Split project into sub-crates, add capture protobuf #629
Conversation
Regression Detector ResultsRun ID: 5f47e30e-938d-42f7-b7d2-8d816afb1c0e ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
Regression Detector ResultsRun ID: 26ebed31-40ec-4599-a583-d477b1e6d4dc ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
Regression Detector ResultsRun ID: 0873321a-bb59-4369-a6bc-fdd2169e5193 ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
Regression Detector ResultsRun ID: 0b3f8d72-3085-4611-b8d7-ac1111a41370 ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
Regression Detector ResultsRun ID: bb6ae185-04a6-4ad7-a533-0929e618e1c6 ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
blt
force-pushed
the
capture_proto
branch
2 times, most recently
from
301f92f
to
595dbcf
Compare
Regression Detector ResultsRun ID: 331a26da-b855-46d2-8f83-aae673c0993a ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
| - name: Install protobuf (Apt) | ||
| run: sudo apt-get update && sudo apt-get install -y protobuf-compiler | ||
| if: matrix.os == 'ubuntu-20.04' | ||
|
|
||
| - name: Install protobuf (Brew) | ||
| run: brew install protobuf | ||
| if: matrix.os == 'macos-latest' |
There was a problem hiding this comment.
No action needed, but something to note for memory's sake: if the protoc setup steps get annoying, we could change things around so we don't need it available in CI. The specific strategy varies; the essence is that the commits will include the rust changes corresponding to any proto changes that were made. We could flag protoc out of the CI build and use the generated rust files as-is. We'd probably want to add a hash of the proto files to the rust files to ensure they line up. The opentelemetry-proto rust crate uses a similar strategy.
There was a problem hiding this comment.
That's not a bad idea.
| // The kind of metric recorded by this line. | ||
| MetricKind kind = 3; | ||
| // The value of the metric recorded by this line. | ||
| double value = 4; |
There was a problem hiding this comment.
The JSON Line can specify a floating point or integer value (corresponding to a gauge or a counter, respectively). I'm open to keeping this as-is, but I thought I'd call it out. What do you think?
There was a problem hiding this comment.
I originally put that there out of an abundance of caution but considering that we already do wacky float / integer conversions in and out of metrics-rs I don't think were were actually gaining anything.
This commit splits the project into two sub-crates, one 'lading' which is familiar and one 'lading-capture' which has the traditional JSON form of a `Line` now exported and a new protobuf based capture payload intended for network transmission. REF SMP-631 Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Signed-off-by: Brian L. Troutwine <[email protected]>
Regression Detector ResultsRun ID: b432d970-d323-4540-8078-08a52746206b ExplanationA regression test is an integrated performance test for Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval. We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:
The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed. No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%. Fine details of change detection per experiment.
|
What does this PR do?
This commit splits the project into two sub-crates, one 'lading' which is familiar and one 'lading-capture' which has the traditional JSON form of a
Linenow exported and a new protobuf based capture payload intended for network transmission.Related issues
REF SMP-631