# Get documents, where writters are Joel Coen and Ethan Coen.
db.movieDetails.find({ "writters" : ["Joel Coen", "Ethan Coen"] }).count()# Get documents, where Jeff Bridges is playing leading role.
> db.movieDetails.find({ "actors.0": "Jeff Bridges" }).pretty()# Working with mongodb cursors
> var c = db.movieDetails.find();
> var doc = function() { return c.hasNext() ? c.next() : null; }
> c.objsLeftInBatch();
# Example output: 104
> doc() # Iterate the function
> doc() # Iterate the function
> doc() # Iterate the function
> c.objsLeftInBatch();
# Example output: 101# Include or exclude fields in return statement.
> db.movieDetails.find({ rated: "PG"}, { title: 1, _id: 0}).pretty()# Greater than operator
> db.movieDetails.find({ runtime: { $gt: 90 }).pretty()
# Less than operator
> db.movieDetails.find({ runtime: { $gt: 90, $lt: 120 }).pretty()
# Embedded document and equal to operator
> db.movieDetails.find({ "tomato.meter": { $gte: 95}, runtime: { $gt: 180 } }, { title: 1, runtime: 1, _id: 0 }).pretty()
# Not equal operator
> db.movieDetails.find({ rated: { $ne: "UNRATED" } }).count()
# IN operator
> db.movieDetails.find({ rated: { $in: ["G", "PG"] } }).pretty()# Exists operator
> db.movieDetails.find({ "tomato.meter": { $exists: true } }).pretty()
> db.movieDetails.find({ "tomato.meter": { $exists: false } }).pretty()
# Type Operator
> db.moviesScratch.find({ "_id": { $type: "string" } }).count()# OR operator
> db.movieDetails.find({ $or: [ { "tomato.meter": { $gt: 95 } }, { "metacritic": { $gt: 88 } } ] }).pretty()
# And operator
> db.movieDetails.find({ $and: [ { "tomato.meter": { $gt: 95 } }, { "metacritic": { $gt: 88 } } ] }).pretty()
# Equalent query
> db.movieDetails.find({ { "tomato.meter": { $gt: 95 } }, { "metacritic": { $gt: 88 } }).pretty()
# Example for using of $and operator
> db.movieDetails.find({ $and: [ { "metacritic": { $ne: null } }, { "metacritic": { $exists: true } } ] }).count()# Reg Exp
> db.movieDetails.find({ "awards.text": { $regex: /^Won\s.*/ } } )# Array operators
> db.movieDetails.find( { genres: { $all: ["Comedy", "Crime", "Drama" ] } } ).pretty()
> db.movieDetails.find({ countries: { $size: 1 } }).pretty()
> db.movieDetails.find({ boxOffice: { $elemMatch: { country: "UK", revenie: { $gt: 15 } } } }).pretty()# Create a asc index
> db.students.createIndex({ student_id: 1});
# Explain database configurations
> db.students.explain().find({ student: 5 });
# Create a complex index. student_id will be asc, class_id will be desc.
> db.students.createIndex({ student_id: 1, class_id: -1 });
# Get collection indexes
> db.students.getIndexes();
# Delete index
> db.students.dropIndex({ student_id: 1});
# Create .not notation index
db.students.createIndex({ 'scores.score': 1 });
# Create unique index
> db.stuff.createIndex({ thing: 1 }, { unique: true });
# Geospatial Indexes
> db.collection.ensureIndex({ location: '2d' })
# Suppose you have a 2D geospatial index defined on the key location in the collection places. Write a query that will find the closest three places (the closest three documents) to the location 74, 140.
> db.places.find( { location : { $near : [74,140] } }).limit(3)
# Geospatial Spherical
> db.places.ensureIndex({ location: '2dg' })
# What is the query that will query a collection named "stores" to return the stores that are within 1,000,000 meters of the location latitude=39, longitude=-130? Type the query in the box below. Assume the stores collection has a 2dsphere index on "loc" and please use the "$near" operator
> db.stores.find({ loc:{ $near: { $geometry: { type: "Point", coordinates: [-130, 39]}, $maxDistance:1000000 } } })
# Text index
> db.sentences.ensureIndex({ 'words': 'text' })
> db.sentences.find({ 'text': { $search: 'dog' } } )# Profiling
> db.system.profile.find({ ns: /school.students/}).sort({ts: 1}).pretty()
> db.system.profile.find({millis: { $gt: 1 }}).sort({ts: 1}).pretty()
> db.getProfilingLevel()
> db.setProfilingLevel(1, 4)
> db.getProfilingStatus()# Aggregation framework
# Aggregate operator
> db.companies.aggregate([ { $match: { founded_year: 2004 } }, ])
# Projection
> db.companies.aggregate([ { $match: { founded_year: 2004 } }, { $project: { _id: 0, name:1, founded_year: 1 } } ])
# Limit
> db.companies.aggregate([ { $match: { founded_year: 2004 } }, { $limit: 5 }, { $project: { _id: 0, name:1, founded_year: 1 } } ])
# Sort
> db.companies.aggregate([ { $match: { founded_year: 2004 } }, { $sort: { name: 1 } }, { $limit: 5 }, { $project: { _id: 0, name:1, founded_year: 1 } } ])
# Skip
> db.companies.aggregate([ { $match: { founded_year: 2004 } }, { $sort: { name: 1 } }, { $skip: 10 }, { $limit: 5 }, { $project: { _id: 0, name:1, founded_year: 1 } } ])
# Unwind
> db.companies.aggregate([ { $unwind: "$funding_rounds" }, { $unwind: "$funding_rounds.investments" }, { $match: { "funding_rounds.investments.financial_org.permalink": "greylock" } }, { $project : { _id: 0, name: 1, fundingOrganization: "$funding_rounds.investments.financial_org.permalink" } } , ])
db.movieDetails.find({ "countries.1": "Sweden" },{ title: 1, _id: 0 });