feat(ingest/superset): leverage threads for superset API calls #13006
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| executor.submit(process_chart, chart_data): chart_data | ||
| for chart_data in self.paginate_entity_api_results("chart/", PAGE_SIZE) | ||
| } | ||
| for future in as_completed(future_to_chart): |
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let's use our ThreadedIteratorExecutor class for this
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Good call. Updated to use datahub's ThreadedIteratorExecutor class
| @@ -1024,17 +1050,15 @@ def construct_dataset_from_dataset_data( | |||
| return dataset_snapshot | |||
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| def emit_dataset_mces(self) -> Iterable[MetadataWorkUnit]: | |||
| for dataset_data in self.paginate_entity_api_results("dataset/", PAGE_SIZE): | |||
| def process_dataset(dataset_data): | |||
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nesting methods within other methods is typically not a great practice
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Yep. Moved it to a private method outside.
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Before we had timeouts on long dataset ingestions because it would take approx 6 hours, while the lifespan of a single preset jwt was 5 hours. This means we were unable to ingest all the datasets in the lifespan of the jwt. This pr improves the speed by leveraging threads for api calls. This was able to improve the ingestion time down to 1 hour and 6 minutes.
This pr also hopes to resolve this issue, which is a similar problem with expiring access token. I plan to put up another pr after this if it is still too slow for some ingestions to refresh the jwt on large ingestions.
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