


How to Efficiently Construct a Tree Hierarchy from a Flat Table and Optimize its Storage in an RDBMS?
Jan 25, 2025 am 05:57 AM
Efficient and elegant data structure analysis
Suppose there is a flat data structure that contains columns such as 'ID', 'name', 'Parentid', and 'Order'. The goal is to efficiently build a tree structure. If only the basic data structures such as the array and hash table are available, an effective method includes:
- Create hash table:
- Initialize a hash table, the key is the 'ID' value, and the value is the corresponding 'name' value. Data table: For each line in the table, retrieve its 'ID' and 'Parentid' values, and add them to the hash table.
- Recursive build tree: Start with the root node ('parentid' to 0), and traverses the trees recursively. For each node, it has to check whether it has a sub -node by retrieve its 'ID' and obtain its name in the hash table.
- The result of assembly: When traversing the tree, the output format required for assembly (e.g., HTML or text).
- Optimize the storage of tree structures in RDBMS Although the flat surface structure mentioned in the problem is a common method, there are other methods that can optimize the tree storage in the relationship between the relationship:
The closure table explicitly stores each ancestor-offspring relationship. This allows the use of SQL to query the offspring or ancestors efficiently.
Example:
<.> 2. Embedding set:
The nested set is to allocate an integer range for each node in the tree. The scope interval defines the location of the node in the tree level structure.
Example:CREATE TABLE ClosureTable ( ancestor_id INT REFERENCES MyTable(id), descendant_id INT REFERENCES MyTable(id), PRIMARY KEY (ancestor_id, descendant_id) );
<:> Table:
<結(jié)> Tree structure:
<.> 3. Administration table:
The adjacent table shows the tree as a two -row table: ID and Parent_id. Each line represents a node, and the Parent_id column points to its parent node.
CREATE TABLE NestedSets ( id INT PRIMARY KEY, left_value INT, right_value INT );<示> Example:
The choice of tree storage optimization technology depends on factors such as data size, query mode and database performance requirements.
<code> |-----| [0, 9] |-----| | | | | |-----| |-----| |-----| | [0, 2] | | [4, 6] | | [8, 9] | | | | | | | |-----| |-----| |-----| |-----| | [0, 1] | | [2, 3] | | [4, 5] | | [6, 7] | | | | | | | | | | [0, 0] | | [2, 2] | | [4, 4] | | [6, 6] |</code>
additional problem: Yes, use the technology described above (closing table, nested, adjacent table), there is a fundamental better method to store the tree structure in RDBMS.
The above is the detailed content of How to Efficiently Construct a Tree Hierarchy from a Flat Table and Optimize its Storage in an RDBMS?. For more information, please follow other related articles on the PHP Chinese website!

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