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    <p>Unfortunately, if you can't change the data model, and you're using MySQL, you're stuck in a situation where you need recursive queries and you're using a DBMS that doesn't support recursive queries.</p> <p>Quassnoi wrote an interesting series of blog articles, showing techniques for querying hierarchical data. His solutions are quite clever, but very complex. <a href="http://explainextended.com/2009/03/17/hierarchical-queries-in-mysql/" rel="nofollow noreferrer">http://explainextended.com/2009/03/17/hierarchical-queries-in-mysql/</a></p> <p>PostgreSQL is another open-source RDBMS, which does <a href="http://www.postgresql.org/docs/9.2/static/queries-with.html" rel="nofollow noreferrer">support recursive queries</a>, so you could fetch a whole tree stored in the way you show. But if you can't change the data model, I'd assume you can't switch to a different RDBMS.</p> <p>There are several alternative data models that make it much easier to fetch arbitrarily-deep trees:</p> <ul> <li><a href="https://stackoverflow.com/questions/192220/what-is-the-most-efficient-elegant-way-to-parse-a-flat-table-into-a-tree/192462#192462">Closure Table</a></li> <li>Nested Sets aka Modified Preorder Tree Traversal</li> <li>Path Enumeration aka Materialized Path</li> </ul> <p>I cover these in my presentation <a href="http://www.slideshare.net/billkarwin/models-for-hierarchical-data" rel="nofollow noreferrer">Models for Hierarchical Data with SQL and PHP</a>, and in my book <a href="http://pragprog.com/book/bksqla/sql-antipatterns" rel="nofollow noreferrer">SQL Antipatterns: Avoiding the Pitfalls of Database Programming</a>.</p> <p>Finally, there's another solution that I've seen used in the code for <a href="http://slashdot.org/" rel="nofollow noreferrer">Slashdot</a>, for their comments hierarchies: They store "parent_id" like in Adjacency List, but they also store a "root_id" column. Every member of a given tree has the same value for root_id, which is the highest ancestor node in its tree. Then it's easy to fetch a whole tree in one query:</p> <pre><code>SELECT * FROM site WHERE root_id = 123; </code></pre> <p>Then your application fetches all the nodes back from the database into an array, and you have to write the code to loop over this array, inserting the nodes into a tree data structure in memory. This is a good solution if you have many separate trees, and each tree has relatively few entries. It's good for Slashdot's case.</p>
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