What is MapReduce?
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- čas přidán 6. 10. 2016
- Building efficient data centers that can hold thousands of machines is hard enough. Programming thousands of machines is even harder. One approach pioneered by Google is known as MapReduce. MapReduce provides a programming model that simplifies programming thousands of machines by breaking down distributed programs into two steps: map, and reduce.
Credits: Talking: Geoffrey Challen (Assistant Professor, Computer Science and Engineering, University at Buffalo). Producing: Greg Bunyea (Undergraduate, Computer Science and Engineering, University at Buffalo).
Part of the www.internet-class.org online internet course. A blue Systems Research Group (blue.cse.buffalo.edu) production.
FINALLY. This made sense. I watched a few others try to explain it in the weirdest way, immediately jumping into details instead of giving a bigger picture first.
Thank you my GTA character
lol
thanks for explaining this so clearly.
this is one of the rare explanations in youtube that isn't inane or polluted with pointless jargon.
People love complicating simple stuff!
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A simple topic made unnecessarily difficult to understand by others poor explanation. Thanks so much, concept is now crystal clear to me.
almost everything is this, ppl wanna seem smart so they spew jargon.
This is the single best explanation on the topic on CZcams. It helped me 6 years ago and it still holds up now that I'm revising. Thanks!
Finally a good professor on this matter.
How random. Came here looking to learn more about Map Reduce before a Facebook interview next week, and the guy doing the video ends up being one of my old CS professors.
I still refer to this video and I get to understand MR better with every play, if only I could like this video every time I watched it. Thank you for the content.
straight to the point and specific, great explanation
This the most explicit and best explanation on MapReduce concept ever!!!
Thank you so much for the simple yet effective visuals. Perfect for people who just need the basic knowledge before stepping into all of the complicated parts.
This video was super helpful for me!! Not only talked about the counting example but also explained that there are some tasks that do not fit in this framework!! Now I think I got the concept!! Thanks!!
Thanks a lot! I struggled a bit to learn what is map reduce from documents. This video makes everything so clear!
Brilliantly put, I must say, when you explain it like that, it makes our understanding of distributed computing much easier to understand. Saving your video is a play list for future references and sharing. thank you~
amazing. cramming for a parallel and distributed systems in an hour. thanks so much!
This is an excellent explanation! thank you so much :D
This is channel is so underrated.
WOW, what a crystal clear explanation. Thank you!
Absolutely brilliant explanation. Best I've seen so far.
I just shed a tear. That was beautiful!
Simply amazed by you dude. Loved it. Thanks !
Thanks for your clear explanations! Very useful 👏🏼
so cool, so consistent! Five minutes and I already understand the essence! Thank u so much!
you mean concise?
Thank you that was a great concept explanation video! Easy to understand and right to the point.
Thank you so much for the explanation and excellent example
Wonderfully explained, thank you!
simple and to the point , thanks !
Well done, precise and elaborate
Excellent tutorial :) Thanks for uploading.
Wow thank you so much for such a simple and crystal clear example..
Well done!!! I enjoyed listening to a 5 min video and I got the concept of the MapReduce, thank you sooo much :)
AMAZING explanation, thanks!!
Best explanation in the CZcams! Thanks🙏🏻
Bless you! Wonderfully explained.
High quality explanation in a simple way.
Thank you! A terrific explanation.
Best video on map-reduce on internet
Thank you so much for great and short explain!
Easy to understand, great work done!
Very good explanation, Thank You !!
Great explanation! Thank you for that!
thank you for explaining so clearly
Amazing explanation! Thank you.
Great explanation! Thank you
Fantastic introduction. Thanks
Thank you for the explanation!
Nicely done. Give this man a raise.
straight to the point. nice video
Beautifully explained thanks 🙏
Once you understand the why, it is so much clear. Thank you
Very clear explanation. Thanks
MapReduce is distributed sorting
Map: splitting data up to multiple computers, and those computers individually conducts the sorting
Reduce: combining the sorted results into a lookup table
Very easy to understand, thank you!
Wonderful explanation! Good job
Very easy explanation. Thanks a lot.
Thank you so much, man! Neat explanation.
Got a clear idea about it. Thanks from India.
BEST explanation .
Excellent explanation, seldom found.
One of the best explanation ever
This was a great explenation. Thanks!
Thanks for this man. You really helped me.
Very good and simple explanation!
Thank you soo much best explanation !!
Perfectly explained, helped me a lot thank you 😊
Amazing introduction!
MapReduce explanation made easy. Good job
Best explanation so far. Nice one Brof...
Nice explanation, Thank you
You MapReduced the haadop MapReduce concept in 5 minutes.
Beautifully Explained 👍
Yes, that was great. Thanks so much.
I like the way he speaks and orgnaizes the training material
amazingly explained
Good video! Thanks man!
That's incredible!
your explanation was very helpful, thanks for the video
Great video finally got it!
Great explanation...Keep up good work.
Great explanation
When you got a thing for teaching you know you got it. !
Well explained
Thank you.
this guy woke up and chose th DRIP for his presentation.. love it
very clear explanation
Fantastic!
So clear I could see through the whiteboard.
Very Good explanation
Thank you for explaining what my lecturer took 2 hours in 5min
Thanks man ❤
Great Video :)
Great video
Thank you, sir
Finally, someone can make sense!
Thanks a lot!!
Amazing!
great! thanks.
great stuff
Helped me alot! Thankyou!
great explanation bro
The Shuffle step groups data with similar key and sends it for reduce. How does Shuffle work? How does it group the data produced by mappers that is spread across multiple nodes?