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Commit 7d0977d8 authored by Kubernetes Submit Queue's avatar Kubernetes Submit Queue Committed by GitHub
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Merge pull request #52238 from…

Merge pull request #52238 from mattjmcnaughton/mattjmcnaughton/address-golint-errors-in-podautoscaler Automatic merge from submit-queue. If you want to cherry-pick this change to another branch, please follow the instructions <a href="https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md">here</a>. Fix golint errors in `pkg/controller/podautoscaler` **What this PR does / why we need it**: Address `golint` errors in `pkg/controller/podautoscaler`. Note, I did not address issues around exported types/functions missing comments, because I'm not sure what the convention within the k8s project is. ```release-note NONE ``` Signed-off-by: 's avatarmattjmcnaughton <mattjmcnaughton@gmail.com>
parents e1d923a7 ff6fa927
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Showing with 40 additions and 41 deletions
pkg/controller/podautoscaler/legacy_replica_calculator_test.go
View file @ 7d0977d8
...@@ -604,7 +604,7 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) { ...@@ -604,7 +604,7 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
// Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio). // Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio).
target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01 target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01
finalCpuPercentTarget := int32(target * 100) finalCPUPercentTarget := int32(target * 100)
resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target) resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target)
// i.e. .60 * 20 -> scaled down expectation. // i.e. .60 * 20 -> scaled down expectation.
...@@ -641,7 +641,7 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) { ...@@ -641,7 +641,7 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
resource.MustParse(fmt.Sprint(perPodRequested) + "m"), resource.MustParse(fmt.Sprint(perPodRequested) + "m"),
}, },
targetUtilization: finalCpuPercentTarget, targetUtilization: finalCPUPercentTarget,
expectedUtilization: int32(totalUsedCPUOfAllPods*100) / totalRequestedCPUOfAllPods, expectedUtilization: int32(totalUsedCPUOfAllPods*100) / totalRequestedCPUOfAllPods,
expectedValue: numContainersPerPod * totalUsedCPUOfAllPods / 10, expectedValue: numContainersPerPod * totalUsedCPUOfAllPods / 10,
}, },
...@@ -652,8 +652,8 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) { ...@@ -652,8 +652,8 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
// Reuse the data structure above, now testing "unscaling". // Reuse the data structure above, now testing "unscaling".
// Now, we test that no scaling happens if we are in a very close margin to the tolerance // Now, we test that no scaling happens if we are in a very close margin to the tolerance
target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004 target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004
finalCpuPercentTarget = int32(target * 100) finalCPUPercentTarget = int32(target * 100)
tc.resource.targetUtilization = finalCpuPercentTarget tc.resource.targetUtilization = finalCPUPercentTarget
tc.currentReplicas = startPods tc.currentReplicas = startPods
tc.expectedReplicas = startPods tc.expectedReplicas = startPods
tc.runTest(t) tc.runTest(t)
......
pkg/controller/podautoscaler/rate_limitters.go
View file @ 7d0977d8
...@@ -46,7 +46,7 @@ func (r *FixedItemIntervalRateLimiter) NumRequeues(item interface{}) int { ...@@ -46,7 +46,7 @@ func (r *FixedItemIntervalRateLimiter) NumRequeues(item interface{}) int {
func (r *FixedItemIntervalRateLimiter) Forget(item interface{}) { func (r *FixedItemIntervalRateLimiter) Forget(item interface{}) {
} }
// NewDefaultHPARateLimitter creates a rate limitter which limits overall (as per the // NewDefaultHPARateLimiter creates a rate limitter which limits overall (as per the
// default controller rate limiter), as well as per the resync interval // default controller rate limiter), as well as per the resync interval
func NewDefaultHPARateLimiter(interval time.Duration) workqueue.RateLimiter { func NewDefaultHPARateLimiter(interval time.Duration) workqueue.RateLimiter {
return NewFixedItemIntervalRateLimiter(interval) return NewFixedItemIntervalRateLimiter(interval)
......
pkg/controller/podautoscaler/replica_calculator_test.go
View file @ 7d0977d8
...@@ -206,7 +206,7 @@ func (tc *replicaCalcTestCase) prepareTestClient(t *testing.T) (*fake.Clientset, ...@@ -206,7 +206,7 @@ func (tc *replicaCalcTestCase) prepareTestClient(t *testing.T) (*fake.Clientset,
} }
return true, &metrics, nil return true, &metrics, nil
} else { }
name := getForAction.GetName() name := getForAction.GetName()
mapper := api.Registry.RESTMapper() mapper := api.Registry.RESTMapper()
metrics := &cmapi.MetricValueList{} metrics := &cmapi.MetricValueList{}
...@@ -235,7 +235,6 @@ func (tc *replicaCalcTestCase) prepareTestClient(t *testing.T) (*fake.Clientset, ...@@ -235,7 +235,6 @@ func (tc *replicaCalcTestCase) prepareTestClient(t *testing.T) (*fake.Clientset,
} }
return true, metrics, nil return true, metrics, nil
}
}) })
return fakeClient, fakeMetricsClient, fakeCMClient return fakeClient, fakeMetricsClient, fakeCMClient
...@@ -729,7 +728,7 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) { ...@@ -729,7 +728,7 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
// Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio). // Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio).
target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01 target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01
finalCpuPercentTarget := int32(target * 100) finalCPUPercentTarget := int32(target * 100)
resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target) resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target)
// i.e. .60 * 20 -> scaled down expectation. // i.e. .60 * 20 -> scaled down expectation.
...@@ -766,7 +765,7 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) { ...@@ -766,7 +765,7 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
resource.MustParse(fmt.Sprint(perPodRequested) + "m"), resource.MustParse(fmt.Sprint(perPodRequested) + "m"),
}, },
targetUtilization: finalCpuPercentTarget, targetUtilization: finalCPUPercentTarget,
expectedUtilization: int32(totalUsedCPUOfAllPods*100) / totalRequestedCPUOfAllPods, expectedUtilization: int32(totalUsedCPUOfAllPods*100) / totalRequestedCPUOfAllPods,
expectedValue: numContainersPerPod * totalUsedCPUOfAllPods / 10, expectedValue: numContainersPerPod * totalUsedCPUOfAllPods / 10,
}, },
...@@ -777,8 +776,8 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) { ...@@ -777,8 +776,8 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
// Reuse the data structure above, now testing "unscaling". // Reuse the data structure above, now testing "unscaling".
// Now, we test that no scaling happens if we are in a very close margin to the tolerance // Now, we test that no scaling happens if we are in a very close margin to the tolerance
target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004 target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004
finalCpuPercentTarget = int32(target * 100) finalCPUPercentTarget = int32(target * 100)
tc.resource.targetUtilization = finalCpuPercentTarget tc.resource.targetUtilization = finalCPUPercentTarget
tc.currentReplicas = startPods tc.currentReplicas = startPods
tc.expectedReplicas = startPods tc.expectedReplicas = startPods
tc.runTest(t) tc.runTest(t)
......
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