MongoDB like syntax for DynamoDB
npm install --save dynongo
First of all, we have to connect with the database.
const db = require('dynongo');
db.connect();
Please use IAM roles or environment variables to connect with the dynamodb database. This way, no keys have to be embedded in your code. You can find more information on the SDK page.
If you still want to use embedded credentials, you can by providing an accessKeyId
, secretAccessKey
and an optional region
property.
db.connect({
accessKeyId: 'AKIAI44QH8DHBEXAMPLE',
secretAccessKey: 'wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY',
region: 'us-west-1'
});
Or if you rather work with temporary security credentials, you can do that as well.
db.connect({
accessKeyId: 'AKIAI44QH8DHBEXAMPLE',
secretAccessKey: 'wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY',
sessionToken: 'AQoDYXdzEJr...<remainder of security token>',
region: 'us-west-1'
});
The retry configuration can be passed during initialisation, or per individual query. The mechanism is based on p-retry
and requires the same options. Configuring retry will allow the user to automatically retry the DynamoDB operation if it's a retryable error.
db.connect({
retries: {
retries: 3,
factor: 1,
randomize: false
}
})
You can simply pass a number as well when you don't want to configure the retry strategy.
db.connect({
retries: 3
})
It is possible to connect to a local DynamoDB database
by setting the local
property to true
. It will use port 8000 by default, but if you want to change that port, you can provide a localPort
property.
db.connect({
local: true,
host: '192.168.5.5', // localhost if not provided
localPort: 4444 // 8000 if not provided
});
It's a good thing to prefix the tables with the name of the project and maybe the environment like production or staging. Instead
of always repeating those names every time you want to query the table, you can provide the prefix and prefix delimiter once. The
default delimiter is the .
.
db.connect({
prefix: 'myapp-development',
prefixDelimiter: '-' // . if not provided
});
In order for the developer to execute methods on a table, you have to retrieve the table object from the database.
const Employee = db.table('Employee');
The table name will be automatically prefixed by the prefix
provided in the connection object.
If you provided a prefix
in the connection object but you don't want that for a specific table, you could ask for a raw table. A raw table is like a regular table without the prefix.
const Employee = db.rawTable('Employee');
Every method can override the retry options passed with the .connect()
method or can customise the retry configuration for the specific method.
Employee
.find({Organisation: 'Amazon'})
.where({Salary: {$gt: 3000}})
.select('FirstName Name')
.retry({retries: 3, factor: 1, randomize: false})
.exec()
.then(employees => {
// => [{FirstName: 'Foo', Name: 'Bar'}]
});
If you don't want to configure the retry strategy, you can simply pass the number of retries.
Employee
.find({Organisation: 'Amazon'})
.where({Salary: {$gt: 3000}})
.select('FirstName Name')
.retry(2)
.exec()
.then(employees => {
// => [{FirstName: 'Foo', Name: 'Bar'}]
});
Employee.find({Organisation: 'Amazon'}).where({Salary: {$gt: 3000}}).select('FirstName Name').exec()
.then(employees => {
// => [{FirstName: 'Foo', Name: 'Bar'}]
});
Employee.findOne({Organisation: 'Amazon'}).where({Salary: {$between: [3000, 4000]}}).select('FirstName Name').exec()
.then(employee => {
// => {FirstName: 'Foo', Name: 'Bar'}
});
Employee.find({Organisation: 'Amazon'}).where({Salary: {$gt: 3000}}).count().exec()
.then(count => {
// => 8
});
Employee.insert({Organisation: 'Amazon', Email: '[email protected]'}, {Title: 'CFO', HiredAt: 'last year', FirstName: 'Foo', Name: 'Bar', Salary: 4500}).exec()
.then(employee => {
// => {FirstName: 'Foo', Name: 'Bar', Salary: 4500, Title: 'CFO', HiredAt: 'last year', Organisation: 'Amazon', Email: '[email protected]'}
});
The first parameter in the update
method is the primary key (hash + range) and the second method is a query that
defines the updates of the fields.
You can use $set: { field: { $ifNotExists: value } }
to only set the value if the field does not exists on the record
Employee.update({Organisation: 'Amazon', Email: '[email protected]'}, {$set: {Title: 'CTO', HiredAt: {$ifNotExists: 'today'}}, $inc: {Salary: 150}, $push: {Hobby: {$each: ['swimming', 'walking']}}}).exec()
.then(employee => {
// => {FirstName: 'Foo', Name: 'Bar', Salary: 4650, Title: 'CTO', HiredAt: 'last year', Organisation: 'Amazon', Email: '[email protected]', Hobby: ['cycling', 'swimming', 'walking']}
});
Or, if working with Sets you can use $addToSet
to add unique values to a Set, it supports single value, arrays and $each
operator.
Employee.update({Organisation: 'Amazon', Email: '[email protected]'}, {$addToSet: {Departments: ['IT', 'IT', 'HR']}}).exec()
.then(employee => {
// => {FirstName: 'Foo', Name: 'Bar', Salary: 4650, Title: 'CTO', Organisation: 'Amazon', Email: '[email protected]', Hobby: ['cycling', 'swimming', 'walking'], Departments: ['IT', 'HR']}
});
You can use $removeFromSet
to remove one, or many elements from sets
Employee.update({Organisation: 'Amazon', Email: '[email protected]'}, {$removeFromSet: {Departments: ['IT']}}).exec()
.then(employee => {
// => {FirstName: 'Foo', Name: 'Bar', Salary: 4650, Title: 'CTO', Organisation: 'Amazon', Email: '[email protected]', Hobby: ['cycling', 'swimming', 'walking'], Departments: ['HR']}
});
You can use $unshift
to prepend a list with one or multiple values.
Employee.update({Organisation: 'Amazon', Email: '[email protected]'}, {$unshift: {Hobby: 'programming'}}).exec()
.then(employee => {
// => {FirstName: 'Foo', Name: 'Bar', Salary: 4650, Title: 'CTO', Organisation: 'Amazon', Email: '[email protected]', Hobby: ['programming', 'cycling', 'swimming', 'walking'], Departments: ['IT']}
});
If no Amazon employee exists with that email address exists, the method will fail.
You can also add extra conditions, for instance if we want to increase the salary by $150 only if the current salary is less then $4500.
Employee.update({Organisation: 'Amazon', Email: '[email protected]'}, {$inc: {Salary: 150}}).where({Salary: {$lt: 4500}}).exec()
.catch(err => {
// ConditionalCheckFailedException: The conditional request failed
});
The remove method expects the primary key (hash + range).
Employee.remove({Organisation: 'Amazon', Email: '[email protected]'}).exec()
.then(() => {
// => removed
});
This method is the same as the remove
method, except that it will return the removed record..
Employee.findOneAndRemove({Organisation: 'Amazon', Email: '[email protected]'}).exec()
.then(result => {
// => {Organisation: 'Amazon', Email: '[email protected]'}
});
By default, all reads are eventually consistent which means the response migh include some stale data.
When you request a strongly consistent read, DynamoDB returns a response with the most up-to-date data, reflecting the updates from all prior write operations that were successful.
Dynongo supports strongly consistent reads by adding the .consistent()
chaining operator.
Employee
.find({Organisation: 'Amazon'})
.where({Salary: {$gt: 3000}})
.select('FirstName Name')
.consistent()
.exec()
.then(employees => {
// => [{FirstName: 'Foo', Name: 'Bar'}]
});
More information can be found in the AWS documentation.
The BatchWriteItem operation puts or deletes multiple items in one or more tables. A single call to BatchWrite can write up to 16 MB of data, which can comprise as many as 25 put or delete requests. Individual items to be written can be as large as 400 KB.
You can create Put and Delete request by calling the method on Table with the correct parameters.
const result = await db.batchWrite(
Table1.createBatchPutItem(
{partitionKey: 'PK', sortKey: 'SK'},
{name: 'Sander', lastname: 'Machado'}
),
Table1.createBatchPutItem(
{partitionKey: 'PK', sortKey: 'SK23'},
{name: 'Sander', lastname: 'Doe'}
),
Table2.createBatchDeleteItem(
{partitionKey: '123', sortKey: '456'}
),
Table2.createBatchDeleteItem(
{partitionKey: 'PK2', sortKey: 'SK3'}
),
Table2.createBatchPutItem(
{partitionKey: 'PK', sortKey: 'SK'},
{name: 'name', lastname: 'lastname'}
)
).exec();
The library also supports transactions. Transactions simplify the developer experience of making coordinated, all-or-nothing changes to multiple items both within and across tables. You can only provide up to 10 transaction requests per transaction.
import dynongo from 'dynongo';
const result = await dynongo
.transactRead(
dynongo.table('User')
.find({Id: '1234', Key: 'BankRoll'}),
dynongo.table('BankAccount')
.find({Key: 'Salary'})
)
.exec();
//=> [{Id: '1234', Key: 'BankRoll', Value: 100}, {Key: 'Salary', Value: 1500}]
For instance, what if we want to increment the bankroll of a user, but only if we still have enough money on our own back account.
import dynongo from 'dynongo';
await dynongo
.transactWrite(
dynongo.table('User')
.update({Id: '1234', Key: 'BankRoll'}, {$inc: {Amount: 150}})
)
.withConditions(
dynongo.table('BankAccount')
.find({Key: 'Salary'})
.where({value: {$gte: 150}})
)
.exec();
You can retrieve a list of all the tables.
db.listTables().exec().then(tables => {
console.log(tables);
//=> ['foo', 'bar', 'baz']
});
If you passed in a prefix
property in the connection object, only the tables with that prefix will
be returned.
You can implement paging by using the startFrom()
method together with the LastEvaluatedKey
property returned when using the raw()
method.
const result = Employee.find({Organisation: 'Amazon'}).where({Salary: {$gt: 3000}}).limit(1).raw().exec()
.then(result => {
/**
* {
* "Items": [
* { UserId: '1', FirstName: 'Foo', Name: 'Bar' }
* ],
* "Count": 1,
* "ScannedCount": 1,
* "LastEvaluatedKey": {
* Organisation: 'Amazon',
* UserId: '1'
* }
* }
*/
// Retrieve the next page
return Employee.find({Organisation: 'Amazon'}).where({Salary: {$gt: 3000}}).startFrom(result.LastEvaluatedKey).limit(1).raw().exec()
})
.then(result => {
/**
* {
* "Items": [
* { UserId: '2', FirstName: 'Unicorn', Name: 'Rainbow' }
* ],
* "Count": 1,
* "ScannedCount": 1,
* "LastEvaluatedKey": {
* Organisation: 'Amazon',
* UserId: '2'
* }
* }
*/
});
You can also use dynongo-pager to make paging even easier.
A table can be created by either calling create()
on a table instance or by calling createTable
on the database instance.
The first way is by calling the create()
method.
const Employee = db.table('Employee');
const schema = {
TableName: 'Employee',
AttributeDefinitions: [
{ AttributeName: 'id', AttributeType: 'S' }
],
KeySchema: [
{ AttributeName: 'id', KeyType: 'HASH' }
],
ProvisionedThroughput: {
ReadCapacityUnits: 1,
WriteCapacityUnits: 1
}
};
Employee.create(schema).exec()
.then(() => {
// => Table is being created
});
The second way is by calling the createTable()
method.
db.createTable(schema).exec()
.then(() => {
// Table is being created
});
This is shorthand for the first method.
Creating a table can take a while. The previous examples do not wait for the action to be completed. But there
might be use cases where you have to wait untill the table is created entirely before continuing.
This can be done with the wait()
method.
db.createTable(schema).wait().exec()
.then(() => {
// Table is created
});
This will make sure the table is polled every 1000 milliseconds untill the status of the table is active
. If you want to poll
at another speed, you can by providing the number of milliseconds in the wait
method.
db.createTable(schema).wait(5000).exec();
This will poll the status of the table every 5 seconds instead of every second.
A table can be dropped by either calling drop()
on a table instance or by calling dropTable()
on the database instance.
The first way is by calling the drop()
method.
const Employee = db.table('Employee');
Employee.drop().exec()
.then(() => {
// => Table is being dropped
});
The second way is by calling the dropTable()
method.
db.dropTable('Employee').exec()
.then(() => {
// => Table is being dropped
})
This method is just a shorthand method for the first example.
Dropping a table can take a while, especially when the table has a lot of data. The previous examples do not wait for the action to be completed. But there
might be use cases where you have to wait untill the table is removed entirely before continuing. This can be done with the wait()
method.
db.dropTable('Employee').wait().exec()
.then(() => {
// => Table is dropped
})
This will make sure the table is polled every 1000 milliseconds untill the table does not exist anymore. If you want to poll at another speed, you can by providing
the number of milliseconds in the wait
method.
db.dropTable('Employee').wait(5000).exec();
This will poll the status of the table every 5 seconds instead of every second.
- dynongo-pager - Easy paging for DynamoDB with dynongo
MIT © Sam Verschueren