Quickstart: Azure Cosmos DB for Apache Gremlin library for Node.js
APPLIES TO: Gremlin
Azure Cosmos DB for Apache Gremlin is a fully managed graph database service implementing the popular Apache Tinkerpop
, a graph computing framework using the Gremlin query language. The API for Gremlin gives you a low-friction way to get started using Gremlin with a service that can grow and scale out as much as you need with minimal management.
In this quickstart, you use the gremlin
library to connect to a newly created Azure Cosmos DB for Gremlin account.
Library source code | Package (npm)
Prerequisites
- An Azure account with an active subscription.
- No Azure subscription? Sign up for a Azure account.
- Node.js (LTS)
- Don't have Node.js installed? Try this quickstart in GitHub Codespaces.codespaces.new/github/codespaces-blank?quickstart=1)
- Azure Command-Line Interface (CLI)
Setting up
This section walks you through creating an API for Gremlin account and setting up a Node.js project to use the library to connect to the account.
Create an API for Gremlin account
The API for Gremlin account should be created prior to using the Node.js library. Additionally, it helps to also have the database and graph in place.
Create shell variables for accountName, resourceGroupName, and location.
# Variable for resource group name resourceGroupName="msdocs-cosmos-gremlin-quickstart" location="westus" # Variable for account name with a randomly generated suffix let suffix=$RANDOM*$RANDOM accountName="msdocs-gremlin-$suffix"
If you haven't already, sign in to the Azure CLI using
az login
.Use
az group create
to create a new resource group in your subscription.az group create \ --name $resourceGroupName \ --location $location
Use
az cosmosdb create
to create a new API for Gremlin account with default settings.az cosmosdb create \ --resource-group $resourceGroupName \ --name $accountName \ --capabilities "EnableGremlin" \ --locations regionName=$location \ --enable-free-tier true
Get the API for Gremlin endpoint NAME for the account using
az cosmosdb show
.az cosmosdb show \ --resource-group $resourceGroupName \ --name $accountName \ --query "name"
Find the KEY from the list of keys for the account with
az-cosmosdb-keys-list
.az cosmosdb keys list \ --resource-group $resourceGroupName \ --name $accountName \ --type "keys" \ --query "primaryMasterKey"
Record the NAME and KEY values. You use these credentials later.
Create a database named
cosmicworks
usingaz cosmosdb gremlin database create
.az cosmosdb gremlin database create \ --resource-group $resourceGroupName \ --account-name $accountName \ --name "cosmicworks"
Create a graph using
az cosmosdb gremlin graph create
. Name the graphproducts
, then set the throughput to400
, and finally set the partition key path to/category
.az cosmosdb gremlin graph create \ --resource-group $resourceGroupName \ --account-name $accountName \ --database-name "cosmicworks" \ --name "products" \ --partition-key-path "/category" \ --throughput 400
Create a new Node.js console application
Create a Node.js console application in an empty folder using your preferred terminal.
Open your terminal in an empty folder.
Initialize a new module
npm init es6 --yes
Create the app.js file
touch app.js
Install the npm package
Add the gremlin
npm package to the Node.js project.
Open the package.json file and replace the contents with this JSON configuration.
{ "main": "app.js", "type": "module", "scripts": { "start": "node app.js" }, "dependencies": { "gremlin": "^3.*" } }
Use the
npm install
command to install all packages specified in the package.json file.npm install
Configure environment variables
To use the NAME and URI values obtained earlier in this quickstart, persist them to new environment variables on the local machine running the application.
To set the environment variable, use your terminal to persist the values as
COSMOS_ENDPOINT
andCOSMOS_KEY
respectively.export COSMOS_GREMLIN_ENDPOINT="<account-name>" export COSMOS_GREMLIN_KEY="<account-key>"
Validate that the environment variables were set correctly.
printenv COSMOS_GREMLIN_ENDPOINT printenv COSMOS_GREMLIN_KEY
Code examples
The code in this article connects to a database named cosmicworks
and a graph named products
. The code then adds vertices and edges to the graph before traversing the added items.
Authenticate the client
Application requests to most Azure services must be authorized. For the API for Gremlin, use the NAME and URI values obtained earlier in this quickstart.
Open the app.js file.
Import the
gremlin
module.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
- Create
accountName
andaccountKey
variables. Store theCOSMOS_GREMLIN_ENDPOINT
andCOSMOS_GREMLIN_KEY
environment variables as the values for each respective variable.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
- Use
PlainTextSaslAuthenticator
to create a new object for the account's credentials.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
- Use
Client
to connect using the remote server credentials and the GraphSON 2.0 serializer. Then, useOpen
to create a new connection to the server.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Create vertices
Now that the application is connected to the account, use the standard Gremlin syntax to create vertices.
Use
submit
to run a command server-side on the API for Gremlin account. Create a product vertex with the following properties:Value label product
id 68719518371
name
Kiama classic surfboard
price
285.55
category
surfboards
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Create a second product vertex with these properties:
Value label product
id 68719518403
name
Montau Turtle Surfboard
price
600.00
category
surfboards
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Create a third product vertex with these properties:
Value label product
id 68719518409
name
Bondi Twin Surfboard
price
585.50
category
surfboards
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Create edges
Create edges using the Gremlin syntax to define relationships between vertices.
- Create an edge from the
Montau Turtle Surfboard
product named replaces to theKiama classic surfboard
product.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Tip
This edge defintion uses the g.V(['<partition-key>', '<id>'])
syntax. Alternatively, you can use g.V('<id>').has('category', '<partition-key>')
.
- Create another replaces edge from the same product to the
Bondi Twin Surfboard
.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Query vertices & edges
Use the Gremlin syntax to traverse the graph and discover relationships between vertices.
- Traverse the graph and find all vertices that
Montau Turtle Surfboard
replaces.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
- Write to the console the result of this traversal.
// <imports>
import gremlin from 'gremlin'
// </imports>
// <environment_variables>
const accountName = process.env.COSMOS_GREMLIN_ENDPOINT
const accountKey = process.env.COSMOS_GREMLIN_KEY
// </environment_variables>
// <authenticate_client>
const credentials = new gremlin.driver.auth.PlainTextSaslAuthenticator(
'/dbs/cosmicworks/colls/products',
`${accountKey}`
)
// </authenticate_client>
// <connect_client>
const client = new gremlin.driver.Client(
`wss://${accountName}.gremlin.cosmos.azure.cn:443/`,
{
credentials,
traversalsource: 'g',
rejectUnauthorized: true,
mimeType: 'application/vnd.gremlin-v2.0+json'
}
)
client.open()
// </connect_client>
// <drop_graph>
await client.submit('g.V().drop()')
// </drop_graph>
// <create_vertices_1>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518371',
prop_name: 'Kiama classic surfboard',
prop_price: 285.55,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_1>
// <create_vertices_2>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518403',
prop_name: 'Montau Turtle Surfboard',
prop_price: 600.00,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_2>
// <create_vertices_3>
await client.submit(
'g.addV(\'product\').property(\'id\', prop_id).property(\'name\', prop_name).property(\'price\', prop_price).property(\'category\', prop_partition_key)', {
prop_id: '68719518409',
prop_name: 'Bondi Twin Surfboard',
prop_price: 585.50,
prop_partition_key: 'surfboards'
}
)
// </create_vertices_3>
// <create_edges_1>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518371'
}
)
// </create_edges_1>
// <create_edges_2>
await client.submit(
'g.V([prop_partition_key, prop_source_id]).addE(\'replaces\').to(g.V([prop_partition_key, prop_target_id]))', {
prop_partition_key: 'surfboards',
prop_source_id: '68719518403',
prop_target_id: '68719518409'
}
)
// </create_edges_2>
// <query_vertices_edges>
const result = await client.submit(
'g.V().hasLabel(\'product\').has(\'category\', prop_partition_key).has(\'name\', prop_name).outE(\'replaces\').inV()', {
prop_partition_key: 'surfboards',
prop_name: 'Montau Turtle Surfboard'
}
)
// </query_vertices_edges>
// <output_vertices_edges>
console.dir(result)
// </output_vertices_edges>
Run the code
Validate that your application works as expected by running the application. The application should execute with no errors or warnings. The output of the application includes data about the created and queried items.
Open the terminal in the Node.js project folder.
Use
npm <script>
to run the application. Observe the output from the application.npm start
Clean up resources
When you no longer need the API for Gremlin account, delete the corresponding resource group.
Create a shell variable for resourceGroupName if it doesn't already exist.
# Variable for resource group name resourceGroupName="msdocs-cosmos-gremlin-quickstart"
Use
az group delete
to delete the resource group.az group delete \ --name $resourceGroupName