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  • 👋Welcome to the Rockset-Confluent workshop
  • Preface
    • Workshop Introduction
    • 💟Rockset Pairs with Kafka for Real-Time Analytics
    • ⚒️Build a Real-Time Recommendation & Customer 360 Application
    • 👀Workshop pre-reqs
      • Create a user_activity_v1 schema on Mockaroo
      • Create a user_purchases_v1 schema on Mockaroo
      • Getting Started with Confluent Cloud
      • Create 2 Kafka Topics
      • Create Confluent API keys
      • Send data to Kafka
  • Workshop Part I: Build a real-time recommendation and other analytical queries
    • ✏️Rockset account setup
      • 🔑Get Kafka credentials from your email
      • ➿Rockset integration and collection overview
      • ⛏️Create Rockset Account
    • 🧺Populate Rockset collections with Kafka and S3 data
      • 🪄Create a kafka integration
        • Select the Kafka data source
        • Fill in the integration details
      • 🪄Create collections
        • Create a CustomerClickActivities collection
          • Create SQL transformations on CustomerClickActivities
        • Create a CustomerPurchaseActivities collection
          • Create SQL transformations on CustomerPurchaseActivities
        • Create an Aggregate CustomerPurchaseActivities collection
          • Create SQL transformation on AggregateCustomerPurchaseActivities
        • Create a ProductInformation collection
          • Create SQL transformations on ProductInformation
        • Create a CustomerInformation collection
          • Create SQL transformations on CustomerInformation
    • 🖊️Write analytical queries
      • Write a real-time recommendation query
        • Return the customer's last purchase
        • Return the customer's latest activities after their last purchase
        • Find previous purchases that contain the customer's items
        • Aggregate all the purchases
        • Filter results so it doesn't contain the product of interest
        • Identify the product ID with the product name
        • Create a Query Lambda
        • Wrap up on real-time recommendation query
      • Display all users who created an account
        • Create a Query Lambda
        • Wrap up for displaying all users
      • Return a customer's previous purchase
        • Associate the product IDs with the product names
        • Create a Query Lambda
      • Return the total and average customer spend
        • Create a Query Lambda
    • 🗝️Create an API key
    • 🧘‍♀️Analytical query wrap up
  • Workshop Part II: Build a customer 360 app on Retool
    • Create real-time internal tools with Retool
    • Retool account setup
      • Sign up for a free trial
    • Create resource queries
    • Create a customer 360 app
      • List all the users who made purchases
      • Show specific details of a specific customer
      • Show a customer's purchase
      • Show items recommended
      • Show customer's spend
      • Final touch ups
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On this page
  1. Workshop Part I: Build a real-time recommendation and other analytical queries
  2. Write analytical queries
  3. Return a customer's previous purchase

Create a Query Lambda

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Last updated 2 years ago

1. Similar to what we did earlier, we’ll turn this SQL query into a data API. Go ahead and save the query by clicking on the Save as drop-down and selecting Save as Query Lambda:

Query Editor- save query

2. Save the query as:

  • Name: CustomerPurchases

  • Workspace: kafkaWorkshop

3. On the Query Editor, click on the Show Details button:

4. You’ll see the detailed API information:

NOTE: You can find us on the Rockset Community if you have questions or comments about the workshop.

Query Lambda details
Query Editor
API details
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