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Learn MongoDB

Description

MongoDB stores data records as BSON documents gathered in collections (= SQL table). BSON is a binary representation of JSON documents.
MongoDB documents are composed of field-and-value pairs. The value of a field can be any of the BSON data types.

var mydoc = {
               // field _id is a primary key
               _id: ObjectId("5099803df3f4948bd2f98391"),
               // name holds an embedded document that contains the fields first and last
               name: { first: "Alan", last: "Turing" },
               birth: new Date('Jun 23, 1912'),
               death: new Date('Jun 07, 1954'),
               contribs: [ "Turing machine", "Turing test", "Turingery" ],
               views : NumberLong(1250000)
            }

Connect and authenticate

# connect
mongosh mongodb://localhost:27017
# alias
mongosh

# connect and authenticate, use an environment variable to hide the password
mongosh "mongodb://user:${DBPASSWORD}@<host>:<port>/admin?authSource=admin"

Authenticate

db.auth("username", "pwd")

db.auth("username", passwordPrompt())

Database

// list the databases
show dbs

// switch to [dbname]
use [dbname]

// create a new database with a new collection (and insert data)
use [newdbname]
db.[newCollectionName].insertOne( { x: 1 } )

// drop the current database
db.dropDatabase()

Collection

It gathers documents and is an equivalent of an SQL table.
A collection does not require its documents to have the same schema (the same set of fields and the same data types)

// list collections
db.getCollectionInfos()
db.runCommand('listCollections')

db.createCollection("[collectionName]",
{
  [option]: [value]
})¨

// empty collection
db.myCollection.deleteMany({})

View

It is a read-only queryable object whose contents are defined by an aggregation pipeline on other collections or views.
It is computed when you read the view, and it is not stored to disk.
Create and Query a View

// 2 syntaxes to create a view
db.createCollection(
  "<viewName>",
  {
    "viewOn" : "<source>",
    "pipeline" : [<pipeline>],
    "collation" : { <collation> }
  }
)

db.createView(
  "<viewName>",
  "<source>",
  [<pipeline>],
  {
    "collation" : { <collation> }
  }
)

// drop a view
db.<viewName>.drop()

Time Series Collections

MongoDB treats time series collections as writable non-materialized views backed by an internal collection. Create and Query a Time Series Collection

db.createCollection(
"weather",
{
  timeseries: {
  timeField: "timestamp",
  metaField: "metadata",
  granularity: "seconds"
}})

Densify and fill

densify allows to create missing spots in the TS
- bounds: "full" spans from the full range of the original TS
- bounds: [ <from>, <to> ] spans from the defined bounds
fill allows to set values in those new spots.
- locf to get the same value as the previous spot
- linear to get the linear interpolation between the previous and the next point

[{
  $densify: {
    field: "event",
    range: {
      step: 15,
      unit: "minute",
      bounds: "full"
    }
  }
}, {
  $fill: {
    sortBy: {
      event: 1
    },
    output: {
      capacity: {
        method: "locf"
      }
    }
  }
}]

Query

find

db.myCollection.find( { } )
// SELECT *

db.myCollection.find( { item: 1, status: 1 } )
// SELECT _id, item, status
// _id is returned by default

db.myCollection.find( { item: 1, status: 1, _id: 0 } )
// SELECT item, status

db.myCollection.find( { status: 0 } )
// returns all fields but status

Query and Projection Operators)

db.myCollection.find( { name: "item1" } )
// SELECT ... WHERE name = "item1"

db.myCollection.find( { name: /^item/ } )
// SELECT ... WHERE name LIKE "item%"

db.myCollection.find( { status: "active", quantity: { $lt: 10 } } )
// SELECT ... WHERE status = "active" AND quantity < 10

db.myCollection.find( { $or: [ { status: "active" }, { qty: { $lt: 10 } } ] } )
// SELECT ... WHERE status = "active" OR quantity < 10

db.myCollection.find( { status: { $in: [ "active", "deleted" ] } } )
// SELECT ... WHERE status in ("active", "deleted")

regex

Aggregation

db.myCollection.aggregate(
  [
    { },
    { }
  ]
)

match

$match : { name : "item1" }

sort

$sort : { property1 : 1, property2: -1 } }
// ORDER BY property1 ASC, property2 DESC

project

$project: {
  _id: 0,                       // hide _id
  property2: "$_id.property1",  // include _id.property and rename as property2
  property3: 1                  // include property3
}

group

{
  $group : {
    _id : "$item",
    totalAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } }
  }
},
{
  $match: { "totalAmount": { $gte: 100 } }
}
// GROUP BY item HAVING totalAmount > 100

$group: {
   _id: null,
   count: { $count: { } }
}
// SELECT COUNT(*)

{ $group: { _id: { state: "$state", city: "$city" }, cityTotalPopulation: { $sum: "$population" } } },
{ $group: { _id: "$_id.state", avgCityPopulation: { $avg: "$cityTotalPopulation" } } }
// SELECT SUM(population) AS cityTotalPopulation ... GROUP BY state, city
// SELECT AVG(cityTotalPopulation) ... GROUP BY state

// group and project
{
  $group: {
    _id: {
      metadata: "$metadata",
    },
    value: {
      $avg: "$value",
    },
    count: {
      $count: {},
    }
  }
},
{
  $project: {
      _id: 0,
      metadata: "$_id.metadata",
      value: 1,
      count: 1
    }
}

densify

Creates new documents in a sequence of documents where certain values in a field are missing.

{
  $densify: {
    field: "timestamp",
    partitionByFields: ["metadata", "value"],
    range: {
      step: 60,
      unit: "minute",
      bounds: [
        new Date("2024-03-25T12:00:00.000Z"),
        new Date("2024-03-26T12:00:00.000Z"),
      ],
    },
  },
}

fill

{
  $fill: {
    sortBy: { timestamp: 1 },
    partitionBy: { "metadata": "$metadata" },
    output: {
      metadata: {
        method: "locf",
      },
      value: {
        method: "locf",
      },
    },
  },
}

Index

// list indexes
db.myCollection.getIndexes()

// create an index on name
db.myCollection.createIndex( { name: 1 } )
// for a single-field index, the sort order (ascending or descending) of the index key does not matter because MongoDB can traverse the index in either direction.

db.myCollection.dropIndex( "index name" )
db.myCollection.dropIndex( { name: 1 } )

Backup and restore

# restore the backup folder dump to the local mongodb instance
mongorestore dump/

don't know what to do with file while restore

This may happen because the mongorestore command point to a backup sub-folder not to the backup folder itself.

Authentication

// list the users of the current database
db.getUsers()
db.runCommand('usersInfo')

// get info of a specific user
db.getUser("tom", { showCredentials: true, showPrivileges: true, showAuthenticationRestrictions: true })

// create admin
use admin
db.createUser(
  {
    user: "admin",
    pwd: "mypwd",
    roles: [ { role: "userAdminAnyDatabase", db: "admin" } ]
  }
)

// create a user for the demo database
use demo
db.createUser(
  {
    user: "tom",
    pwd: passwordPrompt(), // or cleartext password
    roles: [ { role: "readWrite", db: "demo" },
             { role: "read", db: "finances" } ]
  }
)

// change password
use admin
db.changeUserPassword("tom", "secretpassword")
db.changeUserPassword("tom", passwordPrompt())

// delete a user
db.dropUser("tom")

/etc/mongod.conf

security:
authorization: "enabled"

Bash

mongo <<EOF
    use admin
    db.auth("admin", "${MONGODBADMINPWD}")
    use mydb
    db.dropDatabase()
EOF

Compass

Installation

Windows

choco install mongodb mongodb-shell

Key	Value
Service name	MongoDB
Data directory	C:\Program Files\MongoDB\Server\6.0\data\
Log directory	C:\Program Files\MongoDB\Server\6.0\log\

Install the Database Tools in C:\Program Files\MongoDB\Tools

Archlinux

yay mongodb-bin
# install dependencies mongodb-bin-debug, mongosh-bin, mongosh-bin-debug

# GUI
yay mongodb-compass

# tools
yay mongodb-tools

# service
sc-status mongodb.service

Ubuntu

# import the MongoDB public GPG key
curl -fsSL https://www.mongodb.org/static/pgp/server-8.0.asc | \
   sudo gpg -o /usr/share/keyrings/mongodb-server-8.0.gpg \
   --dearmor

# create the list file
echo "deb [ arch=amd64,arm64 signed-by=/usr/share/keyrings/mongodb-server-8.0.gpg ] https://repo.mongodb.org/apt/ubuntu focal/mongodb-org/8.0 multiverse" | \
   sudo tee /etc/apt/sources.list.d/mongodb-org-8.0.list

# reload the Package Database and install
sudo apt-get update
sudo apt-get install -y mongodb-org
# the following packages is installed:
# mongodb-database-tools mongodb-mongosh mongodb-org-database mongodb-org-database-tools-extra mongodb-org-mongos
# mongodb-org-server mongodb-org-shell mongodb-org-tools
# a user 'mongodb' and a group 'mongodb' are created.

# start the service
sc-start mongod

Error

src/third_party/tcmalloc/dist/tcmalloc/system-alloc.cc:755] MmapAligned() failed - unable to allocate with tag (hint=0x6c0200000000, size=1073741824, alignment=1073741824) - is something limiting address placement?
src/third_party/tcmalloc/dist/tcmalloc/arena.cc:48] CHECK in Alloc: FATAL ERROR: Out of memory trying to allocate internal tcmalloc data (bytes=131072, object-size=640); is something preventing mmap from succeeding (sandbox, VSS limitations)?

Mongodb

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