The data type of the field is String. I would like to fetch the data where character length of field name is greater than 40.
I tried these queries but returning error. 1.
db.usercollection.find( {$where: "(this.name.length > 40)"} ).limit(2); output :error: { "$err" : "TypeError: Cannot read property 'length' of undefined near '40)' ", "code" : 16722 }
this is working in 2.4.9 But my version is 2.6.5
As for the logical condition, there are String Aggregation Operators that you can use $strLenCP operator to check the length of the string. If the length is $gt a specified value, then this is a true match and the document is "kept".
to do a text search on all fields, you first must create a text index on all fields. as the mongodb documentation indicates, "To allow for text search on all fields with string content, use the wildcard specifier ($**) to index all fields that contain string content."
string. A string of terms that MongoDB parses and uses to query the text index. MongoDB performs a logical OR search of the terms unless specified as a phrase. See Behavior for more information on the field.
In MongoDB, we can perform text search using text index and $text operator. Text index: MongoDB proved text indexes that are used to find the specified text from the string content. Text indexes should be either a string or an array of string elements.
For MongoDB 3.6 and newer:
The $expr
operator allows the use of aggregation expressions within the query language, thus you can leverage the use of $strLenCP
operator to check the length of the string as follows:
db.usercollection.find({ "name": { "$exists": true }, "$expr": { "$gt": [ { "$strLenCP": "$name" }, 40 ] } })
For MongoDB 3.4 and newer:
You can also use the aggregation framework with the $redact
pipeline operator that allows you to proccess the logical condition with the $cond
operator and uses the special operations $$KEEP
to "keep" the document where the logical condition is true or $$PRUNE
to "remove" the document where the condition was false.
This operation is similar to having a $project
pipeline that selects the fields in the collection and creates a new field that holds the result from the logical condition query and then a subsequent $match
, except that $redact
uses a single pipeline stage which is more efficient.
As for the logical condition, there are String Aggregation Operators that you can use $strLenCP
operator to check the length of the string. If the length is $gt
a specified value, then this is a true match and the document is "kept". Otherwise it is "pruned" and discarded.
Consider running the following aggregate operation which demonstrates the above concept:
db.usercollection.aggregate([ { "$match": { "name": { "$exists": true } } }, { "$redact": { "$cond": [ { "$gt": [ { "$strLenCP": "$name" }, 40] }, "$$KEEP", "$$PRUNE" ] } }, { "$limit": 2 } ])
If using $where
, try your query without the enclosing brackets:
db.usercollection.find({$where: "this.name.length > 40"}).limit(2);
A better query would be to to check for the field's existence and then check the length:
db.usercollection.find({name: {$type: 2}, $where: "this.name.length > 40"}).limit(2);
or:
db.usercollection.find({name: {$exists: true}, $where: "this.name.length > 40"}).limit(2);
MongoDB evaluates non-$where
query operations before $where
expressions and non-$where
query statements may use an index. A much better performance is to store the length of the string as another field and then you can index or search on it; applying $where
will be much slower compared to that. It's recommended to use JavaScript expressions and the $where
operator as a last resort when you can't structure the data in any other way, or when you are dealing with a small subset of data.
A different and faster approach that avoids the use of the $where
operator is the $regex
operator. Consider the following pattern which searches for
db.usercollection.find({"name": {"$type": 2, "$regex": /^.{41,}$/}}).limit(2);
Note - From the docs:
If an index exists for the field, then MongoDB matches the regular expression against the values in the index, which can be faster than a collection scan. Further optimization can occur if the regular expression is a “prefix expression”, which means that all potential matches start with the same string. This allows MongoDB to construct a “range” from that prefix and only match against those values from the index that fall within that range.
A regular expression is a “prefix expression” if it starts with a caret
(^)
or a left anchor(\A)
, followed by a string of simple symbols. For example, the regex/^abc.*/
will be optimized by matching only against the values from the index that start withabc
.Additionally, while
/^a/, /^a.*/,
and/^a.*$/
match equivalent strings, they have different performance characteristics. All of these expressions use an index if an appropriate index exists; however,/^a.*/
, and/^a.*$/
are slower./^a/
can stop scanning after matching the prefix.
Queries with $where
and $expr
are slow if there are too many documents.
Using $regex
is much faster than $where
, $expr
.
db.usercollection.find({ "name": /^[\s\S]{40,}$/, // name.length >= 40 }) or db.usercollection.find({ "name": { "$regex": "^[\s\S]{40,}$" }, // name.length >= 40 })
This query is the same meaning with
db.usercollection.find({ "$where": "this.name && this.name.length >= 40", }) or db.usercollection.find({ "name": { "$exists": true }, "$expr": { "$gte": [ { "$strLenCP": "$name" }, 40 ] } })
I tested each queries for my collection.
# find $where: 10529.359ms $expr: 5305.801ms $regex: 2516.124ms # count $where: 10872.006ms $expr: 2630.155ms $regex: 158.066ms
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