Skip to content
forked from tywalch/electrodb

A dynamodb library to ease the use of having multiple entities and complex hierarchical relationships in one dynamodb table

Notifications You must be signed in to change notification settings

filmaj/electrodb

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ElectroDB

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.
  • Simple Sort Key Condition Querying: Write efficient sort key queries by easily building compose keys.
  • Simple 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.

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"
}

Table of Contents

Installation

Install from NPM

npm install electrodb --save

Usage

Require or import Entity 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 or import Service from 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"],
			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.

attributes: {
	<AttributeName>: {
		"type": string|string[],
		"required"?: boolean,
		"default"?: value|() => value
		"validate"?: RegExp|() => boolean
		"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", or an array of strings representing a finite list of acceptable values: ["option1", "option2", "option3"].
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, () => boolean no Either regex or a synchronous callback to return a boolean.
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.

There are two ways to provide facets:

  1. As a Facet Array
  2. 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

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)

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)'
}

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:

  1. You must always supply the Partition Key in full for all queries to DynamoDB.
  2. You currently only have the following operators available on a Sort Key: begins_with, between, >, >=, <, <=, and Equals.
  3. 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:

  1. All LatteLarrys locations in all Malls
  2. All LatteLarrys locations in one Mall
  3. All LatteLarrys locations inside a specific Mall
  4. 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();

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();

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

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();

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();

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 Query .go() and .params()

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);

Query Examples

Below are all chain possibilities available, given the MallStore model.

// leases  
// pk: ["mallId"]  
// sk: ["buildingId", "unitId", "storeId"]

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";

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

  1. As Project Manager I need to find all tasks and details on a specific employee.
  2. As a Regional Manager I need to see all details about an office and its employees
  3. As an Employee I need to see all my Tasks.
  4. As a Product Manager I need to see all the tasks for a project.
  5. As a Client I need to find a physical office close to me.
  6. As a Hiring manager I need to find employees with comparable salaries.
  7. As HR I need to find upcoming employee birthdays/anniversaries
  8. 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: {
			type: "string",
		},
		firstName: {
			type: "string",
		},
		lastName: {
			type: "string",
		},
		office: {
			type: "string",
		},
		title: {
			type: "string",
		},
		team: {
			type: ["development", "marketing", "finance", "product"],
		},
		salary: {
			type: "string",
		},
		manager: {
			type: "string",
		},
		dateHired: {
			type: "string",
		},
		birthday: {
			type: "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: {
			type: "string",
		},
		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: "assignements",
			index: "gsi3pk-gsi3sk-index",
			pk: {
				field: "gsi3pk",
				facets: ["employee"],
			},
			sk: {
				field: "gsi3sk",
				facets: ["project", "task"],
			},
		},
	},
};

const OfficesModel = new Entity({
	entity: "offices",
	version: "1",
	table: "electro",
	service: "electrotest",
	attributes: {
		office: {
			type: "string",
		},
		country: {
			type: "string",
		},
		state: {
			type: "string",
		},
		city: {
			type: "string",
		},
		zip: {
			type: "string",
		},
		address: {
			type: "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 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 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 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 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 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 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 birthday/anniversary 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 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

  1. As a Maintenance Worker I need to know which stores are currently in each Mall down to the Building they are located.
  2. As a Helpdesk Employee I need to locate related stores in Mall locations by Store Category.
  3. 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 (Requirement #1)

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

All Stores in a particular mall building (Requirement #1)

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

What store is located in unit "B47"? (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 (Requirement #2)

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

Stores by upcoming lease (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 (Requirement #3)

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

Spite-stores with release renewals this year (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 Larry's in a particular mall building (crazy for any store except a coffee shop)

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

Coming Soon:

  • .page() finish method (like .params() and .go()) to allow for easier pagination of results
  • 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.

About

A dynamodb library to ease the use of having multiple entities and complex hierarchical relationships in one dynamodb table

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 100.0%