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#Mongodb compass and query how to

Suppose you want to extract all properties of type “House” from the AirBnB database. Information about the indexes defined for the selected collection is also shown. The other 3 menus ( Explain Plan, Indexes and Validation) will not be used in this tutorial, but are used, as you can see from their names, respectively to analyze the execution plan of a query, manage indexes and insert validation rules for the documents stored in the collection.įinally, in the upper right part of the screen some information about the number of comments saved, the space occupied both by the collection and on average by each document is always displayed.

#Mongodb compass and query how to

Next we’ll see how to use it to understand which queries can return results of interest. The Schema menu is used to analyze the schema of the data in the collection and retrieve some statistics about the distribution of the data. The second menu is related to aggregation pipelines and is used for more complex queries that require transformation operations of the data present in the documents. Also, if there is any syntax error the badge next to the form field will have a red colored background. As you type, in fact, MongoDB Compass will suggest the fields and operators that might be useful to compose the query. Very useful features of the query form are the auto-completion and the syntax validation. To enter all these options, simply expand the query form by clicking on the OPTIONS button. It is possible to insert filters, projections, sort conditions and limitation of the number of records returned. For each document displayed, you can edit it, copy it to your clipboard, duplicate it and delete it using the buttons on the right associated with each document.Īs mentioned earlier, this screen can be used to query the collections. The other views are the JSON (available since version 1.2) and the tabular view. If there are complex structures within a document (embedded documents, arrays) it is possible to expand them to display the data present. By applying the and operation we will select all the documents that satisfy all the condition expressions.The default view is that of the list. In MongoDB, we can apply the multiple conditions using the and operator. Read: MongoDB backup and restore MongoDB find multiple conditions and

We successfully find the documents by applying multiple conditions using MongoDB Compass.

See the ouput below the applied condition block.

After applying the conditions click on FIND button.

Here, we have applied the conditions as display those fields where the born year is greater than 1945 and display two fields devname and born and sort the result according to devname ascending order.

Now check the documents in MongoDB Compass.

The following documents are inserted into the inventory collection: db.inventory.insertMany([ In the example, we apply multiple conditions to documents and find the documents accordingly. You will more understand with the help of an example so let’s get started: prasad at 3:53 Add a comment 1 Answer Sorted by: 83 You can do this via aggregation framework in Compass, using unwind and group. Also, see Aggregation Pipeline Stages and Aggregation operators. Note that, the find() method “returns documents” the method is returning a cursor to the documents. You can use Compass's Aggregation Pipeline Builder to create aggregattion queries using grouping to get count, sum, average, etc. Optional, documents that match the query filter and to return all fields in the matching documents. To return all documents in a collection or pass an empty document. Optional, used to specify selection filter using query operators. Let’s discuss the query(syntax) in detail: Parameter Syntax: db.collection.find(query, projection) The find query in MongoDB is used to choose documents from a collection, inspect them, and return a cursor to the selected documents. MongoDB find query with multiple conditions

MongoDB find multiple conditions python.

MongoDB compass find multiple conditions.

MongoDB find query with multiple conditions.