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@@ -499,6 +499,63 @@ func checkForKeyAndInitIfMissing(
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}
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}
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+// buildNodeMap creates the main set of node data for ClusterNodes from
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+// the data maps built from Prometheus queries. Some of the Prometheus
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+// data has access to the provider_id field and some does not. To get
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+// around this problem, we use the data that includes provider_id
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+// to build up the definitive set of nodes and then use the data
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+// with less-specific identifiers (i.e. without provider_id) to fill
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+// in the remaining fields.
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+//
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+// For example, let's say we have nodes identified like so:
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+// cluster name/node name/provider_id. For the sake of the example,
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+// we will also limit data to CPU cost, CPU cores, and preemptibility.
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+//
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+// We have CPU cost data that looks like this:
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+// cluster1/node1/prov_node1_A: $10
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+// cluster1/node1/prov_node1_B: $8
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+// cluster1/node2/prov_node2: $15
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+//
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+// We have Preemptible data that looks like this:
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+// cluster1/node1/prov_node1_A: true
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+// cluster1/node1/prov_node1_B: false
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+// cluster1/node2/prov_node2_B: false
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+//
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+// We have CPU cores data that looks like this:
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+// cluster1/node1: 4
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+// cluster1/node2: 6
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+//
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+// This function first combines the data that is fully identified,
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+// creating the following:
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+// cluster1/node1/prov_node1_A: CPUCost($10), Preemptible(true)
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+// cluster1/node1/prov_node1_B: CPUCost($8), Preemptible(false)
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+// cluster1/node2/prov_node2: CPUCost($15), Preemptible(false)
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+//
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+// It then uses the less-specific data to extend the specific data,
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+// making the following:
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+// cluster1/node1/prov_node1_A: CPUCost($10), Preemptible(true), Cores(4)
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+// cluster1/node1/prov_node1_B: CPUCost($8), Preemptible(false), Cores(4)
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+// cluster1/node2/prov_node2: CPUCost($15), Preemptible(false), Cores(6)
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+//
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+// In the situation where provider_id doesn't exist for any metrics,
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+// that is the same as all provider_id's being empty strings. If
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+// provider_id doesn't exist at all, then we (without having to do
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+// extra work) easily fall back on identifying nodes only by cluster name
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+// and node name because the provider_id part of the key will always
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+// be the empty string.
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+//
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+// It is worth nothing that, in this approach, if a node is not present
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+// in the more specific data but is present in the less-specific data,
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+// that data is never processed into the final node map. For example,
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+// let's say the CPU cores map has the following entry:
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+// cluster1/node8: 6
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+// But node of the maps with provider_id (CPU cost, RAM cost, etc.)
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+// have an identifier for cluster1/node8 (regardless of provider_id).
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+// In this situation, the final node map will not have a cluster1/node8
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+// entry. This could be fixed by iterating over all of the less specific
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+// identifiers and, inside that iteration, all of the identifiers in
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+// the node map, but this would introduce a roughly quadratic time
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+// complexity.
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func buildNodeMap(
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cpuCostMap, ramCostMap, gpuCostMap map[NodeIdentifier]float64,
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cpuCoresMap, ramBytesMap, ramUserPctMap,
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@@ -511,6 +568,8 @@ func buildNodeMap(
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nodeMap := make(map[NodeIdentifier]*Node)
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+ // Initialize the map with the most-specific data:
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+
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for id, cost := range cpuCostMap {
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checkForKeyAndInitIfMissing(nodeMap, id, clusterAndNameToType)
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nodeMap[id].CPUCost = cost
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Michael Dresser