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"𝐀 8 𝐰𝐞𝐞𝐤 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐭𝐨 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐜𝐫𝐚𝐜𝐤 𝐭𝐡𝐞 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬 𝐨𝐟 𝐭𝐨𝐩 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐛𝐚𝐬𝐞𝐝 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐛𝐲 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐢𝐧𝐠 𝐚 𝐭𝐡𝐨𝐮𝐠𝐡𝐭 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐚𝐧𝐝 𝐚𝐧 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 𝐭𝐨 𝐬𝐨𝐥𝐯𝐞 𝐚𝐧 𝐮𝐧𝐬𝐞𝐞𝐧 𝐏𝐫𝐨𝐛𝐥𝐞𝐦."
𝐇𝐞𝐫𝐞 𝐢𝐬 𝐡𝐨𝐰 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐫𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 -
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤 (𝐂𝐨𝐮𝐫𝐬𝐞 𝐀𝐜𝐜𝐞𝐬𝐬 𝐟𝐫𝐨𝐦 𝐈𝐧𝐝𝐢𝐚) : rzp.io/l/SQLINR
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤 (𝐂𝐨𝐮𝐫𝐬𝐞 𝐀𝐜𝐜𝐞𝐬𝐬 𝐟𝐫𝐨𝐦 𝐨𝐮𝐭𝐬𝐢𝐝𝐞 𝐈𝐧𝐝𝐢𝐚) : rzp.io/l/SQLUSD
30 INTERVIEWS IN 30 DAYS- BIG DATA INTERVIEW SERIES
This mock interview series is launched as a community initiative under Data Engineers Club aimed at aiding the community's growth and development
Our highly experienced guest interviewer, Solon Kumar Das, / solondas shares invaluable insights and practical guidance drawn from his extensive expertise in the Big Data Domain.
Our expert guest interviewee, Ankit Raj, / ankit-raj-7b26601b8 has an interesting approach to answering the interview questions on Apache Spark, SQL and Azure Cloud Services.
Link of Free SQL & Python series developed by me are given below -
SQL Playlist - • SQL tutorial for every...
Python Playlist - • Complete Python By Sum...
Don't miss out - Subscribe to the channel for more such informative interviews and unlock the secrets to success in this thriving field!
Social Media Links :
LinkedIn - / bigdatabysumit
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Instagram - / bigdatabysumit
Student Testimonials - trendytech.in/#testimonials
TIMESTAMPS : Questions Discussed
00:00 Introduction
02:25 Project Responsibilities
08:30 Deltalake Features Advantages
11:04 ACID Transactions and Delta Tables
12:37 Z-Ordering
13:23 Spark Optimization Techniques
18:00 Memory Management in Spark
20:43 Coding Questions
Music track: Retro by Chill Pulse
Source: freetouse.com/music
Background Music for Video (Free)
Tags
#mockinterview #bigdata #career #dataengineering #data #datascience #dataanalysis #productbasedcompanies #interviewquestions #apachespark #google #interview #faang #companies #amazon #walmart #flipkart #microsoft #azure #databricks #jobs

[@ravulapallivenkatagurnadha9605]

Much needed videos

[@hdr-tech4350]

3rd txn of every user
Cumulative sum of sales amount of each product id

[@SanjayKumar-rw2gj]

Solution provider by interviewer is wrong

[@soumen_22]

The cumulative sum question example output I think is wrong. As per my understanding it should be 90 instead of 210 in row4 of output example as in the input 6th row product id changed than 5th row.
Even the solution shown will give wrong output. It will partition based on product_id and the cum sum of each product_id will come together like below.
id product_id sales_date sales_amt cumsum
1 1 2024-01-01 100 100
2 1 2024-01-02 150 250
4 1 2024-01-03 120 370
6 1 2024-01-04 90 460
3 2 2024-01-01 200 200
5 2 2024-01-02 180 380
But expectation was something else right if I am not wrong.

[@bhumikalalchandani321]

Yes

[@adiadi-xe7ds]

@15:00
Q: AQE already enabled in spark 3.0, if you still facing an out of memory error. what will be the solution?
A: if we increase the shuffle partitions(default 200 to more than 200), will out of memory error resolves?

[@subhashyadav9262]

select * from (
select *,ROW_NUMBER()over(partition by user_id order by transaction_date asc)cnt from int1
)aa where cnt=3

[@laxmipoojamule4297]

Sir please upload python video it's been more than 2 weeks