To copy rows into another collection, use MongoDB. The syntax is as follows wherein “yourOldCollectionName” is the old collection, whereas where this collection will get copied is our new collection i.e. “yourNewCollectionName” −db.yourOldCollectionName.aggregate([{ $sample: { size: 333333 }}, {$out: "yourNewCollectionName"} ], {allowDiskUse: true});Let us first create a collection with documents −> db.sourceCollection.insertOne({"EmployeeName":"Robert", "EmployeeSalary":15000}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0397c1f5e889d7a5199506") } > db.sourceCollection.insertOne({"EmployeeName":"David", "EmployeeSalary":25000}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0397c3f5e889d7a5199507") } > db.sourceCollection.insertOne({"EmployeeName":"Mike", "EmployeeSalary":29000}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0397c4f5e889d7a5199508") }Following is the query to display all documents from a collection with ... Read More

In this case, use the concept of index on a particular field. Let us first create a collection with documents. Here, we have created index as well using createIndex() −> db.decreasetimeusingindex.createIndex({"StudentName":1}); {    "createdCollectionAutomatically" : true,    "numIndexesBefore" : 1,    "numIndexesAfter" : 2,    "ok" : 1 } > db.decreasetimeusingindex.insertOne({"StudentName":"John Smith", "StudentAge":21}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e03960af5e889d7a51994ff") } > db.decreasetimeusingindex.insertOne({"StudentName":"John Doe", "StudentAge":24}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e039611f5e889d7a5199500") } > db.decreasetimeusingindex.insertOne({"StudentName":"Adam Smith", "StudentAge":22}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e03961df5e889d7a5199501") }Following is the query to display all documents from a ... Read More

Extract a particular element from a nested array with the help of dot(.) notation. Let us first create a collection with documents −> db.extractParticularElementDemo.insertOne( ...    { ...       "_id" : 101, ...       "StudentName" : "John", ...       "StudentInformation" : [ ...          { ...             "Age" : 21, ...             "StudentPersonalInformation" : [ ...                { ...                   "StudentNickName" : "Mike", ...       ... Read More

Use MongoDB $literal to set a string literal. Let us first create a collection with documents −>db.replacevaluedemo.insertOne({"StudentName":"Chris", "StudentFavouriteSubject":{"TeacherName":"Bob", "SubjectCode":"MySQL111"}}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0390a3f5e889d7a51994fd") } >db.replacevaluedemo.insertOne({"StudentName":"Mike", "StudentFavouriteSubject":{"TeacherName":"David", "SubjectCode":"3221Java"}}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0390b8f5e889d7a51994fe") }Following is the query to display all documents from a collection with the help of find() method −> db.replacevaluedemo.find().pretty();This will produce the following output −{    "_id" : ObjectId("5e0390a3f5e889d7a51994fd"),    "StudentName" : "Chris",    "StudentFavouriteSubject" : {       "TeacherName" : "Bob",       "SubjectCode" : "MySQL111"    } } {    "_id" : ObjectId("5e0390b8f5e889d7a51994fe"),    "StudentName" ... Read More

Use aggregation $gte and $lte along with $sum to count and sum a field between 2 dates. Let us first create a collection with documents −> db.countandsumdemo.insertOne({"Value":10, "created_at":ISODate('2019-10-11')}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e038e6df5e889d7a51994fa") } > db.countandsumdemo.insertOne({"Value":50, "created_at":ISODate('2019-01-31')}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e038e77f5e889d7a51994fb") } > db.countandsumdemo.insertOne({"Value":100, "created_at":ISODate('2019-06-31')}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e038e8af5e889d7a51994fc") }Following is the query to display all documents from a collection with the help of find() method −> db.countandsumdemo.find().pretty();This will produce the following output −{    "_id" : ObjectId("5e038e6df5e889d7a51994fa"),    "Value" : 10,    "created_at" : ISODate("2019-10-11T00:00:00Z") ... Read More

To create index in the background, use createIndex() method and set “background: true” as in the below syntax −db.yourCollectionName.createIndex({"yourFieldName1":1,"yourFieldName2":1},{background: true} );Let us implement the above syntax in order to create index and set background −> db.indexCreationDemo.createIndex({"StudentName":1,"StudentAge":1},{background: true} ); {    "createdCollectionAutomatically" : true,    "numIndexesBefore" : 1,    "numIndexesAfter" : 2,    "ok" : 1 }Let us display the indexes −> db.indexCreationDemo.getIndexes();This will produce the following output −[    {       "v" : 2,       "key" : {          "_id" : 1       },       "name" : "_id_",       "ns" : "web.indexCreationDemo"    },    {       "v" : 2,       "key" : {          "StudentName" : 1,          "StudentAge" : 1       },       "name" : "StudentName_1_StudentAge_1",       "ns" : "web.indexCreationDemo",       "background" : true    } ]

The collation introduced in version MongoDB 3.4. Maybe, you implemented collation in a previous version.For our example, we are using MongoDB version 4.0.5. Following is the query to check the current version on system −> db.version()This will produce the following output −4.0.5Let us first create a collection with documents −> db.collationExample.createIndex({Value: 1}, {collation: {locale: "en", strength: 1}}); {    "createdCollectionAutomatically" : true,    "numIndexesBefore" : 1,    "numIndexesAfter" : 2,    "ok" : 1 } > db.collationExample.insertOne({'Value':'x'}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e038a3cf5e889d7a51994f5") } > db.collationExample.insertOne({'Value':'X'}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e038a48f5e889d7a51994f6") } > ... Read More

To calculate average, use aggregate along with $avg. Let us first create a collection with documents −> db.calculateAverage.insertOne({'Value':[10, 20, 80]}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0383e3f5e889d7a51994dc") } > db.calculateAverage.insertOne({'Value':[12, 15, 16]}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0383edf5e889d7a51994dd") } > db.calculateAverage.insertOne({'Value':[30, 35, 40]}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e0383f5f5e889d7a51994de") }Following is the query to display all documents from a collection with the help of find() method −> db.calculateAverage.find().pretty();This will produce the following output −{    "_id" : ObjectId("5e0383e3f5e889d7a51994dc"),    "Value" : [       10,       20,     ... Read More

To promote subfields to top level in projection, use $objectToArray and $arrayToObject. Let us first create a collection with documents:> db.promoteSubfieldsDemo.insertOne({'s':10, 'y':{'t':20, 'u':30, }}); {    "acknowledged" : true,    "insertedId" : ObjectId("5e038004190a577c668b55d5") }Following is the query to display all documents from a collection with the help of find() method −> db.promoteSubfieldsDemo.find().pretty();This will produce the following output −{    "_id" : ObjectId("5e038004190a577c668b55d5"),    "s" : 10,    "y" : {       "t" : 20,       "u" : 30    } }Following is the query to promote subfields to top level in projection without listing all keys ... Read More

To delete specific record, use “$pull” and since we are updating the already created collection, use UPDATE().Let us create a collection with documents −> db.demo213.insertOne({ ...   "id": 101, ...   "details1": [ ...      { ...         "Name": "Chris", ...         "details2": [ ...            { ...               "StudentName": "David", ...               "Subject": "MongoDB" ...            }, ...            { ...               ... Read More