Batch Address Validation Pipeline
Prerequisites
- Experience with message queues (Redis, SQS, or RabbitMQ) - Production API key with high rate limits - Understanding of async/worker patterns
When you need to validate large volumes of addresses, individual API calls are not efficient. This guide shows you how to build a high-throughput validation pipeline using batch endpoints and async processing.
Step 1: Design the Pipeline
Architecture overview: CSV upload → Queue → Batch API → Results store → Export. Each stage handles errors independently.
Step 2: Implement the Upload Handler
Accept CSV files, parse them into batches of 1,000 addresses, and push each batch to a job queue (Redis/SQS).
Step 3: Build the Batch Worker
async function processBatch(addresses) {\n const response = await client.addresses.validateBatch({\n addresses,\n options: { include_geocode: true }\n });\n return response.results;\n}
Step 4: Handle Partial Failures
The batch endpoint returns individual status codes per address. Separate successes from failures and retry only the failed ones.
Step 5: Implement Rate Limit Backpressure
Monitor X-RateLimit-Remaining headers and dynamically adjust worker concurrency to stay within limits.
Step 6: Store and Export Results
Write validated addresses to your database with confidence scores. Generate an export report with validation statistics.
Step 7: Monitor and Alert
Set up monitoring for queue depth, error rates, and throughput. Alert when error rate exceeds 5% or queue depth grows beyond threshold.