mirror of
https://github.com/ClusterCockpit/cc-backend
synced 2025-08-23 18:43:00 +02:00
remove outdated components
This commit is contained in:
Christoph Kluge
@@ -1,468 +0,0 @@
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<!--
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@component Main cluster status view component; renders current system-usage information
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Properties:
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- `cluster String`: The cluster to show status information for
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-->
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<script>
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import {
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Row,
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Col,
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Table,
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Icon
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} from "@sveltestrap/sveltestrap";
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import {
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queryStore,
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gql,
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getContextClient,
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} from "@urql/svelte";
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import {
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init,
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} from "../generic/utils.js";
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//import Roofline from "../generic/plots/Roofline.svelte";
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import Roofline from "../generic/plots/Roofline.svelte";
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import Pie, { colors } from "../generic/plots/Pie.svelte";
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import { formatTime } from "../generic/units.js";
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/* Svelte 5 Props */
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let {
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cluster,
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useCbColors = false
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} = $props();
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/* Const Init */
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const { query: initq } = init();
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const client = getContextClient();
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/* State Init */
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let from = $state(new Date(Date.now() - 5 * 60 * 1000));
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let to = $state(new Date(Date.now()));
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let plotWidths = $state([]);
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let statesWidth = $state(0);
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let healthWidth = $state(0);
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// let nodesCounts = $state({});
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// let jobsJounts = $state({});
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/* Derived */
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// Note: nodeMetrics are requested on configured $timestep resolution
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// Result: The latest 5 minutes (datapoints) for each node independent of job
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const jobRoofQuery = $derived(queryStore({
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client: client,
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query: gql`
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query ($filter: [JobFilter!]!, $metrics: [String!]!) {
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jobsMetricStats(filter: $filter, metrics: $metrics) {
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id
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jobId
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duration
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numNodes
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numAccelerators
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subCluster
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stats {
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name
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data {
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avg
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}
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}
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}
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}
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`,
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variables: {
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filter: [{ state: ["running"] }, { cluster: { eq: cluster } }],
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metrics: ["flops_any", "mem_bw"], // Fixed names for job roofline
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},
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}));
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// Optimal new query, does not exist
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// const nodeRoofQuery = $derived(queryStore({
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// client: client,
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// query: gql`
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// query ($filter: [JobFilter!]!, $metrics: [String!]!) {
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// nodeRoofline(filter: $filter, metrics: $metrics) {
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// nodeName
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// nodeState
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// numJobs
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// stats {
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// name
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// data {
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// avg
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// }
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// }
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// }
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// }
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// `,
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// variables: {
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// filter: [{ state: ["running"] }, { cluster: { eq: cluster } }],
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// metrics: ["flops_any", "mem_bw"], // Fixed names for job roofline
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// },
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// }));
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// Load Required Roofline Data Averages for all nodes of cluster: use for node avg data and name, use secondary (new?) querie(s) for slurmstate and numjobs
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const nodesData = $derived(queryStore({
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client: client,
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query: gql`
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query ($cluster: String!, $metrics: [String!], $from: Time!, $to: Time!) {
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nodeMetrics(
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cluster: $cluster
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metrics: $metrics
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from: $from
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to: $to
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) {
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host
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subCluster
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metrics {
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name
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metric {
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series {
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statistics {
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avg
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}
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}
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}
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}
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}
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}
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`,
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variables: {
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cluster: cluster,
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metrics: ["flops_any", "mem_bw"],
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from: from,
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to: to,
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},
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}));
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// Load for jobcount per node only -- might me required for total running jobs anyways in parent component!
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// Also, think about extra query with only TotalJobCount and Items [Resources, ...some meta infos], not including metric data
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const paging = { itemsPerPage: -1, page: 1 };
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const sorting = { field: "startTime", type: "col", order: "DESC" };
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const filter = [
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{ cluster: { eq: cluster } },
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{ state: ["running"] },
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];
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const nodeJobsQuery = gql`
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query (
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$filter: [JobFilter!]!
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$sorting: OrderByInput!
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$paging: PageRequest!
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) {
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jobs(filter: $filter, order: $sorting, page: $paging) {
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items {
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jobId
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resources {
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hostname
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}
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}
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count
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}
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}
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`;
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const nodesJobs = $derived(queryStore({
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client: client,
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query: nodeJobsQuery,
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variables: { paging, sorting, filter },
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})
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);
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// Last required query: Node State
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const nodesState = $derived(queryStore({
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client: client,
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query: gql`
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query (
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$filter: [NodeFilter!]
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$sorting: OrderByInput
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) {
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nodes(filter: $filter, order: $sorting) {
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count
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items {
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hostname
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cluster
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subCluster
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nodeState
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}
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}
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}
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`,
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variables: {
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filter: { cluster: { eq: cluster }},
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sorting: sorting // Unused in Backend: Use Placeholder
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// Subcluster filter?
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},
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}));
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// Accumulated NodeStates for Piecharts
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const nodesStateCounts = $derived(queryStore({
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client: client,
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query: gql`
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query ($filter: [NodeFilter!]) {
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nodeStates(filter: $filter) {
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state
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count
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}
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}
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`,
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variables: {
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filter: { cluster: { eq: cluster }}
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},
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}));
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const refinedStateData = $derived.by(() => {
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return $nodesStateCounts?.data?.nodeStates.filter((e) => ['allocated', 'reserved', 'idle', 'mixed','down', 'unknown'].includes(e.state))
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});
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const refinedHealthData = $derived.by(() => {
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return $nodesStateCounts?.data?.nodeStates.filter((e) => ['full', 'partial', 'failed'].includes(e.state))
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});
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/* Function */
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function transformJobsStatsToData(subclusterData) {
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/* c will contain values from 0 to 1 representing the duration */
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let data = null
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const x = [], y = [], c = [], day = 86400.0
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if (subclusterData) {
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for (let i = 0; i < subclusterData.length; i++) {
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const flopsData = subclusterData[i].stats.find((s) => s.name == "flops_any")
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const memBwData = subclusterData[i].stats.find((s) => s.name == "mem_bw")
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const f = flopsData.data.avg
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const m = memBwData.data.avg
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const d = subclusterData[i].duration / day
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const intensity = f / m
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if (Number.isNaN(intensity) || !Number.isFinite(intensity))
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continue
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x.push(intensity)
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y.push(f)
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// Long Jobs > 1 Day: Use max Color
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if (d > 1.0) c.push(1.0)
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else c.push(d)
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}
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} else {
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console.warn("transformJobsStatsToData: metrics for 'mem_bw' and/or 'flops_any' missing!")
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}
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if (x.length > 0 && y.length > 0 && c.length > 0) {
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data = [null, [x, y], c] // for dataformat see roofline.svelte
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}
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return data
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}
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function transformNodesStatsToData(subclusterData) {
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let data = null
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const x = [], y = []
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if (subclusterData) {
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for (let i = 0; i < subclusterData.length; i++) {
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const flopsData = subclusterData[i].metrics.find((s) => s.name == "flops_any")
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const memBwData = subclusterData[i].metrics.find((s) => s.name == "mem_bw")
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const f = flopsData.metric.series[0].statistics.avg
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const m = memBwData.metric.series[0].statistics.avg
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let intensity = f / m
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if (Number.isNaN(intensity) || !Number.isFinite(intensity)) {
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// continue // Old: Introduces mismatch between Data and Info Arrays
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intensity = 0.0 // New: Set to Float Zero: Will not show in Log-Plot (Always below render limit)
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}
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x.push(intensity)
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y.push(f)
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}
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} else {
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// console.warn("transformNodesStatsToData: metrics for 'mem_bw' and/or 'flops_any' missing!")
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}
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if (x.length > 0 && y.length > 0) {
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data = [null, [x, y]] // for dataformat see roofline.svelte
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}
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return data
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}
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function transformJobsStatsToInfo(subclusterData) {
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if (subclusterData) {
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return subclusterData.map((sc) => { return {id: sc.id, jobId: sc.jobId, numNodes: sc.numNodes, numAcc: sc?.numAccelerators? sc.numAccelerators : 0, duration: formatTime(sc.duration)} })
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} else {
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console.warn("transformJobsStatsToInfo: jobInfo missing!")
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return []
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}
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}
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function transformNodesStatsToInfo(subClusterData) {
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let result = [];
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if (subClusterData && $nodesState?.data) {
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// Use Nodes as Returned from CCMS, *NOT* as saved in DB via SlurmState-API!
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for (let j = 0; j < subClusterData.length; j++) {
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// nodesCounts[subClusterData[i].subCluster] = $nodesState.data.nodes.count; // Probably better as own derived!
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const nodeName = subClusterData[j]?.host ? subClusterData[j].host : "unknown"
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const nodeMatch = $nodesState.data.nodes.items.find((n) => n.hostname == nodeName && n.subCluster == subClusterData[j].subCluster);
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const nodeState = nodeMatch?.nodeState ? nodeMatch.nodeState : "notindb"
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let numJobs = 0
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if ($nodesJobs?.data) {
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const nodeJobs = $nodesJobs.data.jobs.items.filter((job) => job.resources.find((res) => res.hostname == nodeName))
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numJobs = nodeJobs?.length ? nodeJobs.length : 0
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}
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result.push({nodeName: nodeName, nodeState: nodeState, numJobs: numJobs})
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};
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};
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return result
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}
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function legendColors(targetIdx) {
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// Reuses first color if targetIdx overflows
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let c = [...colors['default']];
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return c[(c.length + targetIdx) % c.length];
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}
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</script>
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<!-- Gauges & Roofline per Subcluster-->
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{#if $initq.data && $jobRoofQuery.data}
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{#each $initq.data.clusters.find((c) => c.name == cluster).subClusters as subCluster, i}
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<Row cols={{ lg: 2, md: 2 , sm: 1}} class="mb-3 justify-content-center">
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<Col class="px-3 mt-2 mt-lg-0">
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<b>Bubble Node</b>
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<div bind:clientWidth={plotWidths[i]}>
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{#key $nodesData?.data?.nodeMetrics || $nodesJobs?.data?.jobs}
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<b>{subCluster.name} Total: {$jobRoofQuery.data.jobsMetricStats.filter(
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(data) => data.subCluster == subCluster.name,
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||||
).length} Jobs</b>
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<Roofline
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||||
allowSizeChange
|
||||
width={plotWidths[i] - 10}
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height={300}
|
||||
cluster={cluster}
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||||
subCluster={subCluster}
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roofData={transformNodesStatsToData($nodesData?.data?.nodeMetrics.filter(
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||||
(data) => data.subCluster == subCluster.name,
|
||||
)
|
||||
)}
|
||||
nodesData={transformNodesStatsToInfo($nodesData?.data?.nodeMetrics.filter(
|
||||
(data) => data.subCluster == subCluster.name,
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||||
)
|
||||
)}
|
||||
/>
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||||
{/key}
|
||||
</div>
|
||||
</Col>
|
||||
<Col class="px-3 mt-2 mt-lg-0">
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||||
<b>Bubble Jobs</b>
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||||
<div bind:clientWidth={plotWidths[i]}>
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||||
{#key $jobRoofQuery.data.jobsMetricStats}
|
||||
<b>{subCluster.name} Total: {$jobRoofQuery.data.jobsMetricStats.filter(
|
||||
(data) => data.subCluster == subCluster.name,
|
||||
).length} Jobs</b>
|
||||
<Roofline
|
||||
allowSizeChange
|
||||
width={plotWidths[i] - 10}
|
||||
height={300}
|
||||
subCluster={subCluster}
|
||||
roofData={transformJobsStatsToData($jobRoofQuery?.data?.jobsMetricStats.filter(
|
||||
(data) => data.subCluster == subCluster.name,
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||||
)
|
||||
)}
|
||||
jobsData={transformJobsStatsToInfo($jobRoofQuery?.data?.jobsMetricStats.filter(
|
||||
(data) => data.subCluster == subCluster.name,
|
||||
)
|
||||
)}
|
||||
/>
|
||||
{/key}
|
||||
</div>
|
||||
</Col>
|
||||
</Row>
|
||||
{/each}
|
||||
{/if}
|
||||
|
||||
<hr/>
|
||||
<hr/>
|
||||
|
||||
{#if $initq.data && $nodesStateCounts.data}
|
||||
<Row cols={{ lg: 4, md: 2 , sm: 1}} class="mb-3 justify-content-center">
|
||||
<Col class="px-3 mt-2 mt-lg-0">
|
||||
<b>Node State</b>
|
||||
<div bind:clientWidth={statesWidth}>
|
||||
{#key refinedStateData}
|
||||
<b>Total: {refinedStateData.reduce((sum, item) => {
|
||||
return sum + item.count;
|
||||
}, 0)} Nodes
|
||||
</b>
|
||||
<Pie
|
||||
canvasId="hpcpie-slurm-old"
|
||||
size={statesWidth}
|
||||
sliceLabel="Nodes"
|
||||
quantities={refinedStateData.map(
|
||||
(sd) => sd.count,
|
||||
)}
|
||||
entities={refinedStateData.map(
|
||||
(sd) => sd.state,
|
||||
)}
|
||||
/>
|
||||
{/key}
|
||||
</div>
|
||||
</Col>
|
||||
<Col class="px-4 py-2">
|
||||
{#key refinedStateData}
|
||||
<Table>
|
||||
<tr class="mb-2">
|
||||
<th>Legend</th>
|
||||
<th>Current State</th>
|
||||
<th>#Nodes</th>
|
||||
</tr>
|
||||
{#each refinedStateData as sd, i}
|
||||
<tr>
|
||||
<td><Icon name="circle-fill" style="color: {legendColors(i)};" /></td>
|
||||
<td>{sd.state}</td>
|
||||
<td>{sd.count}</td>
|
||||
</tr>
|
||||
{/each}
|
||||
</Table>
|
||||
{/key}
|
||||
</Col>
|
||||
|
||||
<Col class="px-3 mt-2 mt-lg-0">
|
||||
<b>Node Health</b>
|
||||
<div bind:clientWidth={healthWidth}>
|
||||
{#key refinedHealthData}
|
||||
<b>Total: {refinedStateData.reduce((sum, item) => {
|
||||
return sum + item.count;
|
||||
}, 0)} Nodes
|
||||
</b>
|
||||
<Pie
|
||||
canvasId="hpcpie-health-old"
|
||||
size={healthWidth}
|
||||
sliceLabel="Nodes"
|
||||
quantities={refinedHealthData.map(
|
||||
(sd) => sd.count,
|
||||
)}
|
||||
entities={refinedHealthData.map(
|
||||
(sd) => sd.state,
|
||||
)}
|
||||
/>
|
||||
{/key}
|
||||
</div>
|
||||
</Col>
|
||||
<Col class="px-4 py-2">
|
||||
{#key refinedHealthData}
|
||||
<Table>
|
||||
<tr class="mb-2">
|
||||
<th>Legend</th>
|
||||
<th>Current Health</th>
|
||||
<th>#Nodes</th>
|
||||
</tr>
|
||||
{#each refinedHealthData as hd, i}
|
||||
<tr>
|
||||
<td><Icon name="circle-fill" style="color: {legendColors(i)};" /></td>
|
||||
<td>{hd.state}</td>
|
||||
<td>{hd.count}</td>
|
||||
</tr>
|
||||
{/each}
|
||||
</Table>
|
||||
{/key}
|
||||
</Col>
|
||||
</Row>
|
||||
{/if}
|
||||
@@ -1,127 +0,0 @@
|
||||
<!--
|
||||
@component Main cluster status view component; renders current system-usage information
|
||||
|
||||
Properties:
|
||||
- `cluster String`: The cluster to show status information for
|
||||
-->
|
||||
|
||||
<script>
|
||||
import {
|
||||
Row,
|
||||
Col,
|
||||
} from "@sveltestrap/sveltestrap";
|
||||
import {
|
||||
queryStore,
|
||||
gql,
|
||||
getContextClient,
|
||||
} from "@urql/svelte";
|
||||
import {
|
||||
init,
|
||||
convert2uplot,
|
||||
} from "../generic/utils.js";
|
||||
import Histogram from "../generic/plots/Histogram.svelte";
|
||||
|
||||
/* Svelte 5 Props */
|
||||
let {
|
||||
cluster
|
||||
} = $props();
|
||||
|
||||
/* Const Init */
|
||||
const { query: initq } = init();
|
||||
const client = getContextClient();
|
||||
|
||||
/* Derived */
|
||||
// Note: nodeMetrics are requested on configured $timestep resolution
|
||||
const nodeStatusQuery = $derived(queryStore({
|
||||
client: client,
|
||||
query: gql`
|
||||
query (
|
||||
$filter: [JobFilter!]!
|
||||
$selectedHistograms: [String!]
|
||||
) {
|
||||
jobsStatistics(filter: $filter, metrics: $selectedHistograms) {
|
||||
histDuration {
|
||||
count
|
||||
value
|
||||
}
|
||||
histNumNodes {
|
||||
count
|
||||
value
|
||||
}
|
||||
histNumCores {
|
||||
count
|
||||
value
|
||||
}
|
||||
histNumAccs {
|
||||
count
|
||||
value
|
||||
}
|
||||
}
|
||||
}
|
||||
`,
|
||||
variables: {
|
||||
filter: [{ state: ["running"] }, { cluster: { eq: cluster } }],
|
||||
selectedHistograms: [], // No Metrics requested for node hardware stats
|
||||
},
|
||||
}));
|
||||
</script>
|
||||
|
||||
{#if $initq.data && $nodeStatusQuery.data}
|
||||
<!-- Static Stats as Histograms : Running Duration && Allocated Hardware Counts-->
|
||||
<Row cols={{ lg: 2, md: 1 }}>
|
||||
<Col class="p-2">
|
||||
{#key $nodeStatusQuery.data.jobsStatistics}
|
||||
<Histogram
|
||||
data={convert2uplot($nodeStatusQuery.data.jobsStatistics[0].histDuration)}
|
||||
title="Duration Distribution"
|
||||
xlabel="Current Job Runtimes"
|
||||
xunit="Runtime"
|
||||
ylabel="Number of Jobs"
|
||||
yunit="Jobs"
|
||||
usesBins
|
||||
xtime
|
||||
/>
|
||||
{/key}
|
||||
</Col>
|
||||
<Col class="p-2">
|
||||
{#key $nodeStatusQuery.data.jobsStatistics}
|
||||
<Histogram
|
||||
data={convert2uplot($nodeStatusQuery.data.jobsStatistics[0].histNumNodes)}
|
||||
title="Number of Nodes Distribution"
|
||||
xlabel="Allocated Nodes"
|
||||
xunit="Nodes"
|
||||
ylabel="Number of Jobs"
|
||||
yunit="Jobs"
|
||||
/>
|
||||
{/key}
|
||||
</Col>
|
||||
</Row>
|
||||
<Row cols={{ lg: 2, md: 1 }}>
|
||||
<Col class="p-2">
|
||||
{#key $nodeStatusQuery.data.jobsStatistics}
|
||||
<Histogram
|
||||
data={convert2uplot($nodeStatusQuery.data.jobsStatistics[0].histNumCores)}
|
||||
title="Number of Cores Distribution"
|
||||
xlabel="Allocated Cores"
|
||||
xunit="Cores"
|
||||
ylabel="Number of Jobs"
|
||||
yunit="Jobs"
|
||||
/>
|
||||
{/key}
|
||||
</Col>
|
||||
<Col class="p-2">
|
||||
{#key $nodeStatusQuery.data.jobsStatistics}
|
||||
<Histogram
|
||||
data={convert2uplot($nodeStatusQuery.data.jobsStatistics[0].histNumAccs)}
|
||||
title="Number of Accelerators Distribution"
|
||||
xlabel="Allocated Accs"
|
||||
xunit="Accs"
|
||||
ylabel="Number of Jobs"
|
||||
yunit="Jobs"
|
||||
/>
|
||||
{/key}
|
||||
</Col>
|
||||
</Row>
|
||||
{/if}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user