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    <p>In the link from dm's post Dwight Merriman mentions using a path key and doing regex matches</p> <pre><code>{ path : "a.b.c.d.e.f" } </code></pre> <p>Another way to do this would be with arrays</p> <pre><code>{ path : ["a", "b", "c", "d", "e", "f"] } db.test.ensureIndex({path: 1}) </code></pre> <p>that should make it pretty fast. </p> <p>if each node can only be in a single path then you wouldn't need to do worry about where it is located in the list</p> <pre><code>db.test.find({path: "a"}) </code></pre> <p>would find all children of "a"</p> <p>Instead of path names I would probably use the _id of the nodes.</p> <p><strong>Update</strong></p> <ul> <li>one thing to be careful of is that an index can only have one array in it. </li> <li><p>Be careful to use explain on your queries</p> <p>db.test.find({path: {$in: ["a", "b"]})</p></li> </ul> <p>gives you </p> <pre><code> db.test.find({path: {$in: ["a", "b"]}}).explain() { "cursor" : "BtreeCursor path_1 multi", "nscanned" : 2, "nscannedObjects" : 2, "n" : 1, "millis" : 0, "nYields" : 0, "nChunkSkips" : 0, "isMultiKey" : true, "indexOnly" : false, "indexBounds" : { "path" : [ [ "a", "a" ], [ "b", "b" ] ] } } </code></pre> <p>but </p> <pre><code> db.test.find({path: {$all: ["a", "b"]}}).explain() { "cursor" : "BtreeCursor path_1", "nscanned" : 1, "nscannedObjects" : 1, "n" : 1, "millis" : 0, "nYields" : 0, "nChunkSkips" : 0, "isMultiKey" : true, "indexOnly" : false, "indexBounds" : { "path" : [ [ "a", "a" ] ] } } </code></pre> <p>only uses the first element and then scans all matching results for b.<br> If a is your root element or is in most of your records then your doing a nearly full scan of the records instead of an efficient index query.</p>
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