SQL 이해 주요 개념 및 학습 경로

### SQL 마스터하기: 종합 가이드
* 📅 SQL은 **1970년에 발명**되어 **1986년 ANSI에 의해 표준화**되었으며, 관계형 데이터베이스에 널리 사용되는 언어입니다.
* 🔍 SQL 쿼리는 **작업(예: 선택, 업데이트), 열 사양, 테이블 참조 및 데이터 검색을 위한 조건**으로 구성됩니다.
* 📊 SQL 데이터베이스는 **CPU, 메모리, 스토리지를 추가하여 수직적으로 확장**할 수 있지만 복잡한 쿼리에는 추가적인 최적화 기술이 필요할 수 있습니다.
* 🔗 **보기를 사용하면 복잡한 쿼리를 추상화**하고 단순화하여 실행 및 유지 관리를 쉽게 할 수 있습니다.
* 💼 저장 프로시저를 사용하면 **여러 SQL 문을 순서대로 실행**할 수 있으며, 엔터프라이즈 환경에서 **트랜잭션 관리를 위해 자주 사용**됩니다.
* 🛠 최대 절전 모드와 같은 ORM(객체 관계 매핑) 프레임워크는 데이터베이스 상호 작용을 자동화할 수 있지만, **ORM을 사용하기 전에 SQL 쿼리를 마스터하는 것**이 좋습니다.
* 🔒 데이터 조작에 능숙해지려면 **SQL 쿼리 작성을 연습**하고 다양한 데이터베이스로 작업하는 것이 중요합니다.
* 💬 댓글로 좋아하는 데이터베이스와 SQL 모험을 공유하고, **Señor España의 더 많은 기술 콘텐츠**를 보려면 좋아요를 누르고 구독하는 것을 잊지 마세요.

SQL은 관계형 데이터베이스를 효과적으로 관리하고 쿼리할 수 있는 범용 언어입니다.

All right, let's go. It's time for a Señor España pop quiz. What do the enterprise databases like Oracle and IBM DB2 and Microsoft SQL server, developer databases like MySQL and Postgres, and even embedded databases like SQLLite, all have in common? Well, you're probably starting to Google right now, but let me just kill the suspense here. They have what's known as SQL in common. SQL stands for Structured Query Language. Now, a couple of quick facts about this particular language, which is used to process and deal with storing of data inside of relational databases. The first, it was invented, do a little 'I' there, invented in 1970. That is almost 54 years ago. Many, many moons before even I was even born. And then, roughly around 14 years later, it was made as a standard by the ANSI organization in 1986. Now, the big part about that is that it is a standard that everybody learns as a technology here.

And the cool thing about this is they made a way for all these databases to function by being able to store data in a table format. So you're going to have a series of rows and columns, and that is how you store your data. Now the second part about that is, the big part about SQL is how you compose these queries. And so because it's so portable, once you learn this language one time, you can use it across almost every relational database that actually functions off SQL, off this standard that's there. So let's break down the anatomy of a query, and then I'll give you some tips on how to kind of get started in your learning and really become an expert overnight. All right, the first is you're going to have the actual action of what you want to do. So it's going to start out with the insert, the update of whatever you want to do and, depending on what you're kind of going for, or a select if you want to read data out.

And then you're going to have either a wild card, which is saying, Give me everything from that particular column that I have, that row that I have, or you can specify the actual column names that you want. So, we'll just say col1, col2 ... you get the gist there. Next, you're going to say the From statement. So, you have to tell it, All right, I want data, I want to do this action, I want these particular columns. But where do I want to do it on? Well, it'll be the database name and the actual table that I want to do it from. Now, the last part of that is the where you have some condition that occurs. And that can be a filter based upon like I'll do a simple one like where ID = 1, a particular number, or you can do where some other condition, price > 50, whatever you're doing is really about being able to select the proper data.

out of your particular database. Now, so that you could do all these queries, they're very easy to do, and then you're going to have ways where you can actually escalate this, because these databases do hold quite a large amount of information or very, very capable. And their nature, they always scale kind of vertically, naturally, by adding more CPU, adding more memory, adding more storage to fulfill the needs that you need from that particular project that you're working on. But let's talk about a couple of other ways that you can go. Now, this is a very simple query, but it can get very complicated and very complex. Now, you can read any kind of guide on SQL online, and it will take you from this example to where you can actually write two of these statements and join data together from different tables. It's gets very exciting to work with. But as your queries get more and more complex, you're going to want to go across two different things that I want to discuss.

that should be top of mind when you want to do. The first is what we like to call a view. Now a view is a way to kind of abstract away the complexity of your particular query, where you can kind of alias it or just simplify it so it's easier to read, it's easier to execute, and it can be fine-tuned from there to work. So in this particular one, if I was doing, let's say we had books and authors, books in a table, we could say, Select my favorite books as the name of the view, but it actually has this particular context underneath the actual query. So in next, another enterprise, we start to get to that enterprise tier that I mentioned before. They'll have functionality called stored procedures. All right, so let's do the store procedures. So store procedures. We do a called stored proc and I've worked with this a lot, especially in Microsoft SQL server. So it is a way of having multiple statements that you want to execute in a row.

It can get as complex, so multiple operations that you want to do. It even has the capability to be able to pass in certain your variables and information that you want to serialize or hydrate this particular role of where they should execute. You'll find other things of doing transactions. And these are very good because they're able to process a series of actual queries. And if something goes wrong, I want you to roll them back, all right, to do all the data there. So, and then lastly, what I love to mention is I do want you to, after you kind of conquer a bit of these, and these are all dependent upon the actual data bases that you're using. I had my start in MySQL and Postgres. And then I started to work with a lot of enterprise databases where you had more of these particular enterprise features that you could kind of do, and you pick your database depending on the project that you want to do. But in today's world, you're going to kind of see this particular acronym a lot.

Which is Object Relational Mapping. So ORM, and there'll be a series of frameworks out there. Now, you're going to be confronted with that early in your education on SQL, but I highly recommend that you go through the basics first. Because what this is going to do is be able to say, you have, you mapped the context of your application, whatever kind of object that you're working with. So say, I was doing that, building that bookstore database with books and authors. So I can just say, books create many, or create one, all right? And depending on which database I use, it will actually, the ORM software framework will map to the syntax required for that particular destination database. And so it makes it very, very portable for me to go. And really obfuscates away the ability of writing queries. But I do, highly recommend that you get into the practice of writing queries first. Work your way up, work with different databases.

And then, depending on your project needs, the ORM layers do actually make the process of getting started with a project very, very fast because you don't have to spend time writing all those, but that's kind of the way I would definitely want you to learn, it's the way that I learned this, and become the expert that I am today. So, in conclusion, this is SQL. I want you to definitely put in the comments below your favorite database that you like to work with and some of your adventures around SQL. I want to see you hear about some of those crazy queries that you've written before. Until next time, technically yours, Señor España. If you like this video and want to see more like it, please like and subscribe. If you have any questions or want to share your thoughts about this topic, please leave a comment below.

What is SQL?

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데이터베이스에서 SQL의 공통점

엔터프라이즈, 개발자 및 임베디드 데이터베이스는 모두 SQL(구조화된 쿼리 언어)을 공통된 기능으로 공유합니다.

SQL은 1970년에 발명되어 1986년 ANSI에 의해 표준이 되었으며, 데이터를 테이블 형식으로 저장하는 일관된 방법을 제공합니다.

이 언어의 이식성을 통해 사용자는 다양한 관계형 데이터베이스에 자신의 지식을 적용할 수 있으므로 데이터 관리의 기본 기술이 됩니다.

SQL 쿼리는 와일드카드를 사용하거나 열 이름을 지정하는 옵션과 함께 데이터베이스에서 특정 열과 행을 선택하는 작업을 포함합니다.

또한 쿼리에는 데이터베이스와 테이블을 나타내는 From 문과 특정 조건에 따라 데이터를 필터링하는 Where 절이 필요합니다.

쿼리가 복잡해지면 서로 다른 테이블의 데이터를 조인해야 할 수 있으며 데이터베이스의 기능을 확장하기 위해 추가 리소스가 필요할 수 있습니다.

데이터베이스 주요 기능 뷰 및 저장 프로시저

뷰는 별칭이나 추상화를 제공하여 복잡한 쿼리를 간소화하여 읽고 실행하기 쉽게 만듭니다.

저장 프로시저를 사용하면 변수를 전달하고 트랜잭션을 관리하는 기능을 통해 여러 문을 연속으로 실행할 수 있습니다.

데이터베이스 선택은 프로젝트의 필요에 따라 달라지며, 엔터프라이즈 데이터베이스는 더 고급 기능을 제공합니다.

ORM(객체 관계형 매핑) 이해하기

ORM은 애플리케이션 객체를 데이터베이스 테이블에 매핑하여 데이터 관계를 더 쉽게 관리할 수 있도록 도와주는 프레임워크입니다.

다양한 데이터베이스의 구문에 맞게 조정하여 이식성을 제공합니다.

ORM을 사용하면 데이터 처리를 간소화하고 쿼리 작성을 난독화할 수 있지만, 먼저 SQL 쿼리 작성을 배우고 연습하는 것이 좋습니다.

프로젝트 개발에서 ORM 레이어의 이점

ORM 계층은 광범위한 코드를 작성할 필요가 없으므로 프로젝트 시작을 가속화합니다.

발표자는 SQL 학습의 중요성을 강조하고 시청자에게 댓글로 자신이 좋아하는 데이터베이스와 SQL 경험을 공유하도록 초대합니다.

이 동영상은 좋아요, 구독, 댓글을 통한 참여를 장려하여 추가 토론을 유도합니다.