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Hey, guys, what's going on?

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So we have talked about acid, the four properties in a theoretical manner, but it's time to put them

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in practice and explain those four properties in an actual database setting.

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So I'm going to pick this, but you can do the same exercise with any database you want for some.

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I would luck to use Docker because this way I can try out many, many databases with just one command

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and I have spit up another database just like that.

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So let's go ahead.

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And it's been a database right here.

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I've got to keep this up because I'm going to need that to a terminals, but I'm going to open up a

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new one right here.

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And let's do a little bit about Puskás Container going to Docker Run.

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Let's call it doctorand.

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Let's give it a name, dash, dash name is going to call it acid.

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It's got acid and we get to do we don't really need to expose the port or anything because we're going

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to really go into the container itself, bash into the container.

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The next command is let's go ahead and detach that and then let's pull up Puskás 13.

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I think that's the latest thing before we run that actually we forgot something very important, which

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is that she was Griss password equal postscripts.

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You have to give it pulseless user password as go go ahead and run that just like that is going to take

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a little bit while in your end to load the image.

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But once you have it, you're ready to rock and roll.

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Let's go ahead.

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And so so let's make sure that the container is running just like that.

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Yes.

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Here is my PJI acid.

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It's running.

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They always make sure that it's running because you might have spilled something in the command or did

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something bizarre or something is wrong.

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Right.

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So go ahead and do it and get it into the acid.

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And what can I do?

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We will execute a physical because of the PostgreSQL command.

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And I want to log in as Deshu that Posterous user that just like that, we are in the process commensal

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now.

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We can execute beautiful stuff.

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We can create a database, we can play that create tables.

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So since I am in the Postgres database, I have a database called Polska, so I'm going to play up with

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that database right there.

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Right.

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I was going to do create a table called Products to Test at Tomasetti and I'll go ahead and create table

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products.

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Let's do a PID serial.

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So that's a little increment in my school, I think it's called.

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And sure.

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Let's make this the primary key.

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And I think we can just continue doing that stuff right and then the online name as a text boom.

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What else price is double our shorts, double our Flodden because I keep forgetting in different databases.

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When you work on many databases, you get confused.

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And the finally is inventory.

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How much inventory do we have in this product?

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And let's just use an integer here.

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And that should be it.

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Yeah, that's what I thought.

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It's not called double.

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It's got to be flawed, I think.

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I think it's double in my school or I keep forgetting.

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All right, now we have a product sale, let's go ahead and create a sales table so we can produce sales.

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Great table sales.

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Let's go ahead and do a sale I.D. That's a cereal.

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Also primary key and enter the primary key.

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That's the product ID I can create as a foreign key, but doesn't have to.

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So that's an integer, right?

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That's a product I.D. to draw.

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Boom, price float.

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We learned our lesson, so that's an entry in the sales, could be a product, could be sold in a different

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price.

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Right.

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But the current price of the product is in the product table.

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This is what was sold.

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That and then the quantity as also an integer, a boob.

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All right.

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Now we have two beautiful tables let's test out at Tomasetti.

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So the first thing, listeners populate some some rows on this table.

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So I was going to do insert into products.

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And let's give it a name, I don't know what are we insert name and a prize and inventory or simply

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say, I'm just going to do it one one.

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Royo let's call this a table at tables.

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Very confusing phone selling phones.

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And the price of the phone is nine nine nine nine nine nine nine.

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That's an expensive phone inventory.

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Let's say you have hundred units, then boom.

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And then.

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That's it.

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That's the only product we have.

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OK, so now let's test out our Atomos City.

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So I mean, if we did select store for our products, you can see that we have this row.

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But we're going to do is we're going to make a sale.

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We're going to sell, let's say, 10 phones.

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Like we sold 10 phones.

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What does that mean?

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The fear of walking with Demand-Driven designed that is one has scribed, but it's in the database,

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it's broken into multiple queries in a single transaction, and so a sale is often units.

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That means you have to deduct 10 units from the inventory and then you have to insert a row in the sales

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table saying that you have inserted that you cannot do that.

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And two transaction, you have to do it in an atomic transaction.

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That's why we explained in the video the lecture.

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So we've got to begin a transaction.

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And then we're going to the first transaction we're going to do is update products, right?

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What was the phone idea?

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Let's just do from products you might want to query or process.

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Idea number one, processed product line number one.

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So we're going to do is update products.

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Set name.

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A bread product, set, inventory, inventory, equal inventory, minus 10.

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Well, that's in this transaction.

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So now if I query that product again, you can see it's 90, right?

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Very, very critical here.

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So now if I go ahead and insert.

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Let's assume.

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I crashed right here.

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If I crashed right here.

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What will happen, you just lost 10 units from your phones that you did a really sold OK, and that's

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the idea of atomistic because you have to follow it up.

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Right.

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So, like, let's say I crashed right here.

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I don't know, just this killed the whole container just like that.

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If you do that without automaticity, it will be a disaster if you come back to the database.

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And then you said select star from product and you saw that it's a 90, but no.

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It says hundred y.

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Because of animosity, we started a transaction, we did an update, but we crashed, we exited fossickers

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in this case simulating a crash, right.

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That is the idea of at the most of all, the transaction have to be done in as an attempt to split those

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and those do the transaction again in the right way.

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Again, transaction doing an update.

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To them, victory, and then now I'm going to insert a sale and certain the sales process ideia.

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Price and quantity, and let's just do values.

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Number one, I sold it and I thought I sold it at nine nine nine nine nine Sam Price, they sold 10

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units room.

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And you can break it out into five minutes at this price and five minutes at this price will not.

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And as we did of that, now, clearly the sale of Sable's you can see that we have 10 beautiful units

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right here and my products are 90.

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So now if you some of those puppies up.

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You get a hundred, and that's called consistency's.

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We just explained atomos and consistency and the same concept.

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And this is only viewable in my transaction.

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So now if I went to a completely different terminal and tried to query again, I'm not I'm not committing

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yet.

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Right.

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And I do like to do the same thing.

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Hopefully we got a school there, a big acid, then if I do select star from products, you can say

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they're still 100 and if you call it the sales, stable.

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There is nothing and that's part of isolation, because now we're we're in an atomic manner, so these

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two things were inserted in that transaction, but we didn't roll back or commit the moment I commit.

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Now, we have a nice view and out of the data and the data is now flushed and available, visible to

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all transaction.

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Now, if I created it again, you can see that we have a sales now zero.

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So that is one.

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And if you query the product table, you can see that's 90.

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So what I was to talk about here, talking about Midcity City, we talked about consistency because

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if you don't have to Midcity, you don't have consistency.

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And you can argue with that, obviously, guys, because you can say, hey, I can I can be smart and

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make a single query.

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Right.

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And I didn't for the longest time, Mongo DB, for example, didn't have Atomic City across documents.

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It has only atomos of the across a single document.

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And people are fine with that because most of the time they will do their data model so that it is a

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single document and instead of not, say, normalized like we do here.

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All right, let's jump into isolation.

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All right, guys, so I went ahead and inserted a few rows in the table that you don't have to see the

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process.

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I'm going to cut it out.

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It's a straightforward thing.

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We sold a couple of units it here, a couple of units right here.

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So now let's test out isolation and to decide isolation.

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Guys, I want to do the following.

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Right.

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So to this isolation, guys, I want to do the following just with normal transactions.

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I'm going to start a transaction in my first session right here.

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And I'm going to do a normal query saying select product and the count of the product.

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All right.

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I just want to see how how much sales did I made on getting our for each product from sales and group

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by group.

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If I do that all of a sudden now and this query, I have three sales for like two and three sales for

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product one, which is pretty good right now.

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I want to actually print the report that that shows that what are this list?

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Just the whole thing.

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So in order to do that, you do select product.

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Price, maybe you do a join, but we don't.

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We're not going to do that quantity from sales.

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Right.

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But before you going to execute that, you're going to execute at another session started right here.

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OK, and inserted a new sail, OK, you just inserted a new sail.

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Right, and you are just doing your own thing right here and generating this large report, but if you

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reach this stage and meanwhile think so, think of these two US as concurrent application transaction

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going at the same time.

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Someone is making a sale, someone is generating a report.

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So in the same time, I'm going to generate a new cell.

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Hey, we just sold a new phone, ram pedi.

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Analysts say price and quantity, home values.

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We sold the new iPhone.

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And at a price nine nine nine nine nine nine is just said, we sold 10 more phones and we also go ahead

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and update the products where sit.

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Quantity, quantity, no set inventory, equal inventory milestone where the equation because we just

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we just made etc. So we need to decrement and then what we did is we actually committed.

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We're done.

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We made us all.

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And we weren't back here.

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We're continuing to generate the report again, this is happening in parallel.

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I'm posing it just to show you.

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But this is now we made a sale and then you printed the record.

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So you printed that.

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You made three or three sales, three sales here.

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And then you made and then you actually printed that stuff.

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And guess what, guys?

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This don't match.

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You said that you and this happens a lot.

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Right.

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And actual companies, where were the actual table doesn't match the counts.

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And this happens if you do this kind of things.

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This I'm going to talk about.

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This is called isolation.

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Isolation.

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We're not fully isolated here.

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So when it will happen here, we printed this poppy.

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Right.

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And we said, OK, we made three phones, actually four phones and two and three ear buds.

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So the ear buds are correct, but the phones are not correct.

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You just produced an inconsistent.

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View, so inconsistency or consistency in general can happen because of animosity, which we explained

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and can also happen because of isolation, which is what I'm about to explain here.

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So how do I make sure that nobody.

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Touches my view when I am beginning my transaction, if I start in this transaction, I want you to

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give me a snapshot, right, of all the coins, and I'm going to do as if at the moment of the where

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the transaction started.

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And that's called a repeatable rate, so it's going to roll back this thing.

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And then we would begin a transaction, but we're going to do isolation level, repeatable rate.

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I think that's how you say the default was.

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Reid committed what that means.

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Anything that has been committed on other transaction, I, I can see it and this isolation level,

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Merks most of the time, sometimes in this case you don't want it, you don't want a repeat operator

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or serializable.

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So let's go ahead and start in a repeatable read.

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And now if I'm going to make my beautiful query, the count, hey, there are three and four, which

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is which is good.

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So we made four sales bad like that, but exclude the second query.

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Took away the sale, but in the meantime, someone started another transaction, we don't care what

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isolation level at that point where they.

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They inserted another.

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Sayle.

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Email, exactly.

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And they committed.

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So they just made it into the sale.

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What?

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If you query this.

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Notice that it didn't show up on your case here.

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Why?

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Because you're your isolation level prevents you from seeing stuff that other people's changing.

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That's that's a beautiful repeatably.

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It's expensive.

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You can understand how it works because it works at them like sea level.

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And Bosco's does it differently.

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Bicyclers and differently.

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SQL Server does it differently.

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Oracle does it exact very similar to bicycle bicycle.

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This is very similar to Oracle, if you want to be very precise.

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But that said, now, if you you have a consistent view, you made five sales technically on the iPhone.

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But if you query again that group by you only see four, you're in this other other query for other

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session.

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If you just select the ID count copied from what is that?

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So we have five units here.

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But here, no matter how many times you execute that, you're going to get a repeatable read your readers

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a repeatable.

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It's not going to change.

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And that's a very attractive feature for a lot of applications.

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Right.

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So now once you commit or roll back, you're done if you execute equity again.

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You see five because you're out of your transaction.

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All right, guys, that was isolation, finally for the fun of it.

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Let's do this, guys.

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Exit right here and then Dr..

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I'm going to do this, I'm going to begin a transaction, and then I'm going to insert a new product

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inserted to explain durability and that new product, and I'm going to prepare here to kill the content

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of the whole the whole container.

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You stop, right?

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But in the exact same second, I am going to insert a new sales and see if this is actually going to

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happen.

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If I say if it says commit, what will happen here.

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Name.

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Price inventory, yeah, that's just inserts a new product that's called.

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TV.

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Yeah, three thousand dollars and there is only 10 units of this, and I can do this and I'm going to

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commit, but at the same time we're going to kill the container.

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So immediately we were killed.

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So now.

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I want to know, did my TV get recorded that Postgres told us that it's committed, right?

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If I do this and a lot of their base doesn't support this, by the way, like this, but it is in the

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movie database.

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But it does support persistance, right?

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Essentially adorability is that means if you tell me that you committed something, that means if I

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00:20:31,050 --> 00:20:34,970
log in again, I better be there to see if it is out there.

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00:20:37,600 --> 00:20:44,230
Yup, it's right there because it told me it committed if if it didn't return the comment, that means

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it hasn't been written and durability is a very you might say you might think of it as like, OK, of

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course, Hosain, it's given that it has to be.

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If I write, something has to be there by noon, some is right to memory first for a performance reason

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and the container or the host dies, they forget to flash to disk.

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You just lost your stuff.

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But, guys, what do you think about this, guys?

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Thank you so much for watching.

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How fun.

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Enjoy the rest of the course that I'm going to see on the next one.

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Goodbye.