MongoDB QueryData

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Querying a collection

The find() function can be used to query the documents.

The format is:

 db.collectionName.find(optional_query_criteria)

Where the query_criteria follows a pattern:

 db.collectionName.find({fieldName: "value"})

Note:

• the criteria is enclosed in curly brackets: {}
• the value needs quotes if it is a string or date value
• quotes are optional for the fieldName, so long as they do not contain spaces
• if the fieldName refers to a nested document, the name must be in matching single or double quotes

Find all documents

For example, show all the data so far in the deptCollection:

db.deptCollection.find()

The data comes back messy. The pretty() function can be used to improve the layout::

db.deptCollection.find().pretty()

Find One document

To find just one document - department 10:

db.deptCollection.find({deptno:10}).pretty()

Finding an employee means using the array name too:

db.deptCollection.find({"employees.empno":7902}).pretty()

However, this does mean you get back all the employees in the department they were found in!

Since Version 2.2 MongoDB's new $elemMatch can be used with arrays to return only the first element matching the $elemMatch condition:

db.deptCollection.find({deptno:20},  
  { _id: 0, employees: {$elemMatch: {empno: 7902}}}).pretty()

$elemMatch limits the contents of the employees array to contain only the first element matching the $elemMatch condition.

This is akin to a SQL query:

 SELECT * FROM Emp WHERE deptno=20 AND empno = 7902

_id is a unique value automatically generated by MongoDB (like a Primary Key, except it is unique for the whole database).

Using _id:0 suppresses the value, however to see it:

db.deptCollection.find({deptno:20},  
  { employees: {$elemMatch: {empno: 7902}}}).pretty()

More about _ids in the next section.

Find with Query Criteria

The query criteria can be as complex as that found in SQL.

To find all employees earning more than 2000 in department 10:

db.deptCollection.find({deptno:10},   
 { employees: {$elemMatch: {sal: { $gt: 2000}}}}).pretty()

Same again for department 20 and the managers:

db.deptCollection.find({deptno:20},  { employees: {$elemMatch: {sal: { $gt: 2000}, job: "MANAGER"}}}).pretty()

employees is an array, so $elemMatch only returns the first matching value. What if we try this instead:

db.deptCollection.find({ "employees.sal" : { $gt: 2000}}).pretty()

Things to note:

• This time employees.sal must be enclosed in matching single or double quotes.
• Comment on what the above query returns.
• If you examine the data carefully, if an element of an array is found to be true, then all the elements are returned, or one only. Is this good practice?

Find departments with no managers:

db.deptCollection.find({ "employees.job" : { $ne: "MANAGER"}}).pretty()

Aggregation Pipeline

So far find() either returns all the elements of an array, if one element matches the search criteria, or $elematch returns the first one found only. The latter is fine if there is only one to be found, but not so good if several items in the array should match the search criteria.

The aggregation pipeline is a framework for data aggregation modelled on the concept of data processing pipelines.

Documents enter a multi-stage pipeline that transforms the documents into aggregated results.

Similar to using GROUP BY in SQL

The MongoDB aggregation pipeline consists of stages.

Each stage transforms the documents as they pass through the pipeline.

We can use this to gather elements of our employees array to get the employees matching the query criteria only, rather than one, or everyone.

Next Step

Updating the collection