Комментарии:
really superb. the way u hav explained the concept is beautifull. can u explain the spark architecture
ОтветитьIt's really nice to understand the complex topics very easily.
ОтветитьWhy can’t you get 100k subscribers...
ОтветитьGreat explanation. Thank you
ОтветитьHi @Tech Primers what is the difference between messaging and Streaming?..
Ответитьthorough explanation! great video, overall! thanks for all the info!
ОтветитьThis video was thorough, clear, and very helpful, thanks!! I'm in school and will share it with my classmates!
ОтветитьGreat video thanks a lot.
Ответитьthis video is really helpful . can you please make video on concepts IBM MQ and avro kafka and Tibco etc . message queue and schema registration etc topics uses in scripting in performance testing and what are the goel to uses these concepts in scripting in performance testing with uses case examples to get proper visualization
ОтветитьBeautifully explained and the use case was too good.
Ответитьa precise and up to the point tutorial, great video.
ОтветитьExcellent explanation. sad to see few idiots dislike this video
ОтветитьExcellent content 👌 simple and contextual. keep up the awesome work
Ответитьthank you
ОтветитьUse cases are bit high standard to understand. Please take some easier ones.
Ответитьi would like to know if I have to synchronize 2 device with different time streams which technology can i use
ОтветитьThank you.
ОтветитьThanks for the video. Could you please state why do we need to place analytics service before AWS streams? What should this service do in this particular example?
ОтветитьThanks
ОтветитьWell done , very well explained
Ответитьvery good 👍
ОтветитьThanks for the great video!!! Already subscribed!!
ОтветитьUr videos are very informative. Thanks for your efforts
ОтветитьExcellent Presentation !! To the point and very clear !!
Ответитьso apache spark can do batch and also streaming processing ?
ОтветитьExcellent video ☺️. Can you please create a demo application for similar use case?
ОтветитьEasy to understand, the way you've explained.
ОтветитьThanks creator for making this video. 🙏
ОтветитьAwesome and power-packed. Thanks for creating such beautiful content.
ОтветитьWish I came across this channel earlier , nonetheless better late than never . Superb content and numbers shout that this channel is pretty underrated .
Ответитьtoo much information
ОтветитьThank you so much!
ОтветитьAre you saying that Amazon Kinesis uses Apache Flink? As I understand, they have similar functionality, but Kinesis is proprietary while Flink is open source.
ОтветитьThank you so much! Your videos are very helpful for me. Good to see that you have passed 100K+ subscribers.
ОтветитьThank you sir 🙏
ОтветитьThanks for the case studies. Quite helpful!
ОтветитьJust wow!!
Maybe you don't realize how helpful and resourceful is your video.
I just got my certificate in data engineering but let me tell you this, you are so concise and clear in your explanations that I feel more confident now using stream processing.
From time to time I will come back to you if I have any questions. I do have it but I will ask them later
This was awesome
ОтветитьVery useful bro. Thanks a lot for this video!..
ОтветитьAwesome explanation.. Thanks
Ответитьwonderful content, very well explained, thanks!!
Ответитьnice explanation
ОтветитьFor realtime steam processing.
If i send each frame into my ML Inference load balanced servers as a post request, even this works right? Then why do we need kafka
Great vedio
ОтветитьThanks for the great Explanation with real time use cases
ОтветитьRegarding streaming, using all these services one by one, doesn't it caues lot of latency delay?
ОтветитьIt's hard to find quality content about advanced topics like this. Well explained 👍
Ответитьwtf wrong with your micro, omfg
ОтветитьPlease say in hindi.
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