Golang NodeInfo.RequestedResource方法代码示例

func podFitsResourcesInternal(pod *api.Pod, nodeName string, nodeInfo *schedulercache.NodeInfo, info *api.Node) (bool, error) {
	allocatable := info.Status.Allocatable
	allowedPodNumber := allocatable.Pods().Value()
	if int64(len(nodeInfo.Pods()))+1 > allowedPodNumber {
		return false,
			newInsufficientResourceError(podCountResourceName, 1, int64(len(nodeInfo.Pods())), allowedPodNumber)
	}
	podRequest := getResourceRequest(pod)
	if podRequest.milliCPU == 0 && podRequest.memory == 0 {
		return true, nil
	}

	totalMilliCPU := allocatable.Cpu().MilliValue()
	totalMemory := allocatable.Memory().Value()

	if totalMilliCPU < podRequest.milliCPU+nodeInfo.RequestedResource().MilliCPU {
		return false,
			newInsufficientResourceError(cpuResourceName, podRequest.milliCPU, nodeInfo.RequestedResource().MilliCPU, totalMilliCPU)
	}
	if totalMemory < podRequest.memory+nodeInfo.RequestedResource().Memory {
		return false,
			newInsufficientResourceError(memoryResoureceName, podRequest.memory, nodeInfo.RequestedResource().Memory, totalMemory)
	}
	glog.V(10).Infof("Schedule Pod %+v on Node %+v is allowed, Node is running only %v out of %v Pods.",
		podName(pod), nodeName, len(nodeInfo.Pods()), allowedPodNumber)
	return true, nil
}

func PodFitsResources(pod *api.Pod, meta interface{}, nodeInfo *schedulercache.NodeInfo) (bool, []algorithm.PredicateFailureReason, error) {
	node := nodeInfo.Node()
	if node == nil {
		return false, nil, fmt.Errorf("node not found")
	}

	var predicateFails []algorithm.PredicateFailureReason
	allowedPodNumber := nodeInfo.AllowedPodNumber()
	if len(nodeInfo.Pods())+1 > allowedPodNumber {
		predicateFails = append(predicateFails, NewInsufficientResourceError(api.ResourcePods, 1, int64(len(nodeInfo.Pods())), int64(allowedPodNumber)))
	}

	var podRequest *schedulercache.Resource
	if predicateMeta, ok := meta.(*predicateMetadata); ok {
		podRequest = predicateMeta.podRequest
	} else {
		// We couldn't parse metadata - fallback to computing it.
		podRequest = GetResourceRequest(pod)
	}
	if podRequest.MilliCPU == 0 && podRequest.Memory == 0 && podRequest.NvidiaGPU == 0 && len(podRequest.OpaqueIntResources) == 0 {
		return len(predicateFails) == 0, predicateFails, nil
	}

	allocatable := nodeInfo.AllocatableResource()
	if allocatable.MilliCPU < podRequest.MilliCPU+nodeInfo.RequestedResource().MilliCPU {
		predicateFails = append(predicateFails, NewInsufficientResourceError(api.ResourceCPU, podRequest.MilliCPU, nodeInfo.RequestedResource().MilliCPU, allocatable.MilliCPU))
	}
	if allocatable.Memory < podRequest.Memory+nodeInfo.RequestedResource().Memory {
		predicateFails = append(predicateFails, NewInsufficientResourceError(api.ResourceMemory, podRequest.Memory, nodeInfo.RequestedResource().Memory, allocatable.Memory))
	}
	if allocatable.NvidiaGPU < podRequest.NvidiaGPU+nodeInfo.RequestedResource().NvidiaGPU {
		predicateFails = append(predicateFails, NewInsufficientResourceError(api.ResourceNvidiaGPU, podRequest.NvidiaGPU, nodeInfo.RequestedResource().NvidiaGPU, allocatable.NvidiaGPU))
	}
	for rName, rQuant := range podRequest.OpaqueIntResources {
		if allocatable.OpaqueIntResources[rName] < rQuant+nodeInfo.RequestedResource().OpaqueIntResources[rName] {
			predicateFails = append(predicateFails, NewInsufficientResourceError(rName, podRequest.OpaqueIntResources[rName], nodeInfo.RequestedResource().OpaqueIntResources[rName], allocatable.OpaqueIntResources[rName]))
		}
	}

	if glog.V(10) {
		// We explicitly don't do glog.V(10).Infof() to avoid computing all the parameters if this is
		// not logged. There is visible performance gain from it.
		glog.Infof("Schedule Pod %+v on Node %+v is allowed, Node is running only %v out of %v Pods.",
			podName(pod), node.Name, len(nodeInfo.Pods()), allowedPodNumber)
	}
	return len(predicateFails) == 0, predicateFails, nil
}

func PodFitsResources(pod *api.Pod, meta interface{}, nodeInfo *schedulercache.NodeInfo) (bool, error) {
	node := nodeInfo.Node()
	if node == nil {
		return false, fmt.Errorf("node not found")
	}
	allowedPodNumber := nodeInfo.AllowedPodNumber()
	if len(nodeInfo.Pods())+1 > allowedPodNumber {
		return false,
			newInsufficientResourceError(podCountResourceName, 1, int64(len(nodeInfo.Pods())), int64(allowedPodNumber))
	}

	var podRequest *schedulercache.Resource
	if predicateMeta, ok := meta.(*predicateMetadata); ok {
		podRequest = predicateMeta.podRequest
	} else {
		// We couldn't parse metadata - fallback to computing it.
		podRequest = getResourceRequest(pod)
	}
	if podRequest.MilliCPU == 0 && podRequest.Memory == 0 && podRequest.NvidiaGPU == 0 {
		return true, nil
	}

	allocatable := nodeInfo.AllocatableResource()
	if allocatable.MilliCPU < podRequest.MilliCPU+nodeInfo.RequestedResource().MilliCPU {
		return false,
			newInsufficientResourceError(cpuResourceName, podRequest.MilliCPU, nodeInfo.RequestedResource().MilliCPU, allocatable.MilliCPU)
	}
	if allocatable.Memory < podRequest.Memory+nodeInfo.RequestedResource().Memory {
		return false,
			newInsufficientResourceError(memoryResourceName, podRequest.Memory, nodeInfo.RequestedResource().Memory, allocatable.Memory)
	}
	if allocatable.NvidiaGPU < podRequest.NvidiaGPU+nodeInfo.RequestedResource().NvidiaGPU {
		return false,
			newInsufficientResourceError(nvidiaGpuResourceName, podRequest.NvidiaGPU, nodeInfo.RequestedResource().NvidiaGPU, allocatable.NvidiaGPU)
	}
	if glog.V(10) {
		// We explicitly don't do glog.V(10).Infof() to avoid computing all the parameters if this is
		// not logged. There is visible performance gain from it.
		glog.Infof("Schedule Pod %+v on Node %+v is allowed, Node is running only %v out of %v Pods.",
			podName(pod), node.Name, len(nodeInfo.Pods()), allowedPodNumber)
	}
	return true, nil
}

func PodFitsResources(pod *api.Pod, nodeInfo *schedulercache.NodeInfo) (bool, error) {
	node := nodeInfo.Node()
	if node == nil {
		return false, fmt.Errorf("node not found")
	}
	allocatable := node.Status.Allocatable
	allowedPodNumber := allocatable.Pods().Value()
	if int64(len(nodeInfo.Pods()))+1 > allowedPodNumber {
		return false,
			newInsufficientResourceError(podCountResourceName, 1, int64(len(nodeInfo.Pods())), allowedPodNumber)
	}
	podRequest := getResourceRequest(pod)
	if podRequest.milliCPU == 0 && podRequest.memory == 0 && podRequest.nvidiaGPU == 0 {
		return true, nil
	}

	totalMilliCPU := allocatable.Cpu().MilliValue()
	totalMemory := allocatable.Memory().Value()
	totalNvidiaGPU := allocatable.NvidiaGPU().Value()

	if totalMilliCPU < podRequest.milliCPU+nodeInfo.RequestedResource().MilliCPU {
		return false,
			newInsufficientResourceError(cpuResourceName, podRequest.milliCPU, nodeInfo.RequestedResource().MilliCPU, totalMilliCPU)
	}
	if totalMemory < podRequest.memory+nodeInfo.RequestedResource().Memory {
		return false,
			newInsufficientResourceError(memoryResourceName, podRequest.memory, nodeInfo.RequestedResource().Memory, totalMemory)
	}
	if totalNvidiaGPU < podRequest.nvidiaGPU+nodeInfo.RequestedResource().NvidiaGPU {
		return false,
			newInsufficientResourceError(nvidiaGpuResourceName, podRequest.nvidiaGPU, nodeInfo.RequestedResource().NvidiaGPU, totalNvidiaGPU)
	}
	glog.V(10).Infof("Schedule Pod %+v on Node %+v is allowed, Node is running only %v out of %v Pods.",
		podName(pod), node.Name, len(nodeInfo.Pods()), allowedPodNumber)
	return true, nil
}