MongoDB Query Document

Grammar

The syntax format for MongoDB query data is as follows:

>db. Collection_name.find ()

The Find () method displays all documents in an unstructured manner.

If you need to read the data in an easy-to-read way, you can use the pretty () method, which has the following syntax:

>db.col.find (). Pretty ()

The pretty () method displays all documents in a formatted manner.

Instance

The following examples let us query the data in the set col:

> Db.col.find (). Pretty () {        "_id": ObjectId ("56063f17ade2f21f36b03133"),        "title": "MongoDB Tutorial",        " Description ":" MongoDB is a Nosql database ",        " by ":" W3cschool ",        " url ":" http://www.w3cschool.cn ",        " tags ": [
   
     "MongoDB",                "database", "                NoSQL", "        likes": 100}
   

In addition to the find () method, there is a FindOne () method that returns only one document.

MongoDB versus RDBMS Where statement comparison

If you are familiar with regular SQL data, the following table provides a better understanding of MongoDB conditional statement queries:

Operation	format	Example	similar statements in an RDBMS
Equals	{<key>:<value>}	db.col.find({"by":"w3cschool"}).pretty()	where by = ‘w3cschool‘
Less than	{<key>:{$lt:<value>}}	db.col.find({"likes":{$lt:50}}).pretty()	where likes < 50
Less than or equal to	{<key>:{$lte:<value>}}	db.col.find({"likes":{$lte:50}}).pretty()	where likes <= 50
Greater than	{<key>:{$gt:<value>}}	db.col.find({"likes":{$gt:50}}).pretty()	where likes > 50
Greater than or equal to	{<key>:{$gte:<value>}}	db.col.find({"likes":{$gte:50}}).pretty()	where likes >= 50
Not equal to	{<key>:{$ne:<value>}}	db.col.find({"likes":{$ne:50}}).pretty()	where likes != 50

MongoDB and condition

The MongoDB find () method can pass in multiple keys (key), each separated by commas, and the regular SQL and condition.

The syntax format is as follows:

>db.col.find ({key1:value1, key2:value2}). Pretty ()

Instance

The following example uses the by and title keys to query data for MongoDB tutorials in w3cschool

> Db.col.find ({"By": "W3cschool", "title": "MongoDB Tutorial"}). Pretty () {        "_id": ObjectId ("56063f17ade2f21f36b03133 "),        " title ":" MongoDB Tutorial ",        " description ":" MongoDB is a Nosql database ",        " by ":" W3cschool ",        " url ":" http://w Ww.w3cschool.cn ",        " tags ": [                " MongoDB ",                " database ",                " NoSQL "        ],        " likes ": 100}

The above example is similar to the WHERE statement:where by= ' W3cschool ' and title= ' MongoDB tutorial '

MongoDB OR Condition

The MongoDB OR conditional statement uses the keyword $orin the following syntax format:

>db.col.find (   {      $or: [     {key1:value1}, {key2:value2}      ]   }). Pretty ()

Instance

In the following example, we demonstrate that the query key by value is W3cschool or the key title value for the MongoDB tutorial document.

>db.col.find ({$or: [{"By": "W3cschool"},{"title": "MongoDB Tutorial"}]}). Pretty () {        "_id": ObjectId (" 56063f17ade2f21f36b03133 "),        " title ":" MongoDB Tutorial ",        " description ":" MongoDB is a Nosql database ",        " by ":" W3cschool ",        " url ":" http://www.w3cschool.cn ",        " tags ": [                " MongoDB ",                " database ",                " NoSQL "        ],        "likes": 100}>

Combined with and OR

The following examples demonstrate the combined use of and and or, similar to the general SQL statement: ' where likes>50 and (by = ' W3cschool ' or title = ' MongoDB tutorial ') '

>db.col.find ({"likes": {$gt: $}, $or: [{"By": "W3cschool"},{"title": "MongoDB Tutorial"}]}). Pretty () {        "_id": ObjectId ("56063f17ade2f21f36b03133"),        "title": "MongoDB Tutorial",        "description": "MongoDB is a Nosql database",        "by ":" W3cschool ",        " url ":" http://www.w3cschool.cn ",        " tags ": [                " MongoDB ",                " database ",                " NoSQL "        ],        "likes": 100}

MongoDB Query Document