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Get-Start-DocumentDB.md

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Get Start with Amazon DocumentDB

Prerequisites

  1. Create a security group

Port 27017 is the default port for Amazon DocumentDB.

  1. Create an Amazon DocumentDB cluster

  2. Install the mongo shell on EC2 or Cloud 9 environment

# install the mongo shell 
echo -e "[mongodb-org-4.0] \nname=MongoDB Repository\nbaseurl=https://repo.mongodb.org/yum/amazon/2013.03/mongodb-org/4.0/x86_64/\ngpgcheck=1 \nenabled=1 \ngpgkey=https://www.mongodb.org/static/pgp/server-4.0.asc" | sudo tee /etc/yum.repos.d/mongodb-org-4.0.repo

sudo yum install -y mongodb-org-shell

# To encrypt data in transit, download the public key for Amazon DocumentDB
# Global region
wget https://s3.amazonaws.com/rds-downloads/rds-combined-ca-bundle.pem
# China region
wget https://s3.cn-north-1.amazonaws.com.cn/rds-downloads/rds-combined-ca-cn-bundle.pem

Quick start use

  1. Connect to your Amazon DocumentDB cluster

    Amazon DocumentDB (with MongoDB compatibility) clusters are deployed within an Amazon VPC. They can be accessed directly by Amazon EC2 instances or other AWS services that are deployed in the same Amazon VPC. Additionally, Amazon DocumentDB can be accessed in different VPCs in the same AWS Region or other Regions via VPC peering.

  1. Get the conntion info DocDB-Connect
mongo --ssl --host <docDB_endpoint>:27017 --sslCAFile rds-combined-ca-cn-bundle.pem --username dbadmin --password <insertYourPassword>
When you enter your password and your prompt becomes `rs0:PRIMARY>` prompt, you are successfully connected to your Amazon DocumentDB cluster.
  1. Insert and query data
# insert a single document
s0:PRIMARY> db.collection.insert({"hello":"DocumentDB"})
WriteResult({ "nInserted" : 1 })

# read one document 
rs0:PRIMARY> db.collection.findOne()
{ "_id" : ObjectId("5fc72948c2e9c52076de75fb"), "hello" : "DocumentDB" }

# insert a few entries into a collection
rs0:PRIMARY> db.profiles.insertMany([
...             { "_id" : 1, "name" : "Matt", "status": "active", "level": 12, "score":202},
...             { "_id" : 2, "name" : "Frank", "status": "inactive", "level": 2, "score":9},
...             { "_id" : 3, "name" : "Karen", "status": "active", "level": 7, "score":87},
...             { "_id" : 4, "name" : "Katie", "status": "active", "level": 3, "score":27}
...             ])
{ "acknowledged" : true, "insertedIds" : [ 1, 2, 3, 4 ] }

# return all the documents in the profiles collection
rs0:PRIMARY> db.profiles.find()
{ "_id" : 1, "name" : "Matt", "status" : "active", "level" : 12, "score" : 202 }
{ "_id" : 2, "name" : "Frank", "status" : "inactive", "level" : 2, "score" : 9 }
{ "_id" : 3, "name" : "Karen", "status" : "active", "level" : 7, "score" : 87 }
{ "_id" : 4, "name" : "Katie", "status" : "active", "level" : 3, "score" : 27 }

# query for a single document using a filter
rs0:PRIMARY> db.profiles.find({name: "Katie"})
{ "_id" : 4, "name" : "Katie", "status" : "active", "level" : 3, "score" : 27 }

# find a profile and modify it using the findAndModify command
rs0:PRIMARY>     db.profiles.findAndModify({
...         query: { name: "Matt", status: "active"},
...         update: { $inc: { score: 10 } }
...     })
{
        "_id" : 1,
        "name" : "Matt",
        "status" : "active",
        "level" : 12,
        "score" : 202
}

# verify that value has changed
rs0:PRIMARY> db.profiles.find({name: "Matt"})
{ "_id" : 1, "name" : "Matt", "status" : "active", "level" : 12, "score" : 212 }
rs0:PRIMARY>

Aggregation query

  1. Count the Number of Documents in a Collection
db.sales.insertMany([
  { "_id" : 1, "item" : "abc", "price" : 10, "quantity" : NumberInt("2"), "date" : ISODate("2014-03-01T08:00:00Z") },
  { "_id" : 2, "item" : "jkl", "price" : 20, "quantity" : NumberInt("1"), "date" : ISODate("2014-03-01T09:00:00Z") },
  { "_id" : 3, "item" : "xyz", "price" : 5, "quantity" : NumberInt( "10"), "date" : ISODate("2014-03-15T09:00:00Z") },
  { "_id" : 4, "item" : "xyz", "price" : 5, "quantity" :  NumberInt("20") , "date" : ISODate("2014-04-04T11:21:39.736Z") },
  { "_id" : 5, "item" : "abc", "price" : 10, "quantity" : NumberInt("10") , "date" : ISODate("2014-04-04T21:23:13.331Z") },
  { "_id" : 6, "item" : "def", "price" : 7.5, "quantity": NumberInt("5" ) , "date" : ISODate("2015-06-04T05:08:13Z") },
  { "_id" : 7, "item" : "def", "price" : 7.5, "quantity": NumberInt("10") , "date" : ISODate("2015-09-10T08:43:00Z") },
  { "_id" : 8, "item" : "abc", "price" : 10, "quantity" : NumberInt("5" ) , "date" : ISODate("2016-02-06T20:20:13Z") },
])

db.sales.aggregate( [ { $group : { _id : "$item" } } ] )

db.sales.aggregate( [
  {
    $group: {
       _id: "$item",
       count: { $sum: 1 }
    }
  }
] )
  1. Group by Item Having
db.sales.aggregate(
  [
    // First Stage
    {
      $group :
        {
          _id : "$item",
          totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } }
        }
     },
     // Second Stage
     {
       $match: { "totalSaleAmount": { $gte: 100 } }
     }
   ]
 )
  1. Calculate Count, Sum, and Average
# Group by Day of the Year
db.sales.aggregate([
  // First Stage
  {
    $match : { "date": { $gte: new ISODate("2014-01-01"), $lt: new ISODate("2015-01-01") } }
  },
  // Second Stage
  {
    $group : {
       _id : { $dateToString: { format: "%Y-%m-%d", date: "$date" } },
       totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } },
       averageQuantity: { $avg: "$quantity" },
       count: { $sum: 1 }
    }
  },
  // Third Stage
  {
    $sort : { totalSaleAmount: -1 }
  }
 ])

# Group by null: calculating the total sale amount, average quantity, and count of all documents in the collection
db.sales.aggregate([
  {
    $group : {
       _id : null,
       totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } },
       averageQuantity: { $avg: "$quantity" },
       count: { $sum: 1 }
    }
  }
 ])
  1. Pivot Data
db.books.insertMany([
  { "_id" : 8751, "title" : "The Banquet", "author" : "Dante", "copies" : 2 },
  { "_id" : 8752, "title" : "Divine Comedy", "author" : "Dante", "copies" : 1 },
  { "_id" : 8645, "title" : "Eclogues", "author" : "Dante", "copies" : 2 },
  { "_id" : 7000, "title" : "The Odyssey", "author" : "Homer", "copies" : 10 },
  { "_id" : 7020, "title" : "Iliad", "author" : "Homer", "copies" : 10 }
])

# Group title by author
db.books.aggregate([
   { $group : { _id : "$author", books: { $push: "$title" } } }
 ])

# Group Documents by author
db.books.aggregate([
   // First Stage
   {
     $group : { _id : "$author", books: { $push: {"title": "$title", "copies": "$copies"} } }
   },
   // Second Stage
   {
     $addFields:
       {
         totalCopies : { $sum: "$books.copies" }
       }
   }
 ])

Reference

Amazon DocumentDB Official guide

Amazon DocumentDB Quick Start Using AWS CloudFormation

group (aggregation)