例子:
> db.stuff.save({"foo":"bar"});
> db.stuff.find({"foo":"bar"}).count();
1
> db.stuff.find({"foo":"BAR"}).count();
0
例子:
> db.stuff.save({"foo":"bar"});
> db.stuff.find({"foo":"bar"}).count();
1
> db.stuff.find({"foo":"BAR"}).count();
0
当前回答
这些已经用于字符串搜索进行了测试
{'_id': /.*CM.*/} ||find _id where _id contains ->CM
{'_id': /^CM/} ||find _id where _id starts ->CM
{'_id': /CM$/} ||find _id where _id ends ->CM
{'_id': /.*UcM075237.*/i} ||find _id where _id contains ->UcM075237, ignore upper/lower case
{'_id': /^UcM075237/i} ||find _id where _id starts ->UcM075237, ignore upper/lower case
{'_id': /UcM075237$/i} ||find _id where _id ends ->UcM075237, ignore upper/lower case
其他回答
博士TL;
正确的方法做到这一点在mongo
不使用RegExp
使用mongodb的内置索引,搜索
第一步:
db.articles.insert(
[
{ _id: 1, subject: "coffee", author: "xyz", views: 50 },
{ _id: 2, subject: "Coffee Shopping", author: "efg", views: 5 },
{ _id: 3, subject: "Baking a cake", author: "abc", views: 90 },
{ _id: 4, subject: "baking", author: "xyz", views: 100 },
{ _id: 5, subject: "Café Con Leche", author: "abc", views: 200 },
{ _id: 6, subject: "Сырники", author: "jkl", views: 80 },
{ _id: 7, subject: "coffee and cream", author: "efg", views: 10 },
{ _id: 8, subject: "Cafe con Leche", author: "xyz", views: 10 }
]
)
第二步:
需要在你想要搜索的任何TEXT字段上创建索引,没有索引查询将会非常慢
db.articles.createIndex( { subject: "text" } )
第三步:
db.articles.find( { $text: { $search: "coffee",$caseSensitive :true } } ) //FOR SENSITIVITY
db.articles.find( { $text: { $search: "coffee",$caseSensitive :false } } ) //FOR INSENSITIVITY
我为不区分大小写的正则表达式创建了一个简单的Func,我在过滤器中使用它。
private Func<string, BsonRegularExpression> CaseInsensitiveCompare = (field) =>
BsonRegularExpression.Create(new Regex(field, RegexOptions.IgnoreCase));
然后,只需按如下方式筛选一个字段。
db.stuff.find({"foo": CaseInsensitiveCompare("bar")}).count();
你可以使用不区分大小写的索引:
下面的示例创建一个没有默认排序规则的集合,然后在名称字段上添加一个索引,排序规则不区分大小写。Unicode国际组件
/* strength: CollationStrength.Secondary
* Secondary level of comparison. Collation performs comparisons up to secondary * differences, such as diacritics. That is, collation performs comparisons of
* base characters (primary differences) and diacritics (secondary differences). * Differences between base characters takes precedence over secondary
* differences.
*/
db.users.createIndex( { name: 1 }, collation: { locale: 'tr', strength: 2 } } )
要使用索引,查询必须指定相同的排序规则。
db.users.insert( [ { name: "Oğuz" },
{ name: "oğuz" },
{ name: "OĞUZ" } ] )
// does not use index, finds one result
db.users.find( { name: "oğuz" } )
// uses the index, finds three results
db.users.find( { name: "oğuz" } ).collation( { locale: 'tr', strength: 2 } )
// does not use the index, finds three results (different strength)
db.users.find( { name: "oğuz" } ).collation( { locale: 'tr', strength: 1 } )
或者你可以创建一个默认排序规则的集合:
db.createCollection("users", { collation: { locale: 'tr', strength: 2 } } )
db.users.createIndex( { name : 1 } ) // inherits the default collation
你可以使用正则表达式。
在你的例子中,这将是:
db.stuff.find( { foo: /^bar$/i } );
不过,我必须说,也许你可以降低(或提高)价值的过程中,而不是承担额外的成本,每次你找到它。显然,这对人名之类的东西不起作用,但可能用在像标签这样的用例上。
在使用基于Regex的查询时要记住一件非常重要的事情——当您在登录系统中执行此操作时,转义正在搜索的每个字符,不要忘记^和$操作符。Lodash有一个很好的函数,如果你已经在使用它:
db.stuff.find({$regex: new RegExp(_.escapeRegExp(bar), $options: 'i'})
为什么?假设一个用户输入。*作为他的用户名。这将匹配所有用户名,只需猜测任何用户的密码就可以登录。