Implement incremental json loading#389
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@m-goggins when you ran the test on 5 million. Did you happen to monitor memory usage over that 5 min span? Did the program quickly reach its max memory usage, or did it slowly rise over the entire 5 mins? Also, curious as to what the total amount of memory required was. |
…om/CDCgov/RecordLinker into implement-incremental-json-loading
ericbuckley
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May 28, 2025
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Looks good @m-goggins just one small suggestion with the memory tracking code.
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Description
This PR updates the load testing scrambler to load and work on a single cluster at a time from a very large (~2GB) file of generated data. I used
ijsonto help with the incremental json loading, which fortunately allows us to read in each cluster individually and as a whole rather than in bytes at a time.To test this, I generated 1.5 million clusters (each with a single record) using the
gen_seed_data_script.py. The resulting file was roughly 2GB (200MB when zipped). I then ran the scrambler on the unzipped version of the file and was able to sample and generate ~5 million scrambled records in 5 minutes on my local.python3 -m tests.load.scripts.scramble_data --file="./test_original_data.json" --max-seed-records 5000000Related Issues
Closes #387
Additional Notes
The next bit of work will be updating the locustfile to reflect the per cluster randomization and ensuring that we hit the
/seedendpoint with only 100 records at a time usingijsonwith a batching function.<--------------------- REMOVE THE LINES BELOW BEFORE MERGING --------------------->
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