Map Reduce explained with example | System Design
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- Опубликовано: 14 окт 2024
- In this video I explain the basics of Map Reduce model, an important concept for any software engineer to be aware of. This will help you identify and apply Map Reduce related questions during your System Design Interviews
Map Reduce Paper: static.googleu...
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thank you so much, today i went to my first day of internship as a 15 year old girl and didn't get the complicated words they explained me but u thought me in a way I will never forget in my whole life.
thank you so much!!!!
where in the world are 15-year olds doing internships that involve map-reduce?? that's wild
15 is the new 18 (pause)@@chanwoopark5397
15 year olds, doing internships, and dealing with MapReduce and distributed systems. My 25 years old senior software engineer @$* not being able to comprehend the situation. Which world you live in mah lil sister?
@@chanwoopark5397 I did the internship in my brothers company so... It wasn't that hard for me to get in...
@@backslash8874 brotha, it's just like 3 months internship wasn't that hard, my brother is the owner of the company so he just accepted to let me in. I was told to do a couple of work and understand d the concept first, I tried my best to go to internship coz I wanna become a senior like you. And see, that's the difference, I will introduce myself as a intern not a senior like you. 🤗🤗
I really admire you guys,🤗🤗 I waiting to finish my education and I wanna work! Infact I'm kinda girl who watches "the office"😂😂
Most excited video of 2023 for an diagrammatic representation and clear cut explanation ❤❤❤ really great. College staff wants people like you to teach.
The most complex name explained with the most simplest scenario. I understand this better now
The professors we want in Indian engineering colleges ❤
Good job bro in 9 minutes i can score 20 marks easily 😂👍👍
I watched many videos but your's 🔥🔥.
I understood, thankyou!! 👏😊
Thank you for this! I have a data engineering interview tomorrow and the example really helped me understand the concept well enough to be able to explain it myself if I am asked.
my latest video on data platform might also help you prepare for the interview, all the best!
finally i know what is MapReduce, thanks !
What a quality sir, hand off
Very clear and understanding explanation.
I love you man
Such a clean explanation
great explanation of map reduce.
Excellent video I was looking for a simple explanation like this
thank you so much it's clear and well explained you answered all my whys and whats
His Voice ❤❤️🔥🔥
love you bro, u made it easy.
Super presentation.. Thank you sir.
Best one I've seen yet
this video made a complex topic in a very simpler way ♥️☺️💯
Excellent explanation!! Thank you.
very nice and informative and detailed. thanks.
Very nice explanation
i lost my jaw when i saw this video , bravo , nicely done men 👍
thank you so much for this sample , beautiful and benefiting explanation
Amazing explanation!
thank you so much, very clear
the example is pretty straight forward
What a wonderful explanation!
Thank you for awesome explanation!
This is a great video. Thank you!
@ByteMonk dank video, very clear and concise but I've got a question: at 8:20 you say we're tasked with finding all the videos with a certain number of likes. Do we really need to go through ALL of the metadata if we're just looking for the condition "number of likes >= [some amount]"??
map reduce function where key deals with the like parameter from the metadata. Faster to search the cluster
Great video! Now do spark!
nice explanition with all the details thanks bro 💕💕
Excellent explanation
Tqsm ☺️
This is what I wanted
Thank you for this super helpful video!
What I have not understood yet is, how can I turn the process back? For example, if I am looking at the output file, how do I know in how many of those input files has the word 'apple' been? From what I understood, it could have been twice in the first (or second) file or once in each.
His voice 🗿
I am assuming that's a compliment :)
@@ByteMonkyes it is😅
@@ByteMonknah man, although you tried so we appreciate it
I can't focus 😂
Amazing explanation sir.
Would like to know how FB store likes and comments.
Suppose user from India likes a video, and another user from the USA likes the same video, are they stored in same place or in a sharded db (country wise), would like to know your perspective
thank you so much, but maybe explain the example directly after the motivation next time.
Bro you are awesome 👍
Very helpful. thank you:)
very good video
great vid. thanks
Love you broo
Thanks!
Thanx 😊
nice!
Thanks!
✨
Damn you're voice🤌🏼
Failure nodes in classic mapreduce
🔥
Is hadoop dead? Who is still using that.
Hadoop, in its original form, has reached a mature stage. It's less of a buzzword and more of a foundational technology upon which other systems are built. Many companies heavily invested in
Hadoop infrastructure during its peak years and still rely on it. For example Yahoo! likely still has large-scale Hadoop systems for storage and batch processing. Facebook has also Built a huge Hadoop infrastructure for data warehousing and analytics. While they've moved a lot of processing to newer systems, legacy Hadoop clusters probably remain.
These companies probably don't use Hadoop in exactly the same way they did during its peak. They likely have layered newer technologies like Spark or cloud-based analytics on top of their Hadoop foundations.
5:00
Looks like author is sleeping all the video)
Looking back at this video, I feel the same :D