dynamo-arc
v2.2.1
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A dynamo data client designed for use with DyanmoDB Single Table applications
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Dynamo Arc
A dynamo data client designed for use with DyanmoDB Single Table applications.
Quick Start
const { makeClient, Store, Cache } = require('dynamo-arc')
// Setup the base client
const dynamo = makeClient({
tableName: 'my-datastore',
clientConfig: { region: 'us-west-2' }
})
// Define a type-store
class RecordStore extends Store {
constructor({ dynamo }) {
super({ type: '_RECORDS_', idKey: 'recordId', dynamo })
}
}
const recordStore = new RecordStore({ dynamo })
const record = await recordStore.get('1')
record.name = 'primary'
record.age = 300
record.scopes = [{ name: 'top', isActive: true}, { name: 'left', isActive: false }]
await recordStore.put(record)
// Setup generic cache
const cache = new Cache({ dynamo: context.dynamo })
const externalRecord = cache.get(
'a',
async () => externalService.get('a'),
{ ttl: 20000 }
)
The Basics
Dynamo Arc provides a simple API for interacting with a DynamoDB table that stores multiple schemas, which we call the Single Table Pattern. An incredible presentation of this method is given in this AWS RE:invent talk. If you are not familiar with how to use a single table to store multiple data schemas it is strongly recommended that you watch the video, it will greatly increase the chances that you use this library correctly.
To quickly summarize: when using this library it is assumed your entire application uses a single DynamoDB table with generic partition keys, with optional range keys, that use a composite form to identify the record. For example _PROJECT_:abcd
would identify a record of the project type whose ID was abcd
and _USER_:3243
would identify a record of the user type whose ID was 3243
. The actual data for the object is stored in a generic key, in this case data
, which is a DynamoDB Map. This allows any number of types to occupy the same table, using a generic table-level schema, which comes with a ridiculous list of benefits at the minor cost of complexity that it takes to understand the composite keys.
This library provides a simple, async-friendly API for interacting with such a table. Interactions at the store level will be with plain JS object; all the complexity of composite key handling are abstracted.
Concepts
The dynamo client: using this library requires constructing a special DynamoDB client using the exported makeClient function, which is provided to the various stores that are defined for each record/schema type. The examples throughout this documentation refer to this object as the dynamo client, while the code uses the variable dynamo
.
stores: each record type will have a dedicated store used to handle the composite key logic necessary for packing and unpacking. These are defined by extending the exported Store
class and provided a type
, along with optional field-mapping for idKey
and sortKey
properties to extract from the record.
cache: the exported Cache
class is designed to be used once-per-app to construct a generic ttl cache. Its basic use is shown above in the Quick Start section, with a unique key, a cache-miss function that fetches the item if it is missing or expired in the cache, and optional ttl config. While it might be surprising to overload your primary datastore as a cache, when properly re-using connections DynamoDB can achieve single-digit millisecond response (even in Node) making it a fast, easy to use caching layer.
Configuration
The configuration for all exported functions/classes can be found below.
Dynamo Client
function makeClient({
tableName,
idField = 'id', // partition key of the table
sortField = 'sort_key', // sort key of the table
typeIndex = 'type-index', // index used for the TYPE value
ttlField = 'ttl', // ttl field of the table (necessary for the Cache)
hasTtlField = true,
hasSortField = true,
clientConfig,
translateConfig,
dynamoConfig
}: {
tableName: string
idField?: string
sortField?: string
typeIndex?: string
ttlField?: string
hasTtlField?: boolean
hasSortField?: boolean
clientConfig?: DynamoDBClientConfig
translateConfig?: TranslateConfig
}, client?: DynamoDBClient // must provide either client param or clientConfig)
): ArcDynamoClient {}
makeClient
returns a modified dynamo client, typed as ArcDynamoClient
, that tracks additional data about the table such as its name, various fields, and features. It can either be passed an existing DynamoDBClient
as via its second parameter, or it can create one using the clientConfig
option in the first parameter. These options are mutually exclusive, and one of them is required.
The only required property for the first parameter is the tableName
, which is the full name of the Dynamo table. The other fields are optional with default values.
The translateConfig
configures the DynamoDBDocument client's marshalling options, though Arc uses different default values. The library exports ArcTranslateDefaults
and AwsTranslateDefaults
, though a custom configuration can be supplied.
Store
declare class Store <T>{
public readonly [_type]: string
public readonly [_dynamo]: ArcDynamoClient
public readonly [_logger]: Logger
public readonly [_idKey]: keyof T & string
public readonly [_sortKey]?: (keyof T & string) | undefined
public readonly [_delimiter]: string
constructor(
dynamo: ArcClient,
logger: Logger, // see Logging section below
type: string,
idKey = 'id',
sortKey?: string,
delimiter = ':'
)
}
The only required properties for the Store
are the dynamo
client, which must be the result of the makeClient
function, the type
, which is used to create the composite key for the record, and the idKey
which is used to extract the primary key from the type.
The simplest child class
class RecordStore extends Store {
constructor({ dynamo }) {
super({ type: '_RECORDS_', idKey: 'id', dynamo })
}
A fully configured child class
class RecordStore extends Store {
constructor({ dynamo }) {
super({
dynamo,
type: '_ORDER_ITEM_',
idKey: 'orderId',
sortKey: 'itemId',
delimiter: '::',
logger: console
})
}
API
interface TableKey {
// The properties on a Store's Key are determined
// by its configuration.
// It will have an idKey, and optionally a sortKey
[key: string]: string
}
// Raw Item from Dynamo
interface DynamoRecord {}
// Stand in for the normal DocumentClient params for the given function
// The TableName property is automatically filled in by Arc
interface DynamoParams {}
// Stand in for the normal DocumentClient result for the given function
interface DynamoResult {}
interface Store<T> {
getTableName(): string
/** Join id segments together with the configured delimiter */
join(...idSegments: string[]): string
/** Create the ID field of this type by joining it to the store's configured TYPE */
typeKey(...idSegments: string[]): string
/** Creates the Key object used by dynamo. Includes a sort key if configured on this store */
asKey(id:string, sortKey?: string): StoreKey
/** Convert the DynamoDB record back into the originally stored JS object */
fromDb(item: DynamoRecord): T
/** Convert a plain JS object into a DynamoDB record */
toDb(item: T): DynamoRecord
/** Get a keyed item from Dynamo */
async get(id:string, sortKey?:string): Promise<T>
/** Delete the item from Dynamo matching the provided key */
async delete(id:string, sortKey:string): Promise<void>
/** Delete all items */
async deleteAll(items: T[]): Promise<void>
/** Create or Update the item in Dynamo */
async put(item: T): Promise<T>
/** Put all items */
async putAll(items: T[]): Promise<void>
/** Execute a query against the configured Dynamo table */
async query(params: DynamoParams): Promise<DynamoResult>
/** Execute a scan against the configured Dynamo table */
async scan(params: DynamoParams): Promise<DynamoResult>
/** Execute a batchGet against the configured Dynamo table */
async batchGet(keys: StoreKey[]): Promise<DynamoResult>
/** Execute a batchWrite against the configured Dynamo table */
async batchWrite(changes: (StoreKey | T)): Promise<DynamoResult>
/** Execute a query against the configured Dynamo table with automatic paging, mapped through fromDb() */
async queryAll(params: DynamoParams): Promise<T[]>
/** Execute a scan against the configured Dynamo table with automatic paging, mapped through fromDb() */
async scanAll(params: DynamoParams): Promise<T[]>
/** Execute a batchGet against the configured Dynamo table with automatic paging, mapped through fromDb() */
async batchGetAll(keys: StoreKey[]): Promise<T[]>
/** Execute a batchWrite against the configured Dynamo table with automatic paging */
async batchWriteAll(changes: (StoreKey | T)): Promise<DynamoResult>
/** Execute an automatically paged query by processing one page at a time */
async queryByPage(
params: QueryAllInput,
/** Async function that receives an array of items from the current page. If it resolves `false` paging will stop */
pageFn: (page: T[]) => Promise<void | boolean>
): Promise<void>
/** Execute an automatically paged query against the typeIndex for the type configured on this store */
getAll(): Promise<T[]>
}
Cache
The cache takes a dynamo
object and returns a store that uses dynamo as a caching layer by handling various ttl
values.
Setup
const { Cache } = require('dynamo-arc')
return new Cache({ dynamo: dynamo })
const getter = () => cache.get(
'some-id',
() => someExpensiveOp(),
{ staleAfter: 10000 }
)
const freshValue = await getter()
const cachedValue = await getter()
API
interface CacheOptions {
permanent?: boolean
ttl?: number
staleAfter?: number
}
interface CacheKey extends CacheOptions {
id: string
}
interface Cache {
get<T>(key: string, cacheMissFn: () => Promise<T>, options?: CacheOptions): Promise<T>
set<T>(key: string, value: T, options?: CacheOptions): Promise<T>
// This takes an array of object with an ID and CacheOptions
// It will return the first object from the cache whose ID matches one in the array
// Or it will call the cacheMissFn and write the result to every ID in the array
batchGet<T>(keys: CacheKey[], cacheMissFn: () => Promise<T>): Promise<T>
}
fromDb()/toDb()
Working with a single table means overloading the schema. Since every type is using well-known properties for id
and sort_key
and the various GSIs the rest of the data needs to go into a collision resistant property: data
. When writing an object with put
the object is sent to dynamo after casting through toDb(item)
.
toDb(item) {
let id = item[this[_idKey]]
let data = { ...item }
const dbItem = {
...this.asKey(id, item[this[_sortKey]]),
type: this[_type],
// This is to make it easier to find in the dynamo console
typeId: id,
// datetime props
createdOn: item.createdOn,
updatedOn: Date.now(),
//
data, // <--- where the actual object is stored!!
//
}
return dbItem
}
When reading with get
, queryAll
, scanAll
, or batchGetAll
the raw response from dynamo needs to have the data
property unpacked. Extraction is much simpler, so this is the entire default fromDb(item)
function.
fromDb(item) {
if (!item || !item.data) return null
item = item.data
return item
}
Both of these functions are defined on the Store
, so they can be overriden as necessary. The most common use case for this is overriding toDb
in order to add GSI indexing properties
// Class Method on an "extends Store" class
toDb(item) {
return {
...super.toDb(item),
// custom owner index
gsi1_key: this.typeKey(item.ownerId),
gsi1_sort: item.id
}
}
Note: because the
query
,scan
,batchWrite
andbatchGet
methods do not automatically page they return the raw dynamo response so that the caller can access the paging properties. This means their responses are not run throughfromDb()
first!
Querying GSIs
Getting data out of a GSI is easy as long as the GSI key uses the this.typeKey()
as seen above, which ensure the store's configured type is combined with the intended ID. Doing the same on the query filters the query so that only records of the correct type are read from the GSI, despite the Single Table's GSI containing records of many types
// Class Method on an "extends Store" class
async getByOwnerId(ownerId) {
return this.queryAll({
IndexName: 'gsi1-index',
ScanIndexForward: false,
KeyConditionExpression: '#ownerId = :ownerId',
ExpressionAttributeNames: { '#ownerId': 'gsi1_key' },
ExpressionAttributeValues: { ':ownerId': this.typeKey(ownerId) }
})
}
Stream processing queries
the store.queryByPage
function provides streaming access to the results of a query. Since only one page is brought into memory at a time this can allow queries to be processed that might otherwise cause the process to consume more memory than its host can provide.
/** Execute an automatically paged query by processing one page at a time */
queryByPage(params: DynamoParams, pageFn: T[]) => any)
The pageFn
is passed an array of fromDb()
mapped rows and its result is awaited. The paging process can be halted early by returning the storeSymbols.pageBreak
symbol from the pageFn
.
forEachPage is an older, deprecated method that functions similar to queryByPage
, but uses a pre-canned query that pages the entire typeIndex
for the current store. This behavior (and more!) is possible with queryByPage
.
Modeling Relationships
In Graph Theory an edge is a relationship between two nodes. Since DynamoDB is a NoSQL store there are no native relationships, but they can be simulated by creating records that use the primary and sort keys on the table. These records are called edges. Arc has tools for managing edges modelling either parent-child relationships (one-to-many) or associative relationships (many-to-many).
There are two classes for working with edges.
EdgeStore
- Used for managing edges in an associative relationshipBaseEdgeStore
- Used for managing edges in an associative relationship. This Class is intended to provide additional flexibility for cases when the safety checks or automatic edge-selection on theEdgeStore
orChildStore
are too restrictive. When possible prefer theEdgeStore
orChildStore
.
How it works
Here is an example of a parent child relationship as it would appear in Dynamo
const node = { id: '_USER_:4332' }
const edge = { id: '_USER_PREF_:4332', sort_key: 'volume', /* ... */}
Notice how in the edge-record the id is the same as the User ID. This allows a query to select all of the user preference relationship by knowing only the User ID and the type (_USER_PREF_
).
Here is an example of a two-way relationship
const user = { id: '_USER_:4332' }
const team = { id: '_TEAM_:8867' }
const edge = {
id: '_USER_TEAM_MEMBER_:4332',
sort_key: '8867',
gsi1_key: '_USER_TEAM_MEMBER_:8867',
gsi1_sort: '4332'
/* ... */
}
Here, again, a relationship to one node is stored on the primary key. A secondary relationship is modeled on a GSI, using the same method. This allows a two-way, or "many-to-many", relationship to be modeled.
Child Relationships
Modeling child relationships can be done using the standard store and a Global Secondary Index (GSI).
A common one-to-many relationship is a set of object with a single "owner".
import { Store, StoreSubConfig } from 'dynamo-arc'
class ProjectStore extends Store<Project> {
constructor({ dynamo }: StoreSubConfig<Project>) {
super({
dynamo,
type: '_PROJECT_',
idKey: 'id',
sortKey: 'ownerId',
})
}
async getByOwnerId(ownerId) {
return this.queryAll({
IndexName: 'gsi1-index',
ScanIndexForward: false,
KeyConditionExpression: '#ownerId = :ownerId',
ExpressionAttributeNames: { '#ownerId': 'gsi1_key' },
ExpressionAttributeValues: { ':ownerId': this.typeKey(item.ownerId) }
})
}
toDb(item) {
return {
...super.toDb(item),
// custom owner index used by getByOwnerId
gsi1_key: this.typeKey(item.ownerId),
gsi1_sort: item.id
}
}
}
const projectStore = new ProjectStore({ dynamo })
const projectA = { id: 'a', ownerId: 'X' }
const projectB = { id: 'b', ownerId: 'X' }
await projectStore.put(projectA)
await projectStore.put(projectB)
const [a, b] = await projectStore.getByOwnerId('X')
The above example demonstrates everything needed for a parent-child (one-to-many) relationship between an owner and a project. Since DynamoDB can have up to 20 GSIs per total (previously 5) each type can have 20 unique parent-child relationships modeled.
Associate Relationships with EdgeStore
The EdgeStore
simplifies working with many-to-many relationships between two types. It requires the dynamo
client to be configured with a sortField
. It must also be provided a secondaryIndex
in its constructor to use as a GSI for selecting secondary edges.
Associate Relationship Configuration
import { EdgeStore, EdgeStoreSubConfig } from 'dyanamo-arc'
interface User {
id: string
teams: Team[]
}
interface Team {
id: string
members: User[]
}
interface UserTeam {
userId: string
teamId: string
role: string
}
class UserTeamStore extends EdgeStore<UserTeam> {
// The EdgeStoreSubConfig simplifies sub-class configs by omitting
// properties that are expected to be hard-coded, such as the strings below
// This allows new UserTeamStore() to safely provide only "dynamo"
constructor({ dynamo }: EdgeStoreSubConfig<UserTeam>) {
super({
dynamo,
type: '_EGDE_',
idKey: 'userId',
sortKey: 'teamId',
secondaryIndex: 'gsi1-index',
})
}
// The EdgeStore makes its type-generic methods "protected"
// in order to force sub-classes to provide type-specific names
// Users of the UserTeamStore shouldn't have to track which of "user" or "team"
// is the "primary" or "secondary" nodes, they should be given clear names
async getTeamsForUser(userId: string): Promise<UserTeam>[] {
return this.getEdgesByPrimaryId(userId)
}
async getUsersOnTeam(teamId: string): Promise<UserTeam>[] {
return this.getEdgesBySecondaryId(teamId)
}
}
const userTeamStore = new UserTeamStore({ dynamo })
const teamsForUserX = await userTeamStore.getTeamsForUser('X')
const usersOnTeamA = await userTeamStore.getUsersOnTeam('a')
// add user X to team b
await userTeamStore.put({ userId: 'X', teamId: 'b', role: 'member' })
// remove user X from team b
await userTeamStore.delete('X', 'b')
// force team b to have the following users
await userTeamStore.syncEdgesBySecondary('b', [
{ userId: 'X', teamId: 'b', role: 'member' },
{ userId: 'Y', teamId: 'b', role: 'member' },
])
The
EdgeStoreSubConfig
is a utility type that simplifies the config ofEdgeStore
sub-classes by removing the properties that sub-class constructor would hard-code for theEdgeStore
BaseEdgeStore
The BaseEdgeStore
extends the Store
with a pair of methods that assist with creating a batchWriteAll
call to add and remove records. It is used by the EdgeStore
to implement the syncEdgesBy[Primary|Secondary]
and getEdgesBy[Primary|Secondary]Id
functions. If the EdgeStore
has an implementation that does not work with your model you can implement your own Edge Store on top of the BaseEdgeStore
.
The BaseEdgeStore
implements the following
async syncEdges(dbEdges: Edge[], edges: Edge[]): Promise<[Edge[], Edge[]]>
: Filter the provided edges and execute abatchWriteAll
against Dynamo.protected filterEdges(leftEdges: Edge[], rightEdges: Edge[]): Edge[]
: Used to filter edges in the left that are missing from the right. The default implementation compares the keys defined for the store.