How Can We Efficiently Parse a Hierarchical Tree Structure from a Flat Table?

Efficiently parse tree structures from flat tables

The given flat table represents a hierarchical tree structure. In order to extract this tree efficiently, we will introduce several methods:

Array-based method:

1. Create an array using node IDs as keys and node objects as values.
2. Traverse the table rows and allocate node objects based on ParentId and Order.
3. Rebuild the tree by iteratively linking nodes to their parents.

Recursive SQL with path enumeration:

1. Traverse the tree using a recursive SQL query, starting from a node that has no parent (ParentId is null).
2. Use the dotted number naming convention in the Name column to track tree paths.

Nested set method:

1. Convert a flat table into a nested set structure by calculating the lvalue and rvalue of each node.
2. Query the tree using nested set operators to find ancestors, descendants, or other hierarchical relationships.

Closure table method:

1. Create a separate closure table to store all ancestor-descendant relationships.
2. Join a closure table with a flat table to obtain a hierarchical representation.
3. Filter the closure table to extract specific parts of the tree.

Conclusion:

Array-based methods provide a compact solution in memory, while recursive SQL provides a standard and efficient way to query hierarchies in the database. Nested sets and closure tables are more complex, but can handle tree structures with millions of entries. The choice of method depends on the size and structural requirements of the tree data.

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