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If your job is easily parallelizable then you can run multiple lambdas in parallel. For the above use case they probably should have kicked off one lambda per p
by RhodesianHunter 8y ago
If your job is easily parallelizable then you can run multiple lambdas in parallel. For the above use case they probably should have kicked off one lambda per prefix or similar.
- djhworld 8y agoThat's exactly what we were doing. 1 Lambda to download and aggregate all files under a prefix. The problem was the task just couldn't complete in < 5 minutes.
- manigandham 8y agoYou have to fan out further then, process each file separately and aggregate the aggregates, using SQS or something else to queue up the processing. Azure's Durable Functions have an advantage here in making extreme fan-out situations easy.
- djhworld 8y agoWe considered it, but at the time we just felt implementing map/reduce over Lambda would just introduce a more complex architecture for such a simple problem. Maybe the recently introduced SQS->Lambda support might make it a bit cleaner, but in the end we opted for EC2.