numberinput :1234567891234567output :************4567We can use Py spark or pythonCode In Pyspark:---------------------from pyspark.sql import SparkSessionfrom pyspark.sql.functions import substring# Create a SparkSessionspark = SparkSession.builder.appName("HideCreditCard").getOrCreate()# Sample input credit card numberinput_cc_number = "1234567891234567"# Hide all characters except the last four... Continue Reading →
PySpark: Cleansing Data with Regex
๐ Delving into PySpark: Cleansing Data with Regex Magic!โ๏ธ๐ Example: Transforming Names with Special Characters ๐Picture yourself in the realm of data, where you've stumbled upon a trove of Indian names. However, these names are shrouded in a layer of noise, with special characters cluttering them. ๐ Step 1๏ธโฃ: The ChallengeImagine a dataset of Indian... Continue Reading →
AWS DE Questions
This post details AWS data engineering interview and highlights the most common concepts you can expect to be asked in interview processes.1. Start by providing a concise introduction to your professional projects, emphasizing your role as a data engineer.2. Share your knowledge of cloud platforms (AWS, GCP, Azure) as it pertains to data engineering.3. Discuss... Continue Reading →
TOP 50 SQl queries for interview
-- Q-1. Write an SQL query to fetch โFIRST_NAMEโ from Worker table using the alias name as <WORKER_NAME>. select first_name AS WORKER_NAME from worker; -- Q-2. Write an SQL query to fetch โFIRST_NAMEโ from Worker table in upper case. select UPPER(first_name) from worker; -- Q-3. Write an SQL query to fetch unique values of DEPARTMENT... Continue Reading →
Cloud Data Engineering Road Map
๐ถ๐ป Cloud Data Engineering Road Map ๐๐ปโ Basic Version Control toolhttps://lnkd.in/gEqyhzZRhttps://lnkd.in/g_t2xKnGhttps://lnkd.in/gZT7QNjS โ Data Warehousing Conceptshttps://lnkd.in/gq99PDcp โ Core Pythonhttps://lnkd.in/gQpmSnM โ Spark SQLhttps://lnkd.in/gDcR5bwM โ Databrickshttps://lnkd.in/gSpKBWbJhttps://lnkd.in/gpbMg9nU โ Sparkhttps://lnkd.in/gtqRtTPvhttps://lnkd.in/gs2gkqRq โ Pysparkhttps://lnkd.in/gmkPpmAXhttps://lnkd.in/gh-_KzjE โ Delta Lakehttps://lnkd.in/gt6ggER6 โ Cloud ETL Tool + Storagehttps://lnkd.in/gTs8y4Ai โ Cloud MPP Warehousehttps://lnkd.in/gMTHCrNZ โ Databricks Unity Cataloghttps://lnkd.in/gH6Q2a5K๐ Learn , Lead and Make Leaders ๐. Happy Learning ๐Follow ๐... Continue Reading →
System Design Challenges
Get a good grasp on these 45 key problems, and you'll be ready for a whopping 95% of your System Design Interview challenges-๐๐๐ฌ๐ฒ 1. Design URL Shortener like TinyURL 2. Design Text Storage Service like Pastebin 3. Design Content Delivery Network (CDN) 4. Design Parking Garage 5. Design Vending Machine 6. Design Distributed Key-Value Store... Continue Reading →
PySpark: Sales Data Analysis
Exploring PySpark: Advanced Data Analysisโ๏ธ๐ฑ Scenario: Analyzing Multi-Dimensional Sales Data๐Imagine being tasked with analyzing sales data that spans multiple dimensions, including time, regions, and product categories. To unlock insights from this complex dataset, PySpark's powerful capabilities come into play.๐ Step 1๏ธโฃ: Defining the ChallengeYour goal is to gain a comprehensive understanding of sales performance by... Continue Reading →
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