What is the most efficient/elegant way to parse a flat table into a tree?
Assume you have a flat table that stores an ordered tree hierarchy:
Id Name ParentId Order
1 'Node 1' 0 10
2 'Node 1.1' 1 10
3 'Node 2' 0 20
4 'Node 1.1.1' 2 10
5 'Node 2.1' 3 10
6 'Node 1.2' 1 20
Here's a diagram, where we have [id] Name. Root node 0 is fictional.
[0] ROOT
/ \
[1] Node 1 [3] Node 2
/ \ \
[2] Node 1.1 [6] Node 1.2 [5] Node 2.1
/
[4] Node 1.1.1
What minimalistic approach would you use to output that to HTML (or text, for that matter) as a correctly ordered, correctly indented tree?
Assume further you only have basic data structures (arrays and hashmaps), no fancy objects with parent/children references, no ORM, no framework, just your two hands. The table is represented as a result set, which can be accessed randomly.
Pseudo code or plain English is okay, this is purely a conceptional question.
Bonus question: Is there a fundamentally better way to store a tree structure like this in a RDBMS?
EDITS AND ADDITIONS
To answer one commenter's (Mark Bessey's) question: A root node is not necessary, because it is never going to be displayed anyway. ParentId = 0 is the convention to express "these are top level". The Order column defines how nodes with the same parent are going to be sorted.
The "result set" I spoke of can be pictured as an array of hashmaps (to stay in that terminology). For my example was meant to be already there. Some answers go the extra mile and construct it first, but thats okay.
The tree can be arbitrarily deep. Each node can have N children. I did not exactly have a "millions of entries" tree in mind, though.
Don't mistake my choice of node naming ('Node 1.1.1') for something to rely on. The nodes could equally well be called 'Frank' or 'Bob', no naming structure is implied, this was merely to make it readable.
I have posted my own solution so you guys can pull it to pieces.
Answer
Now that MySQL 8.0 supports recursive queries, we can say that all popular SQL databases support recursive queries in standard syntax.
WITH RECURSIVE MyTree AS (
SELECT * FROM MyTable WHERE ParentId IS NULL
UNION ALL
SELECT m.* FROM MyTABLE AS m JOIN MyTree AS t ON m.ParentId = t.Id
)
SELECT * FROM MyTree;
I tested recursive queries in MySQL 8.0 in my presentation Recursive Query Throwdown in 2017.
Below is my original answer from 2008:
There are several ways to store tree-structured data in a relational database. What you show in your example uses two methods:
- Adjacency List (the "parent" column) and
- Path Enumeration (the dotted-numbers in your name column).
Another solution is called Nested Sets, and it can be stored in the same table too. Read "Trees and Hierarchies in SQL for Smarties" by Joe Celko for a lot more information on these designs.
I usually prefer a design called Closure Table (aka "Adjacency Relation") for storing tree-structured data. It requires another table, but then querying trees is pretty easy.
I cover Closure Table in my presentation Models for Hierarchical Data with SQL and PHP and in my book SQL Antipatterns: Avoiding the Pitfalls of Database Programming.
CREATE TABLE ClosureTable (
ancestor_id INT NOT NULL REFERENCES FlatTable(id),
descendant_id INT NOT NULL REFERENCES FlatTable(id),
PRIMARY KEY (ancestor_id, descendant_id)
);
Store all paths in the Closure Table, where there is a direct ancestry from one node to another. Include a row for each node to reference itself. For example, using the data set you showed in your question:
INSERT INTO ClosureTable (ancestor_id, descendant_id) VALUES
(1,1), (1,2), (1,4), (1,6),
(2,2), (2,4),
(3,3), (3,5),
(4,4),
(5,5),
(6,6);
Now you can get a tree starting at node 1 like this:
SELECT f.*
FROM FlatTable f
JOIN ClosureTable a ON (f.id = a.descendant_id)
WHERE a.ancestor_id = 1;
The output (in MySQL client) looks like the following:
+----+
| id |
+----+
| 1 |
| 2 |
| 4 |
| 6 |
+----+
In other words, nodes 3 and 5 are excluded, because they're part of a separate hierarchy, not descending from node 1.
Re: comment from e-satis about immediate children (or immediate parent). You can add a "path_length" column to the ClosureTable to make it easier to query specifically for an immediate child or parent (or any other distance).
INSERT INTO ClosureTable (ancestor_id, descendant_id, path_length) VALUES
(1,1,0), (1,2,1), (1,4,2), (1,6,1),
(2,2,0), (2,4,1),
(3,3,0), (3,5,1),
(4,4,0),
(5,5,0),
(6,6,0);
Then you can add a term in your search for querying the immediate children of a given node. These are descendants whose path_length is 1.
SELECT f.*
FROM FlatTable f
JOIN ClosureTable a ON (f.id = a.descendant_id)
WHERE a.ancestor_id = 1
AND path_length = 1;
+----+
| id |
+----+
| 2 |
| 6 |
+----+
Re comment from @ashraf: "How about sorting the whole tree [by name]?"
Here's an example query to return all nodes that are descendants of node 1, join them to the FlatTable that contains other node attributes such as name, and sort by the name.
SELECT f.name
FROM FlatTable f
JOIN ClosureTable a ON (f.id = a.descendant_id)
WHERE a.ancestor_id = 1
ORDER BY f.name;
Re comment from @Nate:
SELECT f.name, GROUP_CONCAT(b.ancestor_id order by b.path_length desc) AS breadcrumbs
FROM FlatTable f
JOIN ClosureTable a ON (f.id = a.descendant_id)
JOIN ClosureTable b ON (b.descendant_id = a.descendant_id)
WHERE a.ancestor_id = 1
GROUP BY a.descendant_id
ORDER BY f.name
+------------+-------------+
| name | breadcrumbs |
+------------+-------------+
| Node 1 | 1 |
| Node 1.1 | 1,2 |
| Node 1.1.1 | 1,2,4 |
| Node 1.2 | 1,6 |
+------------+-------------+
A user suggested an edit today. SO moderators approved the edit, but I am reversing it.
The edit suggested that the ORDER BY in the last query above should be ORDER BY b.path_length, f.name, presumably to make sure the ordering matches the hierarchy. But this doesn't work, because it would order "Node 1.1.1" after "Node 1.2".
If you want the ordering to match the hierarchy in a sensible way, that is possible, but not simply by ordering by the path length. For example, see my answer to MySQL Closure Table hierarchical database - How to pull information out in the correct order.