What is MapReduce?

[@test-mm7bv]

thanks for explaining this so clearly. this is one of the rare explanations in youtube that isn't inane or polluted with pointless jargon.

[@hoelefouk]

People love complicating simple stuff!

[@marleyharper3261]

I guess im asking the wrong place but does anybody know of a trick to log back into an Instagram account?? I somehow lost my account password. I love any tricks you can give me!

[@justicenasir9989]

@Marley Harper Instablaster =)

[@marleyharper3261]

@Justice Nasir Thanks for your reply. I found the site on google and Im in the hacking process atm. I see it takes a while so I will reply here later with my results.

[@marleyharper3261]

@Justice Nasir it did the trick and I now got access to my account again. I am so happy! Thanks so much, you saved my ass!

[@kevinohare4330]

A simple topic made unnecessarily difficult to understand by others poor explanation. Thanks so much, concept is now crystal clear to me.

[@10Exahertz]

almost everything is this, ppl wanna seem smart so they spew jargon.

[@Rahul_1.618]

This is the single best explanation on the topic on KZbin. It helped me 6 years ago and it still holds up now that I'm revising. Thanks!

[@standcontractdelta8120]

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.

[@igcc13]

Finally a good professor on this matter.

[@kob3570]

Thank you my GTA character

[@twelveguo5869]

lol

[@halasentissi]

😂

[@tshaylatte9502]

Once you understand the why, it is so much clear. Thank you

[@807johnny807]

straight to the point and specific, great explanation

[@newbie2743]

This the most explicit and best explanation on MapReduce concept ever!!!

[@ciloc2768]

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!!

[@atharvashirode9711]

Best video on map-reduce on internet

[@skipa9906]

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.

[@arocco89]

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.

[@ChiefRemoteOfficer]

Nicely done. Give this man a raise.

[@fostercityjoe]

I just shed a tear. That was beautiful!

[@jotarokuzo]

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.

[@nikhil182]

This is channel is so underrated.

[@Alexandra-he8ol]

Best explanation in the KZbin! Thanks🙏🏻

[@aemethes]

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~

[@high_fly_bird]

so cool, so consistent! Five minutes and I already understand the essence! Thank u so much!

[@francisckekbroccoli4245]

you mean concise?

[@xianshuzeng3476]

Thanks a lot! I struggled a bit to learn what is map reduce from documents. This video makes everything so clear!

[@justinkim8856]

I like the way he speaks and orgnaizes the training material

[@ziad4744]

High quality explanation in a simple way.

[@itzindy12]

This is an excellent explanation! thank you so much :D

[@JohnDoe-zc4mu]

One of the best explanation ever

[@Shermila]

Got a clear idea about it. Thanks from India.

[@iqminiclip1222]

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

[@kenii28]

amazing. cramming for a parallel and distributed systems in an hour. thanks so much!

[@user-fy5go3rh8p]

Absolutely brilliant explanation. Best I've seen so far.

[@mohammadrahimtaheri5134]

Thank you so much for the explanation and excellent example

[@brianssendagire262]

Well done, precise and elaborate

[@Daniel-iy1ed]

Beautifully explained thanks 🙏

[@george4746]

Fantastic introduction. Thanks

[@explorer10179]

Wonderfully explained

[@farazirfan47]

Easy to understand, great work done!

[@arnavmathur0207]

Simply amazed by you dude. Loved it. Thanks !

[@MeridiusMaximus]

WOW, what a crystal clear explanation. Thank you!

[@ShabnamKhan-cj4zc]

Wow thank you so much for such a simple and crystal clear example..

[@sebon11]

AMAZING explanation, thanks!!

[@chijiokeonukem4237]

Best explanation so far. Nice one Brof...

[@oleghools4177]

Very easy explanation. Thanks a lot.

[@divyanshuchaudhari5416]

Great explanation...Keep up good work.

[@AndersonSilva-vs4gn]

Very good and simple explanation!

[@alinaqvi385]

Excellent explanation, seldom found.

[@maoryahalomi-work1869]

Thank you so much for great and short explain!

[@JohnDoe-zc4mu]

So clear I could see through the whiteboard.

[@creaturerohit]

simple and to the point , thanks !

[@venustann1300]

thank you for explaining so clearly

[@oluwaseunshadare3645]

MapReduce explanation made easy. Good job

[@pierricknonnis8526]

Thanks for your clear explanations! Very useful 👏🏼

[@danvisan7017]

straight to the point. nice video

[@ssamiuddin1]

Wonderfully explained, thank you!

[@sambuzzmusic]

Thank you for explaining what my lecturer took 2 hours in 5min

[@inamjanibragimov]

Amazing explanation! Thank you.

[@fatemehcheginisalzmann2189]

Well done!!! I enjoyed listening to a 5 min video and I got the concept of the MapReduce, thank you sooo much :)

[@lamprosvelentzas7112]

Great explanation! Thank you for that!

[@twinwalks]

Great explanation!

[@mohammedaminelachhabe2087]

You MapReduced the haadop MapReduce concept in 5 minutes.

[@RM-xr8lq]

if u understand map and reduce u can probably figure out how this work... it is just for distributed system, so ur mapped data will need to be merged/shuffled for individual reducers (also distributed) to see all of relevant keys for someting

[@kibagamij777]

Thank you! A terrific explanation.

[@ExcelTutorials1]

Very easy to understand, thank you!

[@maximiliancunningham6598]

This was a great explenation. Thanks!

[@Sira-]

Thank you that was a great concept explanation video! Easy to understand and right to the point.

[@mustafamohammadi5741]

Wonderful explanation! Good job

[@Jkudjo]

When you got a thing for teaching you know you got it. !

[@albertgao7256]

Finally, someone can make sense!

[@prasannakoirala8489]

Bless you! Wonderfully explained.

[@robertsamal]

Thanks for this man. You really helped me.

[@aakashnandrajog7035]

BEST explanation .

[@btcboy823]

Perfectly explained, helped me a lot thank you 😊

[@maheshwaranparamasivan5177]

Very good explanation, Thank You !!

[@WittCode]

Good video! Thanks man!

[@Nova-Rift]

Good job, very clear!

[@cad1729]

Very clear explanation. Thanks

[@harryjohnsonperu724]

Beautifully Explained 👍

[@vinothkumarsugumar1436]

Thank you soo much best explanation !!

[@SauravSagar19]

Nice explanation, Thank you

[@nandkumarkarlekar4973]

Very Good explanation

[@PasinduTennageprofile]

Excellent tutorial :) Thanks for uploading.

[@abunasar786]

amazingly explained

[@GIULI4994]

your explanation was very helpful, thanks for the video

[@spearchew]

this video is superior to the other five or six i tried

[@shashankkhandelwal6876]

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?

[@steveellison8686]

Yes, that was great. Thanks so much.

[@matejkonopik2628]

this guy woke up and chose th DRIP for his presentation.. love it

[@Dani-bx2lt]

Great explanation

[@bogassolti8082]

Thank you so much, man! Neat explanation.

[@roxanacepoiu5436]

Great explanation! Thank you

[@ClaymorePT]

So, the most complicated work is processed by the map function? Reduce seems to do the simplest job. :/ Since each reduce function is supposed to receive only a specific type of keys, how does the map function knows to which machine should it send the values?

[@omkarwarade1455]

What I think is the intermediate machine shuffler(or shifter) brings all the same keys together and then it passes on to reducer and then the reducer is combining those keys in one.

[@rahulpillai2625]

Amazing introduction!

[@The_Little_I_Know]

Thanks for the clear explanation, in addition, I got a position of GA. Any advice as I am starting off my career please?

[@brothermalcolm]

great visual - could you make a video on hadoop / hive / spark please?

[@saeeduchiha5537]

you are good! but I wish you at least mentioned the alternatives of MapReduce framework and what are the scenarios where its not the best for.

[@simonlan6993]

That's incredible!

[@sandtrick]

What are the newer methods he mentioned?

[@SOmar-zq1nq]

very clear explanation

[@itsamethyst_]

I have a question: Can we use only 1 machine for reduce stage instead of 2? (in case of this example)

[@niels564]

Thank you for the explanation!

[@abrahamodefunso4878]

Well explained Thank you.

[@arpit8273]

So, how it is done now? if they have left using map reduce?