mongoDB prefix wildcard: fulltext-search ($text) find part with search-string

What you are trying to do in your second example is prefix wildcard search in your collection mycoll on field foo. This is not something the textsearch feature is designed for and it is not possible to do it with $text operator. This behaviour does not include wildcard prefix search on any given token in the indexed field. However you can alternatively perform regex search as others suggested. Here is my walkthrough:

>db.mycoll.find()
{ "_id" : ObjectId("53add9364dfbffa0471c6e8e"), "foo" : "my super cool item" }
{ "_id" : ObjectId("53add9674dfbffa0471c6e8f"), "foo" : "your not so cool item" }
> db.mycoll.find({ $text: { $search: "super"} })
{ "_id" : ObjectId("53add9364dfbffa0471c6e8e"), "foo" : "my super cool item" }
> db.mycoll.count({ $text: { $search: "uper"} })
0

The $text operator supports search for a single word, search for one or more words or search for phrase. The kind of search you wish is not supported

The regex solution:

> db.mycoll.find({foo:/uper/})
{ "_id" : ObjectId("53add9364dfbffa0471c6e8e"), "foo" : "my super cool item" }
> 

The answer to your final question: to do mysql style %super% in mongoDB you would most likely have to do:

db.mycoll.find( { foo : /.*super.*/ } );

It's not possible to do it with $text operator.

Text indexes are created with the terms included in the string value or in an array of strings and the search is based in those indices.

You can only group terms on a phrase but not take part of them.

Read $text operator reference and text indexes description.

I don't have enough reputation to comment jasenkoh solution, but this is clearly the best way to deal with this situation.

In OP situation, I would:

db.mycoll.createIndex( { foo: "text" } )
db.mycoll.createIndex( { foo: 1 } )
db.mycoll.find({$or: [{$text: {$search: 'uper'}}, {foo: {$regex: 'uper'}}]})

For better performances (but slightly different results), replace the last line with:

db.mycoll.find({$or: [{$text: {$search: 'uper'}}, {foo: {$regex: '^uper'}}]})

It should work with /uper/.

See http://docs.mongodb.org/manual/reference/operator/query/regex/ for details.

Edit:

As per request in the comments:

The solution wasn't necessarily meant to actually give what the OP requested, but what he needed to solve the problem.

Since $regex searches don't work with text indices, a simple regex search over an indexed field should give the expected result, though not using the requested means.

Actually, it is pretty easy to do this:

db.collection.insert( {foo: "my super cool item"} )
db.collection.insert( {foo: "your not so cool item"})
db.collection.ensureIndex({ foo: 1 })
db.collection.find({'foo': /uper/})

gives us the expected result:

{ "_id" : ObjectId("557f3ba4c1664dadf9fcfe47"), "foo" : "my super cool item" }

An added explain shows us that the index was used efficiently:

{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.collection",
        "indexFilterSet" : false,
        "parsedQuery" : {
            "foo" : /uper/
        },
        "winningPlan" : {
            "stage" : "FETCH",
            "inputStage" : {
                "stage" : "IXSCAN",
                "filter" : {
                    "foo" : /uper/
                },
                "keyPattern" : {
                    "foo" : 1
                },
                "indexName" : "foo_1",
                "isMultiKey" : false,
                "direction" : "forward",
                "indexBounds" : {
                    "foo" : [
                        "[\"\", {})",
                        "[/uper/, /uper/]"
                    ]
                }
            }
        },
        "rejectedPlans" : [ ]
    },
    "serverInfo" : {
        // skipped
    },
    "ok" : 1
}

To make a long story short: No, you can not reuse a $text index, but you can do the query efficiently. Like written in Implement auto-complete feature using MongoDB search , one could probably be even more efficient by using a map/reduce approach, eliminating redundancy and unnecessary stop words from the indices, at the cost of being not real time any more.