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Query Your Data

You can type MongoDB filter documents into the query bar to display only documents which match the specified criteria. To learn more about querying documents, see Query Documents in the MongoDB manual.

  1. In the Filter field, enter a filter document. You can use all of the MongoDB query operators except the $text and $expr operators.

    Beaker IconExample

    The following filter only returns documents which have a Country value of Brazil:

    { Country: "Brazil" }
  2. Click Find to run the query and view the updated results.

Info With Circle IconCreated with Sketch.Note

For query result sets larger than 1000 documents, Compass shows a sampling of the results. Otherwise, Compass shows the entire result set.

For details on sampling, see Sampling.

The Compass Filter supports using the mongo shell mode representation of the MongoDB Extended JSON BSON data types.

Beaker IconExample

The following filter returns documents where start_date is greater than than the BSON Date 2017-05-01:

{ "start_date": {$gt: new Date('2017-05-01')} }

By specifying the Date type in both start_date and the $gt comparison operator, Compass performs the greater than comparison chronologically, returning documents with start_date later than 2017-05-01.

Without the Date type specification, Compass compares the start_dates as strings lexicographically, instead of comparing the values chronologically.

To clear the query bar and the results of the query, click Reset.

$filter corresponds to the WHERE clause in a SQL SELECT statement.

Beaker IconExample

You have 3,235 articles. You would like to see all articles that Joe Bloggs wrote.

Compass Filter Option
{ author : { $eq : "Joe Bloggs" } }
MongoDB Aggregation
db.article.aggregate(
{ $filter : { author : { $eq : "Joe Bloggs" } } }
);
SQL
SELECT * FROM article
WHERE author = "Joe Bloggs";
Beaker IconExample

The following examples use the JSON documents below as sample data. To import this sample data to your MongoDB deployment with MongoDB Compass:

  1. Copy the array of documents below by clicking Copy.
[
{
"name":"Andrea Le",
"email":"andrea_le@fakegmail.com",
"version":5,
"scores":[85, 95, 75],
"dateCreated":{"$date":"2003-03-26"}
},
{
"email":"no_name@fakegmail.com",
"version":4,
"scores":[90, 90, 70],
"dateCreated":{"$date":"2001-04-15"}
},
{
"name":"Greg Powell",
"email":"greg_powell@fakegmail.com",
"version":1,
"scores":[65, 75, 80],
"dateCreated":{"$date":"1999-02-10"}
}
]
  1. In Compass, use the left navigation panel to select the database and the collection you want to import the data to.
  2. Click the Documents tab.
  3. Click Add Data and select Insert Document.
  4. Ensure that View is set to JSON, or {}, and paste the copied JSON documents in the field.
  5. Click Insert.
Info With Circle IconCreated with Sketch.Note

If you do not have a MonogDB deployment or if you would like to query a large sample data set, see Sample Data for Atlas Clusters for instructions on creating a free-tier cluster with sample data. Note that the examples below are intended to filter the sample JSON documents provided on this page and may not properly filter another sample data set.

The following query filter finds all documents where the value of name is "Andrea Le".

{ name: "Andrea Le" }

The query returns the following document because the name field value is an exact match.

{
"_id": {"$oid": "5e349915cebae490877d561d"},
"name":"Andrea Le",
"email":"andrea_le@fakegmail.com",
"version":5,
"scores":[85, 95, 75],
"dateCreated":{"$date":"2003-03-26"}
}

For more query examples, see Query Documents in the MongoDB manual.

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