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Trees and Other Hierarchies in MySQL

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Trees and Other Hierarchies in MySQL

Graphs and SQL Edge list Edge-adjacency list model of a tree Automate tree drawing
Nested sets model of a tree Edge-list model of a network Parts explosions

Most non-trivial data is hierarchical. Customers have orders, which have lineitems, which refer to products, which have prices. Population samples have subjects, who take tests, which give results, which have sub-results and norms. Web sites have pages, which have links, which collect hits, which distribute across dates and times. With such data, we know the depth of the hierarchy before we sit down to write a query. The depth of the hierarchy of tables fixes the number of JOINs we need to write.

But if our data describes a family tree, or a browsing history, or a bill of materials,hierarchical depth depends on the data. We no longer know how many JOINs it will take to walk the tree. We need a different data model.

That model is the graph (Fig 1), which is a set of nodes(vertices) and the edges (lines or arcs) that connectthem. This chapter is about how to model and query graphs in a MySQL database.

Graph theory is a branch of topology. It is the study of geometric relations which aren't changed by stretching and compression—rubber sheet geometry, some call it. Graph theory is ideal for modelling hierarchies—like family trees, browsing histories, search trees and bills of materials—whose shape and size we can't know in advance.

Let the set of nodes in Fig 1 be N, the set of edges be L, and the graph be G. Then G is the tuple or ordered pair {N,L}:

    N = {A,B,C,D,E,F}    L = {AC,CD,CF,BE}    G = {N,L}

If the edges are directed, the graph is a digraph or directed graph. A mixed graph has both directed and undirected edges.

Examples of graphs are organisational charts; itineraries; route maps; parts explosions; massively multiplayer games; language rules; chat histories; network and link analysis in a wide variety of fields, for example search engines, forensics, epidemiology and telecommunications; data mining; models of chemical structure hierarchies; and biochemical processes.

Graph characteristics and models

Nodes and edges : Two nodes are adjacent if there is an edge between them. Two edges are adjacent if they connect to a common node. In a complete graph, all nodes are adjacent to all other nodes.

In a digraph, the number of edges entering a node is its indegree; the number leaving is its outdegree. A node of indegree zero is a root node, a node of outdegree zero is a leaf node.

In a weighted graph, used for example to solve the travelling salesman problem, edges have a weight attribute. A digraph with weighted edges is a network.

Paths and cycles: A connected sequence of edges is a path, its length the number of edges traversed. Two nodes are connected if there is a path between them. If there is a path connecting every pair of nodes, the graph is a connected graph.

A path in which no node repeats is a simple path. A path which returns to its own origin without crossing itself is a cycle or circuit. A graph with multiple paths between at least one pair of nodes is reconvergent. A reconvergent graph may be cyclic or acyclic. A unit length cycle is a loop.

If a graph's edges intersect only at nodes, it is planar. Two paths having no node in common are independent.

Traversing graphs: There are two main approaches, breadth-first and depth-first. Breadth-first traversal visits all a node's siblings before moving on to the next level, and typically uses a queue. Depth-first traversal follows edges down to leaves and back before proceeding to siblings, and typically uses a stack.

Sparsity: A graph where the size of E approaches the maximum N² is dense. When the multiple is much smaller than N, the graph is considered sparse.

Trees: A tree is a connected graph with no cycles. It is also a graph where the indegree of the root node is 0, and the indegree of every other node is 1. A tree where every node is of outdegree <=2 is a binary tree. A forest is a graph in which every connected component is a tree.

Euler paths: A path which traverses every edge in a graph exactly once is an Euler path. An Euler path which is a circuit is an Euler circuit.

If and only if every node of a connected graph has even degree, it has an Euler circuit (which is why the good people of Königsberg cannot go for a walk crossing each of their seven bridges exactly once). If and only if a connected graph has exactly 2 nodes with odd degree, it has a non-circuit Euler path. The degree of an endpoint of a non-cycle Euler path is 1 + twice thenumber of times the path passes through that node, so it is always odd.

Models for computing graphs

Traditionally, computer science textbooks have offered edge lists, adjacency lists and adjacency matrices as data structures for graphs, with algorithms implemented in languages like C, C++ and Java. More recently other models and tools have been suggested, including query languages customised for graphs.

Edge list: The simplest way to represent a graph is to list its edges: for Fig 1, the edge list is {AC,CD,CF,BE}. It is easy to add an edge to the list; deletion is a little harder.

Table 1
Nodes	Adjacent nodes
A	C
B	E
C	F,D,A
D	C
E	B
F	C

Adjacency list: An adjacency list is a ragged array: for each node it lists all adjacent nodes. Thus it represents a directed graph of n nodes as a list of n lists where list i contains node j if the graph has an edge from node i to node j.

An undirected graph may be represented by having node j in the list for node i, and node i in the list for node j. Table 1 shows the adjacency list of the graph in Fig 1 interpreted as undirected.

Adjacency matrix: An adjacency matrix represents a graph with n nodes as an n x n matrix, where the entry at (i,j) is 1 if there is an edge from node i to node j, or zero if there is not.

An adjacency matrix can represent a weighted graph using the weight as the entry, and can represent an undirected graph by using the same entry in both (i,j) and (j,i), or by using an upper triangular matrix.

There are useful glossaries here and here.

Graphs and SQL

Often standard SQL has been thought cumbersome for graph problems. Craig Mullins once wrote that "the set-based nature of SQL is not simple to master and is anathema to the OO techniques practiced by Java developers."

A few years after Mullins wrote that, SQL is everywhere, and it is increasingly applied to graph problems. DB2, Oracle and SQL Server have recursive operators for processing recursive sets, though they all work a little differently. MySQL has no such special tools, though the Open Query group has a graph engine under development. Meanwhile Joe Celko and Scott Stephens, among others, have published general SQL graph problem solutions that are simpler and smaller than equivalent C++, C# or Java code. Here we implement some of these ideas in MySQL.

Beware that in ports of edge list and adjacency list methods to SQL, there has been name slippage. What's often called the adjacency list model in the SQL world is actually an edge list model. If you follow the now-common practice in the SQL world of referring to edge lists as adjacency lists, don't be surprised to find that the model isn't quite like the adjacency list in Table 1. Here we waffle. We call them edge-adjacency lists.

There are also two newer kinds of models: what Joe Celko called the nested setsmodel—also known as the intervalmodel—which uses greater-than/less-than arithmetic to encode tree relationships and modified preorder tree traversal (MPTT) to query them, and Tropashko's materialised path model, where each node is stored with its (denormalised) path to the root. So we have four main possibilities for modelling graphs in MySQL:

edge-adjacency lists: based on an adaptation by EF Codd of the logic of linked lists to table structures and queries,
adjacency matrices,
nested sets for trees simplify some queries, but insertion and deletion are cumbersome, and
materialised paths.

Here we work out how to implement edge-adjacency, nested sets and materialised path models— or parts of them—in MySQL5&6.

The edge list

The edge list is the simplest possible representation of a graph: minimally, a single edges table where each row specifies one node and its parent (which is NULL for the root node), or more elaborately two tables, one for the nodes, the other a bridging table for their edges.

In the real world, the nodes table might be a table of personnel, orassembly parts, or locations on a map. It might have many other columms of data. The edges table might also have additional columns for edge properties. The key integers of both tables might be BIGINTs.

To model Fig 1, though, we keep things as simple as possible:

Listing 1CREATE TABLE nodes(  nodeID CHAR(1) PRIMARY KEY);CREATE TABLE edges(  childID CHAR(1) NOT NULL,  parentID CHAR(1) NOT NULL,  PRIMARY KEY(childID,parentID));INSERT INTO nodes VALUES('A'), ('B'), ('C'), ('D'), ('E'), ('F');INSERT INTO edges VALUES ('A','C'), ('C','D'), ('C','F'), ('B','E');SELECT * FROM edges;+---------+----------+| childID | parentID |+---------+----------+| A       | C        || B       | E        || C       | D        || C       | F        |+---------+----------+

Now, without any assumptions whatever about whether the graph is connected, whether it is directed, whether it is a tree, or whatever, how hard is it towrite a reachability procedure, a procedure which tells us where we can get to from here, wherever 'here' is?

A simple approach is a breadth-first search:

Seed the list with the starting node,
Add, but do not duplicate, nodes which are children of nodes in the list,
Add, but do not duplicate, nodes which are parents of nodes in the list,
Repeat steps 2 and 3 until there are no more nodes to add.

Here it is as a MySQL stored procedure. It avoids duplicate nodes by defining reached.nodeID as a primary key and adding reachable nodes with INSERT IGNORE:

Listing 2DROP PROCEDURE IF EXISTS ListReached;DELIMITER goCREATE PROCEDURE ListReached( IN root CHAR(1) )BEGIN  DECLARE rows SMALLINT DEFAULT 0;  DROP TABLE IF EXISTS reached;  CREATE TABLE reached (    nodeID CHAR(1) PRIMARY KEY  ) ENGINE=HEAP;  INSERT INTO reached VALUES (root );  SET rows = ROW_COUNT();  WHILE rows > 0 DO    INSERT IGNORE INTO reached      SELECT DISTINCT childID      FROM edges AS e      INNER JOIN reached AS p ON e.parentID = p.nodeID;    SET rows = ROW_COUNT();    INSERT IGNORE INTO reached      SELECT DISTINCT parentID      FROM edges AS e      INNER JOIN reached AS p ON e.childID = p.nodeID;    SET rows = rows + ROW_COUNT();  END WHILE;  SELECT * FROM reached;  DROP TABLE reached;END;goDELIMITER ;CALL ListReached('A');+--------+| nodeID |+--------+| A      || C      || D      || F      |+--------+

To make the procedure more versatile, give it input parameters which tell it whether to list child, parent or all connections, and whether to recognise loops (for example C to C).

To give the model referential integrity, use InnoDB and make edges.childID and edges.parentID foreign keys. To add or delete a node, add or delete desired single rows in nodes and edges. To change an edge, edit it. The model does not require the graph to be connected or treelike, and does not presume direction.

The edge list is basic to what SQLers often call the adjacency list model.

Edge-adjacency list model of a tree

Writers in the SQL graph literature often give solutions using single denormalised tables.Denormalisation can cost, big time. The bigger the table, the bigger the cost. You cannot edit nodes and edges separately. Carrying extra node information during edge computation slows performance. With nodes and edges denormalised to one table, you have to represent the root node with a NULL.

To avoid these difficulties, normalise trees like William Shakespeare's family tree (Fig 2) with two tables, a nodes table (family) containing information about individuals, and an edges table (familytree)with a row for each parent-child link or edge. Later, when we use a different tree model, we won't have to mess with the data being modelled.

Listing 3-- Base data:CREATE TABLE family (  ID smallint(6) PRIMARY KEY AUTO_INCREMENT,  name char(20) default '',  siborder tinyint(4) default NULL,  born smallint(4) unsigned default NULL,  died smallint(4) unsigned default NULL);INSERT INTO family VALUES (1, 'Richard Shakespeare', NULL, NULL, 1561);INSERT INTO family VALUES (2, 'Henry Shakespeare', 1, NULL, 1569);INSERT INTO family VALUES (3, 'John Shakespeare', 2, 1530, 1601);INSERT INTO family VALUES (4, 'Joan Shakespeare', 1, 1558, NULL);INSERT INTO family VALUES (5, 'Margaret Shakespeare', 2, 1562, 1563);INSERT INTO family VALUES (6, 'William Shakespeare', 3, 1564, 1616);INSERT INTO family VALUES (7, 'Gilbert Shakespeare', 4, 1566, 1612);INSERT INTO family VALUES (8, 'Joan Shakespeare', 5, 1568, 1646);INSERT INTO family VALUES (9, 'Anne Shakespeare', 6, 1571, 1579);INSERT INTO family VALUES (10, 'Richard Shakespeare', 7, 1574, 1613);INSERT INTO family VALUES (11, 'Edmond Shakespeare', 8, 1580, 1607);INSERT INTO family VALUES (12, 'Susana Shakespeare', 1, 1583, 1649);INSERT INTO family VALUES (13, 'Hamnet Shakespeare', 1, 1585, 1596);INSERT INTO family VALUES (14, 'Judith Shakespeare', 1, 1585, 1662);INSERT INTO family VALUES (15, 'William Hart', 1, 1600, 1639);INSERT INTO family VALUES (16, 'Mary Hart', 2, 1603, 1607);INSERT INTO family VALUES (17, 'Thomas Hart', 3, 1605, 1670);INSERT INTO family VALUES (18, 'Michael Hart', 1, 1608, 1618);INSERT INTO family VALUES (19, 'Elizabeth Hall', 1, 1608, 1670);INSERT INTO family VALUES (20, 'Shakespeare Quiney', 1, 1616, 1617);INSERT INTO family VALUES (21, 'Richard Quiney', 2, 1618, 1639);INSERT INTO family VALUES (22, 'Thomas Quiney', 3, 1620, 1639);INSERT INTO family VALUES (23, 'John Bernard', 1, NULL, 1674);-- Table which models the tree:CREATE TABLE familytree (  childID smallint NOT NULL,  parentID smallint NOT NULL,  PRIMARY KEY (childID, parentID););INSERT INTO familytree VALUES  (2, 1), (3, 1), (4, 2), (5, 2), (6, 2), (7, 2), (8, 2), (9, 2),  (10, 2), (11, 2), (12, 6), (13, 6), (14, 6), (15, 8), (16, 8),  (17, 8), (18, 8), (19, 12), (20, 14), (21, 14), (22, 14), (23, 19);

(The family PK is auto-increment, but the listing is more reader-friendly when the ID values are shown.)

It will be useful to have a function that returns family.name for a parent or child ID in familytree:

Listing 4-- 5.0.16 OR LATER:SET GLOBAL log_bin_trust_function_creators=TRUE;DROP FUNCTION IF EXISTS PersonName;DELIMITER goCREATE FUNCTION PersonName( personID SMALLINT )RETURNS CHAR(20)BEGIN  DECLARE pname CHAR(20) DEFAULT '';  SELECT name INTO pname FROM family WHERE ID=personID;  RETURN pname;END;goDELIMITER ;SELECT PersonName( parentID ) AS 'Parent of William'FROM familytreeWHERE childID = 6;+-------------------+| Parent of William |+-------------------+| Henry Shakespeare |+-------------------+SELECT PersonName( childID ) AS 'Children of William'FROM familytreeWHERE parentID = ( SELECT ID FROM family WHERE name = 'William Shakespeare' );+---------------------+| Children of William |+---------------------+| Susana Shakespeare  || Hamnet Shakespeare  || Judith Shakespeare  |+---------------------+SELECT PersonName(childID) AS child, PersonName(parentID) AS parentFROM familytree;+----------------------+---------------------+| child                | parent              |+----------------------+---------------------+| Henry Shakespeare    | Richard Shakespeare || John Shakespeare     | Richard Shakespeare || Joan Shakespeare     | Henry Shakespeare   || Margaret Shakespeare | Henry Shakespeare   || William Shakespeare  | Henry Shakespeare   || Gilbert Shakespeare  | Henry Shakespeare   || Joan Shakespeare     | Henry Shakespeare   || Anne Shakespeare     | Henry Shakespeare   || Richard Shakespeare  | Henry Shakespeare   || Edmond Shakespeare   | Henry Shakespeare   || Susana Shakespeare   | William Shakespeare || Hamnet Shakespeare   | William Shakespeare || Judith Shakespeare   | William Shakespeare || William Hart         | Joan Shakespeare    || Mary Hart            | Joan Shakespeare    || Thomas Hart          | Joan Shakespeare    || Michael Hart         | Joan Shakespeare    || Elizabeth Hall       | Susana Shakespeare  || Shakespeare Quiney   | Judith Shakespeare  || Richard Quiney       | Judith Shakespeare  || Thomas Quiney        | Judith Shakespeare  || John Bernard         | Elizabeth Hall      |+----------------------+---------------------+

A same-table foreign key can simplify tree maintenance:

Listing 4acreate table edges (   ID int PRIMARY KEY, 	parentid int,   foreign key(parentID) references edges(ID) ON DELETE CASCADE ON UPDATE CASCADE) engine=innodb; insert into edges(ID,parentID) values (1,null),(2,1),(3,1),(4,2);select * from edges;+----+----------+| ID | parentid |+----+----------+|  1 |     NULL ||  2 |        1 ||  3 |        1 ||  4 |        2 |+----+----------+delete from edges where id=2;select * from edges;+----+----------+| ID | parentid |+----+----------+|  1 |     NULL ||  3 |        1 |+----+----------+

Simple queries retrieve basic facts about the tree, for example GROUP_CONCAT() collects parent nodes with their children in correct order:

Listing 5SELECT parentID AS Parent, GROUP_CONCAT(childID ORDER BY siborder) AS ChildrenFROM familytree tJOIN family f ON t.parentID=f.ID GROUP BY parentID;+--------+-------------------+| Parent | Children          |+--------+-------------------+|      1 | 3,2               ||      2 | 4,5,6,7,8,9,10,11 ||      6 | 12,13,14          ||      8 | 18,17,16,15       ||     12 | 19                ||     14 | 22,21,20          ||     19 | 23                |+--------+-------------------+

Iterate over those comma-separated lists with a bit of application code and you have a hybrid treewalk. The paterfamilias is the root node, individuals with no children are the leaf nodes, and queries to retrieve subtree statistics are straightforward:

Listing 6SELECT  PersonName(ID) AS Paterfamilias,  IFNULL(born,'?') AS Born,  IFNULL(died,'?') AS DiedFROM family AS fLEFT JOIN familytree AS t ON f.ID=t.childIDWHERE t.childID IS NULL;+---------------------+------+------+| Paterfamilias       | Born | Died |+---------------------+------+------+| Richard Shakespeare | ?    | 1561 |+---------------------+------+------+SELECT  PersonName(ID) AS Childless,  IFNULL(born,'?') AS Born,  IFNULL(died,'?') AS DiedFROM family AS fLEFT JOIN familytree AS t ON f.ID=t.parentIDWHERE t.parentID IS NULL;+----------------------+------+------+| Childless            | Born | Died |+----------------------+------+------+| John Shakespeare     | 1530 | 1601 || Joan Shakespeare     | 1558 | ?    || Margaret Shakespeare | 1562 | 1563 || Gilbert Shakespeare  | 1566 | 1612 || Anne Shakespeare     | 1571 | 1579 || Richard Shakespeare  | 1574 | 1613 || Edmond Shakespeare   | 1580 | 1607 || Hamnet Shakespeare   | 1585 | 1596 || William Hart         | 1600 | 1639 || Mary Hart            | 1603 | 1607 || Thomas Hart          | 1605 | 1670 || Michael Hart         | 1608 | 1618 || Shakespeare Quiney   | 1616 | 1617 || Richard Quiney       | 1618 | 1639 || Thomas Quiney        | 1620 | 1639 || John Bernard         | ?    | 1674 |+----------------------+------+------+SELECT ROUND(AVG(died-born),2) AS 'Longevity of the childless'FROM family AS fLEFT JOIN familytree AS t ON f.ID=t.parentIDWHERE t.parentID IS NULL;+----------------------------+| Longevity of the childless |+----------------------------+|                      25.86 |+----------------------------+

In striking contrast with Celko's nested sets model, inserting a new item in this model requires no revision ofexisting rows. We just add a new family row, then a new familytree row with IDs specifying who is parent to whom. Deletion is also a two-step: delete the familytree row for that child-parent link, then delete the family row for that child.

Walking an edge list tree

Traversing subtrees is what gives the edge-adjacency list model its reputation for difficulty. Wecan't know in advance, except in the simplest of trees, how many levels of parent and childhave to be queried, so we need recursion or a logically equivalent loop.

It's a natural problem for a stored procedure. Earlier editions showed a brute force breadth-firstalgorithm that needed three intermediary tables (it can be found in Appendix E). Here is a simpler algorithm thatjust seeds a result table with first-found parent-child pairs, then uses MySQL’s INSERT IGNORE to add remaining pairs:

Listing 7DROP PROCEDURE IF EXISTS famsubtree;DELIMITER goCREATE PROCEDURE famsubtree( root INT )BEGIN  DROP TABLE IF EXISTS famsubtree;  CREATE TABLE famsubtree    SELECT childID, parentID, 0 AS level    FROM familytree    WHERE parentID = root;  ALTER TABLE famsubtree ADD PRIMARY KEY(childID,parentID);  REPEAT    INSERT IGNORE INTO famsubtree      SELECT f.childID, f.parentID, s.level+1      FROM familytree AS f      JOIN famsubtree AS s ON f.parentID = s.childID;  UNTIL Row_Count() = 0 END REPEAT;END ;goDELIMITER ;call famsubtree(1);       -- from the root you can see foreverSELECT Concat(Space(level),parentID) AS Parent, Group_Concat(childID ORDER BY childID) AS ChildFROM famsubtreeGROUP BY parentID;+--------+-------------------+| Parent | Child             |+--------+-------------------+| 1      | 2,3               ||  2     | 4,5,6,7,8,9,10,11 ||   6    | 12,13,14          ||   8    | 15,16,17,18       ||    12  | 19                ||    14  | 20,21,22          ||     19 | 23                |+--------+-------------------+

Simple and quick. The logic ports to any edge list. We can prove that right now by writing a generic version.GenericTree() just needs parameters for the name of the target table, the names of its child and parent ID columns,and the parent ID whose descendants are sought:

Listing 7a: General-purpose edge list tree walkerDROP PROCEDURE IF EXISTS GenericTree;DELIMITER goCREATE PROCEDURE GenericTree(  edgeTable CHAR(64), edgeIDcol CHAR(64), edgeParentIDcol CHAR(64), ancestorID INT)BEGIN  DECLARE r INT DEFAULT 0;  DROP TABLE IF EXISTS subtree;  SET @sql = Concat( 'CREATE TABLE subtree ENGINE=MyISAM SELECT ',                     edgeIDcol,' AS childID, ',                     edgeParentIDcol, ' AS parentID,',                     '0 AS level FROM ',                     edgeTable, ' WHERE ', edgeParentIDcol, '=', ancestorID );  PREPARE stmt FROM @sql;  EXECUTE stmt;  DROP PREPARE stmt;  ALTER TABLE subtree ADD PRIMARY KEY(childID,parentID);  REPEAT    SET @sql = Concat( 'INSERT IGNORE INTO subtree SELECT a.', edgeIDcol,                       ',a.',edgeparentIDcol, ',b.level+1 FROM ',                       edgeTable, ' AS a JOIN subtree AS b ON a.',edgeParentIDcol, '=b.childID' );    PREPARE stmt FROM @sql;    EXECUTE stmt;    SET r=Row_Count();  -- save row_count() result before DROP PREPARE loses the value    DROP PREPARE stmt;  UNTIL r < 1 END REPEAT;END ;goDELIMITER ;

To retrieve details like names and other data associated with node IDs, write a frontend query to join the subtree result tablewith the required detail table(s), for example:

CALL GenericTree('familytree','childID','parentID',1);SELECT Concat(Repeat( ' ', s.level), a.name ) AS Parent, b.name AS ChildFROM subtree sJOIN family a ON s.parentID=a.IDJOIN family b ON s.childID=b.ID;+-----------------------+----------------------+| Parent                | Child                |+-----------------------+----------------------+| Richard Shakespeare   | Henry Shakespeare    || Richard Shakespeare   | John Shakespeare     ||  Henry Shakespeare    | Joan Shakespeare     ||  Henry Shakespeare    | Margaret Shakespeare ||  Henry Shakespeare    | William Shakespeare  ||  Henry Shakespeare    | Gilbert Shakespeare  ||  Henry Shakespeare    | Joan Shakespeare     ||  Henry Shakespeare    | Anne Shakespeare     ||  Henry Shakespeare    | Richard Shakespeare  ||  Henry Shakespeare    | Edmond Shakespeare   ||   William Shakespeare | Susana Shakespeare   ||   William Shakespeare | Hamnet Shakespeare   ||   William Shakespeare | Judith Shakespeare   ||   Joan Shakespeare    | William Hart         ||   Joan Shakespeare    | Mary Hart            ||   Joan Shakespeare    | Thomas Hart          ||   Joan Shakespeare    | Michael Hart         ||    Susana Shakespeare | Elizabeth Hall       ||    Judith Shakespeare | Shakespeare Quiney   ||    Judith Shakespeare | Richard Quiney       ||    Judith Shakespeare | Thomas Quiney        ||     Elizabeth Hall    | John Bernard         |+-----------------------+----------------------+

Is GenericTree() fast? You bet. On standard hardware it processes a 5,000-node tree in less than 0.5 secs—much fasterthan a comparable nested sets query on the same tree! It has no serious scaling issues. And its logic can be used to prune: call GenericTree() then delete the listed rows. Better still, write a generic tree pruner from Listing 7a and aDELETE command. To insert a subtree, prepare a table of new rows, point its top edge at an existing node as parent, and INSERT it.

The edge list treewalk is logically recursive, so how about coding it recursively? Here is a recursive depth-firstPHP treewalk for the familytree and family tables:

Listing 7b: Recursive edge list subtree in PHP$info = recursivesubtree( 1, $a = array(), 0 );foreach( $info as $row )  echo str_repeat( " ", 2*$row[4] ), ( $row[3] > 0 ) ? "{$row[1]}" : $row[1], "
";function recursivesubtree( $rootID, $a, $level ) {  $childcountqry = "(SELECT COUNT(*) FROM familytree WHERE parentID=t.childID) AS childcount";  $qry = "SELECT t.childid,f.name,t.parentid,$childcountqry,$level " .         "FROM familytree t JOIN family f ON t.childID=f.ID " .         "WHERE parentid=$rootID ORDER BY childcount<>0,t.childID";  $res = mysql_qry( $qry );  while( $row = mysql_fetch_row( $res )) {    $a[] = $row;    if( $row[3] > 0 ) $a = recursivesubtree( $row[0], $a, $level+1 );    // down before right  }  return $a;}

A query with a subquery, a fetch loop, and a recursive call--that's all thereis to it. A nice feature of this algorithm is that it writes result rows in display-ready order.To port this to MySQL, you must have set maximum recursion depth in my.cnf/inior in your client:

Listing 7c: Recursive edge list subtree in MySQLSET @@SESSION.max_sp_recursion_depth=25;DROP PROCEDURE IF EXISTS recursivesubtree;DELIMITER goCREATE PROCEDURE recursivesubtree( iroot INT, ilevel INT )BEGIN  DECLARE irows,ichildid,iparentid,ichildcount,done INT DEFAULT 0;  DECLARE cname VARCHAR(64);  SET irows = ( SELECT COUNT(*) FROM familytree WHERE parentID=iroot );  IF ilevel = 0 THEN    DROP TEMPORARY TABLE IF EXISTS _descendants;    CREATE TEMPORARY TABLE _descendants (      childID INT, parentID INT, name VARCHAR(64), childcount INT, level INT  );  END IF;  IF irows > 0 THEN    BEGIN      DECLARE cur CURSOR FOR        SELECT          childid,parentid,f.name,          (SELECT COUNT(*) FROM familytree WHERE parentID=t.childID) AS childcount        FROM familytree t JOIN family f ON t.childID=f.ID        WHERE parentid=iroot        ORDER BY childcount<>0,t.childID;      DECLARE CONTINUE HANDLER FOR SQLSTATE '02000' SET done = 1;      OPEN cur;      WHILE NOT done DO        FETCH cur INTO ichildid,iparentid,cname,ichildcount;        IF NOT done THEN          INSERT INTO _descendants VALUES(ichildid,iparentid,cname,ichildcount,ilevel );          IF ichildcount > 0 THEN            CALL recursivesubtree( ichildid, ilevel + 1 );          END IF;        END IF;      END WHILE;      CLOSE cur;    END;  END IF;  IF ilevel = 0 THEN    -- Show result table headed by name that corresponds to iroot:    SET cname = (SELECT name FROM family WHERE ID=iroot);    SET @sql = CONCAT('SELECT CONCAT(REPEAT(CHAR(32),2*level),IF(childcount,UPPER(name),name))',                      ' AS ', CHAR(39),'Descendants of ',cname,CHAR(39),' FROM _descendants');    PREPARE stmt FROM @sql;    EXECUTE stmt;    DROP PREPARE stmt;  END IF;END;goDELIMITER ;CALL recursivesubtree(1,0);+------------------------------------+| Descendants of Richard Shakespeare |+------------------------------------+| HENRY SHAKESPEARE                  ||   Joan Shakespeare                 ||   Margaret Shakespeare             ||   WILLIAM SHAKESPEARE              ||     SUSANA SHAKESPEARE             ||       ELIZABETH HALL               ||         John Bernard               ||     Hamnet Shakespeare             ||     JUDITH SHAKESPEARE             ||       Shakespeare Quiney           ||       Richard Quiney               ||       Thomas Quiney                ||   Gilbert Shakespeare              ||   JOAN SHAKESPEARE                 ||     William Hart                   ||     Mary Hart                      ||     Thomas Hart                    ||     Michael Hart                   ||   Anne Shakespeare                 ||   Richard Shakespeare              ||   Edmond Shakespeare               || John Shakespeare                   |+------------------------------------+

In MySQL this recursive treewalk can be up to 100 times slower than GenericTree(). Its slowness is comparable to that of a MySQL versionof Kendall Willet's depth-first edge list subtree algorithm:

Listing 7d: Depth-first edge list subtreeCREATE PROCEDURE depthfirstsubtree( iroot INT )BEGIN  DECLARE ilastvisited, inxt, ilastord INT;  SET ilastvisited = iroot;  SET ilastord = 1;  DROP TABLE IF EXISTS descendants;  CREATE TABLE descendants SELECT childID,parentID,-1 AS ord FROM familytree;  UPDATE descendants SET ord=1 WHERE childID=iroot;  this: LOOP    SET inxt = NULL;    SELECT MIN(childID) INTO inxt FROM descendants   -- go down    WHERE parentID = ilastvisited AND ord = -1 ;    IF inxt IS NULL THEN                             -- nothing down, so go right      SELECT MIN(d2.childID) INTO inxt      FROM descendants d1      JOIN descendants d2 ON d1.parentID = d2.parentID AND d1.childID < d2.childID      WHERE d1.childID = ilastvisited;    END IF;    IF inxt IS NULL THEN                             -- nothing right. so go up      SELECT parentID INTO inxt FROM descendants      WHERE childID = ilastvisited AND parentID IS NOT NULL;    END IF;    UPDATE descendants SET ord = ilastord + 1    WHERE childID = inxt AND ord = -1;    IF ROW_COUNT() > 0 THEN      SET ilastord = ilastord + 1;    END IF;    IF inxt IS NULL THEN      LEAVE this;    END IF;    SET ilastvisited = inxt;  END LOOP;END;

One reason Willet's is slower is that MySQL does not permit multiple references to a temporary table in a query. When all algorithms are denied temp tables, though,this algorithm is still slower than recursion, and both are much slower than GenericTree().

Edge list subtree queries perform faster and are easier to write than their reputationsuggests. And edge tables are flexible. For a tree describing a parts explosion rather than a family, just add columns for weight, quantity, assembly time, cost, price and so on. Reports need only aggregate column values and sums. We'll revisit this near the end of the chapter.

Enumerating paths in an edge-adjacency list

Path enumeration in an edge list tree is almost as easy as depth-first subtree traversal:

create a table for paths,
seed it with paths of unit length from the tree table,
iteratively add paths till there are no more to add.

MySQL's INSERT IGNORE command simplifies the code by removing the need for a NOT EXISTS(...) clause in the INSERT ... SELECT statement. Since adjacencies are logically symmetrical, we make path direction the caller's choice, UP or DOWN:

Listing 8DROP PROCEDURE IF EXISTS ListAdjacencyPaths;DELIMITER goCREATE PROCEDURE ListAdjacencyPaths( IN direction CHAR(5) )BEGIN  DROP TABLE IF EXISTS paths;  CREATE TABLE paths(    start SMALLINT,    stop SMALLINT,    len SMALLINT,    PRIMARY KEY(start,stop)  ) ENGINE=HEAP;  IF direction = 'UP' THEN    INSERT INTO paths      SELECT childID,parentID,1      FROM familytree;  ELSE    INSERT INTO paths      SELECT parentID,childID,1      FROM familytree;  END IF;  WHILE ROW_COUNT() > 0 DO    INSERT IGNORE INTO paths      SELECT DISTINCT        p1.start,        p2.stop,        p1.len + p2.len      FROM paths AS p1 INNER JOIN paths AS p2 ON p1.stop = p2.start;  END WHILE;  SELECT start, stop, len  FROM paths  ORDER BY start, stop;  DROP TABLE paths;END;goDELIMITER ;

To find the paths from just one node, seed the paths table with paths from the starting node, then iteratively search a JOIN of familytree and paths for edges which will extend existing paths in the user-specified direction:

Listing 8aDROP PROCEDURE IF EXISTS ListAdjacencyPathsOfNode;DELIMITER goCREATE PROCEDURE ListAdjacencyPathsOfNode( IN node SMALLINT, IN direction CHAR(5) )BEGIN  TRUNCATE paths;  IF direction = 'UP' THEN    INSERT INTO paths      SELECT childID,parentID,1      FROM familytree      WHERE childID = node;  ELSE    INSERT INTO paths      SELECT parentID,childID,1      FROM familytree      WHERE parentID = node;  END IF;  WHILE ROW_COUNT() > 0 DO    IF direction = 'UP' THEN      INSERT IGNORE INTO paths        SELECT DISTINCT          paths.start,          familytree.parentID,          paths.len + 1        FROM paths          INNER JOIN familytree ON paths.stop = familytree.childID;    ELSE      INSERT IGNORE INTO paths        SELECT DISTINCT          paths.start,          familytree.childID,          paths.len + 1        FROM paths          INNER JOIN familytree ON paths.stop = familytree.parentID;    END IF;  END WHILE;    SELECT start, stop, len    FROM paths    ORDER BY start, stop;END;goDELIMITER ;CALL ListAdjacencyPathsOfNode(1,'DOWN');+-------+------+------+| start | stop | len  |+-------+------+------+|     1 |    2 |    1 ||     1 |    3 |    1 ||     1 |    4 |    2 ||     1 |    5 |    2 ||     1 |    6 |    2 ||     1 |    7 |    2 ||     1 |    8 |    2 ||     1 |    9 |    2 ||     1 |   10 |    2 ||     1 |   11 |    2 ||     1 |   12 |    3 ||     1 |   13 |    3 ||     1 |   14 |    3 ||     1 |   15 |    3 ||     1 |   16 |    3 ||     1 |   17 |    3 ||     1 |   18 |    3 ||     1 |   19 |    4 ||     1 |   20 |    4 ||     1 |   21 |    4 ||     1 |   22 |    4 ||     1 |   23 |    5 |+-------+------+------+

These algorithms don't bend the brain. They perform acceptably with large trees. Querying edge-adjacency lists for subtrees and paths is less daunting than their reputation suggests.

Automate tree drawing!

Tables of numbers may be the most boring objects on earth. How to bring them alive? The Google Visualization API library has an ‘OrgChart’ module that can make edge list trees look like Fig 2, but each instance needs fifty or so lines of specific JavaScript code, plus an additional line of code for each row of data in the tree. Could we autogenerate that code? Mais oui! The module needs child node and parent node columns of data, and accepts an optional third column for info that pops up when the mouse hovers. Here is such a query for the Shakespeare family tree ...

Listing 9select concat( node.ID,' ', node.name) as node,       if( edges.parentID is null, '', concat(parent.ID, ' ',parent.name)) as parent,       if( node.born is null, 'Birthdate unknown', concat( 'Born ', node.born )) as tooltip from      family     as nodeleft join familytree as edges  on node.ID=edges.childIDleft join family     as parent on edges.parentID=parent.ID;

and here is a PHP function which generates the HTML and JavaScript needed to paint an OrgChart for any tree query that returns string columns for node, parent and optionally tooltips:

Listing 9afunction orgchart( $qry ) {  $cols = array(); $rows = array();  $res = mysql_query( $qry ) or exit( mysql_error() );  $colcount = mysql_num_fields( $res );  if( $colcount < 2 ) exit( "Org chart needs two or three columns" );  $rowcount = mysql_num_rows( $res );  for( $i=0; $i<$colcount; $i++ ) $cols[] = mysql_fetch_field( $res, $i );  while( $row = mysql_fetch_row( $res )) $rows[] = $row;  echo "\n\n",       "  \n",       "  \n/head>\n\n",       "  
\n",       "\n";}

Nested sets model of a tree

Imagine an oval drawn round every leaf and every subtree in Fig 2, and a final oval round the entire tree. The tree is a set. Each subtree is a subset. That's the basic idea of the nested sets model.

The advantage of the nested sets model is that root, leaves, subtrees, levels, tree height, ancestors, descendants and paths can be retrieved without recursion or application language code. The disadvantages are:

initial setup of the tree table can be difficult,
queries for parents (immediate superiors) and children (immediate subordinates) are more complicated than with an edge list model,
insertion, updates and deletion are extremely cumbersome since they may require updates to much of the tree.

The nested sets model depends on using a modified preorder tree traversal (MPTT) depth-first algorithm to assign each node left and right integers which define the node's tree position. All nodes of a subtree have

left values greater than the subtree parent's left value, and
right values smaller than that of the subtree parent's right value.

so queries for subtrees are dead simple. If the numbering scheme is integer-sequential as in Fig 3, the root node receives a left value of 1 and a right value equal to twice the item count.

To see how to code nested sets using MPTT, trace the ascending integers in Fig 3, starting with 1 on the left side of the root node (Richard Shakespeare). Following edges downward and leftward, the left side of each box gets the next integer. When you reach a leaf (Joan, left=3), the right side of that box gets the next integer (4). If there is another node to the right on the same level, continue in that direction; otherwise continue up the right side of the subtree you just descended. When you arrive back at the root on the right side, you're done. Down, right and up.

A serious problem with this scheme jumps out right away: after you've written the Fig 3 tree to a table, what if historians discover an older brother or sister of Henry and John? Every row in the tree table must be updated!

Celko and others have proposed alternative numbering schemes to get round this problem, but the logical difficulty remains: inserts and updates can invalidate many or all rows, andno SQL CHECK or CONSTRAINTcan prevent it. The nested sets model is not good for trees which require frequent updates, and is pretty much unsupportable for large updatable trees that will be accessed by many concurrent users. But as we'llsee in a moment, it can bevery useful indeed for reporting a tree.

How to build a nested sets representation from an edge list

Obviously, numbering a tree by hand would be error-prone, seriously impractical for large trees, so it's usually best to code the tree initially as an edge list, then use a stored procedure to translate the edge list representation to nested sets. Celko 's depth-first pushdown stack method will translate any edge list tree into a nested sets tree, though slowly:

Create a table nestedsettree for the tree: node, leftedge, rightedge, and a stack pointer (top),
Seed that table with the root node of the edge list tree,
Set a nextedge counter to 1 plus the left value of the root node, i.e. 2,
While that counter is less than the rightedge value of the root node ...
- insert a row for this parent's smallest unwritten child, and drop down a level, or
- if we're out of children, increment rightedge , write it to the current row, and back up a level.

This version has been improved to handle edge list trees with or without a row containing the root node and its NULL parent:

Listing 10DROP PROCEDURE IF EXISTS EdgeListToNestedSet;DELIMITER goCREATE PROCEDURE EdgeListToNestedSet( edgeTable CHAR(64), idCol CHAR(64), parentCol CHAR(64) )BEGIN  DECLARE maxrightedge, rows SMALLINT DEFAULT 0;  DECLARE trees, current SMALLINT DEFAULT 1;  DECLARE nextedge SMALLINT DEFAULT 2;  DECLARE msg CHAR(128);  -- create working tree table as a copy of edgeTable  DROP TEMPORARY TABLE IF EXISTS tree;  CREATE TEMPORARY TABLE tree( childID INT, parentID INT );  SET @sql = CONCAT( 'INSERT INTO tree SELECT ', idCol, ',', parentCol, ' FROM ', edgeTable );  PREPARE stmt FROM @sql; EXECUTE stmt; DROP PREPARE stmt;  -- initialise result table  DROP TABLE IF EXISTS nestedsettree;  CREATE TABLE nestedsettree (    top SMALLINT, nodeID SMALLINT, leftedge SMALLINT, rightedge SMALLINT,    KEY(nodeID,leftedge,rightedge)   ) ENGINE=HEAP;  -- root is child with NULL parent or parent which is not a child   SET @nulls = ( SELECT Count(*) FROM tree WHERE parentID IS NULL );  IF @nulls>1 THEN SET trees=2;  ELSEIF @nulls=1 THEN    SET @root = ( SELECT childID FROM tree WHERE parentID IS NULL );    DELETE FROM tree WHERE childID=@root;  ELSE    SET @sql = CONCAT( 'SELECT Count(DISTINCT f.', parentcol, ') INTO @roots FROM ', edgeTable,                        ' f LEFT JOIN ', edgeTable, ' t ON f.', parentCol, '=', 't.', idCol,                        ' WHERE t.', idCol, ' IS NULL' );    PREPARE stmt FROM @sql; EXECUTE stmt; DROP PREPARE stmt;    IF @roots <> 1 THEN SET trees=@roots;     ELSE      SET @sql = CONCAT( 'SELECT DISTINCT f.', parentCol, ' INTO @root FROM ', edgeTable,                          ' f LEFT JOIN ', edgeTable, ' t ON f.', parentCol, '=', 't.',                          idCol, ' WHERE t.', idCol, ' IS NULL' );      PREPARE stmt FROM @sql; EXECUTE stmt; DROP PREPARE stmt;    END IF;  END IF;  IF trees<>1 THEN    SET msg = IF( trees=0, "No tree found", "Table has multiple trees" );    SELECT msg AS 'Cannot continue';  ELSE    -- build nested sets tree    SET maxrightedge = 2 * (1 + (SELECT + COUNT(*) FROM tree));    INSERT INTO nestedsettree VALUES( 1, @root, 1, maxrightedge );    WHILE nextedge < maxrightedge DO      SET rows=(SELECT Count(*) FROM nestedsettree s JOIN tree t ON s.nodeID=t.parentID AND s.top=current);      IF rows > 0 THEN        BEGIN          INSERT INTO nestedsettree            SELECT current+1, MIN(t.childID), nextedge, NULL            FROM nestedsettree AS s            JOIN tree AS t ON s.nodeID = t.parentID AND s.top = current;          DELETE FROM tree          WHERE childID = (SELECT nodeID FROM nestedsettree WHERE top=(current+1));          SET nextedge = nextedge + 1, current = current + 1;         END;       ELSE         UPDATE nestedsettree SET rightedge=nextedge, top = -top WHERE top=current;         SET nextedge=nextedge+1, current=current-1;      END IF;    END WHILE;    -- show result    IF (SELECT COUNT(*) FROM tree) > 0 THEN      SELECT 'Orphaned rows remain' AS 'Error';    END IF;    DROP TEMPORARY TABLE tree;  END IF;END;goDELIMITER ;CALL EdgeListToNestedSet( 'familytree', 'childID', 'parentID' );SELECT  nodeID, PersonName(nodeID) AS Name,  ABS(top) AS 'Tree Level', leftedge AS 'Left', rightedge AS 'Right'FROM nestedsettreeORDER BY nodeID;+--------+----------------------+------------+------+-------+| nodeID | Name                 | Tree Level | Left | Right |+--------+----------------------+------------+------+-------+|      1 | Richard Shakespeare  |          1 |    1 |    46 ||      2 | Henry Shakespeare    |          2 |    2 |    43 ||      3 | John Shakespeare     |          2 |   44 |    45 ||      4 | Joan Shakespeare     |          3 |    3 |     4 ||      5 | Margaret Shakespeare |          3 |    5 |     6 ||      6 | William Shakespeare  |          3 |    7 |    24 ||      7 | Gilbert Shakespeare  |          3 |   25 |    26 ||      8 | Joan Shakespeare     |          3 |   27 |    36 ||      9 | Anne Shakespeare     |          3 |   37 |    38 ||     10 | Richard Shakespeare  |          3 |   39 |    40 ||     11 | Edmond Shakespeare   |          3 |   41 |    42 ||     12 | Susana Shakespeare   |          4 |    8 |    13 ||     13 | Hamnet Shakespeare   |          4 |   14 |    15 ||     14 | Judith Shakespeare   |          4 |   16 |    23 ||     15 | William Hart         |          4 |   28 |    29 ||     16 | Mary Hart            |          4 |   30 |    31 ||     17 | Thomas Hart          |          4 |   32 |    33 ||     18 | Michael Hart         |          4 |   34 |    35 ||     19 | Elizabeth Hall       |          5 |    9 |    12 ||     20 | Shakespeare Quiney   |          5 |   17 |    18 ||     21 | Richard Quiney       |          5 |   19 |    20 ||     22 | Thomas Quiney        |          5 |   21 |    22 ||     23 | John Bernard         |          6 |   10 |    11 |+--------+----------------------+------------+------+-------+

Verify the function with a query that generates an edge list tree from a nested sets tree:

Listing 10a:SELECT a.nodeID, b.nodeID AS parent FROM nestedsettree AS aLEFT JOIN nestedsettree AS b ON b.leftedge = (  SELECT MAX( leftedge )   FROM nestedsettree AS t   WHERE a.leftedge > t.leftedge AND a.leftedge < t.rightedge) ORDER BY a.nodeID;

For a multi-tree version of Listing 10, implementing edge list and nested sets tree models in a single table, see “Multiple nested sets trees in one table” on our Queries page.

Finding a node's parent and children

In an edge list, the parent of a node is the row's parentID, and its children are the rows where that nodeID is parentID. What could be simpler? In comparison, nested sets queries for parents and their children are tortuous and slow. One way to fetch the child nodes of a given node is to INNER JOIN the nested sets tree table AS parent to itself AS child ON child.leftedge BETWEEN parent.leftedge AND parent.rightedge, then scope on the target row's leftedge and rightedge values. In the resulting list, child.nodeID values one level down occur once and are children, grandkids are two levels down and occur twice, and so on:

Listing 11SELECT PersonName(child.nodeID) AS 'Descendants of William', COUNT(*) AS GenerationFROM nestedsettree AS parentJOIN nestedsettree AS child ON child.leftedge BETWEEN parent.leftedge AND parent.rightedgeWHERE parent.leftedge > 7 AND parent.rightedge < 24       -- William’s leftedge, rightedgeGROUP BY child.nodeID;+------------------------+------------+| Descendants of William | Generation |+------------------------+------------+| Susana Shakespeare     |          1 || Hamnet Shakespeare     |          1 || Judith Shakespeare     |          1 || Elizabeth Hall         |          2 || Shakespeare Quiney     |          2 || Richard Quiney         |          2 || Thomas Quiney          |          2 || John Bernard           |          3 |+------------------------+------------+

ThereforeHAVING COUNT(t2.nodeID)=1 scopes listed descendants to the children:

Listing 11aSELECT PersonName(child.nodeID) AS 'Children of William'FROM nestedsettree AS parentJOIN nestedsettree AS child ON child.leftedge BETWEEN parent.leftedge AND parent.rightedgeWHERE parent.leftedge > 7 AND parent.rightedge < 24GROUP BY child.nodeIDHAVING COUNT(child.nodeID)=1+---------------------+| Children of William |+---------------------+| Susana Shakespeare  || Hamnet Shakespeare  || Judith Shakespeare  |+---------------------+

Retrieving a subtree or a subset of parents requires yet another join:

Listing 11bSELECT Parent, Group_Concat(Child ORDER BY Child) AS ChildrenFROM (  SELECT master.nodeID AS Parent, child.nodeID AS Child  FROM nestedsettree AS master  JOIN nestedsettree AS parent  JOIN nestedsettree AS child ON child.leftedge BETWEEN parent.leftedge AND parent.rightedge  WHERE parent.leftedge > master.leftedge AND parent.rightedge < master.rightedge  GROUP BY master.nodeID, child.nodeID  HAVING COUNT(*)=1) AS tmpWHERE parent in(6,8,12,14)GROUP BY Parent;+--------+-------------------+| Parent | Children          |+--------+-------------------+|      6 | 12,13,14          ||      8 | 15,16,17,18       ||     12 | 19                ||     14 | 20,21,22          |+--------+-------------------+

This takes hundreds of times longer than a query for the same info from an edge list! An aggregating version of Listing 19 is easier to write, but is an even worse performer:

Listing 11cSELECT p.nodeID AS Parent, Group_Concat(c.nodeID) AS ChildrenFROM nestedsettree AS pJOIN nestedsettree AS c  ON p.leftedge = (SELECT MAX(s.leftedge) FROM nestedsettree AS s                   WHERE c.leftedge > s.leftedge AND c.leftedge < s.rightedge)GROUP BY Parent;+--------+-------------------+| Parent | Children          |+--------+-------------------+|      1 | 2,3               ||      2 | 5,6,7,8,9,10,11,4 ||      6 | 12,13,14          ||      8 | 15,16,17,18       ||     12 | 19                ||     14 | 20,21,22          ||     19 | 23                |+--------+-------------------+

Logic that is reciprocal to that of Listing 11a gets us the parent of a node:

retrieve its leftedge and rightedge values,
compute its level,
find the node which is one level up and has edge values outside the node's leftedge and rightedge values.

Listing 12DROP PROCEDURE IF EXISTS ShowNestedSetParent;DELIMITER goCREATE PROCEDURE ShowNestedSetParent( node SMALLINT )BEGIN  DECLARE level, thisleft, thisright SMALLINT DEFAULT 0;  -- find node edges  SELECT leftedge, rightedge    INTO thisleft, thisright  FROM nestedsettree  WHERE nodeID = node;  -- find node level  SELECT COUNT(n1.nodeid)    INTO level  FROM nestedsettree AS n1    INNER JOIN nestedsettree AS n2    ON n2.leftedge BETWEEN n1.leftedge AND n1.rightedge  WHERE n2.nodeid = node  GROUP BY n2.nodeid;  -- find parent  SELECT    PersonName(n2.nodeid) AS Parent  FROM nestedsettree AS n1    INNER JOIN nestedsettree AS n2    ON n2.leftedge BETWEEN n1.leftedge AND n1.rightedge  WHERE n2.leftedge < thisleft AND n2.rightedge > thisright  GROUP BY n2.nodeid  HAVING COUNT(n1.nodeid)=level-1;END;goDELIMITER ;CALL ShowNestedSetParent(6);+-------------------+| Parent            |+-------------------+| Henry Shakespeare |+-------------------+

Other queries

For some query problems, edge list and nested sets queries are equivalently simple. For example to find the tree root and leaves, compare Listing 6 with:

Listing 13SELECT  name AS Paterfamilias,  IFNULL(born,'?') AS Born,  IFNULL(died,'?') AS DiedFROM nestedsettree AS tINNER JOIN family AS f ON t.nodeID=f.IDWHERE leftedge = 1;+---------------------+------+------+| Paterfamilias       | Born | Died |+---------------------+------+------+| Richard Shakespeare | ?    | 1561 |+---------------------+------+------+SELECT  name AS 'Childless Shakespeares',  IFNULL(born,'?') AS Born,  IFNULL(died,'?') AS DiedFROM nestedsettree AS tINNER JOIN family AS f ON t.nodeID=f.IDWHERE rightedge = leftedge + 1;+------------------------+------+------+| Childless Shakespeares | Born | Died |+------------------------+------+------+| Joan Shakespeare       | 1558 | ?    || Margaret Shakespeare   | 1562 | 1563 || John Bernard           | ?    | 1674 || Hamnet Shakespeare     | 1585 | 1596 || Shakespeare Quiney     | 1616 | 1617 || Richard Quiney         | 1618 | 1639 || Thomas Quiney          | 1620 | 1639 || Gilbert Shakespeare    | 1566 | 1612 || William Hart           | 1600 | 1639 || Mary Hart              | 1603 | 1607 || Thomas Hart            | 1605 | 1670 || Michael Hart           | 1608 | 1618 || Anne Shakespeare       | 1571 | 1579 || Richard Shakespeare    | 1574 | 1613 || Edmond Shakespeare     | 1580 | 1607 || John Shakespeare       | 1530 | 1601 |+------------------------+------+------+

Finding subtrees in a nested sets model requires no twisted code, no stored procedure.To retrieve the nestedsettree nodes in William's subtree, just ask for nodeswhose leftedge values are greater, and whose rightedgevalues are smaller than William's:

Listing 14SELECT PersonName(t.nodeID) AS DescendantFROM nestedsettree AS s  JOIN nestedsettree AS t ON s.leftedge < t.leftedge AND s.rightedge > t.rightedge  JOIN family f ON s.nodeID = f.IDWHERE f.name = 'William Shakespeare';

Finding a single path in the nested sets model is about as complicated as edge list path enumeration (Listings 8, 9):

Listing 15SELECT  t2.nodeID AS Node,  PersonName(t2.nodeID) AS Person,  (SELECT COUNT(*)   FROM nestedsettree AS t4   WHERE t4.leftedge BETWEEN t1.leftedge AND t1.rightedge     AND t2.leftedge BETWEEN t4.leftedge AND t4.rightedge   ) AS PathFROM nestedsettree AS t1  INNER JOIN nestedsettree AS t2 ON t2.leftedge BETWEEN t1.leftedge AND t1.rightedge  INNER JOIN nestedsettree AS t3 ON t3.leftedge BETWEEN t2.leftedge AND t2.rightedgeWHERE t1.nodeID=(SELECT ID FROM family WHERE name='William Shakespeare')  AND t3.nodeID=(SELECT ID FROM family WHERE name='John Bernard');+------+---------------------+------+| Node | Person              | Path |+------+---------------------+------+|    6 | William Shakespeare |    1 ||   12 | Susana Shakespeare  |    2 ||   19 | Elizabeth Hall      |    3 ||   23 | John Bernard        |    4 |+------+---------------------+------+

Displaying the tree

Here the nested sets model shines. The arithmetic that was used to build the tree makes short work of summary queries. For example to retrieve a node list which preserves all parent-child relations, we need just two facts:

listing order is the order taken in the node walk that created the tree, i.e. leftedge,
a node's indentation depth is simply the JOIN (edge) count from root to node:

Listing 16SELECT  CONCAT( SPACE(2*COUNT(parent.nodeid)-2), PersonName(child.nodeid) )  AS 'The Shakespeare Family Tree'FROM nestedsettree AS parent  INNER JOIN nestedsettree AS child  ON child.leftedge BETWEEN parent.leftedge AND parent.rightedgeGROUP BY child.nodeidORDER BY child.leftedge;+-----------------------------+| The Shakespeare Family Tree |+-----------------------------+| Richard Shakespeare         ||   Henry Shakespeare         ||     Joan Shakespeare        ||     Margaret Shakespeare    ||     William Shakespeare     ||       Susana Shakespeare    ||         Elizabeth Hall      ||           John Bernard      ||       Hamnet Shakespeare    ||       Judith Shakespeare    ||         Shakespeare Quiney  ||         Richard Quiney      ||         Thomas Quiney       ||     Gilbert Shakespeare     ||     Joan Shakespeare        ||       William Hart          ||       Mary Hart             ||       Thomas Hart           ||       Michael Hart          ||     Anne Shakespeare        ||     Richard Shakespeare     ||     Edmond Shakespeare      ||   John Shakespeare          |+-----------------------------+

To retrieve only a subtree, add a query clause which restricts nodes to those whose edges are within the range of the parent node's left and right edge values, for example for William and his descendants...

WHERE parent.leftedge >= 7 AND parent.rightedge <=24

Node insertions, updates and deletions

Nested sets arithmetic also helps with insertions, updates and deletions, but the problem remains that changing just one node can require changing much of the tree.

Inserting a node in the tree requires at least two pieces of information: the nodeID to insert, and the nodeID of its parent. The model is normalised so the nodeID first must have been added to the parent (family) table. The algorithm for adding the node to the tree is:

increment leftedge by 2 in nodes where the rightedge value is greater than the parent's rightedge,
increment rightedge by 2 in nodes where the leftedge value is greater than the parent's leftedge,
insert a row with the given nodeID, leftedge = 1 + parent's leftedge, rightedge = 2 + parent's leftedge.

That's not difficult, but all rows will have to be updated!

Listing 17DROP PROCEDURE IF EXISTS InsertNestedSetNode;DELIMITER goCREATE PROCEDURE InsertNestedSetNode( IN node SMALLINT, IN parent SMALLINT )BEGIN  DECLARE parentleft, parentright SMALLINT DEFAULT 0;  SELECT leftedge, rightedge    INTO parentleft, parentright  FROM nestedsettree  WHERE nodeID = parent;  IF FOUND_ROWS() = 1 THEN    BEGIN      UPDATE nestedsettree        SET rightedge = rightedge + 2      WHERE rightedge > parentleft;      UPDATE nestedsettree        SET leftedge = leftedge + 2      WHERE leftedge > parentleft;      INSERT INTO nestedsettree        VALUES ( 0, node, parentleft + 1, parentleft + 2 );    END;  END IF;END;goDELIMITER ;

"Sibline" or horizontal order is obviously significant in family trees, but may not be significant in other trees. Listing 17 adds the new node at the left edge of the sibline. To specify another position, modify the procedure to accept a third parameter for the nodeID which is to be to the left or right of the insertion point.

Updating a node in place requires nothing more than editing nodeID to point at a different parent row.

Deleting a node raises the problem of how to repair links severed by the deletion. In tree models of parts explosions, the item to be deleted is often replaced by a new item, so it can be treated like a simple nodeID update. In organisational boss-employee charts, though, does a colleague move over, does a subordinate get promoted, does everybody in the subtree move up a level, or does something else happen? No formula can catch all the possibilities. Listing 18 illustrates how to handle two common scenarios, move everyone up, and move someone over. All possibilities except simple replacement of the nodeID involve changes elsewhere in the tree.

Listing 18DROP PROCEDURE IF EXISTS DeleteNestedSetNode;DELIMITER goCREATE PROCEDURE DeleteNestedSetNode( IN mode CHAR(7), IN node SMALLINT )BEGIN  DECLARE thisleft, thisright SMALLINT DEFAULT 0;  SELECT leftedge, rightedge    INTO thisleft, thisright  FROM nestedsettree  WHERE nodeID = node;  IF mode = 'PROMOTE' THEN    BEGIN                                                         -- Ian Holsman found these two bugs      DELETE FROM nestedsettree      WHERE nodeID = node;      UPDATE nestedsettree        SET leftedge = leftedge - 1, rightedge = rightedge - 1    -- rather than = thisleft      WHERE leftedge BETWEEN thisleft AND thisright;      UPDATE nestedsettree        SET rightedge = rightedge - 2      WHERE rightedge > thisright;      UPDATE nestedsettree        SET leftedge = leftedge - 2      WHERE leftedge > thisright;                                 -- rather than > thisleft    END;  ELSEIF mode = 'REPLACE' THEN    BEGIN      UPDATE nestedsettree        SET leftedge = thisleft - 1, rightedge = thisright      WHERE leftedge = thisleft + 1;      UPDATE nestedsettree        SET rightedge = rightedge - 2      WHERE rightedge > thisleft;      UPDATE nestedsettree        SET leftedge = leftedge - 2      WHERE leftedge > thisleft;      DELETE FROM nestedsettree      WHERE nodeID = node;    END;  END IF;END;goDELIMITER ;

Nesteds set model summary

Some nested sets queries are quicker than their edge list counterparts, some aren't. Given the concurrency nightmare which nested sets impose for inserts and deletions, it is reasonable to reserve the nested sets model for fairly static trees whose users are mostly interested in querying subtrees. You could think of the nested sets model as a specialised OLAP tool: maintain an OLTP tree in an edge list representation, and build a nested sets OLAP table when certain reports are needed.

If you will be using the nested sets model, you may be converting back and forth with edge list models, so here is a simple query which generates an edge list from a nested sets tree:

Listing 19SELECT  p.nodeID AS parentID,  c.nodeID AS childIDFROM nestedsettree AS p  INNER JOIN nestedsettree AS c  ON p.leftedge = (SELECT MAX(s.leftedge)                   FROM nestedsettree AS s                   WHERE c.leftedge > s.leftedge                     AND c.leftedge < s.rightedge)ORDER BY p.nodeID;

Edge list model of a non-tree graph

Many graphs are not trees. Imagine a small airline which has just acquired licences for flights no longer than 6,000 km between Los Angeles (LAX), New York (JFK), Heathrow in London, Charles de Gaulle in Paris, Amsterdam-Schiphol, Arlanda in Sweden, and Helsinki-Vantaa. You have been asked to compute the shortest possible one-way routes that do not deviate more than 90° from the direction of the first hop—roughly, one-way routes and no circuits.

Airports are nodes, flights are edges, routes are paths. We will need three tables.

Airports (nodes)

To identify an airport we need its code, location name, latitude and longitude. Latitude and longitude are usually given as degrees, minutes and seconds, north or south of the equator, east or west of Greenwich. To hide details that aren't directly relevant to nodes and edges, code latitude and longitude as simple reals where longitudes west of Greenwich and latitudes south of the equator are negative, whilst longitudes east of Greenwich and latitudes north of the equator are positive:

Listing 20CREATE TABLE airports (  code char(3) NOT NULL,  city char(100) default NULL,  latitude float NOT NULL,  longitude float NOT NULL,  PRIMARY KEY (code)) ENGINE=MyISAM;INSERT INTO airports VALUES ('JFK', 'New York, NY', 40.75, -73.97);INSERT INTO airports VALUES ('LAX', 'Los Angeles, CA', 34.05, -118.22);INSERT INTO airports VALUES ('LHR', 'London, England', 51.5, -0.45);INSERT INTO airports VALUES ('HEL', 'Helsinki, Finland', 60.17, 24.97);INSERT INTO airports VALUES ('CDG', 'Paris, France', 48.86, 2.33);INSERT INTO airports VALUES ('STL', 'St Louis, MO', 38.63, -90.2);INSERT INTO airports VALUES ('ARN', 'Stockholm, Sweden', 59.33, 18.05);

Flights (edges)

The model attaches two weights to flights: distance and direction.

We need a method of calculating the Great Circle Distance—the geographical distance between any two cities - another natural job for astored function. The distance calculation

converts to radians the degree coordinates of any two points on the earth's surface,
calculates the angle of the arc subtended by the two points, and
converts the result, also in radians, to surface (circumferential) kilometres (1 radian=6,378.388 km).

Listing 21SET GLOBAL log_bin_trust_function_creators=TRUE;   -- since 5.0.16DROP FUNCTION IF EXISTS GeoDistKM;DELIMITER goCREATE FUNCTION GeoDistKM( lat1 FLOAT, lon1 FLOAT, lat2 FLOAT, lon2 FLOAT ) RETURNS floatBEGIN  DECLARE pi, q1, q2, q3 FLOAT;  SET pi = PI();  SET lat1 = lat1 * pi / 180;  SET lon1 = lon1 * pi / 180;  SET lat2 = lat2 * pi / 180;  SET lon2 = lon2 * pi / 180;  SET q1 = COS(lon1-lon2);  SET q2 = COS(lat1-lat2);  SET q3 = COS(lat1+lat2);  SET rads = ACOS( 0.5*((1.0+q1)*q2 - (1.0-q1)*q3) );  RETURN 6378.388 * rads;END;goDELIMITER ;

That takes care of flight distances. Flight direction is, approximately, the arctangent (ATAN) of the difference between flights.depart and flights.arrive latitudes and longitudes. Now we can seed the airline's flights table with one-hop flights up to 6,000 km long:

Listing 22CREATE TABLE flights (  id INT PRIMARY KEY AUTO_INCREMENT,  depart CHAR(3),  arrive CHAR(3),  distance DECIMAL(10,2),  direction DECIMAL(10,2)) ENGINE=MYISAM;INSERT INTO flights  SELECT    NULL,    depart.code,    arrive.code,    ROUND(GeoDistKM(depart.latitude,depart.longitude,arrive.latitude,arrive.longitude),2),    ROUND(DEGREES(ATAN(arrive.latitude-depart.latitude,arrive.longitude-depart.longitude)),2)  FROM airports AS depart  INNER JOIN airports AS arrive ON depart.code <> arrive.code  HAVING Km <= 6000;SELECT * FROM flights;+----+--------+--------+----------+-----------+| id | depart | arrive | distance | direction |+----+--------+--------+----------+-----------+|  1 | LAX    | JFK    | 3941.18  | 8.61      ||  2 | LHR    | JFK    | 5550.77  | -171.68   ||  3 | CDG    | JFK    | 5837.46  | -173.93   ||  4 | STL    | JFK    | 1408.11  | 7.44      ||  5 | JFK    | LAX    | 3941.18  | -171.39   ||  6 | STL    | LAX    | 2553.37  | -170.72   ||  7 | JFK    | LHR    | 5550.77  | 8.32      ||  8 | HEL    | LHR    | 1841.91  | -161.17   ||  9 | CDG    | LHR    | 354.41   | 136.48    || 10 | ARN    | LHR    | 1450.12  | -157.06   || 11 | LHR    | HEL    | 1841.91  | 18.83     || 12 | CDG    | HEL    | 1912.96  | 26.54     || 13 | ARN    | HEL    | 398.99   | 6.92      || 14 | JFK    | CDG    | 5837.46  | 6.07      || 15 | LHR    | CDG    | 354.41   | -43.52    || 16 | HEL    | CDG    | 1912.96  | -153.46   || 17 | ARN    | CDG    | 1545.23  | -146.34   || 18 | JFK    | STL    | 1408.11  | -172.56   || 19 | LAX    | STL    | 2553.37  | 9.28      || 20 | LHR    | ARN    | 1450.12  | 22.94     || 21 | HEL    | ARN    | 398.99   | -173.08   || 22 | CDG    | ARN    | 1545.23  | 33.66     |+----+--------+--------+----------+-----------+

The distances agree approximately with public information sources for flight lengths. For a pair of airports A and B not very near the poles, the error in calculating direction using ATAN(), is small. To remove that error, instead of ATAN() use a formula from spherical trigonometry (for example one of the formulas at http://www.dynagen.co.za/eugene/where/formula.html).

Routes (paths)

A route is a path along one or more of these edges, so flights:routes is a 1:many relationship. For simplicity, though, we denormalise our representation of routes with a variation of the materialised path model to store all the hops of one route as a list of flights in one routes column. The column routes.route is the sequence of airports, from first departure to final arrival, the column routes.hops is the number of hops in that route, and the column routes.direction is the direction:

Listing 23CREATE TABLE routes (  id INT PRIMARY KEY AUTO_INCREMENT,  depart CHAR(3),  arrive CHAR(3),  hops SMALLINT,  route CHAR(50),  distance DECIMAL(10,2),  direction DECIMAL(10,2)) ENGINE=MYISAM;

Starting with an empty routes table, how do we populate it with theshortest routes between all ordered pairs of airports?

Insert all 1-hop flights from the flights table.
Add in the setof shortest multi-hop routes for all pairs ofairports which don't have rows in the flights table.

For 1-hop flights we just write

Listing 24INSERT INTO routes  SELECT    NULL,    depart,    arrive,    1,    CONCAT(depart,',',arrive),    distance,    direction  FROM flights;

NULL being the placeholder for the auto-incrementing id column.

For multi-hop routes, we iteratively add in sets of all allowed 2-hop, 3-hop, ... n-hop routes, replacing longer routes byshorter routes as we find them, until there is nothing more to add or replace. That also breaks down to two logical steps:add hops to build the set of next allowed routes, and update longer routes with shorter ones.

Next allowed routes

The set of next allowed routes is the set of shortest routes that can be built by adding, to existing routes, flights which leave from the last arrival airport of an existing route, which arrive at an airport which is not yet in the given route, and which stay within ± 90° of the route's initial compass direction. That is, every new route is a JOIN between routes and flights in which

depart = routes.depart,
arrive = flights.arrive,
flights.depart = routes.arrive,
distance = MIN(routes.distance + flights.distance),
LOCATE( flights.arrive,routes.route) = 0,
flights.direction+360 > routes.direction+270 AND flights.direction+360 < routes.direction+450

This is a natural logical unit of work for a VIEW:

Listing 25CREATE OR REPLACE VIEW nextroutes AS  SELECT    routes.depart,    flights.arrive,    routes.hops+1 AS hops,    CONCAT(routes.route, ',', flights.arrive) AS route,    MIN(routes.distance + flights.distance) AS distance,    routes.direction  FROM routes INNER JOIN flights    ON routes.arrive = flights.depart    AND LOCATE(flights.arrive,routes.route) = 0  WHERE flights.direction+360>routes.direction+270    AND flights.direction+360 
  How to add these new hops to routes? In standard SQL, this variant on a query by Scott Stephens should do it... 
  Listing 26INSERT INTO routes  SELECT NULL,depart,arrive,hops,route,distance,direction FROM nextroutes  WHERE (nextroutes.depart,nextroutes.arrive) NOT IN (    SELECT depart,arrive FROM routes  ); 
  but MySQL does not yet support subqueries on the table being updated. We have to use asubquery-less (and faster) version of that logic: 
  Listing 27INSERT INTO routes  SELECT    NULL,    nextroutes.depart,    nextroutes.arrive,    nextroutes.hops,    nextroutes.route,    nextroutes.distance,    nextroutes.direction  FROM nextroutes  LEFT JOIN routes ON nextroutes.depart = routes.depart        AND nextroutes.arrive = routes.arrive  WHERE routes.depart IS NULL AND routes.arrive IS NULL; 
  Running that code right after the initial seeding from flights gives ...  
  SELECT * FROM routes;+----+--------+--------+------+-------------+----------+-----------+| id | depart | arrive | hops | route       | distance | direction |+----+--------+--------+------+-------------+----------+-----------+|  1 | LAX    | JFK    |    1 | LAX,JFK     | 3941.18  | 8.61      ||  2 | LHR    | JFK    |    1 | LHR,JFK     | 5550.77  | -171.68   ||  3 | CDG    | JFK    |    1 | CDG,JFK     | 5837.46  | -173.93   ||  4 | STL    | JFK    |    1 | STL,JFK     | 1408.11  | 7.44      ||  5 | JFK    | LAX    |    1 | JFK,LAX     | 3941.18  | -171.39   ||  6 | STL    | LAX    |    1 | STL,LAX     | 2553.37  | -170.72   ||  7 | JFK    | LHR    |    1 | JFK,LHR     | 5550.77  | 8.32      ||  8 | HEL    | LHR    |    1 | HEL,LHR     | 1841.91  | -161.17   ||  9 | CDG    | LHR    |    1 | CDG,LHR     | 354.41   | 136.48    || 10 | ARN    | LHR    |    1 | ARN,LHR     | 1450.12  | -157.06   || 11 | LHR    | HEL    |    1 | LHR,HEL     | 1841.91  | 18.83     || 12 | CDG    | HEL    |    1 | CDG,HEL     | 1912.96  | 26.54     || 13 | ARN    | HEL    |    1 | ARN,HEL     | 398.99   | 6.92      || 14 | JFK    | CDG    |    1 | JFK,CDG     | 5837.46  | 6.07      || 15 | LHR    | CDG    |    1 | LHR,CDG     | 354.41   | -43.52    || 16 | HEL    | CDG    |    1 | HEL,CDG     | 1912.96  | -153.46   || 17 | ARN    | CDG    |    1 | ARN,CDG     | 1545.23  | -146.34   || 18 | JFK    | STL    |    1 | JFK,STL     | 1408.11  | -172.56   || 19 | LAX    | STL    |    1 | LAX,STL     | 2553.37  | 9.28      || 20 | LHR    | ARN    |    1 | LHR,ARN     | 1450.12  | 22.94     || 21 | HEL    | ARN    |    1 | HEL,ARN     | 398.99   | -173.08   || 22 | CDG    | ARN    |    1 | CDG,ARN     | 1545.23  | 33.66     || 23 | ARN    | JFK    |    2 | ARN,LHR,JFK | 7000.89  | -157.06   || 24 | CDG    | LAX    |    2 | CDG,JFK,LAX | 9778.64  | -173.93   || 25 | CDG    | STL    |    2 | CDG,JFK,STL | 7245.57  | -173.93   || 26 | HEL    | JFK    |    2 | HEL,LHR,JFK | 7392.68  | -161.17   || 27 | JFK    | ARN    |    2 | JFK,LHR,ARN | 7000.89  | 8.32      || 28 | JFK    | HEL    |    2 | JFK,LHR,HEL | 7392.68  | 8.32      || 29 | LAX    | CDG    |    2 | LAX,JFK,CDG | 9778.64  | 8.61      || 30 | LAX    | LHR    |    2 | LAX,JFK,LHR | 9491.95  | 8.61      || 31 | LHR    | LAX    |    2 | LHR,JFK,LAX | 9491.95  | -171.68   || 32 | LHR    | STL    |    2 | LHR,JFK,STL | 6958.88  | -171.68   || 33 | STL    | CDG    |    2 | STL,JFK,CDG | 7245.57  | 7.44      || 34 | STL    | LHR    |    2 | STL,JFK,LHR | 6958.88  | 7.44      |+----+--------+--------+------+-------------+----------+-----------+ 
  ... adding 12 two-hop rows. 
  Replace longer routes with shorter ones 
  As we build routes with more hops, it is logically possible that the nextroutes view will find shorter routes for an existing routes pair of depart and arrive. Standard SQL for replacing existing routes rows with nextroutes rows which match (depart, arrive) and have shorter distance values would be: 
  Listing 28UPDATE routes SET (hops,route,distance,direction) = (  SELECT hops, route, distance, direction  FROM nextroutes  WHERE nextroutes.depart = routes.depart AND nextroutes.arrive = routes.arrive)WHERE (depart,arrive) IN (  SELECT depart,arrive FROM nextroutes  WHERE nextroutes.distance < routes.distance); 
  but MySQL does not support SET(col1,...) syntax, and as with Listing 7,MySQL does not yet accept subqueries referencing the table being updated, so we have to write more literal SQL: 
  Listing 29UPDATE routes, nextroutesSET  routes.hops=nextroutes.hops,  routes.route=nextroutes.route,  routes.distance=nextroutes.distance,  routes.direction=nextroutes.directionWHERE routes.arrive=nextroutes.arrive  AND routes.depart=nextroutes.depart  AND nextroutes.distance < routes.distance; 
  Running this code right after the first run of Listing 27 updates no rows. To test the logic of iteration, continue running Listings 27 and 29 until no rows are being added or changed. The final result is: 
  SELECT * FROM ROUTES;+----+--------+--------+------+-----------------+----------+-----------+| id | depart | arrive | hops | route           | distance | direction |+----+--------+--------+------+-----------------+----------+-----------+|  1 | LAX    | JFK    |    1 | LAX,JFK         | 3941.18  | 8.61      ||  2 | LHR    | JFK    |    1 | LHR,JFK         | 5550.77  | -171.68   ||  3 | CDG    | JFK    |    1 | CDG,JFK         | 5837.46  | -173.93   ||  4 | STL    | JFK    |    1 | STL,JFK         | 1408.11  | 7.44      ||  5 | JFK    | LAX    |    1 | JFK,LAX         | 3941.18  | -171.39   ||  6 | STL    | LAX    |    1 | STL,LAX         | 2553.37  | -170.72   ||  7 | JFK    | LHR    |    1 | JFK,LHR         | 5550.77  | 8.32      ||  8 | HEL    | LHR    |    1 | HEL,LHR         | 1841.91  | -161.17   ||  9 | CDG    | LHR    |    1 | CDG,LHR         | 354.41   | 136.48    || 10 | ARN    | LHR    |    1 | ARN,LHR         | 1450.12  | -157.06   || 11 | LHR    | HEL    |    1 | LHR,HEL         | 1841.91  | 18.83     || 12 | CDG    | HEL    |    1 | CDG,HEL         | 1912.96  | 26.54     || 13 | ARN    | HEL    |    1 | ARN,HEL         | 398.99   | 6.92      || 14 | JFK    | CDG    |    1 | JFK,CDG         | 5837.46  | 6.07      || 15 | LHR    | CDG    |    1 | LHR,CDG         | 354.41   | -43.52    || 16 | HEL    | CDG    |    1 | HEL,CDG         | 1912.96  | -153.46   || 17 | ARN    | CDG    |    1 | ARN,CDG         | 1545.23  | -146.34   || 18 | JFK    | STL    |    1 | JFK,STL         | 1408.11  | -172.56   || 19 | LAX    | STL    |    1 | LAX,STL         | 2553.37  | 9.28      || 20 | LHR    | ARN    |    1 | LHR,ARN         | 1450.12  | 22.94     || 21 | HEL    | ARN    |    1 | HEL,ARN         | 398.99   | -173.08   || 22 | CDG    | ARN    |    1 | CDG,ARN         | 1545.23  | 33.66     || 23 | ARN    | JFK    |    2 | ARN,LHR,JFK     | 7000.89  | -157.06   || 24 | CDG    | LAX    |    2 | CDG,JFK,LAX     | 9778.64  | -173.93   || 25 | CDG    | STL    |    2 | CDG,JFK,STL     | 7245.57  | -173.93   || 26 | HEL    | JFK    |    2 | HEL,LHR,JFK     | 7392.68  | -161.17   || 27 | JFK    | ARN    |    2 | JFK,LHR,ARN     | 7000.89  | 8.32      || 28 | JFK    | HEL    |    2 | JFK,LHR,HEL     | 7392.68  | 8.32      || 29 | LAX    | CDG    |    2 | LAX,JFK,CDG     | 9778.64  | 8.61      || 30 | LAX    | LHR    |    2 | LAX,JFK,LHR     | 9491.95  | 8.61      || 31 | LHR    | LAX    |    2 | LHR,JFK,LAX     | 9491.95  | -171.68   || 32 | LHR    | STL    |    2 | LHR,JFK,STL     | 6958.88  | -171.68   || 33 | STL    | CDG    |    2 | STL,JFK,CDG     | 7245.57  | 7.44      || 34 | STL    | LHR    |    2 | STL,JFK,LHR     | 6958.88  | 7.44      || 35 | ARN    | LAX    |    3 | ARN,LHR,JFK,LAX | 10942.07 | -157.06   || 36 | ARN    | STL    |    3 | ARN,LHR,JFK,STL | 8409.00  | -157.06   || 37 | HEL    | LAX    |    3 | HEL,LHR,JFK,LAX | 11333.86 | -161.17   || 38 | HEL    | STL    |    3 | HEL,LHR,JFK,STL | 8800.79  | -161.17   || 39 | LAX    | ARN    |    3 | LAX,JFK,CDG,ARN | 10942.07 | 8.61      || 40 | LAX    | HEL    |    3 | LAX,JFK,CDG,HEL | 11333.86 | 8.61      || 41 | STL    | ARN    |    3 | STL,JFK,CDG,ARN | 8409.00  | 7.44      || 42 | STL    | HEL    |    3 | STL,JFK,CDG,HEL | 8800.79  | 7.44      |+----+--------+--------+------+-----------------+----------+-----------+ 
  All that's left to do is to assemble the code in a stored procedure: 
  Listing 30DROP PROCEDURE IF EXISTS BuildRoutes;DELIMITER goCREATE PROCEDURE BuildRoutes()BEGIN  DECLARE rows INT DEFAULT 0;  TRUNCATE routes;  -- STEP 1, LISTING 24: SEED ROUTES WITH 1-HOP FLIGHTS  INSERT INTO routes    SELECT      NULL,      depart,      arrive,      1,      CONCAT(depart,',',arrive),      distance,      direction  FROM flights;  SET rows = ROW_COUNT();  WHILE (rows > 0) DO    -- STEP 2, LISTINGS 25, 27: ADD NEXT SET OF ROUTES    INSERT INTO routes      SELECT        NULL,        nextroutes.depart,        nextroutes.arrive,        nextroutes.hops,        nextroutes.route,        nextroutes.distance,        nextroutes.direction      FROM nextroutes      LEFT JOIN routes ON nextroutes.depart = routes.depart AND nextroutes.arrive = routes.arrive      WHERE routes.depart IS NULL AND routes.arrive IS NULL;    SET rows = ROW_COUNT();  END WHILE;END;goDELIMITER ; 
  In MySQL 5.0.6 or 5.0.7, BuildRoutes() fails to insert four rows: 
  +--------+--------+-----------------+------+----------+-----------+
 | depart | arrive |route           | hops |distance | direction |
 +--------+--------+-----------------+------+----------+-----------+
 | ARN    | LAX    | ARN,LHR,JFK,LAX|    3 | 10942.07 | -157.06   |
 | ARN    | STL    | ARN,LHR,JFK,STL|    3 | 8409.00  | -157.06   |
 | HEL    | LAX    | HEL,LHR,JFK,LAX|    3 | 11333.86 | -161.17   |
 | HEL    | STL    | HEL,LHR,JFK,STL|    3 | 8800.79  | -161.17   |
 +--------+--------+-----------------+------+----------+-----------+ 
  That MySQL bug (#11302) was corrected in 5.0.9. 
  Route queries 
  Route queries are straightforward. How do we check that the algorithm produced no duplicate depart-arrive pairs? The following query should yield zero rows, 
  Listing 31SELECT depart, arrive, COUNT(*)FROM routesGROUP BY depart,arriveHAVING COUNT(*) > 1; 
  and does. Reachability queries are just as simple, for example where can we fly to from Helsinki? 
  Listing 32SELECT *FROM routesWHERE depart='HEL'ORDER BY distance;+----+--------+--------+------+-----------------+----------+-----------+| id | depart | arrive | hops | route           | distance | direction |+----+--------+--------+------+-----------------+----------+-----------+| 21 | HEL    | ARN    |    1 | HEL,ARN         | 398.99   | -173.08   ||  8 | HEL    | LHR    |    1 | HEL,LHR         | 1841.91  | -161.17   || 16 | HEL    | CDG    |    1 | HEL,CDG         | 1912.96  | -153.46   || 26 | HEL    | JFK    |    2 | HEL,LHR,JFK     | 7392.68  | -161.17   || 38 | HEL    | STL    |    3 | HEL,LHR,JFK,STL | 8800.79  | -161.17   || 37 | HEL    | LAX    |    3 | HEL,LHR,JFK,LAX | 11333.86 | -161.17   |+----+--------+--------+------+-----------------+----------+-----------+ 
  An extended edge list model is simple to implement, gracefully accepts extended attributes for nodes, edge and paths, does not unduly penalise updates, and responds to queries with reasonable speed.  
  Parts explosions 
  A bill of materials for a house would include the cement block, lumber, shingles, doors, wallboard, windows, plumbing, electrical system, heating system, and so on. Each subassembly also has a bill of materials; the heating system has a furnace, ducts, and so on. A bill of materials implosion links component pieces to a major assembly. A bill of materials explosion breaks apart assemblies and subassemblies into their component parts. 
  Which graph model best handles a parts explosion? Combining edge list and "nested sets" algorithms seems a natural solution.  
  Imagine a new company that plans to make variously sized bookcases, either packaged as do-it-yourself kits of, or assembled from sides, shelves, shelf brackets, backboards, feet and screws. Shelves and sides are cut from planks. Backboards are trimmed from laminated sheeting. Feet are machine-carved from readycut blocks. Screws and shelf brackets are purchased in bulk. Here are the elements of one bookcase: 
    1 backboard, 2 x 1 m    1 laminate    8 screws  2 sides 2m x 30 cm    1 plank length 4m    12 screws  8 shelves 1 m x 30 cm (incl. top and bottom)    2 planks    24 shelf brackets  4 feet 4cm x 4cm    4 cubes    16 screws 
  which may be packaged in a box for sale at one price, or assembled as a finished product at a different price. At any time we need to be able to answer questions like 
   
   Do we have enough parts to make the bookcases on order? 
   What assemblies or packages would be most profitable to make given the current inventory? 
   
  There is no reason to break the normalising rule that item detail belongs in a nodes table, and graph logic belongs in an edges table. Edges also require a quantity attribute, for example a shelf includes four shelf brackets. Nodes and edges may also have costs and prices:  
   
   item purchase cost, 
   item assembly cost, 
   assembly cost, 
   assembly selling price. 
   
  In many parts problems like this one, items occur in multiple assemblies and subassemblies. The graph is not a tree. Also, it is often desirable to model multiple graphs without the table glut that would arise from giving each graph its own edges table. A simple way to solve this problem is to represent multiple graphs (assemblies) in the edges table by giving every row not only childID and parentID pointers, but a pointer which identifies the root itemID of the graph to which the row belongs.  
  So the data model is just two tables, for items (nodes) and for product graphs or assemblies (edges). Assume that the company begins with a plan to sell the 2m x 1m bookcase in two forms, assembled and kit, and that the purchasing department has bought quantities of raw materials (laminate, planks, shelf supports, screws, wood cubes, boxes). Here are the nodes (items) and edges (assemblies):  
  Listing 33CREATE TABLE items (  itemID INT PRIMARY KEY AUTO_INCREMENT,  name CHAR(20) NOT NULL,  onhand INT NOT NULL DEFAULT 0,  reserved INT NOT NULL DEFAULT 0,  purchasecost DECIMAL(10,2) NOT NULL DEFAULT 0,  assemblycost DECIMAL(10,2) NOT NULL DEFAULT 0,  price DECIMAL(10,2) NOT NULL DEFAULT 0); 
  CREATE TABLE assemblies ( 
    assemblyID INT NOT NULL, 
    assemblyroot INT NOT NULL, 
    childID INT NOT NULL, 
    parentID INT NOT NULL, 
    quantity DECIMAL(10,2) NOT NULL, 
    assemblycost DECIMAL(10,2) NOT NULL, 
    PRIMARY KEY(assemblyID,childID,parentID) 
  ); 
  INSERT INTO items VALUES    -- inventory 
    (1,'laminate',40,0,4,0,8), 
    (2,'screw',1000,0,0.1,0,.2), 
    (3,'plank',200,0,10,0,20), 
    (4,'shelf bracket',400,0,0.20,0,.4), 
    (5,'wood cube',100,0,0.5,0,1), 
    (6,'box',40,0,1,0,2), 
    (7,'backboard',0,0,0,3,0), 
    (8,'side',0,0,0,8,0), 
    (9,'shelf',0,0,0,4,0), 
    (10,'foot',0,0,0,1,0), 
    (11,'bookcase2x30',0,0,0,10,0), 
    (12,'bookcase2x30 kit',0,0,0,2,0); 
  INSERT INTO assemblies VALUES 
    (1,11,1,7,1,0),      -- laminate to backboard 
    (2,11,2,7,8,0),      -- screws to backboard 
    (3,11,3,8,.5,0),     -- planks to side 
    (4,11,2,8,6,0),      -- screws to side 
    (5,11,3,9,0.25,0),   -- planks to shelf 
    (6,11,4,9,4,0),      -- shelf brackets to shelf 
    (7,11,5,10,1,0),     -- wood cubes to foot 
    (8,11,2,10,1,0),     -- screws to foot 
    (9,11,7,11,1,0),     -- backboard to bookcase 
    (10,11,8,11,2,0),    -- sides to bookcase 
    (11,11,9,11,8,0),    -- shelves to bookcase 
    (12,11,10,11,4,0),   -- feet to bookcase 
    (13,12,1,7,1,0),     -- laminate to backboard 
    (14,12,2,7,8,0),     -- screws to backboard 
    (15,12,3,8,0.5,0),   -- planks to side 
    (16,12,2,8,6,0),     -- screws to sides 
    (17,12,3,9,0.25,0),  -- planks to shelf 
    (18,12,4,9,4,0),     -- shelf brackets to shelves 
    (19,12,5,10,1,0),    -- wood cubes to foot 
    (20,12,2,10,1,0),    -- screws to foot 
    (21,12,7,12,1,0),    -- backboard to bookcase kit 
    (22,12,8,12,2,0),    -- sides to bookcase kit 
    (23,12,9,12,8,0),    -- shelves to bookcase kit 
    (24,12,10,12,4,0),   -- feet to bookcase kit 
    (25,12,6,12,1,0);    -- container box to bookcase kit 
  Now, we want a parts list, a bill of materials, which will list show parent-child relationships and quantities, and sum the costs. Could we adapt the depth-first "nested sets" treewalk algorithm (Listing 10) to this problem even though our graph is not a tree and our sets are not properly nested? Yes indeed. We just have to modify the treewalk to handle multiple parent nodes for any child node, and add code to percolate costs and quantities up the graph. Navigation remains simple using leftedge and rightedge values. This is just the sort of problem the Celko algorithm is good for: reporting! 
  Listing 34DROP PROCEDURE IF EXISTS ShowBOM;DELIMITER goCREATE PROCEDURE ShowBOM( IN root INT )BEGIN  DECLARE thischild, thisparent, rows, maxrightedge INT DEFAULT 0;  DECLARE thislevel, nextedgenum INT DEFAULT 1;  DECLARE thisqty, thiscost DECIMAL(10,2);  -- Create and seed intermediate table:  DROP TABLE IF EXISTS edges;  CREATE TABLE edges (    childID smallint NOT NULL,    parentID smallint NOT NULL,    PRIMARY KEY (childID, parentID)  ) ENGINE=HEAP;  INSERT INTO edges    SELECT childID,parentID    FROM assemblies    WHERE assemblyRoot = root;  SET maxrightedge = 2 * (1 + (SELECT COUNT(*) FROM edges));  -- Create and seed result table:  DROP TABLE IF EXISTS bom;  CREATE TABLE bom (    level SMALLINT,    nodeID SMALLINT,    parentID SMALLINT,    qty DECIMAL(10,2),    cost DECIMAL(10,2),    leftedge SMALLINT,    rightedge SMALLINT  ) ENGINE=HEAP;  INSERT INTO bom    VALUES( thislevel, root, 0, 0, 0, nextedgenum, maxrightedge );  SET nextedgenum = nextedgenum + 1;  WHILE nextedgenum < maxrightedge DO    -- How many children of this node remain in the edges table?    SET rows = (      SELECT COUNT(*)      FROM bom AS s      INNER JOIN edges AS t ON s.nodeID=t.parentID AND s.level=thislevel    );    IF rows > 0 THEN      -- There is at least one child edge.      -- Compute qty and cost, insert into bom, delete from edges.      BEGIN        -- Alas MySQL nulls MIN(t.childid) when we combine the next two queries        SET thischild = (          SELECT MIN(t.childID)          FROM bom AS s          INNER JOIN edges AS t ON s.nodeID=t.parentID AND s.level=thislevel        );        SET thisparent = (          SELECT DISTINCT t.parentID          FROM bom AS s          INNER JOIN edges AS t ON s.nodeID=t.parentID AND s.level=thislevel        );        SET thisqty = (          SELECT quantity FROM assemblies          WHERE assemblyroot = root            AND childID = thischild            AND parentID = thisparent        );        SET thiscost = (          SELECT a.assemblycost + (thisqty * (i.purchasecost + i.assemblycost ))          FROM assemblies AS a          INNER JOIN items AS i ON a.childID = i.itemID          WHERE assemblyroot = root            AND a.parentID = thisparent            AND a.childID = thischild        );        INSERT INTO bom          VALUES(thislevel+1, thischild, thisparent, thisqty, thiscost, nextedgenum, NULL);        DELETE FROM edges        WHERE childID = thischild AND parentID=thisparent;        SET thislevel = thislevel + 1;        SET nextedgenum = nextedgenum + 1;      END;    ELSE      BEGIN        -- Set rightedge, remove item from edges        UPDATE bom        SET rightedge=nextedgenum, level = -level        WHERE level = thislevel;        SET thislevel = thislevel - 1;        SET nextedgenum = nextedgenum + 1;      END;    END IF;  END WHILE;  SET rows := ( SELECT COUNT(*) FROM edges );  IF rows > 0 THEN    SELECT 'Orphaned rows remain';  ELSE    -- Total    SET thiscost = (SELECT SUM(qty*cost) FROM bom);    UPDATE bom    SET qty = 1, cost = thiscost    WHERE nodeID = root;    -- Show the result    SELECT      CONCAT(Space(Abs(level)*2), ItemName(nodeid,root)) AS Item,      ROUND(qty,2) AS Qty,      ROUND(cost, 2) AS Cost    FROM bom    ORDER BY leftedge;  END IF;END;goDELIMITER ;-- Function used by ShowBOM() to retrieve bom item names:DROP FUNCTION IF EXISTS ItemName;SET GLOBAL log_bin_trust_function_creators=TRUE;DELIMITER goCREATE FUNCTION ItemName( id INT, root INT ) RETURNS CHAR(20)BEGIN  DECLARE s CHAR(20) DEFAULT '';  SELECT name INTO s FROM items WHERE itemid=id;  RETURN IF( id = root, UCASE(s), s );END;go 
  DELIMITER ;CALL ShowBOM(11);+---------------------+------+--------+ 
  |Item               | Qty  | Cost  | 
  +---------------------+------+--------+ 
  |  BOOKCASE2X30      | 1.0 | 327.93 | 
  |    backboard       | 1.0 |   3.00 | 
  |      laminate      | 1.0 |   4.00 | 
  |      screw         | 8.0 |   0.80 | 
  |    side            | 2.0 |  16.00 | 
  |      screw         | 6.0 |   0.60 | 
  |      plank         | 0.5 |   5.00 | 
  |    shelf           | 8.0 |  32.00 | 
  |      plank         | 0.3 |   2.50 | 
  |      shelf bracket |  4.0 |  0.80 | 
  |    foot            | 4.0 |   4.00 | 
  |      screw         | 1.0 |   0.10 | 
  |      wood cube     |  1.0|   0.50 | 
  +---------------------+------+--------+ 
    
  With ShowBOM() in hand, it's easy to compare costs of assemblies and subassemblies. By adding price columns, we can do the same for prices and profit margins. And now that MySQL has re-enabled prepared statements in stored procedures, it will be relatively easy to write a more general version of ShowBOM(). We leave that to you. 
  Shorter and sweeter 
  But ShowBOM()is not the small, efficient bit of nested sets reporting code we were hopingfor. There is a simpler solution: hide graph cycles from the edges table bymaking them references to rows in a nodes table, so we can treat the edges tablelike a tree; then apply a breadth-first edge-listsubtree algorithm to generate the Bill of Materials. Again assume acabinetmaking company making bookcases (with a different costing model). Forclarity, skip inventory tracking for now. An items table ww_nodestracks purchased and assembled bookcase elements with their individual costs,and an assemblies/edges ww_edgestable tracks sets of edges that combine to make products. 
  Listing 35: DDL for a simpler parts explosionDROP TABLE IF EXISTS ww_nodes; 
  CREATE TABLE ww_nodes ( 
    nodeID int, 
    description CHAR(50), 
    cost decimal(10,2) 
  ); 
  INSERT INTO ww_nodes VALUES (1,'finished bookcase',10); 
  INSERT INTO ww_nodes VALUES (2,'backboard2x1',1); 
  INSERT INTO ww_nodes VALUES (3,'laminate2x1',8); 
  INSERT INTO ww_nodes VALUES (4,'screw',.10); 
  INSERT INTO ww_nodes VALUES (5,'side',4); 
  INSERT INTO ww_nodes VALUES (6,'plank',20); 
  INSERT INTO ww_nodes VALUES (7,'shelf',4); 
  INSERT INTO ww_nodes VALUES (8,'shelf bracket',.5); 
  INSERT INTO ww_nodes VALUES (9,'feet',1); 
  INSERT INTO ww_nodes VALUES (10,'cube4cmx4cm',1); 
  INSERT INTO ww_nodes VALUES (11,'bookcase kit',2); 
  INSERT INTO ww_nodes VALUES (12,'carton',1); 
    
  DROP TABLE IF EXISTS ww_edges; 
  CREATE TABLE ww_edges ( 
    rootID INT, 
    nodeID int, 
    parentnodeID int, 
    qty decimal(10,2) 
  ); 
  INSERT INTO ww_edges VALUES (1,1,null,1); 
  INSERT INTO ww_edges VALUES (1,2,1,1); 
  INSERT INTO ww_edges VALUES (1,3,2,1); 
  INSERT INTO ww_edges VALUES (1,4,2,8); 
  INSERT INTO ww_edges VALUES (1,5,1,2); 
  INSERT INTO ww_edges VALUES (1,6,5,1); 
  INSERT INTO ww_edges VALUES (1,4,5,12); 
  INSERT INTO ww_edges VALUES (1,7,1,8); 
  INSERT INTO ww_edges VALUES (1,6,7,.5); 
  INSERT INTO ww_edges VALUES (1,8,7,4); 
  INSERT INTO ww_edges VALUES (1,9,1,4); 
  INSERT INTO ww_edges VALUES (1,10,9,1); 
  INSERT INTO ww_edges VALUES (1,4,9,1); 
    
  INSERT INTO ww_edges VALUES (11,11,null,1); 
  INSERT INTO ww_edges VALUES (11,2,11,1); 
  INSERT INTO ww_edges VALUES (11,3,2,1); 
  INSERT INTO ww_edges VALUES (11,4,2,8); 
  INSERT INTO ww_edges VALUES (11,5,11,2); 
  INSERT INTO ww_edges VALUES (11,6,5,1); 
  INSERT INTO ww_edges VALUES (11,4,5,12); 
  INSERT INTO ww_edges VALUES (11,7,11,8); 
  INSERT INTO ww_edges VALUES (11,6,7,.5); 
  INSERT INTO ww_edges VALUES (11,8,7,4); 
  INSERT INTO ww_edges VALUES (11,9,11,4); 
  INSERT INTO ww_edges VALUES (11,10,9,1); 
  INSERT INTO ww_edges VALUES (11,4,9,11); 
  INSERT INTO ww_edges VALUES (11,12,11,1); 
  Hereis an adaptation of the breadth-first edge list algorithm to retrieve a Bill ofMaterials for a product identified by a rootID: 
  ·  Initialise a level-tracking variable to zero. 
  ·  Seed a tempreporting table with the rootIDof the desired product. 
  ·  While rows are being retrieved, increment the level tracking variable andadd rows to the temptable whose parentnodeIDsare nodes at the current level. 
  ·  Print the BOM ordered bypath with indentation proportional to tree level. 
  Listing 36: A simpler parts explosion 
  DROP PROCEDURE IF EXISTS ww_bom; 
  DELIMITER go 
  CREATE PROCEDURE ww_bom( root INT ) 
  BEGIN 
    DECLARE lev INT DEFAULT 0; 
    DECLARE totalcost DECIMAL( 10,2); 
    DROP TABLE IF EXISTS temp; 
    CREATE TABLE temp                                 -- initialise temp table with root node 
    SELECT 
      e.nodeID AS nodeID, 
      n.description AS Item, 
      e.parentnodeID, 
      e.qty, 
      n.cost AS nodecost, 
      e.qty * n.cost AS cost, 
      0 as level,                                     -- tree level 
      CONCAT(e.nodeID,'') AS path                     -- path to this node as a string 
    FROM ww_nodes n 
    JOIN ww_edges e USING(nodeID)                     -- root node 
    WHERE e.nodeID = root AND e.parentnodeID IS NULL; 
    WHILE FOUND_ROWS() > 0 DO  
      BEGIN 
        SET lev = lev+1;                              -- increment level 
        INSERT INTO temp                              -- add children of this level 
        SELECT  
          e.nodeID, 
          n.description AS Item, 
          e.parentnodeID, 
          e.qty, 
          n.cost AS nodecost, 
          e.qty * n.cost AS cost, 
          lev,                                 
          CONCAT(t.path,',',e.nodeID) 
        FROM ww_nodes n 
        JOIN ww_edges e USING(nodeID) 
        JOIN temp t ON e.parentnodeID = t.nodeID 
        WHERE e.rootID = root AND t.level = lev-1; 
      END; 
    END WHILE; 
    WHILE lev > 0 DO                                  -- percolate costs up the graph 
      BEGIN 
        SET lev = lev - 1; 
        DROP TABLE IF EXISTS tempcost; 
        CREATE TABLE tempcost                         -- compute child cost 
        SELECT p.nodeID, SUM(c.nodecost*c.qty) AS childcost 
        FROM temp p  
        JOIN temp c ON p.nodeid=c.parentnodeid 
        WHERE c.level=lev 
        GROUP by p.nodeid; 
        UPDATE temp JOIN tempcost USING(nodeID)       -- update parent item cost 
        SET nodecost = nodecost + tempcost.childcost; 
        UPDATE temp SET cost = qty * nodecost         -- update parent cost 
        WHERE level=lev-1; 
      END; 
    END WHILE; 
    SELECT                                            -- list BoM 
      CONCAT(SPACE(level*2),Item) AS Item, 
      ROUND(nodecost,2) AS 'Unit Cost', 
      ROUND(Qty,0) AS Qty,ROUND(cost,2) AS Cost FROM temp 
    ORDER by path;   
  END go 
  DELIMITER ; 
  CALL ww_bom( 1 ); 
  +-------------------+-----------+------+--------+ 
  | Item              | Unit Cost | Qty  | Cost   | 
  +-------------------+-----------+------+--------+ 
  | finished bookcase |    206.60 |  1.0 | 206.60 | 
  |   backboard2x1    |      9.80 |  1.0 |   9.80 | 
  |     laminate2x1   |      8.00 |  1.0 |   8.00 | 
  |     screw         |      0.10 |  8.0 |   0.80 | 
  |   side            |     25.20 |  2.0 |  50.40 | 
  |     screw         |      0.10 | 12.0 |   1.20 | 
  |     plank         |     20.00 |  1.0 |  20.00 | 
  |   shelf           |     16.00 |  8.0 | 128.00 | 
  |     plank         |     20.00 |  0.5 |  10.00 | 
  |     shelf bracket |      0.50 |  4.0 |   2.00 | 
  |   foot            |      2.10 |  4.0 |   8.40 | 
  |     cube4cmx4cm   |      1.00 |  1.0 |   1.00 | 
  |     screw         |      0.10 |  1.0 |   0.10 | 
  +-------------------+-----------+------+--------+ 
  Summary 
  Stored procedures, stored functions and Views make it possible to implement edge list graph models, nested sets graph models, and breadth-first and depth-first graph search algorithms in MySQL5&6.  
  Further Reading 
  Celko J, "Trees and Hierarchies in SQL For Smarties", Morgan Kaufman, San Francisco, 2004. 
  Codersource.net, "Branch and Bound Algorithm in C#", http://www.codersource.net/csharp_branch_and_bound_algorithm_implementation.aspx. 
  Math Forum, "Euler's Solution: The Degree of a Vertex", http://mathforum.org/isaac/problems/bridges2.html 
  Muhammad RB, "Trees", http://www.personal.kent.edu/~rmuhamma/GraphTheory/MyGraphTheory/trees.htm. 
  Mullins C, "The Future of SQL", http://www.craigsmullins.com/idug_sql.htm. 
  Rodrigue J-P, "Graph Theory: Definition and Properties", http://people.hofstra.edu/geotrans/eng/ch2en/meth2en/ch2m1en.html. 
  Santry P, "Recursive SQL User Defined Functions", http://www.wwwcoder.com/main/parentid/191/site/1857/68/default.aspx. 
  Shasha D, Wang JTL, and Giugno R, "Algorithmics and applications of tree and graph searching", In Symposium on Principles of Database Systems, 2002, p 39--52. 
  Stephens S, "Solving directed graph problems with SQL, Part I", http://builder.com.com/5100-6388_14-5245017.html. 
  Stephens, S, "Solving directed graph problems with SQL, Part II", http://builder.com.com/5100-6388_14-5253701.html. 
  Steinbach T, "Migrating Recursive SQL from Oracle to DB2 UDB", http://www-106.ibm.com/developerworks/db2/library/techarticle/0307steinbach/0307steinbach.html. 
  Tropashko V, "Nested Intervals Tree Encoding in SQL, http://www.sigmod.org/sigmod/record/issues/0506/p47-article-tropashko.pdf 
  Van Tulder G, "Storing Hierarchical Data in a Database", http://www.sitepoint.com/print/hierarchical-data-database. 
  Venagalla S, "Expanding Recursive Opportunities with SQL UDFs in DB2 v7.2", http://www-106.ibm.com/developerworks/db2/library/techarticle/0203venigalla/0203venigalla.html. 
  Wikipedia, "Graph Theory", http://en.wikipedia.org/wiki/Graph_theory. 
  Wikipedia, “Tree traversal”, Wikipedia, “Tree traversal”, http://en.wikipedia.org/wiki/Tree_traversal. 
  Willets K, "SQL Graph Algorithms", http://willets.org/sqlgraphs.html.

Trees and Other Hierarchies in MySQL

Trees and Other Hierarchies in MySQL

Graph characteristics and models

Models for computing graphs

Graphs and SQL

The edge list

Edge-adjacency list model of a tree

Walking an edge list tree

Enumerating paths in an edge-adjacency list

Automate tree drawing!

Nested sets model of a tree

How to build a nested sets representation from an edge list

Finding a node's parent and children

Other queries

Displaying the tree

Node insertions, updates and deletions

Nesteds set model summary

Edge list model of a non-tree graph

Airports (nodes)

Flights (edges)

Routes (paths)

Next allowed routes

Replace longer routes with shorter ones

Route queries

Parts explosions

Shorter and sweeter

Summary

Further Reading

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