The available documentation doesn't include specific memory control settings for Apify integrations within Clay. The Apify integration allows you to configure input data, run conditions, and rate limits, but memory allocation controls aren't mentioned in our current resources.
You can control request frequency through rate limiting in the HTTP API integration, which may indirectly help with resource usage by limiting concurrent requests.
Are you experiencing specific memory-related issues with your Apify actor runs, such as timeouts or performance problems?
Hey! In Apify, you can control memory usage by setting the memoryMbytes value in the actor run request. For example: LBKS{ "memoryMbytes": 2048 }LBKSThis allocates 2048 MB to the actor. Just note that since each row in Clay triggers a separate 1-1 API call, you could still hit limits depending on how heavy each task is.
Let me know if you want help adjusting the API setup or optimizing the actor config.
Hey — thanks for hanging in there. From what you’re describing, it sounds like you're having an issue with the memory limits during the run? Right?
There’s no way around that directly, but you can manage it by splitting the run into smaller sub-batches. That helps stay within the memory cap and keeps everything running smoothly.
Let me know if you have more questions
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