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#8 Find Documents in MongoDB

We will use the database that we created at last session. You can read this article and reproduce it in your local environment.

The find() is a powerful tool that empowers us to execute diverse selections based on specific criteria.

1. Find all documents in a collection

#personnel is a collection name
db.personnel.find()

2.Find documents matching a specific condition

# Example 1: find the employee "Amanda Hall"'s data
> db.personnel.find({name:"Amanda Hall"})
< {
  _id: ObjectId('66053f848ccb6407b4ba21cd'),
  name: 'Amanda Hall',
  age: 33,
  working_experience: 9,
  department: 'Quality Assurance',
  salary: 69000,
  skills: [
    'Testing',
    'Bug Tracking',
    'Automation'
  ]
}
# Example 2: find the employees whose age are 35
> db.personnel.find({age:35})
< {
  _id: ObjectId('66053f848ccb6407b4ba21c6'),
  name: 'Michael Johnson',
  age: 35,
  working_experience: 8,
  department: 'Finance',
  salary: 70000,
  skills: [
    'Accounting',
    'Financial Analysis',
    'Excel'
  ]
}

3. Find documents where a field matches a regular expression

# Example 3: find the employee whose name is like "Jan"
> db.personnel.find({ name: /Jan/ })
< {
  _id: ObjectId('66053f848ccb6407b4ba21c5'),
  name: 'Jane Smith',
  age: 28,
  working_experience: 4,
  department: 'Marketing',
  salary: 55000,
  skills: [
    'Digital Marketing',
    'SEO',
    'Social Media Management'
  ]
}

4. Find documents where a field matches any value in an array

# Example 4: find the employee who has Python and Machine Learning skills
> db.personnel.find({ skills:{ $in:["Python","Machine Learning"]}})
< {
  _id: ObjectId('66053f848ccb6407b4ba21cb'),
  name: 'Michelle Martinez',
  age: 31,
  working_experience: 5,
  department: 'Research and Development',
  salary: 63000,
  skills: [
    'Research',
    'Data Analysis',
    'Python',
    'Machine Learning'
  ]
}
  • { skills: { $in: ["Python", "Machine Learning"] } } It specifies that we want to find documents where the “skills” field matches any of the values listed in the array ["Python", "Machine Learning"].

5. Find documents where a field matches multiple conditions (AND)

Example 5: find out the employee who has accounting skill AND in the finance department
> db.personnel.find({ skills:"Accounting", department:"Finance"})
< {
  _id: ObjectId('66053f848ccb6407b4ba21c6'),
  name: 'Michael Johnson',
  age: 35,
  working_experience: 8,
  department: 'Finance',
  salary: 70000,
  skills: [
    'Accounting',
    'Financial Analysis',
    'Excel'
  ]
}

6. Find documents where a field matches multiple conditions (OR)

Example 6: find out the employee who has Market Analysis skill OR in the finance department

> db.personnel.find({ $or: [{skills:"Market Analysis"}, {department:"Finance"}]})
< {
  _id: ObjectId('66053f848ccb6407b4ba21c6'),
  name: 'Michael Johnson',
  age: 35,
  working_experience: 8,
  department: 'Finance',
  salary: 70000,
  skills: [
    'Accounting',
    'Financial Analysis',
    'Excel'
  ]
}

{
  _id: ObjectId('66053f848ccb6407b4ba21cc'),
  name: 'Daniel Thompson',
  age: 29,
  working_experience: 4,
  department: 'Product Management',
  salary: 58000,
  skills: [
    'Product Development',
    'Product Launch',
    'Market Analysis'
  ]
}
  • { $or: [...] }: The operator means that the query should match documents that satisfy any of the conditions specified within the array.
  • [{skills:"Market Analysis"}, {department:"Finance"}]: This is an array containing two conditions.

7. Find documents and display specific field

Example 7: only show me the name and salary of each employee
#(It returns 10 result but here I only listed three)

> db.personnel.find({}, {name: 1, salary: 1})
< {
  _id: ObjectId('66053f848ccb6407b4ba21c4'),
  name: 'John Doe',
  salary: 60000
}
{
  _id: ObjectId('66053f848ccb6407b4ba21c5'),
  name: 'Jane Smith',
  salary: 55000
}
{
  _id: ObjectId('66053f848ccb6407b4ba21c6'),
  name: 'Michael Johnson',
  salary: 70000
}
...
  • The first parameter {} represents the filter criteria, which in this case is empty, meaning it will return all documents from the personnel collection.
  • The second parameter {name: 1, salary: 1} specifies which fields to include in the result. 1 indicates inclusion, while 0 would indicate exclusion.

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