How to store directory / hierarchy / tree structur

问题:

How do i store a directory / hierarchy / tree structure in the database? Namely MSSQL Server.

@olavk: Doesn't look like you've seen my own answer. The way i use is way better than recursive queries :)

p.p.s. This is the way to go!

回答1:

There are many ways to store hierarchies in SQL databases. Which one to choose depends on which DBMS product you use, and how the data will be used. As you have used the MSSQL2005 tag, I think you should start considering the "Adjacency List" model; if you find that it doesn't perform well for your application, then have a look at Vadim Tropashko's comparison which highlights differences between models with a focus on multiple performance characteristics.

回答2:

If using Sql Server 2008 is an option: maybe you should check out new hierarchyid data type.

回答3:

There also is the Nested-Set Model of Trees which has some advantages over the ParentID model. See http://www.evanpetersen.com/item/nested-sets.html and http://falsinsoft.blogspot.nl/2013/01/tree-in-sql-database-nested-set-model.html

回答4:

This is more of a bookmark for me than a question, but it might help you too. I've used this article's approach to store a directory / tree structure in the database.

There are some useful code snippets in the article as well.

Hope this helps.

I'm not affiliated with that website in any way

回答5:

Are you using SQL Server 2005? Recursive queries make querying hierarchical data much more elegant.

Edit: I do think materialized paths are a bit of a hack. The path contain non-normalized redundant data, and you have to use triggers or something to keep them updated. Eg. if a node changes parent, the whole subtree have to have their paths updated. And subtree queries have to use some ugly substring matching rather than an elegant and fast join.

回答6:

I faced the similar problem with one of my projects. We had a huge hierarchy which will keep increasing forever. I needed to traverse it fast and then finding the right group after some complex validations. Rather than going to SQL Server and scratching my head how can I do it efficiently there when I knew that Recursive queries are the only viable solution. But do you really know if there is any optimization at all possible in Recursive Queries. Is there any guarantee that your hierarchy will not increase in future and one fine day you find out that your recursive queries are too slow to be used in production?

So, I decided to give a shot to Neo4J. It's a graph database with many useful algorithms in-built, amazingly fast traversal with decent documentation and examples. Store the hierarchy in Neo4J and access hierarchy using a Thrift Service (or something else). Yes you will have to write code which will integrate your SQL queries with Neo4J but you will have a scalable and more future-proof solution.

Hope you find this useful.

回答7:

The question is similar to this question that was closed. I found answers to both questions very helpful in my pursuits, and they eventually led me to the MongoDB manual that presents 5 different ways to model tree structures: https://docs.mongodb.com/manual/applications/data-models-tree-structures/

While MongoDB is not a relational database, the models presented are applicable to relational databases, as well as other formats such as JSON. You clearly need to figure out which model is right based on the pros/cons presented.

The author of this question found a solution that combined both the Parent and Materialized Paths models. Maintaining the depth and parent could present some problems (extra logic, performance), but there are clearly upsides for certain needs. For my project, Materialized Paths will work best and I overcame some issues (sorting and path length) through techniques from this article.

回答8:

The typical way is a table with a foreign key (e.g. "ParentId") onto itself.