MLeap for local model scoring #249
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Codecov Report
@@ Coverage Diff @@
## master #249 +/- ##
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- Coverage 86.41% 28.4% -58.02%
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Files 312 312
Lines 10187 8316 -1871
Branches 336 420 +84
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- Hits 8803 2362 -6441
- Misses 1384 5954 +4570
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Codecov Report
@@ Coverage Diff @@
## master #249 +/- ##
==========================================
+ Coverage 86.41% 86.49% +0.08%
==========================================
Files 312 312
Lines 10187 10184 -3
Branches 336 336
==========================================
+ Hits 8803 8809 +6
+ Misses 1384 1375 -9
Continue to review full report at Codecov.
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local/README.md
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| @@ -44,6 +39,6 @@ val scoreFn = new OpWorkflowRunnerLocal(workflow).score(opParams) | |||
| Below is an example of measured scoring performance on 6m records with 10 fields and 12 transformations applied. | |||
| Executed on MacBook Pro i7 3.5Ghz in a single thread. | |||
| ``` | |||
| Scored 6,000,000 records in 239s | |||
| Average time per record: 0.0399215ms | |||
| Scored 6,000,000 records in 710s | |||
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interesting that there is 3x throughput difference
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I had to warm up the JVM. Updated the numbers.
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It's slightly faster.
leahmcguire
approved these changes
Mar 22, 2019
| /** | ||
| * Internal PFA model representation | ||
| * Internal OP model representation |
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Related issues
Aardpfark is no longer supported.
Describe the proposed solution
Switching to MLeap runtime instead.
Describe alternatives you've considered
N/A