open-nomad/ui/app/components/topo-viz.js

363 lines
11 KiB
JavaScript

import Component from '@glimmer/component';
import { tracked } from '@glimmer/tracking';
import { action, set } from '@ember/object';
import { inject as service } from '@ember/service';
import { next } from '@ember/runloop';
import { scaleLinear } from 'd3-scale';
import { extent, deviation, mean } from 'd3-array';
import { line, curveBasis } from 'd3-shape';
import styleStringProperty from '../utils/properties/style-string';
export default class TopoViz extends Component {
@service system;
@tracked element = null;
@tracked topology = { datacenters: [] };
@tracked activeNode = null;
@tracked activeAllocation = null;
@tracked activeEdges = [];
@tracked edgeOffset = { x: 0, y: 0 };
@tracked viewportColumns = 2;
@tracked highlightAllocation = null;
@tracked tooltipProps = {};
@styleStringProperty('tooltipProps') tooltipStyle;
get isSingleColumn() {
if (this.topology.datacenters.length <= 1 || this.viewportColumns === 1)
return true;
// Compute the coefficient of variance to determine if it would be
// better to stack datacenters or place them in columns
const nodeCounts = this.topology.datacenters.map(
(datacenter) => datacenter.nodes.length
);
const variationCoefficient = deviation(nodeCounts) / mean(nodeCounts);
// The point at which the varation is too extreme for a two column layout
const threshold = 0.5;
if (variationCoefficient > threshold) return true;
return false;
}
get datacenterIsSingleColumn() {
// If there are enough nodes, use two columns of nodes within
// a single column layout of datacenters to increase density.
if (this.viewportColumns === 1) return true;
return (
!this.isSingleColumn ||
(this.isSingleColumn && this.args.nodes.length <= 20)
);
}
// Once a cluster is large enough, the exact details of a node are
// typically irrelevant and a waste of space.
get isDense() {
return this.args.nodes.length > 50;
}
dataForNode(node) {
return {
node,
datacenter: node.datacenter,
memory: node.resources.memory,
cpu: node.resources.cpu,
allocations: [],
isSelected: false,
};
}
dataForAllocation(allocation, node) {
const jobId = allocation.belongsTo('job').id();
return {
allocation,
node,
jobId,
groupKey: JSON.stringify([jobId, allocation.taskGroupName]),
memory: allocation.allocatedResources.memory,
cpu: allocation.allocatedResources.cpu,
memoryPercent: allocation.allocatedResources.memory / node.memory,
cpuPercent: allocation.allocatedResources.cpu / node.cpu,
isSelected: false,
};
}
@action
buildTopology() {
const nodes = this.args.nodes;
const allocations = this.args.allocations;
// Nodes may not have a resources property due to having an old Nomad agent version.
const badNodes = [];
// Wrap nodes in a topo viz specific data structure and build an index to speed up allocation assignment
const nodeContainers = [];
const nodeIndex = {};
nodes.forEach((node) => {
if (!node.resources) {
badNodes.push(node);
return;
}
const container = this.dataForNode(node);
nodeContainers.push(container);
nodeIndex[node.id] = container;
});
// Wrap allocations in a topo viz specific data structure, assign allocations to nodes, and build an allocation
// index keyed off of job and task group
const allocationIndex = {};
allocations.forEach((allocation) => {
const nodeId = allocation.belongsTo('node').id();
const nodeContainer = nodeIndex[nodeId];
// Ignore orphaned allocations and allocations on nodes with an old Nomad agent version.
if (!nodeContainer) return;
const allocationContainer = this.dataForAllocation(
allocation,
nodeContainer
);
nodeContainer.allocations.push(allocationContainer);
const key = allocationContainer.groupKey;
if (!allocationIndex[key]) allocationIndex[key] = [];
allocationIndex[key].push(allocationContainer);
});
// Group nodes into datacenters
const datacentersMap = nodeContainers.reduce(
(datacenters, nodeContainer) => {
if (!datacenters[nodeContainer.datacenter])
datacenters[nodeContainer.datacenter] = [];
datacenters[nodeContainer.datacenter].push(nodeContainer);
return datacenters;
},
{}
);
// Turn hash of datacenters into a sorted array
const datacenters = Object.keys(datacentersMap)
.map((key) => ({ name: key, nodes: datacentersMap[key] }))
.sortBy('name');
const topology = {
datacenters,
allocationIndex,
selectedKey: null,
heightScale: scaleLinear()
.range([15, 40])
.domain(extent(nodeContainers.mapBy('memory'))),
};
this.topology = topology;
if (badNodes.length && this.args.onDataError) {
this.args.onDataError([
{
type: 'filtered-nodes',
context: badNodes,
},
]);
}
}
@action
captureElement(element) {
this.element = element;
this.determineViewportColumns();
}
@action
showNodeDetails(node) {
if (this.activeNode) {
set(this.activeNode, 'isSelected', false);
}
this.activeNode = this.activeNode === node ? null : node;
if (this.activeNode) {
set(this.activeNode, 'isSelected', true);
}
if (this.args.onNodeSelect) this.args.onNodeSelect(this.activeNode);
}
@action showTooltip(allocation, element) {
const bbox = element.getBoundingClientRect();
this.highlightAllocation = allocation;
this.tooltipProps = {
left: window.scrollX + bbox.left + bbox.width / 2,
top: window.scrollY + bbox.top,
};
}
@action hideTooltip() {
this.highlightAllocation = null;
}
@action
associateAllocations(allocation) {
if (this.activeAllocation === allocation) {
this.activeAllocation = null;
this.activeEdges = [];
if (this.topology.selectedKey) {
const selectedAllocations =
this.topology.allocationIndex[this.topology.selectedKey];
if (selectedAllocations) {
selectedAllocations.forEach((allocation) => {
set(allocation, 'isSelected', false);
});
}
set(this.topology, 'selectedKey', null);
}
} else {
if (this.activeNode) {
set(this.activeNode, 'isSelected', false);
}
this.activeNode = null;
this.activeAllocation = allocation;
const selectedAllocations =
this.topology.allocationIndex[this.topology.selectedKey];
if (selectedAllocations) {
selectedAllocations.forEach((allocation) => {
set(allocation, 'isSelected', false);
});
}
set(this.topology, 'selectedKey', allocation.groupKey);
const newAllocations =
this.topology.allocationIndex[this.topology.selectedKey];
if (newAllocations) {
newAllocations.forEach((allocation) => {
set(allocation, 'isSelected', true);
});
}
// Only show the lines if the selected allocations are sparse (low count relative to the client count or low count generally).
if (
newAllocations.length < 10 ||
newAllocations.length < this.args.nodes.length * 0.75
) {
this.computedActiveEdges();
} else {
this.activeEdges = [];
}
}
if (this.args.onAllocationSelect)
this.args.onAllocationSelect(
this.activeAllocation && this.activeAllocation.allocation
);
if (this.args.onNodeSelect) this.args.onNodeSelect(this.activeNode);
}
@action
determineViewportColumns() {
this.viewportColumns = this.element.clientWidth < 900 ? 1 : 2;
}
@action
resizeEdges() {
if (this.activeEdges.length > 0) {
this.computedActiveEdges();
}
}
@action
computedActiveEdges() {
// Wait a render cycle
next(() => {
const path = line().curve(curveBasis);
// 1. Get the active element
const allocation = this.activeAllocation.allocation;
const activeEl = this.element.querySelector(
`[data-allocation-id="${allocation.id}"]`
);
const activePoint = centerOfBBox(activeEl.getBoundingClientRect());
// 2. Collect the mem and cpu pairs for all selected allocs
const selectedMem = Array.from(
this.element.querySelectorAll('.memory .bar.is-selected')
);
const selectedPairs = selectedMem.map((mem) => {
const id = mem.closest('[data-allocation-id]').dataset.allocationId;
const cpu = mem
.closest('.topo-viz-node')
.querySelector(`.cpu .bar[data-allocation-id="${id}"]`);
return [mem, cpu];
});
const selectedPoints = selectedPairs.map((pair) => {
return pair.map((el) => centerOfBBox(el.getBoundingClientRect()));
});
// 3. For each pair, compute the midpoint of the truncated triangle of points [Mem, Cpu, Active]
selectedPoints.forEach((points) => {
const d1 = pointBetween(points[0], activePoint, 100, 0.5);
const d2 = pointBetween(points[1], activePoint, 100, 0.5);
points.push(midpoint(d1, d2));
});
// 4. Generate curves for each active->mem and active->cpu pair going through the bisector
const curves = [];
// Steps are used to restrict the range of curves. The closer control points are placed, the less
// curvature the curve generator will generate.
const stepsMain = [0, 0.8, 1.0];
// The second prong the fork does not need to retrace the entire path from the activePoint
const stepsSecondary = [0.8, 1.0];
selectedPoints.forEach((points) => {
curves.push(
curveFromPoints(
...pointsAlongPath(activePoint, points[2], stepsMain),
points[0]
),
curveFromPoints(
...pointsAlongPath(activePoint, points[2], stepsSecondary),
points[1]
)
);
});
this.activeEdges = curves.map((curve) => path(curve));
this.edgeOffset = { x: window.scrollX, y: window.scrollY };
});
}
}
function centerOfBBox(bbox) {
return {
x: bbox.x + bbox.width / 2,
y: bbox.y + bbox.height / 2,
};
}
function dist(p1, p2) {
return Math.sqrt(Math.pow(p2.x - p1.x, 2) + Math.pow(p2.y - p1.y, 2));
}
// Return the point between p1 and p2 at len (or pct if len > dist(p1, p2))
function pointBetween(p1, p2, len, pct) {
const d = dist(p1, p2);
const ratio = d < len ? pct : len / d;
return pointBetweenPct(p1, p2, ratio);
}
function pointBetweenPct(p1, p2, pct) {
const dx = p2.x - p1.x;
const dy = p2.y - p1.y;
return { x: p1.x + dx * pct, y: p1.y + dy * pct };
}
function pointsAlongPath(p1, p2, pcts) {
return pcts.map((pct) => pointBetweenPct(p1, p2, pct));
}
function midpoint(p1, p2) {
return pointBetweenPct(p1, p2, 0.5);
}
function curveFromPoints(...points) {
return points.map((p) => [p.x, p.y]);
}