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Streaming Model API #13
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Benchmarks showed that TagByOperation was a performance bottleneck* as it requires disc access per query batch. To mitigate this I implemented operation caching inside the DoFn. For readability, I also renamed this operation to "SplitByOperation" as that more accurately describes its purpose. On a dataset with 1m examples, TagByOperation took ~25% of the total wall time. After implementing caching, this was reduced to ~2%.
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Streaming Model API
This PR introduces a streaming model API for
RunInference
.Overview
In addition to the current api:
It is now possible to use a PCollection of inference_spec_type as a side input or run inference on queries directly:
Notes
This PR depends on #11 and #12
This PR introduces
beam.GroupIntoBatches
and_TemporalJoin
which both require stateful DoFn support. This is not supported in Dataflow v1 and currentlyRunInference
is broken in Dataflow v2 due to BEAM-2717