Comments by "Winnetou17" (@Winnetou17) on "ByteByteGo" channel.

  1.  @yatinarora1252  Conceptually is EXACTLY sharding.
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  2. I think it reduces latency in the event where the busy CEO is doing something else and the other part has to wait for the CEO to handle its request. The ambassador can start handling the request immediately.
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  3. Did you just say that C is slower than Java nowadays ?
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  4. Regarding that search... if there are many articles with the misspelling, the system might genuinely think that's a different term and that's why it's returning those specific results. Though I don't really know.
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  5. I'm very curious too. Theoretically, if they have 9 servers, even if they're very beefy (think of maxed out Epyc CPUs), that's still, I think, very cheap compared to most all cloud solutions of the same size. And something tells me that they don't have hundreds of programmers and devops either.
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  6.  @r_v_t  The big 4 ? I assume you mean Windows, Linux and MacOS.... what's the fourth ? Android (which is also Linux, but with different userland tools) ?
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  7. Regarding the strategies of this video, you can do all of them at the same time.
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  8.  @DemPilafian  Yikes!
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  9. Single big High definition ? I'm not sure if all my data can fit into a 1280x720 ...
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  10. NO - the key surely does not exist (and it's useful as you can skip that level) YES - the key might or might not exist - you have to search. As an example, a father would say "I'm not certain if my son is doing drugs, but I'm certain it didn't travel to China". The bloom filter has situations when it knows for sure the key doesn't exist and can tell you that. If it would be all the time, then it will be a firm YES and firm NO all the time, indeed.
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  11. What is wrong with you people ? That's exactly what's said in the video. And much simpler than what you try to explain. Am I missing something ? There's other comments like this too, arguing that somehow the video is incorrect, when in fact it is, or at least what they say is the same as what the video says. Which is if the bloom filter says there's no key, you can trust that and skip to the next level.
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  12. The difference isn't only in compiled, JIT and interpreted. JS is also weak typed, while Java is strong typed. Weak typing means you have to check the type at run time, when, say, doing a+2. In Java this will work directly, no other checks done at run time (and a compile time error if the type mismatches).
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  13. That's exactly what is said in the video
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  14.  @Maverick56912  Blasphemy!
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  15.  @LifeIsCrazyAsShit  I had this exact problem in a big table in MySQL several years ago. For example, doing SELECT whatever FROM table_name WHERE id > 433453 LIMIT 100 OFFSET 1000000; This killed the performance, because the id column was a clustered index (PRIMARY KEY). It knew to jump to that id immediately, but couldn't compute the offset and also do that jump directly, it had to go through all that one million rows/ids. So the higher the offset, the slower it ran (and that table had between 25 and 35 million rows). The job was to export basically the whole table, but in order, from where it left off. And we had small batches of exports. Once I changed the job to remember the last id, I changed the query to simply be SELECT whatever FROM table_name WHERE id > 124342343 LIMIT 100; And voila! the speed was back. No matter the id, if I was at the beggining, middle or end of the table, the query was fast, in constant time basically. So the lesson is - watch out when using OFFSET. Some indexes allow "jumping", but some don't, and in these cases, high offset values are a performance killer.
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