MongoDB mongosh 치트 시트

db.coll.findOne() // returns a single documentdb.coll.find() // returns a cursor that displays 20 results, use "it" to display moredb.coll.find().pretty()db.coll.find({name: "Max", age: 32}) // implicit logical "AND".db.coll.find({date: ISODate("2020-09-25T13:57:17.180Z")})db.coll.find({name: "Max", age: 32}).explain("executionStats") // or "queryPlanner" or "allPlansExecution"db.coll.distinct("name")

// Countdb.coll.countDocuments({age: 32}) // $count aggregation alias that returns an accurate countdb.coll.estimatedDocumentCount() // uses collection metadata to estimate the document count

// Comparisondb.coll.find({"year": {$gt: 1970}})db.coll.find({"year": {$gte: 1970}})db.coll.find({"year": {$lt: 1970}})db.coll.find({"year": {$lte: 1970}})db.coll.find({"year": {$ne: 1970}})db.coll.find({"year": {$in: [1958, 1959]}})db.coll.find({"year": {$nin: [1958, 1959]}})

// Logicaldb.coll.find({name:{$not: {$eq: "Max"}}})db.coll.find({$or: [{"year" : 1958}, {"year" : 1959}]})db.coll.find({$nor: [{price: 1.99}, {sale: true}]})db.coll.find({   $and: [      {$or: [{qty: {$lt :10}}, {qty :{$gt: 50}}]},      {$or: [{sale: true}, {price: {$lt: 5 }}]}   ]})

// Elementdb.coll.find({name: {$exists: true}})db.coll.find({"zipCode": {$type: 2 }})db.coll.find({"zipCode": {$type: "string"}})

// Aggregation Pipelinedb.coll.aggregate([   {$match: {status: "A"}},   {$group: {_id: "$cust_id", total: {$sum: "$amount"}}},   {$sort: {total: -1}}])

// Create text index for searchdb.coll.createIndex({ title: "text", content: "text" })
// Basic text searchdb.coll.find({$text: {$search: "cake"}})
// Text search queriesdb.coll.find({ $text: { $search: "mongodb database" } })db.coll.find({ $text: { $search: "\"exact phrase\"" } })db.coll.find({ $text: { $search: "mongodb -database" } })  // exclude "database"
// Text search with scoresdb.coll.find({$text: {$search: "cake"}}, {score: {$meta: "textScore"}}).sort({score: {$meta: "textScore"}})

// Create geospatial indexesdb.places.createIndex({ location: "2dsphere" })  // For GeoJSONdb.places.createIndex({ location: "2d" })        // For legacy coordinates
// Find locations near a pointdb.places.find({   location: {      $near: {         $geometry: { type: "Point", coordinates: [-73.9857, 40.7484] },         $maxDistance: 1000  // meters      }   }})
// Find locations within a polygondb.places.find({   location: {      $geoWithin: {         $geometry: {            type: "Polygon",            coordinates: [[               [-74.0059, 40.7128],               [-74.0059, 40.7589],               [-73.9352, 40.7589],               [-73.9352, 40.7128],               [-74.0059, 40.7128]            ]]         }      }   }})

// Regexdb.coll.find({name: /^Max/}) // regex: starts by letter "M"db.coll.find({name: /^Max$/i}) // regex case insensitive

// Arraydb.coll.find({tags: {$all: ["Realm", "Charts"]}})db.coll.find({field: {$size: 2}}) // can't be indexed, so instead store the size of the array & update itdb.coll.find({results: {$elemMatch: {product: "xyz", score: {$gte: 8}}}})

// Projectionsdb.coll.find({"x": 1}, {"actors": 1}) // actors + _iddb.coll.find({"x": 1}, {"actors": 1, "_id": 0}) // actorsdb.coll.find({"x": 1}, {"actors": 0, "summary": 0}) // all but "actors" and "summary"

// Sort, skip, limitdb.coll.find({}).sort({"year": 1, "rating": -1}).skip(10).limit(3)

// Read Concerndb.coll.find().readConcern("majority")

db.coll.updateOne({"_id": 1}, {$set: {"year": 2016, name: "Max"}})db.coll.updateOne({"_id": 1}, {$unset: {"year": 1}})db.coll.updateOne({"_id": 1}, {$rename: {"year": "date"} })db.coll.updateOne({"_id": 1}, {$inc: {"year": 5}})db.coll.updateOne({"_id": 1}, {$mul: {price: NumberDecimal("1.25"), qty: 2}})db.coll.updateOne({"_id": 1}, {$min: {"imdb": 5}})db.coll.updateOne({"_id": 1}, {$max: {"imdb": 8}})db.coll.updateOne({"_id": 1}, {$currentDate: {"lastModified": true}})db.coll.updateOne({"_id": 1}, {$currentDate: {"lastModified": {$type: "timestamp"}}})

// Arraydb.coll.updateOne({"_id": 1}, {$push :{"array": 1}})db.coll.updateOne({"_id": 1}, {$pull :{"array": 1}})db.coll.updateOne({"_id": 1}, {$addToSet :{"array": 2}})db.coll.updateOne({"_id": 1}, {$pop: {"array": 1}}) // last elementdb.coll.updateOne({"_id": 1}, {$pop: {"array": -1}}) // first elementdb.coll.updateOne({"_id": 1}, {$pullAll: {"array" :[3, 4, 5]}})db.coll.updateOne({"_id": 1}, {$push: {"scores": {$each: [90, 92]}}})db.coll.updateOne({"_id": 2}, {$push: {"scores": {$each: [40, 60], $sort: 1}}}) // array sorteddb.coll.updateOne({"_id": 1, "grades": 80}, {$set: {"grades.$": 82}})db.coll.updateMany({}, {$inc: {"grades.$[]": 10}})db.coll.updateMany({}, {$set: {"grades.$[element]": 100}}, {multi: true, arrayFilters: [{"element": {$gte: 100}}]})

// FindOneAndUpdatedb.coll.findOneAndUpdate({"name": "Max"}, {$inc: {"points": 5}}, {returnNewDocument: true})

// Upsertdb.coll.updateOne({"_id": 1}, {$set: {item: "apple"}, $setOnInsert: {defaultQty: 100}}, {upsert: true})

// Replacedb.coll.replaceOne({"name": "Max"}, {"firstname": "Maxime", "surname": "Beugnet"})

// Write concerndb.coll.updateMany({}, {$set: {"x": 1}}, {"writeConcern": {"w": "majority", "wtimeout": 5000}})

// Update many documents efficientlydb.coll.updateMany({status: "pending"}, {$set: {status: "processed"}})
// Delete many documentsdb.coll.deleteMany({status: "old"})
// Insert many documents efficientlydb.coll.insertMany([   {name: "user1", status: "active"},   {name: "user2", status: "active"},   {name: "user3", status: "active"}])
// Bulk operation for mixed insert, update, and delete operations// Ordered by default, executed serially. If unordered, MongoDB// executes operations in parallel.db.coll.bulkWrite([   { insertOne: { document: { name: "Alice", age: 30 } } },   { updateOne: { filter: { name: "Bob" }, update: { $set: { age: 25 } } } },   { deleteOne: { filter: { name: "Charlie" } } }], ordered: false)

// Index Typesdb.coll.createIndex({"name": 1})                // single field indexdb.coll.createIndex({"name": 1, "date": 1})     // compound indexdb.coll.createIndex({foo: "text", bar: "text"}) // text indexdb.coll.createIndex({"$**": "text"})            // wildcard text indexdb.coll.createIndex({"userMetadata.$**": 1})    // wildcard indexdb.coll.createIndex({"loc": "2d"})              // 2d indexdb.coll.createIndex({"loc": "2dsphere"})        // 2dsphere indexdb.coll.createIndex({"_id": "hashed"})          // hashed index

// Index Optionsdb.coll.createIndex({"lastModifiedDate": 1}, {expireAfterSeconds: 3600})      // TTL indexdb.coll.createIndex({"name": 1}, {unique: true})db.coll.createIndex({"name": 1}, {partialFilterExpression: {age: {$gt: 18}}}) // partial indexdb.coll.createIndex({"name": 1}, {collation: {locale: 'en', strength: 1}})    // case insensitive index with strength 1 or 2db.coll.createIndex({"name": 1 }, {sparse: true})