what if there were NO secondary keys?

Thank you so much. I love this video.

So cool! thank you so much for sharing!

Thank you so much for this video. Really high quliaty and direct to the point. Learned a lot!

AWESOME! thank you

Is there a quey return data like [posts => [ Post=> 'hello', User => [ Id=>6, Name=>'jack' ]] as this

maan! I just found this youtube channel, and I can say these 2 words about its content: Quality and Practicality!

MySQL returning same select query result from buffer, where there is update query parallelly executing from client application, how to prevent this, so i can get updated result from mysql?

Ok, but what if i some time need case sensitive and some time not?

One more issue, id is most of the times uuid

I really appreciate your efforts! Could you help me with something unrelated: I have a SafePal wallet with USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). What's the best way to send them to Binance?

If you're confused about what happens to the exercises table that I mentioned we'd want to move to the sharded keyspace, it's because I only address it in the "Avoiding cross-shard queries" video (my bad!). Because it's hard/impossible to find a Vindex that guarantees all rows for a users exercises and exercise logs are on the same shard, we're actually going to utilize Vitess reference tables for that one. It allows you to make a copy of the table on every shard. This is a great option for smaller relatively static tables, such as exercises.

I was trying to google how to pronounce paginate when I clicked on this LOL

Nice. I wonder what exercise made Lily feel great?

Free database hat to the first person to timestamp when you hear my toddler screaming in the background! 😭

Thanks for the video.

The update videos are really nice.

First

Postgres for everything

🎉🎉🎉❤❤❤

The first time I dealt with embedding was to build an app that allows you to chat with documents, I struggled to to get the results/answers properly formatted. Now, It seems easier for me to understand what's going on and I should revisit my code. Thanks Ben!

great teacher

Very Good Explaination

I never read about vector embedding but you explained the basics very easily.

great video !

I was a bit confused when I first read about Vector Embedding, now it's a little clearer. It's really funny how the most important point often comes in the next video. Thanks Ben!

Images not fitting into squares was just... aaaaaaaaa

Beautifully explained! I really appreciate it

What's that app he uses for the database?

Amazing video, Is it possible to handle datetime ragnes based on timezone. Timezones are my nightmare these days.

great video. learning from youtube is amazing BUT its all about finding the right video. this one has 58k views. should be way higher

So when?

Which work bench are you using???

what about joinning?

Unsigned int is perfekt

pgadmin is best for postgresql

So, by 2038, it will be YourSQL, no more mySQL 😂

Hey planetscale, Thanks for the vitess mysq series. If there is any document which are still basic, would be helpful

a very easy to understand explanation! thank you

6:09 not understand ? somebody can explain how does select count(1) from todos will execute or work ?

Come in just about time. I wanted to obtain the rows count before, and my approach was to get the ids of the last few rows haha

Your style of teaching is very unique!

I am learning to use vitess, which is very helpful to us.

Could you please explain what do you mean by "Scrolling and Throwing away that offset data". I believe you are talking at memory level things. It would be so helpful if you explain and show how pagination works at disk level,how pagination queries select data from disk partitiones stored in Binary tree format.

How to do join operations after vertical sharding?

how do we get the hostname

I have a question for you. I'm working with a table which has more than 3 billion rows and each month new 20-25 million rows are being added. And we have created 5 indexes for all efficient searching but when we access data for even a month it takes too long. And the recent data of the week access is good, the data is loaded fast ( here we also just access recent data for that month) but when our recent record touches more than 3-4 million rows after 4-5 days the quary again becomes very very slow? I'm thinking of creating a separate table for each year for balancing the load but I'm not able to understand why for 4-5 day of the start of the month it's working good but then after 4-5 million new rows it's becomes slow again. It's not making sense to me? Any suggestions will be really appreciated.

Hey, thanks for the walkthrough. Those anomalies detects similar latency issues. What’s different between the sort option in ran query table vs anomalies? Also does the anomalies detects some SQLi or any of similar things?

you video tutorial has been always informative, and instructive, really really appriciate

use configs can be bitmaps