ElectroDB

ElectroDB is a dynamodb library to ease the use of having multiple entities and complex hierarchical relationships in a single dynamodb table.

This library is a work in progress, please submit issues/feedback or reach out on twitter @tinkertamper.

Features

Attribute Schema Enforcement: Define a schema for your entities with enforced attribute validation, defaults, types, aliases, and more.
Easily Compose Hierarchical Access Patterns: Plan and design hierarchical keys for your indexes to multiply your possible access patterns.
Single Table Entity Segregation: Entities created with ElectroDB will not conflict with other entities when using a single table.
Simplified Sort Key Condition Querying: Write efficient sort key queries by easily building compose keys.
Simplified Filter Composition: Easily create complex readable filters for Dynamo queries without worrying about the implementation of ExpressionAttributeNames, ExpressionAttributeValues.
Easily Query Across Entities: Define "collections" to create powerful/peformant queries that return multiple entities in a single request.
Automatic Index Selection: Use .find() method to dynamically and effeciently query based on defined sort key structures.
Simplified Pagination API Use .page() to easily iterate through multiquery result sets.

Turn this:

MallStores.query
	.leases({ mallId: "EastPointe" })
	.between({ leaseEndDate:  "2020-04-01" }, { leaseEndDate:  "2020-07-01" })
	.filter(({rent, discount}) => `
		${rent.between("2000.00", "5000.00")} AND ${discount.lte("1000.00")}
	`)
	.params();

Into This:

{
  "IndexName": "idx2",
  "TableName": "electro",
  "ExpressionAttributeNames": {
    "#rent": "rent",
    "#discount": "discount",
		"#pk": "idx2pk",
    "#sk1": "idx2sk"
  },
  "ExpressionAttributeValues": {
    ":rent1": "2000.00",
    ":rent2": "5000.00",
    ":discount1": "1000.00",
    ":pk": "$mallstoredirectory_1#mallid_eastpointe",
    ":sk1": "$mallstore#leaseenddate_2020-04-01#rent_",
    ":sk2": "$mallstore#leaseenddate_2020-07-01#rent_"
  },
  "KeyConditionExpression": "#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2",
  "FilterExpression": "(#rent between :rent1 and :rent2) AND #discount <= :discount1"
}

Installation

Install from NPM

npm install electrodb --save

Usage

Require Entity and/or Service from electrodb:

const {Entity, Service} = require("electrodb");

Entities and Services

To see full examples of ElectroDB in action, go to the Examples section.

Entity allows you to create separate and individual business objects in a DynamoDB table. When queried your results will not include other Entities that exist the same table. For more detail, read Entities.

Service allows you to build a relationships across Entities. A service imports Entity Models, builds individual Entities and builds Collections for cross Entity querying. For more detail, read Services.

You can use Entities independent of Services, you do not need to import models into a Service to use them individually. However, you do you need to use a Service if you intend make queries join multiple Entities.

Entities

In ElectroDB an Entity is represents a single business object. For example, in a simple task tracking application, one Entity could represent an Employee and another Entity might represent a the Task that the employee is assigned to.

Require or import Entity from electrodb:

const {Entity} = require("electrodb");

Services

In ElectroDB a Service represents a collection of Entities and also allows you to build queries span across Entities. Similar to Entities, Services can coexist on a single table without collision. You can use Entities independent of Services, you do not need to import models into a Service to use them individually. However, you do you need to use a Service if you intend make queries join multiple Entities.

Require electrodb:

const {Service} = require("electrodb");

Model

Create an Entity's schema. In the below example.

const  DynamoDB  =  require("aws-sdk/clients/dynamodb");
const {Entity, Service} = require("electrodb");
const client = new DynamoDB.DocumentClient();
const EmployeesModel = {
	entity: "employees",
	version: "1",
	service: "taskapp",
	table: "projectmanagement",
	attributes: {
		employee: {
			type: "string",
			default: () => uuidv4(),
		},
		firstName: {
			type: "string",
			required: true,
		},
		lastName: {
			type: "string",
			required: true,
		},
		office: {
			type: "string",
			required: true,
		},
		title: {
			type: "string",
			required: true,
		},
		team: {
			type: ["development", "marketing", "finance", "product", "cool cats and kittens"],
			required: true,
		},
		salary: {
			type: "string",
			required: true,
		},
		manager: {
			type: "string",
		},
		dateHired: {
			type: "string",
			validate: /^\d{4}-\d{2}-\d{2}$/gi
		},
		birthday: {
			type: "string",
			validate: /^\d{4}-\d{2}-\d{2}$/gi
		},
	},
	indexes: {
		employee: {
			pk: {
				field: "pk",
				facets: ["employee"],
			},
			sk: {
				field: "sk",
				facets: [],
			},
		},
		coworkers: {
			index: "gsi1pk-gsi1sk-index",
			collection: "workplaces",
			pk: {
				field: "gsi1pk",
				facets: ["office"],
			},
			sk: {
				field: "gsi1sk",
				facets: ["team", "title", "employee"],
			},
		},
		teams: {
			index: "gsi2pk-gsi2sk-index",
			pk: {
				field: "gsi2pk",
				facets: ["team"],
			},
			sk: {
				field: "gsi2sk",
				facets: ["title", "salary", "employee"],
			},
		},
		employeeLookup: {
			collection: "assignments",
			index: "gsi3pk-gsi3sk-index",
			pk: {
				field: "gsi3pk",
				facets: ["employee"],
			},
			sk: {
				field: "gsi3sk",
				facets: [],
			},
		},
		roles: {
			index: "gsi4pk-gsi4sk-index",
			pk: {
				field: "gsi4pk",
				facets: ["title"],
			},
			sk: {
				field: "gsi4sk",
				facets: ["salary", "employee"],
			},
		},
		directReports: {
			index: "gsi5pk-gsi5sk-index",
			pk: {
				field: "gsi5pk",
				facets: ["manager"],
			},
			sk: {
				field: "gsi5sk",
				facets: ["team", "office", "employee"],
			},
		},
	},
	filters: {
		upcomingCelebrations: (attributes, startDate, endDate) => {
			let { dateHired, birthday } = attributes;
			return `${dateHired.between(startDate, endDate)} OR ${birthday.between(
				startDate,
				endDate,
			)}`;
		},
	},
};

const TasksModel = {
	entity: "tasks",
	version: "1",
	service: "taskapp",
	table: "projectmanagement",
	attributes: {
		task: {
			type: "string",
			default: () => uuidv4(),
		},
		project: {
			type: "string",
		},
		employee: {
			type: "string",
		},
		description: {
			type: "string",
		},
	},
	indexes: {
		task: {
			pk: {
				field: "pk",
				facets: ["task"],
			},
			sk: {
				field: "sk",
				facets: ["project", "employee"],
			},
		},
		project: {
			index: "gsi1pk-gsi1sk-index",
			pk: {
				field: "gsi1pk",
				facets: ["project"],
			},
			sk: {
				field: "gsi1sk",
				facets: ["employee", "task"],
			},
		},
		assigned: {
			collection: "assignments",
			index: "gsi3pk-gsi3sk-index",
			pk: {
				field: "gsi3pk",
				facets: ["employee"],
			},
			sk: {
				field: "gsi3sk",
				facets: ["project", "task"],
			},
		},
	},
};

Create individual Entities with the Models or join them via a Service:

// Independent Models
let employees = new Entity(EmployeesModel, { client });
let tasks = new Entity(TasksModel, { client });

// Joined via a Service
let TaskApp = new Service({
		version: "1",
		service: "TaskApp",
		table: "projectmanagement",
	},
	{ client },
);
TaskApp.join(EmployeesModel); // TaskApp.entities.employees
TaskApp.join(TasksModel); // TaskApp.entities.tasks

Model Properties

Property	Description
service	Name of the application using the entity, used to namespace all entities
entity	Name of the entity that the schema represents
table	Name of the dynamodb table in aws
version	(optional) The version number of the schema, used to namespace keys
attributes	An object containing each attribute that makes up the schema
indexes	An object containing table indexes, including the values for the table's default Partition Key and Sort Key
filters	An object containing user defined filter template functions.

Service Properties

Property	Description
service	Name of the service, used to namespace all joined entities, will override the model definition.
table	Name of the dynamodb table in aws, will override the model definition.
version	(optional) The version number of the schema, used to namespace keys, will override the model definition.

Model/Service Options

Optional second parameter

Property	Description
client	(optional) A docClient instance for use when querying a DynamoDB table. This is optional if you wish to only use the `params` functionality, but required if you actually need to query against a database.

Attributes

Attributes define an Entity record. The propertyName represents the value your code will use to represent an attribute.

Pro-Tip: Using the field property, you can map an AttributeName to a different field name in your table. This can be useful to utilize existing tables, existing models, or even to reduce record sizes via shorter field names.

Simple Syntax

Assign just the type of the attribute directly to the attribute name. Currently supported options are "string", "number", "boolean", an array of strings representing a fixed set of possible values, or "any" which disables value type checking on that attribute.

attributes: {
	<AttributeName>: "string"|"number"|"boolean"|"any"|string[]
}

Expanded Syntax

Use the expanded syntax build out more robust attribute options.

attributes: {
	<AttributeName>: {
		"type": string|string[],
		"required"?: boolean,
		"default"?: value|() => value
		"validate"?: RegExp|(value: any) => void|string
		"field"?: string
		"readOnly"?: boolean
		"label"?: string
		"cast"?: "number"|"string"|"boolean",
		"get"?: (attribute, schema) => value,
		"set"?: (attribute, schema) => value 
	}
}

Property	Type	Required	Description
`type`	`string`, `string[]`	yes	Accepts the values: `"string"`, `"number"` `"boolean"`, an array of strings representing a finite list of acceptable values: `["option1", "option2", "option3"]`, or `"any"`which disables value type checking on that attribute.
`required`	`boolean`	no	Whether or not the value is required when creating a new record.
`default`	`value`, `() => value`	no	Either the default value itself or a synchronous function that returns the desired value.
`validate`	`RegExp`, `(value: any) => void	string`	no
`field`	`string`	no	The name of the attribute as it exists dynamo, if named differently in the schema attributes. Defaults to the `AttributeName` as defined in the schema.
`readOnly`	`boolean`	no	Prevents update of the property after the record has been created. Attributes used in the composition of the table's primary Partition Key and Sort Key are by read-only by default.
`label`	`string`	no	Used in index composition to prefix key facets. By default, the `AttributeName` is used as the label.
`cast`	`"number"`, `"string"`, `"boolean"`	no	Optionally cast attribute values when interacting with DynamoDB. Current options include: "number", "string", and "boolean".
`set`	`(attribute, schema) => value`	no	A synchronous callback allowing you apply changes to a value before it is set in params or applied to the database. First value represents the value passed to ElectroDB, second value are the attributes passed on that update/put
`get`	`(attribute, schema) => value`	no	A synchronous callback allowing you apply changes to a value after it is retrieved from the database. First value represents the value passed to ElectroDB, second value are the attributes retrieved from the database.

Indexes

The indexes object requires at least the definition of the table's natural Partition Key and (if applicable) Sort Key.

Indexes are defined, and later referenced by their accessPatternName. These defined via a facets array that is made up of attributes names as listed the model.

indexes: {
	<accessPatternName>: {
		"pk": {
			"field": <string>
			"facets": <AttributeName[]>
		},
		"sk"?: {
			"field": <string>
			"facets": <AttributesName[]>
		},
		"index"?: string
		"collection"?: string
	}
}

Property	Type	Required	Description
`pk`	`object`	yes	Configuration for the pk of that index or table
`pk.facets`	`boolean`	no	An array that represents the order in which attributes are concatenated to facets the key (see Facets below for more on this functionality).
`pk.field`	`string`	yes	The name of the attribute as it exists dynamo, if named differently in the schema attributes.
`sk`	`object`	no	Configuration for the sk of that index or table
`sk.facets`	`array	string`	no
`sk.field`	`string`	yes	The name of the attribute as it exists dynamo, if named differently in the schema attributes.
`index`	`string`	no	Required when the `Index` defined is a Secondary Index; but is left blank for the table's primary index.
`collection`	`string`	no	Used when models are joined to a `Service`. When two entities share a `collection` on the same `index`, they can be queried with one request to DynamoDB. The name of the collection should represent what the query would return as a pseudo `Entity`. (see Collections below for more on this functionality).

Facets

A Facet is a segment of a key based on one of the attributes. Facets are concatenated together from either a Partition Key or an Sort Key key, which define an index.

Note: Only attributes with a type of "string", "number", or "boolean" can be used as a facet

There are two ways to provide facets:

As a Facet Array
As a Facet Template

For example, in the following Access Pattern, "locations" is made up of the facets storeId, mallId, buildingId and unitId which map to defined attributes in the schema:

// Input
{
    storeId: "STOREVALUE",
    mallId: "MALLVALUE",
    buildingId: "BUILDINGVALUE",
    unitId: "UNITVALUE"
};

// Output:
{
	pk: '$mallstoredirectory_1#storeId_storevalue',
	sk: '$mallstores#mallid_mallvalue#buildingid_buildingvalue#unitid_unitvalue'
}

For PK values, the service and version values from the model are prefixed onto the key.

For SK values, the entity value from the model is prefixed onto the key.

Facet Arrays

In a Facet Array, each element is the name of the corresponding Attribute defined in the Model. If the Attribute has a label property, that will be used to prefix the facets, otherwise the full Attribute name will be used.

attributes: {
	storeId: {
		type: "string",
		label: "sid",
	},
	mallId: {
		type: "string",
		label: "mid",
	},
	buildingId: {
		type: "string",
		label: "bid",
	},
	unitId: {
		type: "string",
		label: "uid",
	}
},
indexes: {
	locations: {
		pk: {
			field: "pk",
			facets: ["storeId"]
		},
		sk: {
			field: "sk",
			facets: ["mallId", "buildingId", "unitId"]
		}
	}
}
    
// Input
{
    storeId: "STOREVALUE",
    mallId: "MALLVALUE",
    buildingId: "BUILDINGVALUE",
    unitId: "UNITVALUE"
};

// Output:
{
	pk: '$mallstoredirectory_1#sid_storevalue',
	sk: '$mallstores#mid_mallvalue#bid_buildingvalue#uid_unitvalue'
}

Facet Templates

In a Facet Template, you provide a formatted template for ElectroDB to use when making keys. Facet Templates allow for potential ElectroDB adoption on already established tables and records.

Attributes are identified by a prefixed colon and the attributes name. For example, the syntax :storeId will matches storeId attribute in the model.

Convention for a composing a key use the # symbol to separate attributes, and for labels to attach with underscore. For example, when composing both the mallId and buildingId would be expressed as mid_:mallId#bid_:buildingId.

ElectroDB will not prefix templated keys with the Entity, Project, Version, or Collection. This will give you greater control of your keys but will limit ElectroDB's ability to prevent leaking entities with some queries.

Facet Templates have some "gotchas" to consider: 1. Keys only allow for one instance of an attribute, the template :prop1#:prop1 will be interpreted the same as :prop1#. 2. ElectoDB will continue to always add a trailing delimiter to facets with keys are partially supplied. (More documentation coming on this soon)

attributes: {
	storeId: {
		type: "string"
	},
	mallId: {
		type: "string"
	},
	buildingId: {
		type: "string"
	},
	unitId: {
		type: "string"
	}
},
indexes: {
	locations: {
		pk: {
			field: "pk",
			facets: "sid_:storeId"
		},
		sk: {
			field: "sk",
			facets: "mid_:mallId#bid_:buildingId#uid_:unitId"
		}
	}
}


// Input
{
    storeId: "STOREVALUE",
    mallId: "MALLVALUE",
    buildingId: "BUILDINGVALUE",
    unitId: "UNITVALUE"
};

// Output:
{
	pk: 'sid_storevalue',
	sk: 'mid_mallvalue#bid_buildingvalue#uid_unitvalue'
}

Collections

A Collection is a grouping of Entities with the same Partition Key and allows you to make efficient query across multiple entities. If you background is SQL, imagine Partition Keys as Foreign Keys, a Collection represents a View with multiple joined Entities.

Collections are defined on an Index, and the name of the collection should represent what the query would return as a pseudo Entity.

Note: collection should be unique to a single common index across entities.

Using the TaskApp Models defined in Models, these models share a collection called assignments on the index gsi3pk-gsi3sk-index

let TaskApp =  new  Service({
	version:  "1", 
	service:  "TaskApp", 
	table:  "projectmanagement"
},  { client }); 
TaskApp.join(EmployeesModel);  // TaskApp.entities.employees
TaskApp.join(TasksModel);  // TaskApp.entities.tasks

TaskApp.collections.assignments({employee: "JExotic"}).params();

// Results
{
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi3pk', '#sk1': 'gsi3sk' },
  ExpressionAttributeValues: { ':pk': '$taskapp_1#employee_joeexotic', ':sk1': '$assignments' },
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  IndexName: 'gsi3pk-gsi3sk-index'
}

Filters

Filters are no longer the preferred way to add FilterExpressions. Checkout the Where section to find out about how to apply FilterExpressions and ConditionExpressions

Building thoughtful indexes can make queries simple and performant. Sometimes you need to filter results down further. By adding Filters to your model, you can extend your queries with custom filters. Below is the traditional way you would add a filter to Dynamo's DocumentClient directly along side how you would accomplish the same using a Filter function.

{
  IndexName: 'idx2',
  TableName: 'electro',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}

Defined on the model

/**
	* Filter by low rent a specific mall or a leaseEnd withing a specific range  
	* @param {Object} attributes - All attributes from the model with methods for each filter operation  
	* @param {...*} values - Values passed when calling the filter in a query chain.
**/
filters: {
	rentPromotions: function(attributes, minRent, maxRent, promotion)  {
		let {rent, discount} = attributes;
		return `
			${rent.between(minRent, maxRent)} AND ${discount.lte(promotion)}
		`
	}
}


let MallStores  =  new Entity("MallStores", model);
let maxRent = "5000.00";
let minRent = "2000.00";
let promotion = "1000.00";
let stores  =  MallStores.query
	.stores({ mallId: "EastPointe" })
	.between({ leaseEndDate:  "2020-04-01" }, { leaseEndDate:  "2020-07-01" })
	.rentPromotions(minRent, maxRent, promotion)
	.params();

// Results
{
  IndexName: 'idx2',
  TableName: 'electro',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}

Defined via Filter method after query operators

let MallStores  =  new Entity("MallStores", model);
let maxRent = "5000.00";
let minRent = "2000.00";
let promotion = "1000.00";
let stores  =  MallStores.query
	.leases({ mallId: "EastPointe" })
	.between({ leaseEndDate:  "2020-04-01" }, { leaseEndDate:  "2020-07-01" })
	.filter(({rent, discount}) => `
		${rent.between(minRent, maxRent)} AND ${discount.lte(promotion)}
	`)
	.params();

// Results
{
  IndexName: 'idx2',
  TableName: 'electro',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}

Filter functions allow you to write a FilterExpression without having to worry about the complexities of expression attributes. To accomplish this, ElectroDB injects an object attributes as the first parameter to all Filter Functions. This object contains every Attribute defined in the Entity's Model with the following operators as methods:

operator	example	result
`gte`	`rent.gte(maxRent)`	`#rent >= :rent1`
`gt`	`rent.gt(maxRent)`	`#rent > :rent1`
`lte`	`rent.lte(maxRent)`	`#rent <= :rent1`
`lt`	`rent.lt(maxRent)`	`#rent < :rent1`
`eq`	`rent.eq(maxRent)`	`#rent = :rent1`
`begins`	`rent.begins(maxRent)`	`begins_with(#rent, :rent1)`
`exists`	`rent.exists()`	`attribute_exists(#rent)`
`notExists`	`rent.notExists()`	`attribute_not_exists(#rent)`
`contains`	`rent.contains(maxRent)`	`contains(#rent = :rent1)`
`notContains`	`rent.notContains(maxRent)`	`not contains(#rent = :rent1)`
`between`	`rent.between(minRent, maxRent)`	`(#rent between :rent1 and :rent2)`
`name`	`rent.name()`	`#rent`
`value`	`rent.value(maxRent)`	`:rent1`

This functionality allows you to write the remaining logic of your FilterExpression with ease. Add complex nested and/or conditions or other FilterExpression logic while ElectroDB handles the ExpressionAttributeNames and ExpressionAttributeValues.

Multiple Filters

It is possible to include chain multiple filters. The resulting FilterExpressions are concatinated with an implicit AND operator.

let MallStores = new Entity("MallStores", model);
let stores = MallStores.query
	.leases({ mallId: "EastPointe" })
	.between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
	.filter(({ rent, discount }) => `
		${rent.between("2000.00", "5000.00")} AND ${discount.eq("1000.00")}
	`)
	.filter(({ category }) => `
		${category.eq("food/coffee")}
	`)
	.params();

// Results
{
  TableName: 'StoreDirectory',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#category': 'category',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':category1': 'food/coffee',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#storeid_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#storeid_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  IndexName: 'idx2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND (#discount = :discount1 AND #category = :category1)'
}

Where

The where() method is an improvement on the filter() method. Unlike filter, where will be compatible with upcoming features related to complex types.

Building thoughtful indexes can make queries simple and performant. Sometimes you need to filter results down further or add conditions to an update/patch/put/create/delete action.

FilterExpressions

Below is the traditional way you would add a FilterExpression to Dynamo's DocumentClient directly along side how you would accomplish the same using the where method.

{
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  TableName: 'zoodirectory',
  ExpressionAttributeNames: {
    '#animal': 'animal',
    '#lastFed': 'lastFed',
    '#pk': 'pk',
    '#sk1': 'sk'
  },
  ExpressionAttributeValues: {
    ':animal_w1': 'Warthog',
    ':lastFed_w1': '2020-09-25',
    ':lastFed_w2': '2020-09-28',
    ':pk': '$zoodirectory_1#habitat_africa',
    ':sk1': '$exibits#enclosure_'
  },
  FilterExpression: '#animal = :animal_w1 AND (#lastFed between :lastFed_w1 and :lastFed_w2)'
}

animals.query
		.farm({habitat: "Africa"})
		.where(({animal, dangerous}, {value, name, between}) => `
			${name(animal)} = ${value(animal, "Warthog")} AND ${between(dangerous, "2020-09-25", "2020-09-28")}
		`)
		.params()

ConditionExpressions

Below is the traditional way you would add a ConditionExpression to Dynamo's DocumentClient directly along side how you would accomplish the same using the where method.

{
  UpdateExpression: 'SET #dangerous = :dangerous',
  ExpressionAttributeNames: { '#animal': 'animal', '#dangerous': 'dangerous' },
  ExpressionAttributeValues: {
    ':animal_w1': 'Zebra',
    ':dangerous_w1': false,
    ':dangerous': true
  },
  TableName: 'zoodirectory',
  Key: {
    pk: '$zoodirectory_1#habitat_africa',
    sk: '$exibits#enclosure_5b'
  },
  ConditionExpression: '#animal = :animal_w1 AND #dangerous = :dangerous_w1'
}

animals.update({habitat: "Africa", enclosure: "5b"})
		.set({dangerous: true})
		.where(({animal, dangerous}, {value, name, eq}) => `
			${name(animal)} = ${value(animal, "Zebra")} AND ${eq(dangerous)}
		`)
		.params())

Attributes and Operations

Where functions allow you to write a FilterExpression or ConditionExpression without having to worry about the complexities of expression attributes. To accomplish this, ElectroDB injects an object attributes as the first parameter to all Filter Functions, and an object operations, as the second parameter. Pass the properties from the attributesobject to the methods found on theoperations` object, along with inline values to set filters and conditions:

// A single filter operation
animals.update({habitat: "Africa", enclosure: "5b"})
	.set({keeper: "Joe Exotic"})
	.where((attr, op) => op.eq(attr.dangerous, true))
	.params());

// Multiple conditions
animals.update({habitat: "Africa", enclosure: "5b"})
	.set({keeper: "Joe Exotic"})
	.where((attr, op) => `
		${op.eq(attr.dangerous, true)} AND ${op.contains(attr.diet, "meat")}
	`)
	.params());

The attributes object contains every Attribute defined in the Entity's Model. The operations object contains the following methods:

operator	example	result
`gte`	`gte(rent, value)`	`#rent >= :rent1`
`gt`	`gt(rent, maxRent)`	`#rent > :rent1`
`lte`	`lte(rent, maxRent)`	`#rent <= :rent1`
`lt`	`lt(rent, maxRent)`	`#rent < :rent1`
`eq`	`eq(rent, maxRent)`	`#rent = :rent1`
`begins`	`begins(rent, maxRent)`	`begins_with(#rent, :rent1)`
`exists`	`exists(rent)`	`attribute_exists(#rent)`
`notExists`	`notExists(rent)`	`attribute_not_exists(#rent)`
`contains`	`contains(rent, maxRent)`	`contains(#rent = :rent1)`
`notContains`	`notContains(rent, maxRent)`	`not contains(#rent = :rent1)`
`between`	`between(rent, minRent, maxRent)`	`(#rent between :rent1 and :rent2)`
`name`	`name(rent)`	`#rent`
`value`	`value(rent, maxRent)`	`:rent1`

Multiple Where Clauses

It is possible to include chain multiple where clauses. The resulting FilterExpressions (or ConditionExpressions) are concatinated with an implicit AND operator.

let MallStores = new Entity("MallStores", model);
let stores = MallStores.query
	.leases({ mallId: "EastPointe" })
	.between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
	.where(({ rent, discount }, {between, eq}) => `
		${between(rent, "2000.00", "5000.00")} AND ${eq(discount, "1000.00")}
	`)
	.where(({ category }, {eq}) => `
		${eq(category, "food/coffee")}
	`)
	.params();

// Results
{
  TableName: 'StoreDirectory',
  ExpressionAttributeNames: {
    '#rent': 'rent',
    '#discount': 'discount',
    '#category': 'category',
    '#pk': 'idx2pk',
    '#sk1': 'idx2sk'
  },
  ExpressionAttributeValues: {
    ':rent1': '2000.00',
    ':rent2': '5000.00',
    ':discount1': '1000.00',
    ':category1': 'food/coffee',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-04-01#storeid_',
    ':sk2': '$mallstore#leaseenddate_2020-07-01#storeid_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  IndexName: 'idx2',
  FilterExpression: '(#rent between :rent1 and :rent2) AND (#discount = :discount1 AND #category = :category1)'
}

Building Queries

Forming a composite Partition Key and Sort Key is a critical step in planning Access Patterns in DynamoDB. When planning composite keys, it is critical to consider the order in which they are composed. As of the time of writing this documentation, DynamoDB has the following constraints that should be taken into account when planning your Access Patterns:

You must always supply the Partition Key in full for all queries to DynamoDB.
You currently only have the following operators available on a Sort Key: begins_with, between, >, >=, <, <=, and Equals.
To act on single record, you will need to know the full Partition Key and Sort Key for that record.

Sort Key Operations

operator	use case
`begins_with`	Keys starting with a particular set of characters.
`between`	Keys between a specified range.
`eq`	Keys equal to some value
`gt`	Keys less than some value
`gte`	Keys less than or equal to some value
`lt`	Keys greater than some value
`lte`	Keys greater than or equal to some value

Using facets to make hierarchical keys

Carefully considering your Facet order will allow *ElectroDB to express hierarchical relationships and unlock more available Access Patterns for your application.

For example, let's say you have a MallStore Entity that represents Store Locations inside Malls:

Shopping Mall Stores

let model = {  
	service: "MallStoreDirectory",  
	entity: "MallStore",  
	table: "StoreDirectory",  
	version: "1",  
	attributes: {  
		mallId: {  
			type: "string",  
			required: true,  
		},  
		storeId: {  
			type: "string",  
			required: true,  
		},  
		buildingId: {  
			type: "string",  
			required: true,  
		},  
		unitId: {  
			type: "string",  
			required: true,
		},  
		category: {  
			type: [
				"spite store",
				"food/coffee", 
				"food/meal", 
				"clothing", 
				"electronics", 
				"department", 
				"misc"
			],  
			required: true  
		},  
		leaseEndDate: {  
			type: "string",  
			required: true  
		},
		rent: {
			type: "string",
			required: true,
			validate: /^(\d+\.\d{2})$/
		},
		discount: {
			type: "string",
			required: false,
			default: "0.00",
			validate: /^(\d+\.\d{2})$/
		}  
	},  
	indexes: {  
	    stores: {  
			pk: {
				field: "pk",
				facets: ["storeId"]
			}, 
			sk: {
				field: "sk",
				facets: ["mallId", "buildingId", "unitId"]
			}  
		},  
		malls: {  
			index: "idx1",  
			pk: {
				field: "idx1pk",
				facets: ["mallId"]
			},  
			sk: {
				field: "idx1sk",
				facets: ["buildingId", "unitId", "storeId"]
			}  
		},
		leases: {
			index: "idx2",
			pk: {
				field: "idx2pk",
				facets: ["mallId"]
			},  
			sk: {
				field: "idx2pk",
				facets: ["leaseEndDate", "storeId", "buildingId", "unitId"]
			}  
		}
	},
	filters: {
		byCategory: ({category}, name) => category.eq(name),
		rentDiscount: (attributes, discount, max, min) => {
			return `${attributes.discount.lte(discount)} AND ${attributes.rent.between(max, min)}`
		}
	}  
};

Each record represents one Store location. All Stores are located in Malls we manage.

To satisfy requirements for searching based on location, you could use the following keys: Each MallStore record would have a Partition Key with the store's storeId. This key alone is not enough to identify a particular store. To solve this, compose a Sort Key for the store's location attribute ordered hierarchically (mall/building/unit): ["mallId", "buildingId", "unitId"].

The MallStore entity above, using just the stores Index alone enables four Access Patterns:

All LatteLarrys locations in all Malls
All LatteLarrys locations in one Mall
All LatteLarrys locations inside a specific Mall
A specific LatteLarrys inside of a Mall and Building

Query Chains

Queries in ElectroDB are built around the Access Patterns defined in the Schema and are capable of using partial key Facets to create performant lookups. To accomplish this, ElectroDB offers a predictable chainable API.

Examples in this section using the MallStore schema defined above.

The methods: Get (get), Create (put), Update (update), and Delete (delete) *require all facets described in the Entities' primary PK and SK.

Get Method

Provide all facets in an object to the get method

await StoreLocations.get({
	storeId: "LatteLarrys", 
	mallId: "EastPointe", 
	buildingId: "BuildingA1", 
	unitId: "B47"
}).go();

// {
//   Key: {
//     pk: '$mallstoredirectory_1#storeid_lattelarrys',
//     sk: '$mallstore#mallid_eastpointe#buildingid_buildinga1#unitid_b47'
//   },
//   TableName: 'StoreDirectory'
// }

Delete Method

Provide all facets in an object to the delete method to delete a record.

await StoreLocations.delete({
	storeId: "LatteLarrys", 
	mallId: "EastPointe", 
	buildingId: "BuildingA1", 
	unitId: "B47"
}).go();

// {
//   Key: {
//     pk: '$mallstoredirectory_1#storeid_lattelarrys',
//     sk: '$mallstore#mallid_eastpointe#buildingid_buildinga1#unitid_b47'
//   },
//   TableName: 'StoreDirectory'
// }

Put Record

Provide all required Attributes as defined in the model to create a new record. ElectroDB will enforce any defined validations, defaults, casting, and field aliasing.

let store = {
	storeId: "LatteLarrys",
	mallId: "EastPointe",
	buildingId: "BuildingA1",
	unitId: "B47",
	category: "food/coffee",
	leaseEndDate: "2020-03-22",
  rent: "1500.00"
};

await StoreLocations.put(store).go();

// {
//   Item: {
//     mallId: 'EastPointe',
//     storeId: 'LatteLarrys',
//     buildingId: 'BuildingA1',
//     unitId: 'B47',
//     category: 'food/coffee',
//     leaseEndDate: '2020-03-22',
//     rent: '1500.00',
//     discount: '0.00',
//     pk: '$mallstoredirectory_1#storeid_lattelarrys',
//     sk: '$mallstore#mallid_eastpointe#buildingid_buildinga1#unitid_b47',
//     idx1pk: '$mallstoredirectory_1#mallid_eastpointe',
//     idx1sk: '$mallstore#buildingid_buildinga1#unitid_b47#storeid_lattelarrys',
//     idx2pk: '$mallstore#leaseenddate_2020-03-22#storeid_lattelarrys#buildingid_buildinga1#unitid_b47',
//     __edb_e__: 'MallStore'
//   },
//   TableName: 'StoreDirectory'
// }

Update Record

To update a record, pass all facets to the update method and then pass set attributes that need to be updated.

Note: If your update includes changes to an attribute that is also a facet for a global secondary index, you must provide all facets for that index.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let category = "food/meal";

await StoreLocations
	.update({storeId, mallId, buildingId, unitId})
	.set({category})
	.go();

// {
//   UpdateExpression: 'SET #category = :category',
//   ExpressionAttributeNames: { '#category': 'category' },
//   ExpressionAttributeValues: { ':category': 'food/meal' },
//   TableName: 'StoreDirectory',
//   Key: {
//     pk: '$mallstoredirectory_1#storeid_lattelarrys',
//     sk: '$mallstore#mallid_eastpointe#buildingid_buildinga1#unitid_b47'
//   }
// }

Scan Records

When scanning for rows, you can use filters the same as you would any query. For more detial on filters, see the Filters section.

Note: Scan functionality will be scoped to your Entity. This means your results will only include records that match the Entity defined in the model.

await StoreLocations.scan
	.filter(({category}) => `
		${category.eq("food/coffee")} OR ${category.eq("spite store")}  
	`)
	.filter(({leaseEndDate}) => `
		${leaseEndDate.between("2020-03", "2020-04")}
	`)
	.go();

// {
//   TableName: 'StoreDirectory',
//   ExpressionAttributeNames: {
//     '#category': 'category',
//     '#leaseEndDate': 'leaseEndDate',
//     '#pk': 'pk',
//     '#sk': 'sk'
//   },
//   ExpressionAttributeValues: {
//     ':category1': 'food/coffee',
//     ':category2': 'spite store',
//     ':leaseEndDate1': '2020-03',
//     ':leaseEndDate2': '2020-04',
//     ':pk': '$mallstoredirectory_1#storeid_',
//     ':sk': '$mallstore#mallid_'
//   },
//   FilterExpression: '(begins_with(#pk, :pk) AND begins_with(#sk, :sk)) AND (#category = :category1 OR #category = :category2) AND (#leaseEndDate between :leaseEndDate1 and :leaseEndDate2)'
// }

Patch Records

In DynamoDB, update operations by default will insert a record if record being updated does not exist. In ElectroDB, the patch method will utilize the attribute_exists() parameter dynamically to ensure records are only "patched" and not inserted when updating.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let category = "food/meal";

await StoreLocations
	.patch({storeId, mallId, buildingId, unitId})
	.set({category})
  .go()

// {
//   UpdateExpression: 'SET #category = :category',
//   ExpressionAttributeNames: { '#category': 'category' },
//   ExpressionAttributeValues: { ':category': 'food/meal' },
//   TableName: 'StoreDirectory',
//   Key: {
//     pk: '$mallstoredirectory_1#storeid_lattelarrys',
//     sk: '$mallstore#mallid_eastpointe#buildingid_buildinga1#unitid_b47'
//   },
//   ConditionExpression: 'attribute_exists(pk) AND attribute_exists(sk)'
// }

Create Records

In DynamoDB, put operations by default will overwrite a record if record being updated does not exist. In ElectroDB, the patch method will utilize the attribute_not_exists() parameter dynamically to ensure records are only "created" and not overwriten when inserting new records into the table.

let store = {
	storeId: "LatteLarrys",
	mallId: "EastPointe",
	buildingId: "BuildingA1",
	unitId: "B47",
	category: "food/coffee",
	leaseEndDate: "2020-03-22",
  rent: "1500.00"
};

await StoreLocations.create(store).go();

// {
//   Item: {
//     mallId: 'EastPointe',
//     storeId: 'LatteLarrys',
//     buildingId: 'BuildingA1',
//     unitId: 'B47',
//     category: 'food/coffee',
//     leaseEndDate: '2020-03-22',
//     rent: '1500.00',
//     discount: '0.00',
//     pk: '$mallstoredirectory_1#storeid_lattelarrys',
//     sk: '$mallstore#mallid_eastpointe#buildingid_buildinga1#unitid_b47',
//     idx1pk: '$mallstoredirectory_1#mallid_eastpointe',
//     idx1sk: '$mallstore#buildingid_buildinga1#unitid_b47#storeid_lattelarrys',
//     idx2pk: '$mallstore#leaseenddate_2020-03-22#storeid_lattelarrys#buildingid_buildinga1#unitid_b47',
//     __edb_e__: 'MallStore'
//   },
//   TableName: 'StoreDirectory',
//   ConditionExpression: 'attribute_not_exists(pk) AND attribute_not_exists(sk)'
// }

Find Records

DynamoDB offers three methods to find records: get, query, and scan. In ElectroDB, there is a fourth type: find. Unlike get and query, the find method does not require you to provide keys, but under the covers it will leverage the attributes provided to find the best index to query on. Provide the find method will all properties known to match a record and ElectroDB will generate the most performant query it can to locate the results. This can be helpful with highly dynamic querying needs. If an index cannot be satisfied with the attributes provided, scan will be used as a last resort.

let match = await StoreLocations.find({
	mallId: "EastPointe",
	buildingId: "BuildingA1",
	leaseEndDate: "2020-03-22",
  rent: "1500.00"
}).go()

// {
//   KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
//   TableName: 'StoreDirectory',
//   ExpressionAttributeNames: {
//     '#mallId': 'mallId',
//     '#buildingId': 'buildingId',
//     '#leaseEndDate': 'leaseEndDate',
//     '#storeId': 'storeId',
//     '#rent': 'rent',
//     '#pk': 'idx2pk',
//     '#sk1': 'idx2pk'
//   },
//   ExpressionAttributeValues: {
//     ':mallId1': 'EastPointe',
//     ':buildingId1': 'BuildingA1',
//     ':leaseEndDate1': '2020-03-22',
//     ':storeId1': "LatteLarry's",
//     ':rent1': '1500.00',
//     ':pk': '$mallstoredirectory_1#mallid_eastpointe',
//     ':sk1': "$mallstore#leaseenddate_2020-03-22#storeid_lattelarry's#buildingid_buildinga1#unitid_"
//   },
//   IndexName: 'idx2',
//   FilterExpression: '#mallId = :mallId1 AND#buildingId = :buildingId1 AND#leaseEndDate = :leaseEndDate1 AND#storeId = :storeId1 AND#rent = :rent1'
// }

Query Records

Examples in this section using the MallStore schema defined above.

All queries start from the Access Pattern defined in the schema.

const MallStore = new Entity(schema); 
// Each Access Pattern is available on the Entity instance
// MallStore.query.stores()
// MallStore.query.malls()

Partition Key Facets

All queries require (at minimum) the Facets included in its defined Partition Key. They can be supplied in the order they are composed or in a single object when invoking the Access Pattern.

const MallStore = new Entity(schema);
//	stores
//	pk: ["storeId"]
//	sk: ["mallId", "buildingId", "unitId"]

let storeId = "LatteLarrys";
let mallId = "EastPointe";

// Good: As an object
MallStore.query.stores({storeId});

// Bad: Facets missing, will throw
MallStore.query.stores(); // err: Params passed to ENTITY method, must only include storeId

// Bad: Facets not included, will throw
MallStore.query.stores({mallId}); // err: Params passed to ENTITY method, must only include storeId

After invoking the Access Pattern with the required Partition Key Facets, you can now choose what Sort Key Facets are applicable to your query. Examine the table in Sort Key Operations for more information on the available operations on a Sort Key.

Collection Chains

Collections allow you to query across Entities. To use them you need to join your Models onto a Service instance.

Using the TaskApp Models defined in Models, these models share a collection called assignments on the index gsi3pk-gsi3sk-index

let TaskApp =  new Service({
	version:  "1", 
	service:  "TaskApp", 
	table:  "projectmanagement"
},  { client }); 
TaskApp.join(EmployeesModel);  // TaskApp.entities.employees
TaskApp.join(TasksModel);  // TaskApp.entities.tasks

Available on your Service are two objects: entites and collections. Entities available on entities have the same capabilities as they would if created individually. When a Model added to a Service with join however, its Collections are automatically added and validated with the other Models joined to that Service. These Collections are available on collections.

TaskApp.collections.assignments({employee: "JExotic"}).params();  

// Results
{
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#pk': 'gsi3pk', '#sk1': 'gsi3sk' },
  ExpressionAttributeValues: { ':pk': '$taskapp_1#employee_joeexotic', ':sk1': '$assignments' },
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  IndexName: 'gsi3pk-gsi3sk-index'
}

Collections do not have the same query functionality and as an Entity, though it does allow for inline filters like an Entity. The attributes available on the filter object include all attributes across entities.

TaskApp.collections
	.assignments({employee: "CBaskin"})
	.filter((attributes) => `
		${attributes.project.notExists()} OR ${attributes.project.contains("murder")}
	`)

// Results
{
  TableName: 'projectmanagement',
  ExpressionAttributeNames: { '#project': 'project', '#pk': 'gsi3pk', '#sk1': 'gsi3sk' },
  ExpressionAttributeValues: {
    ':project1': 'murder',
    ':pk': '$taskapp_1#employee_carolbaskin',
    ':sk1': '$assignments'
  },
  KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
  IndexName: 'gsi3pk-gsi3sk-index',
  FilterExpression: '\n\t\tattribute_not_exists(#project) OR contains(#project, :project1)\n\t'
}

Execute Queries

Lastly, all query chains end with either a .go() or a .params() method invocation. These will either execute the query to DynamoDB (.go()) or return formatted parameters for use with the DynamoDB docClient (.params()).

Both .params() and .go() take a query configuration object which is detailed more in the section Query Options.

Params

The params method ends a query chain, and synchronously formats your query into an object ready for the DynamoDB docClient.

For more information on the options available in the config object, checkout the section Query Options.

let config = {};
let stores = MallStores.query
    .leases({ mallId })
    .between(
      { leaseEndDate:  "2020-06-01" }, 
      { leaseEndDate:  "2020-07-31" })
    .filter(attr) => attr.rent.lte("5000.00"))
    .params(config);

// Results:
{
  IndexName: 'idx2',
  TableName: 'electro',
  ExpressionAttributeNames: { '#rent': 'rent', '#pk': 'idx2pk', '#sk1': 'idx2sk' },
  ExpressionAttributeValues: {
    ':rent1': '5000.00',
    ':pk': '$mallstoredirectory_1#mallid_eastpointe',
    ':sk1': '$mallstore#leaseenddate_2020-06-01#rent_',
    ':sk2': '$mallstore#leaseenddate_2020-07-31#rent_'
  },
  KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
  FilterExpression: '#rent <= :rent1'
}

Go

The go method ends a query chain, and asynchronously queries DynamoDB with the client provided in the model.

For more information on the options available in the config object, check out the section Query Options.

let config = {};
let stores  =  MallStores.query
				.leases({ mallId })
				.between(
					{ leaseEndDate:  "2020-06-01" }, 
					{ leaseEndDate:  "2020-07-31" })
				.filter(({rent}) => rent.lte("5000.00"))
				.go(config);

Page

As of September 29th 2020 the .page() now returns the facets that make up the ExclusiveStartKey instead of the ExclusiveStartKey itself. To get back only the ExclusiveStartKey, add the flag exclusiveStartKeyRaw to your query options. If you treated this value opaquely no changes are needed, or if you used the raw flag.

The page method ends a query chain, and asynchronously queries DynamoDB with the client provided in the model. Unlike the .go(), the .page() method returns a tupple.

The first element is the "page", this object contains the facets that make up the ExclusiveStartKey that is returned by the DynamoDB client. This is very useful in multi-tenant applications where only some facets are exposed to the client, or there is a need to prevent leaking keys between entities. If there is no ExclusiveStartKey this value will be null. On subsequent calls to .page(), pass the results returned from the previous call to .page() or construct the facets yourself.

Note: It is highly recommended to use the exclusiveStartKeyRaw flag when using .page() in conjunction with scans. This is because when using scan on large tables the docClient may return an ExclusiveStartKey for a record that does not belong to entity making the query (regardless of the filters set). In these cases ElectroDB will return null (to avoid leaking the keys of other entities) when further pagination may be needed to find your records.

The second element is the results of the query, exactly as it would be returned through a query operation.

Note: When calling .page() the first argument is reserved for the "page" returned from a previous query, the second parameter is for Query Options. For more information on the options available in the config object, check out the section Query Options.

let [page, stores] = await MallStores.query
				.leases({ mallId })
				.page();

let [pageTwo, moreStores] = await MallStores.query
				.leases({ mallId })
				.page(page, {});

// page:
// { 
//   storeId: "LatteLarrys", 
//   mallId: "EastPointe", 
//   buildingId: "BuildingA1", 
//   unitId: "B47"
// }

// stores
// [{
//   mall: '3010aa0d-5591-4664-8385-3503ece58b1c',
//   leaseEnd: '2020-01-20',
//   sector: '7d0f5c19-ec1d-4c1e-b613-a4cc07eb4db5',
//   store: 'MNO',
//   unit: 'B5',
//   id: 'e0705325-d735-4fe4-906e-74091a551a04',
//   building: 'BuildingE',
//   category: 'food/coffee',
//   rent: '0.00'
// },
// {
//   mall: '3010aa0d-5591-4664-8385-3503ece58b1c',
//   leaseEnd: '2020-01-20',
//   sector: '7d0f5c19-ec1d-4c1e-b613-a4cc07eb4db5',
//   store: 'ZYX',
//   unit: 'B9',
//   id: 'f201a1d3-2126-46a2-aec9-758ade8ab2ab',
//   building: 'BuildingI',
//   category: 'food/coffee',
//   rent: '0.00'
// }]

Query Examples

Below are all chain possibilities available.

Assume an index named leases defined as:

leases: {
	index: "gsi1pk-gsi1sk-index",
	pk: {
		field: "pk",
		facets: ["mallId"]
	},
	sk: {
		field: "sk",
		facets: ["leaseEndDate", "rent"]
	}
}

And the following model defined filters:

filters: {
	byCategory: ({category}, name) => category.eq(name),
	rentDiscount: (attributes, discount, max, min) => {
		return `${attributes.discount.lte(discount)} AND ${attributes.rent.between(max, min)}`
	}
}

let mallId = "EastPointe";

// begins_with
MallStore.query.leases({mallId}).go()
MallStore.query.leases({mallId, leaseEndDate: "2020-03"}}).go();
MallStore.query.leases({mallId, leaseEndDate: "2020-03-22", rent: "2000.00"}).go();

// gt, gte, lt, lte
MallStore.query.leases({mallId}).gt({leaseEndDate}).go();
MallStore.query.leases({mallId}).gte({leaseEndDate}).go();
MallStore.query.leases({mallId}).lt({leaseEndDate}).go();
MallStore.query.leases({mallId}).lte({leaseEndDate}).go();

// between
MallStore.query.leases({mallId}).between({leaseEndDate: "2020-03"}, {leaseEndDate: "2020-04"}).go();

// filters -- applied after any of the sort key operators above 
let june = "2020-06";
let july = "2020-07"; 
let discount = "500.00";
let maxRent = "2000.00";
let minRent = "5000.00";

// inline filter
MallStore.query
  .leases({mallId, leaseEndDate: june})
  .filter(attr => attr.storeId.eq("LatteLarrys"))
  .go();

// model defined filters
MallStore.query
  .leases({mallId, leaseEndDate: june})
  .rentDiscount(discount, maxRent, minRent)
  .go();

MallStore.query
  .leases({mallId})
  .between(
    {leaseEndDate: june}, 
    {leaseEndDate: july})
  .byCategory("food/coffee")
  .go();

Query Options

By default ElectroDB enables you to work with records as the names and properties defined in the model. Additionally, it removes the need to deal directly with the docClient parameters which can be complex for a team without as much experience with DynamoDB. The Query Options object can be passed to both the .params() and .go() methods when building you query. Below are the options available:

let options = {
	params: [object],
	raw: [boolean],
	includeKeys: [boolean],
	originalErr: [boolean],
};

Option	Description
params	Properties added to this object will be merged onto the params sent to the document client. Any conflicts with ElectroDB will favor the params specified here.
raw	Returns query results as they were returned by the docClient.
includeKeys	By default, ElectroDB does not return partition, sort, or global keys in its response.
originalErr	By default, ElectroDB alters the stacktrace of any exceptions thrown by the DynamoDB client to give better visibility to the developer. Set this value equal to `true` to turn off this functionality and return the error unchanged.

Examples

Employee App

For an example, lets look at the needs of application used to manage Employees. The application Looks at employees, offices, tasks, and projects.

Employee App Requirements

As Project Manager I need to find all tasks and details on a specific employee.
As a Regional Manager I need to see all details about an office and its employees
As an Employee I need to see all my Tasks.
As a Product Manager I need to see all the tasks for a project.
As a Client I need to find a physical office close to me.
As a Hiring manager I need to find employees with comparable salaries.
As HR I need to find upcoming employee birthdays/anniversaries
As HR I need to find all the employees that report to a specific manager

Entities

const EmployeesModel = {
	entity: "employees",
	version: "1",
	service: "taskapp",
	table: "projectmanagement",
	attributes: {
		employee: "string",
		firstName: "string",
		lastName: "string",
		office: "string",
		title: "string",
		team: ["development", "marketing", "finance", "product"],
		salary: "string",
		manager: "string",
		dateHired: "string",
		birthday: "string",
	},
	indexes: {
		employee: {
			pk: {
				field: "pk",
				facets: ["employee"],
			},
			sk: {
				field: "sk",
				facets: [],
			},
		},
		coworkers: {
			index: "gsi1pk-gsi1sk-index",
			collection: "workplaces",
			pk: {
				field: "gsi1pk",
				facets: ["office"],
			},
			sk: {
				field: "gsi1sk",
				facets: ["team", "title", "employee"],
			},
		},
		teams: {
			index: "gsi2pk-gsi2sk-index",
			pk: {
				field: "gsi2pk",
				facets: ["team"],
			},
			sk: {
				field: "gsi2sk",
				facets: ["title", "salary", "employee"],
			},
		},
		employeeLookup: {
			collection: "assignements",
			index: "gsi3pk-gsi3sk-index",
			pk: {
				field: "gsi3pk",
				facets: ["employee"],
			},
			sk: {
				field: "gsi3sk",
				facets: [],
			},
		},
		roles: {
			index: "gsi4pk-gsi4sk-index",
			pk: {
				field: "gsi4pk",
				facets: ["title"],
			},
			sk: {
				field: "gsi4sk",
				facets: ["salary", "employee"],
			},
		},
		directReports: {
			index: "gsi5pk-gsi5sk-index",
			pk: {
				field: "gsi5pk",
				facets: ["manager"],
			},
			sk: {
				field: "gsi5sk",
				facets: ["team", "office", "employee"],
			},
		},
	},
	filters: {
		upcomingCelebrations: (attributes, startDate, endDate) => {
			let { dateHired, birthday } = attributes;
			return `${dateHired.between(startDate, endDate)} OR ${birthday.between(
				startDate,
				endDate,
			)}`;
		},
	},
};

const TasksModel = {
	entity: "tasks",
	version: "1",
	service: "taskapp",
	table: "projectmanagement",
	attributes: {
		task: "string",
		project: "string",
		employee: "string",
		description: "string",
	},
	indexes: {
		task: {
			pk: {
				field: "pk",
				facets: ["task"],
			},
			sk: {
				field: "sk",
				facets: ["project", "employee"],
			},
		},
		project: {
			index: "gsi1pk-gsi1sk-index",
			pk: {
				field: "gsi1pk",
				facets: ["project"],
			},
			sk: {
				field: "gsi1sk",
				facets: ["employee", "task"],
			},
		},
		assigned: {
			collection: "assignements",
			index: "gsi3pk-gsi3sk-index",
			pk: {
				field: "gsi3pk",
				facets: ["employee"],
			},
			sk: {
				field: "gsi3sk",
				facets: ["project", "task"],
			},
		},
	},
};

const OfficesModel = {
	entity: "offices",
	version: "1",
	table: "electro",
	service: "electrotest",
	attributes: {
		office: "string",
		country: "string",
		state: "string",
		city: "string",
		zip: "string",
		address: "string",
	},
	indexes: {
		locations: {
			pk: {
				field: "pk",
				facets: ["country", "state"],
			},
			sk: {
				field: "sk",
				facets: ["city", "zip", "office"],
			},
		},
		office: {
			index: "gsi1pk-gsi1sk-index",
			collection: "workplaces",
			pk: {
				field: "gsi1pk",
				facets: ["office"],
			},
			sk: {
				field: "gsi1sk",
				facets: [],
			},
		},
	},
};

Join models on a new Service called EmployeeApp

const DynamoDB = require("aws-sdk/clients/dynamodb");
const client = new DynamoDB.DocumentClient({
	region: "us-east-1",
});
const { Service } = require("electrodb");
let EmployeeApp = new Service(
	{
		version: "1",
		service: "EmployeeApp",
		table: "projectmanagement",
	},
	{ client },
);

EmployeeApp.join(EmployeesModel); // EmployeeApp.entities.employees
EmployeeApp.join(TasksModel); // EmployeeApp.entities.tasks
EmployeeApp.join(OfficesModel); // EmployeeApp.entities.tasks

Query Records

All tasks and employee information for a given employee

Fulfilling Requirement #1.

EmployeeApp.collections.assignements({employee: "CBaskin"}).go();

Returns the following:

{
	employees: [{
		employee: "cbaskin",
		firstName: "carol",
		lastName: "baskin",
		office: "big cat rescue",
		title: "owner",
		team: "cool cats and kittens",
		salary: "1,000,000",
		manager: "",
		dateHired: "1992-11-04",
		birthday: "1961-06-06",
	}].
	tasks: [{
		task: "Feed tigers",
		description: "Prepare food for tigers to eat",
		project: "Keep tigers alive",
		employee: "cbaskin"
	}, {
		task: "Fill water bowls",
		description: "Ensure the tigers have enough water",
		project: "Keep tigers alive",
		employee: "cbaskin"
	}]
}

Find all employees and office details for a given office

Fulfilling Requirement #2.

EmployeeApp.collections.workplaces({office: "big cat rescue"}).go()

Returns the following:

{
	employees: [{
		employee: "cbaskin",
		firstName: "carol",
		lastName: "baskin",
		office: "big cat rescue",
		title: "owner",
		team: "cool cats and kittens",
		salary: "1,000,000",
		manager: "",
		dateHired: "1992-11-04",
		birthday: "1961-06-06",
	}],
	offices: [{
		office: "big cat rescue",
		country: "usa",
		state: "florida",
		city: "tampa"
		zip: "12345"
		address: "123 Kitty Cat Lane"
	}]
}

Tasks for a given employee

Fulfilling Requirement #3.

EmployeeApp.entities.tasks.query.assigned({employee: "cbaskin"}).go();

Returns the following:

[
	{
		task: "Feed tigers",
		description: "Prepare food for tigers to eat",
		project: "Keep tigers alive",
		employee: "cbaskin"
	}, {
		task: "Fill water bowls",
		description: "Ensure the tigers have enough water",
		project: "Keep tigers alive",
		employee: "cbaskin"
	}
]

Tasks for a given project

Fulfilling Requirement #4.

EmployeeApp.entities.tasks.query.project({project: "Murder Carol"}).go();

Returns the following:

[
	{
		task: "Hire hitman",
		description: "Find someone to murder Carol",
		project: "Murder Carol",
		employee: "jexotic"
	}
];

Find office locations

Fulfilling Requirement #5.

EmployeeApp.entities.office.locations({country: "usa", state: "florida"}).go()

Returns the following:

[
	{
		office: "big cat rescue",
		country: "usa",
		state: "florida",
		city: "tampa"
		zip: "12345"
		address: "123 Kitty Cat Lane"
	}
]

Find employee salaries and titles

Fulfilling Requirement #6.

EmployeeApp.entities.employees
	.roles({title: "animal wrangler"})
	.lte({salary: "150.00"})
	.go()

Returns the following:

[
	{
		employee: "ssaffery",
		firstName: "saff",
		lastName: "saffery",
		office: "gw zoo",
		title: "animal wrangler",
		team: "keepers",
		salary: "105.00",
		manager: "jexotic",
		dateHired: "1999-02-23",
		birthday: "1960-07-11",
	}
]

Find employee birthdays or anniversaries

Fulfilling Requirement #7.

EmployeeApp.entities.employees
	.workplaces({office: "gw zoo"})
	.upcomingCelebrations("2020-05-01", "2020-06-01")
	.go()

Returns the following:

[
	{
		employee: "jexotic",
		firstName: "joe",
		lastName: "maldonado-passage",
		office: "gw zoo",
		title: "tiger king",
		team: "founders",
		salary: "10000.00",
		manager: "jlowe",
		dateHired: "1999-02-23",
		birthday: "1963-03-05",
	}
]

Find direct reports

Fulfilling Requirement #8.

EmployeeApp.entities.employees
	.reports({manager: "jlowe"})
	.go()

Returns the following:

[
	{
		employee: "jexotic",
		firstName: "joe",
		lastName: "maldonado-passage",
		office: "gw zoo",
		title: "tiger king",
		team: "founders",
		salary: "10000.00",
		manager: "jlowe",
		dateHired: "1999-02-23",
		birthday: "1963-03-05",
	}
]

Shopping Mall Property Management App

For an example, lets look at the needs of application used to manage Shopping Mall properties. The application assists employees in the day-to-day operations of multiple Shopping Malls.

Shopping Mall Requirements

As a Maintenance Worker I need to know which stores are currently in each Mall down to the Building they are located.
As a Helpdesk Employee I need to locate related stores in Mall locations by Store Category.
As a Property Manager I need to identify upcoming leases in need of renewal.

Create a new Entity using the MallStore schema defined above

const DynamoDB = require("aws-sdk/clients/dynamodb");
const client = new DynamoDB.DocumentClient();
const MallStore = new Entity(model, {client});

Access Patterns are accessible on the StoreLocation

PUT Record

Add a new Store to the Mall

await MallStore.create({
	mallId: "EastPointe",
	storeId: "LatteLarrys",
	buildingId: "BuildingA1",
	unitId: "B47",
	category: "spite store",
	leaseEndDate: "2020-02-29",
	rent: "5000.00",
}).go();

Returns the following:

{
	"mallId": "EastPointe",
	"storeId": "LatteLarrys",
	"buildingId": "BuildingA1",
	"unitId": "B47",
	"category": "spite store",
	"leaseEndDate": "2020-02-29",
	"rent": "5000.00",
	"discount": "0.00",
}

UPDATE Record

Change the Store's Lease Date

When updating a record, you must include all Facets associated with the table's primary PK and SK.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
await StoreLocations.update({storeId, mallId, buildingId, unitId}).set({
	leaseEndDate: "2021-02-28"
}).go();

Returns the following:

{
	"leaseEndDate": "2021-02-28"
}

GET Record

Retrieve a specific Store in a Mall

When retrieving a specific record, you must include all Facets associated with the table's primary PK and SK.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
await StoreLocations.get({storeId, mallId, buildingId, unitId}).go();

Returns the following:

{
	"mallId": "EastPointe",
	"storeId": "LatteLarrys",
	"buildingId": "BuildingA1",
	"unitId": "B47",
	"category": "spite store",
	"leaseEndDate": "2021-02-28",
	"rent": "5000.00",
	"discount": "0.00"
}

DELETE Record

Remove a Store location from the Mall

When removing a specific record, you must include all Facets associated with the table's primary PK and SK.

let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let storeId = "LatteLarrys";
await StoreLocations.delete({storeId, mallId, buildingId, unitId}).go();

Returns the following:

{}

Query Records

All Stores in a particular mall

Fulfilling Requirement #1.

let mallId = "EastPointe";
let stores = await StoreLocations.malls({mallId}).query().go();

All Stores in a particular mall building

Fulfilling Requirement #1.

let mallId = "EastPointe";
let buildingId = "BuildingA1";
let stores = await StoreLocations.malls({mallId}).query({buildingId}).go();

Find the store located in unit B47

Fulfilling Requirement #1.

let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let stores = await StoreLocations.malls({mallId}).query({buildingId, unitId}).go();

Stores by Category at Mall

Fulfilling Requirement #2.

let mallId = "EastPointe";
let category = "food/coffee";
let stores = await StoreLocations.malls({mallId}).byCategory(category).go();

Stores by upcoming lease

Fulfilling Requirement #3.

let mallId = "EastPointe";
let q2StartDate = "2020-04-01";
let stores = await StoreLocations.leases({mallId}).lt({leaseEndDate: q2StateDate}).go();

Stores will renewals for Q4

Fulfilling Requirement #3.

let mallId = "EastPointe";
let q4StartDate = "2020-10-01";
let q4EndDate = "2020-12-31";Yes
let stores = await StoreLocations.leases(mallId)
    .between (
      {leaseEndDate: q4StartDate}, 
      {leaseEndDate: q4EndDate})
    .go();

Spite-stores with release renewals this year

Fulfilling Requirement #3.

let mallId = "EastPointe";
let yearStarDate = "2020-01-01";
let yearEndDate = "2020-12-31";
let storeId = "LatteLarrys";
let stores = await StoreLocations.leases(mallId)
    .between (
      {leaseEndDate: yearStarDate}, 
      {leaseEndDate: yearEndDate})
    .filter(attr => attr.category.eq("Spite Store"))
    .go();

All Latte Larrys in a particular mall building

let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let storeId = "LatteLarrys";
let stores = await StoreLocations.malls({mallId}).query({buildingId, storeId}).go();

Coming Soon

Additional query options like limit, pages, attributes, sort and more for easier querying.
Default query options defined on the model to give more general control of interactions with the Entity.
ConditionalExpressions for create/update/delete
Append/Add/Subtract/Remove updates capabilities
Complex attributes (list, map, set)

Files

README.md

Latest commit

History

README.md

File metadata and controls

ElectroDB

Features

Table of Contents

Installation

Usage

Entities and Services

Entities

Services

Model

Model Properties

Service Properties

Model/Service Options

Attributes

Simple Syntax

Expanded Syntax

Indexes

Facets

Facet Arrays

Facet Templates

Collections

Filters

Defined on the model

Defined via Filter method after query operators

Multiple Filters

Where

FilterExpressions

ConditionExpressions

Attributes and Operations

Multiple Where Clauses

Building Queries

Sort Key Operations

Using facets to make hierarchical keys

Shopping Mall Stores

Query Chains

Get Method

Delete Method

Put Record

Update Record

Scan Records

Patch Records

Create Records

Find Records

Query Records

Partition Key Facets

Collection Chains

Execute Queries

Params

Go

Page

Query Examples

Query Options

Examples

Employee App

Employee App Requirements

Entities

Query Records

All tasks and employee information for a given employee

Find all employees and office details for a given office

Tasks for a given employee

Tasks for a given project

Find office locations

Find employee salaries and titles

Find employee birthdays or anniversaries

Find direct reports

Shopping Mall Property Management App

Shopping Mall Requirements

Access Patterns are accessible on the StoreLocation

PUT Record

Add a new Store to the Mall

UPDATE Record

Change the Store's Lease Date

GET Record

Retrieve a specific Store in a Mall

DELETE Record