Trees in MongoDB

Trees in MongoDBPosted on 引用地址：%20in%20MongoDB.html 树结构存储最好的方式常常依赖于要执行的操作；下面讨论一下不同的存储方案。在实践中，许多开发人员找到了一些使用起来很方便的模式：单文档存储整根树(Full Tree in single Document)，父连接(P

Trees in MongoDB Posted on

引用地址：%20in%20MongoDB.html

树结构存储最好的方式常常依赖于要执行的操作；下面讨论一下不同的存储方案。在实践中，许多开发人员找到了一些使用起来很方便的模式：“单文档存储整根树(Full Tree in single Document)”，“父连接(Parent Links)”和“祖先数组(Array of Ancestors)”。

1 模式 1.1 单文档存储整根树(Full Tree in Signle Document)

{

comments: [

{by: "mathias", text: "...", replies: []}

{by: "eliot", text: "...", replies: [

{by: "mike", text: "...", replies: []}

]}

]

}

优点：

缺点：

1.2 (父连接)Parent Links

用单个集合来存储所有节点，服务器空间，每个节点包含他父节点的ID，是一种简单的解决方案。这种方法最大的问题是获取完整子树时需要查找多次数据库（或使用db.eval函数）。

> t = db.tree1; > t.find() { "_id" : 1 } { "_id" : 2, "parent" : 1 } { "_id" : 3, "parent" : 1 } { "_id" : 4, "parent" : 2 } { "_id" : 5, "parent" : 4 } { "_id" : 6, "parent" : 4 } > // find children of node 4 > t.ensureIndex({parent:1}) > t.find( {parent : 4 } ) { "_id" : 5, "parent" : 4 } { "_id" : 6, "parent" : 4 } 1.3 (子链接)Child Links

另一种选择是在每个节点文档中存储所有子节点的ID。这个方法是有限制的，如果不操作完整子树是没有问题。他可能也是用于存储一个节点有多个父节点情况的最有效方法。

> t = db.tree2 > t.find() { "_id" : 1, "children" : [ 2, 3 ] } { "_id" : 2 } { "_id" : 3, "children" : [ 4 ] } { "_id" : 4 } > // find immediate children of node 3 > t.findOne({_id:3}).children [ 4 ] > // find immediate parent of node 3 > t.ensureIndex({children:1}) > t.find({children:3}) { "_id" : 1, "children" : [ 2, 3 ] } 1.4 (祖先数组)Array of Ancestors

在这种方法中将一个节点的所有祖先节点存储到一个数组中。这使得类似于“获取X节点的所有子节点”的操作快且容易。

> t = db.mytree; > t.find() { "_id" : "a" } { "_id" : "b", "ancestors" : [ "a" ], "parent" : "a" } { "_id" : "c", "ancestors" : [ "a", "b" ], "parent" : "b" } { "_id" : "d", "ancestors" : [ "a", "b" ], "parent" : "b" } { "_id" : "e", "ancestors" : [ "a" ], "parent" : "a" } { "_id" : "f", "ancestors" : [ "a", "e" ], "parent" : "e" } { "_id" : "g", "ancestors" : [ "a", "b", "d" ], "parent" : "d" } > t.ensureIndex( { ancestors : 1 } ) > // find all descendents of b: > t.find( { ancestors : 'b' }) { "_id" : "c", "ancestors" : [ "a", "b" ], "parent" : "b" } { "_id" : "d", "ancestors" : [ "a", "b" ], "parent" : "b" } { "_id" : "g", "ancestors" : [ "a", "b", "d" ], "parent" : "d" } > // get all ancestors of f: > anc = db.mytree.findOne({_id:'f'}).ancestors [ "a", "e" ] > db.mytree.find( { _id : { $in : anc } } ) { "_id" : "a" } { "_id" : "e", "ancestors" : [ "a" ], "parent" : "a" }

ensureIndex和MongoDB的multikey特性可以使上面的查询更高效。

除了祖先数组，我们也存储了节点的直接父节点，使得查找节点的直接父节点更容易。

1.5 物化路径(Materialized Path[Full Path in Each Node))

物化路径使得对树的特定查询容易。我们在每个节点中存储文档在树中位置的全路径。通常情况下上面提到的“祖先数组”方法都工作很好；当不得不处理字符串建造、正则表达式，字符逃逸，物化路径更容易。（理论上，物化路径将会更快。）

MongoDB实现物化路径最好的方式是将路径存储成字符串，然后采用正则表达式查询。以“^”开头的正则表达可以被高效执行。把数据看作一个字符串，你需要选择一个分隔符，我们采用“,”。举例：

> t = db.tree test.tree > // get entire tree -- we use sort() to make the order nice > t.find().sort({path:1}) { "_id" : "a", "path" : "a," } { "_id" : "b", "path" : "a,b," } { "_id" : "c", "path" : "a,b,c," } { "_id" : "d", "path" : "a,b,d," } { "_id" : "g", "path" : "a,b,g," } { "_id" : "e", "path" : "a,e," } { "_id" : "f", "path" : "a,e,f," } { "_id" : "g", "path" : "a,b,g," } > t.ensureIndex( {path:1} ) > // find the node 'b' and all its descendents: > t.find( { path : /^a,b,/ } ) { "_id" : "b", "path" : "a,b," } { "_id" : "c", "path" : "a,b,c," } { "_id" : "d", "path" : "a,b,d," } { "_id" : "g", "path" : "a,b,g," } > // find the node 'b' and its descendents, where path to 'b' is not already known: > nodeb = t.findOne( { _id : "b" } ) { "_id" : "b", "path" : "a,b," } > t.find( { path : new RegExp("^" + nodeb.path) } ) { "_id" : "b", "path" : "a,b," } { "_id" : "c", "path" : "a,b,c," } { "_id" : "d", "path" : "a,b,d," } { "_id" : "g", "path" : "a,b,g," }

Ruby实例：

嵌套数据集：