AWS Lambda Overview

AWS Lambda is a serverless computing platform that runs code in response to events and automatically manages the compute resources required by that code.

Featureslink

Supported languageslink

AWS Lambda supports the following languages:

• Node.js (JavaScript)
• Python
• Java (Java 8 compatible)
• C# (.NET Core)
• Go

Function request and responselink

Fivetran uses the AWS SDK for the AWS Lambda Functions connector. For more information about how Fivetran syncs data from your cloud function, see our Sync overview documentation.

Request formatlink

Fivetran’s request has a standard format. It is a JSON object with three root nodes:

• agent is an informational object.

• state is a JSON object that contains cursors from the previous successful function execution. It is key to performing incremental updates. A cursor is a bookmark that marks the data Fivetran has already synced, for example, a timestamp, ID, or index. For the initial sync, state is an empty JSON object {}. Fivetran expects an updated state object in every response.

  For more information about the state object, see How to Use the state Object.

• secrets (optional) is a JSON object that contains access keys or API keys for the upstream APIs. Secrets allow you to store information (API tokens or database passwords) that you don’t want to maintain in your code. We use encryption at rest to store the secrets. We pass the secrets into your function every time we call the function. Enter your secrets using a JSON format in the connector setup form.

  For more information about the secrets object, see How to Use the secrets Object.

Example request

{
    "agent" : "Fivetran AWS Lambda Connector/<external_id>/<schema>",
    "state": {
        "cursor": "2020-01-01T00:00:00Z"
    },
    "secrets": {
        "apiToken": "abcdefghijklmnopqrstuvwxyz_0123456789"
    }
}

In this example,

• external_id is the unique ID tied to your connector. You can find the ID in your connector setup form. You need this to configure your AWS account to connect with Fivetran.
• schema is the destination schema name you enter when you first set up your connector.

Response formatlink

The response is a JSON object with five root nodes:

• state contains the updated state value(s).

• insert specifies the entities and records to be inserted. Fivetran reads the data and infers the data type and the number of columns.

• delete (optional) specifies the entities and records to be deleted. Use this node to mark records as deleted. Fivetran doesn’t delete the record; instead it marks the record as deleted by setting _fivetran_deleted column value to true. If you specify the delete node, you must also specify the schema node.

  Fivetran creates the _fivetran_deleted column in the destination table, only if your function response has the delete node.

• schema (optional) specifies primary key columns for each entity. You must be very consistent with the schema node and the primary key columns to avoid any unwanted behavior. If you don’t specify the schema, Fivetran appends the data.

• hasMore is an indicator for Fivetran to make a follow-up call for fetching the next set of data. Fivetran keeps making repeated calls until it receives hasMore = false.

  For more information about the hasMore node, see How to Use the hasMore Object.

Example response

{
    "state": {
        "transaction": "2020-01-02T00:00:00Z",
    },
    "insert": {
        "transaction": [
            {"id":1, "amount": 100},
            {"id":3, "amount": 50}
        ],
    },
    "delete": {
        "transaction": [
            {"id":2},
        ],
    },
    "schema" : {
        "transaction": {
            "primary_key": ["id"]
        },
    },
    "hasMore" : false
}

In this example,

• state contains the transaction cursor.

• transaction is an entity. Fivetran creates the TRANSACTION table with id and amount columns.

• The function inserts records 1 and 3 into the TRANSACTION table.

• The function marks record 2 as deleted from the TRANSACTION table.

• hasMore is set to false to indicate that there are no more records.

Custom error handlinglink

Cloud functions may fail due to various reasons, including code execution errors, runtime issues, or internal errors. Add an error handling mechanism in your Lambda function response to report an error on your Fivetran dashboard.

Design your Lambda function to report an error:

• Use the errorMessage node in your response to indicate function execution errors. Fivetran creates a Task on the connector dashboard with your custom error message. For example, for the following response, Fivetran creates a Task This is an error on your dashboard:

  {
  "errorMessage": "This is an error"
  }
  

• Use the errorType and stackTrace nodes to pass additional information about the error. You must specify the errorMessage node to use the errorType and stackTrace nodes. For example, for the following response, Fivetran creates a Task alert on your dashboard with the error type and stack trace details:

  {
  "errorMessage": "name 'response' is not defined",
  "errorType": "NameError",
  "stackTrace": [
      [
      "/var/task/lambda_function.py",
      35,
      "lambda_handler",
      "response['errorMessage'] = \"This is an error\""
      ]
  ]
  }
  

Setup guidelink

Follow our step-by-step AWS Lambda setup guide to connect AWS Lambda with your destination using Fivetran connectors.

Frequently asked questionslink

For more information about cloud functions, see the following:

• Can Custom Data be Exchanged between Fivetran and a Cloud Function
• How Can I Upsert Data Using a Cloud Function
• How Can I View Detailed Logs for My Cloud Function