How to deploy a scheduled query on an empty table using CloudFormation?

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05-10-2024

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Deploying Scheduled Queries on Empty Tables with CloudFormation

The Problem:

You want to automatically run a scheduled query against a table in your Amazon Redshift cluster, but the table is initially empty. This presents a challenge because typical CloudFormation approaches rely on existing resources.

Rephrased:

Imagine you want to set up a recurring task to analyze data in a Redshift table, but the table is still brand new and has no data yet. How do you schedule this query using CloudFormation when the table isn't populated yet?

Solution:

This issue can be overcome using a combination of CloudFormation, Lambda functions, and a clever workaround.

Scenario:

Let's say you want to schedule a daily query that summarizes data in a Redshift table called customer_data. This table might be populated with data from external sources later on. Here's how you can achieve this:

Original Code (Incomplete):

Resources:
  # ... other resources
  ScheduledQuery:
    Type: AWS::Redshift::ScheduledQuery
    Properties:
      Schedule: "cron(0 0 * * ? *)"  # Daily at midnight
      Database: 'your_database'
      DbUser: 'your_user'
      Query: 'SELECT * FROM customer_data'
      ScheduleDescription: 'Daily Customer Data Summary'
      WithEvents: true

Problem: This code will fail because the customer_data table might not exist when CloudFormation tries to create the scheduled query.

Solution Breakdown:

1. Lambda Function: Create a Lambda function that will handle the scheduled query. This function will first check if the table exists. If it does, it will run the query; otherwise, it will skip execution.

2. CloudWatch Event: Use CloudWatch Events to trigger the Lambda function on a schedule.

3. CloudFormation Template: Use CloudFormation to create the Lambda function, CloudWatch Event rule, and the Redshift table (if it doesn't exist).

Revised Code:

Resources:
  # ... other resources
  CustomerDataTable:
    Type: AWS::Redshift::Table
    Properties:
      Database: 'your_database'
      DbUser: 'your_user'
      Table: 'customer_data'
      # ... table definition 

  ScheduledQueryLambda:
    Type: AWS::Serverless::Function
    Properties:
      Handler: index.handler
      Runtime: nodejs14.x
      CodeUri: ./lambda-function  # Path to your Lambda code
      MemorySize: 128
      Timeout: 30
      Policies:
        - AWSLambdaBasicExecutionRole
      Events:
        ScheduledQueryTrigger:
          Type: Schedule
          Properties:
            Schedule: 'cron(0 0 * * ? *)'  # Daily at midnight
  ScheduledQueryEvent:
    Type: AWS::Events::Rule
    Properties:
      ScheduleExpression: "cron(0 0 * * ? *)"  # Daily at midnight
      State: ENABLED
      Targets:
        - Id: "ScheduledQueryLambda"
          Arn: !GetAtt ScheduledQueryLambda.Arn

Lambda Function (index.js):

const AWS = require('aws-sdk');
const redshift = new AWS.Redshift();

exports.handler = async (event) => {
  try {
    // Check if the table exists
    const tableExists = await checkTableExists('your_database', 'customer_data');

    if (tableExists) {
      // Run the query
      await runQuery('your_database', 'your_user', 'SELECT * FROM customer_data');
      console.log('Query executed successfully.');
    } else {
      console.log('Table does not exist. Skipping query execution.');
    }
  } catch (error) {
    console.error('Error:', error);
  }
};

async function checkTableExists(database, table) {
  try {
    await redshift.describeTables({
      Database: database,
      TableName: table
    }).promise();
    return true;
  } catch (error) {
    return false;
  }
}

async function runQuery(database, user, query) {
  await redshift.executeStatement({
    Database: database,
    DbUser: user,
    Sql: query
  }).promise();
}

Explanation:

• The CustomerDataTable resource creates the Redshift table.
• The ScheduledQueryLambda function defines a Lambda function that will be triggered by a CloudWatch event.
• The ScheduledQueryEvent resource creates a CloudWatch Event rule to trigger the Lambda function daily.
• The Lambda function uses the redshift client to check if the customer_data table exists. If it does, it runs the query; otherwise, it skips execution.

Advantages:

• Dynamic Scheduling: This approach allows you to schedule queries even on tables that are not yet populated.
• Robustness: The Lambda function handles the check for table existence, preventing errors during scheduled query execution.
• Flexibility: You can easily modify the query, schedule, and Lambda function code to meet your specific needs.

Conclusion:

By combining CloudFormation, Lambda functions, and CloudWatch Events, you can successfully deploy scheduled queries on empty tables. This approach ensures that your query runs smoothly as soon as the table is populated, allowing you to leverage valuable data insights from your Redshift cluster.