And this can also be an additional headache if you try to parse SQL. They were added to perform complex elaborations on the data directly on the database, so they can be as powerful as traditional programming languages. These extensions are even more varied from database engine to database engine. SQL Procedural ExtensionsĪctual SQL implementations come with procedural extensions that implement some form of procedural programming. SQL is designed to handle many aspects of the life cycle of working with data: yes, you can query data, but you can also create the format of data (i.e., the schema of a table) and regulate access control to the data. This means that there is a very formal and clear description of the language if you need it. The language is an ISO/IEC standard that is periodically updated, the latest version is SQL2016. It has a formal mathematical foundation in relational algebra and calculus. It is a declarative language, so you describe what you want to achieve (e.g., get me a row of data with id=5) and not how to achieve it (e.g. SQL (Structured Query Language) is a domain-specific language designed to handle data in relational database. We are going to see ready-to-use libraries and tools to parse SQL, and an example project in which we will build our own SQL parser. That is what this article is about: parsing SQL. Then you need to parse SQL or to find a way to move from SQL world to your programming language world. And what happens if your application requires you to verify that something gets executed in a certain way, or to offer some guarantees? It can be a business need or a regulatory requirement. Even worse, they will not be very productive with it. However we can all agree that it is not a language that developers will love. Some can argue about that and in fact some people on Hacker News do that. SQL is an old language and not designed for large scale programming. SQL can also be a constraint, simply for what it lacks: unit testing integrated with your source code and all the other tools that you can use with Java, C#, etc. So you spend a lot of time working on glue code and around the limitations of SQL. In that case, you have some transformations done in SQL (and run on the database) and some others in your source code. It can also be a problem when you need to make transformations that SQL and your database cannot handle. For instance, if you need to change the database used by a large application. These issues became real problems when you need to make big changes. In some cases, you need a traditional programming language to work with the data you cannot do everything related to data in SQL.The SQLs implemented in SQLite, MySQL, PostgreSQL, etc. there is not one SQL, but many variations of it.What are the limits of SQL? After a while you learn of a couple of issues: And to do that, you need to parse SQL, and that is what this article is about. You might need to move from one SQL dialect to another one or to analyze the SQL code you use. This does not necessarily mean migrating away from SQL. However, it has limitations and when you hit them your only course of action might be to work with a traditional programming language. That is great because if you know SQL, you know how to handle data. It is in the same league of HTML: maybe you never learned it formally but you kind of know how to use it. In this article we will talk about parsing SQL. If you worked with data you have probably worked with SQL. SQL is a language to handle data in a relational database. The code for this tutorial is on GitHub: parsing-sql
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |