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Filename :
MetricTankMetaInspector.tsx
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import { css, cx } from '@emotion/css'; import React, { PureComponent } from 'react'; import { MetadataInspectorProps, rangeUtil } from '@grafana/data'; import { stylesFactory } from '@grafana/ui'; import { config } from 'app/core/config'; import { GraphiteDatasource } from '../datasource'; import { getRollupNotice, getRuntimeConsolidationNotice, parseSchemaRetentions } from '../meta'; import { GraphiteOptions, GraphiteQuery, MetricTankSeriesMeta } from '../types'; export type Props = MetadataInspectorProps<GraphiteDatasource, GraphiteQuery, GraphiteOptions>; export interface State { index: number; } export class MetricTankMetaInspector extends PureComponent<Props, State> { renderMeta(meta: MetricTankSeriesMeta, key: string) { const styles = getStyles(); const buckets = parseSchemaRetentions(meta['schema-retentions']); const rollupNotice = getRollupNotice([meta]); const runtimeNotice = getRuntimeConsolidationNotice([meta]); const normFunc = (meta['consolidator-normfetch'] ?? '').replace('Consolidator', ''); const totalSeconds = buckets.reduce( (acc, bucket) => acc + (bucket.retention ? rangeUtil.intervalToSeconds(bucket.retention) : 0), 0 ); return ( <div className={styles.metaItem} key={key}> <div className={styles.metaItemHeader}> Schema: {meta['schema-name']} <div className="small muted">Series count: {meta.count}</div> </div> <div className={styles.metaItemBody}> <div className={styles.step}> <div className={styles.stepHeading}>Step 1: Fetch</div> <div className={styles.stepDescription}> First data is fetched, either from raw data archive or a rollup archive </div> {rollupNotice && <p>{rollupNotice.text}</p>} {!rollupNotice && <p>No rollup archive was used</p>} <div> {buckets.map((bucket, index) => { const bucketLength = bucket.retention ? rangeUtil.intervalToSeconds(bucket.retention) : 0; const lengthPercent = (bucketLength / totalSeconds) * 100; const isActive = index === meta['archive-read']; return ( <div key={bucket.retention} className={styles.bucket}> <div className={styles.bucketInterval}>{bucket.interval}</div> <div className={cx(styles.bucketRetention, { [styles.bucketRetentionActive]: isActive })} style={{ flexGrow: lengthPercent }} /> <div style={{ flexGrow: 100 - lengthPercent }}>{bucket.retention}</div> </div> ); })} </div> </div> <div className={styles.step}> <div className={styles.stepHeading}>Step 2: Normalization</div> <div className={styles.stepDescription}> Normalization happens when series with different intervals between points are combined. </div> {meta['aggnum-norm'] > 1 && <p>Normalization did occur using {normFunc}</p>} {meta['aggnum-norm'] === 1 && <p>No normalization was needed</p>} </div> <div className={styles.step}> <div className={styles.stepHeading}>Step 3: Runtime consolidation</div> <div className={styles.stepDescription}> If there are too many data points at this point Metrictank will consolidate them down to below max data points (set in queries tab). </div> {runtimeNotice && <p>{runtimeNotice.text}</p>} {!runtimeNotice && <p>No runtime consolidation</p>} </div> </div> </div> ); } render() { const { data } = this.props; // away to dedupe them const seriesMetas: Record<string, MetricTankSeriesMeta> = {}; for (const series of data) { if (series?.meta?.custom?.seriesMetaList) { for (const metaItem of series.meta.custom.seriesMetaList as MetricTankSeriesMeta[]) { // key is to dedupe as many series will have identitical meta const key = `${JSON.stringify(metaItem)}`; if (seriesMetas[key]) { seriesMetas[key].count += metaItem.count; } else { seriesMetas[key] = metaItem; } } } } if (Object.keys(seriesMetas).length === 0) { return <div>No response meta data</div>; } return ( <div> <h2 className="page-heading">Metrictank Lineage</h2> {Object.keys(seriesMetas).map((key) => this.renderMeta(seriesMetas[key], key))} </div> ); } } const getStyles = stylesFactory(() => { const { theme } = config; const borderColor = theme.isDark ? theme.palette.gray25 : theme.palette.gray85; const background = theme.isDark ? theme.palette.dark1 : theme.palette.white; const headerBg = theme.isDark ? theme.palette.gray15 : theme.palette.gray85; return { metaItem: css` background: ${background}; border: 1px solid ${borderColor}; margin-bottom: ${theme.spacing.md}; `, metaItemHeader: css` background: ${headerBg}; padding: ${theme.spacing.xs} ${theme.spacing.md}; font-size: ${theme.typography.size.md}; display: flex; justify-content: space-between; `, metaItemBody: css` padding: ${theme.spacing.md}; `, stepHeading: css` font-size: ${theme.typography.size.md}; `, stepDescription: css` font-size: ${theme.typography.size.sm}; color: ${theme.colors.textWeak}; margin-bottom: ${theme.spacing.sm}; `, step: css` margin-bottom: ${theme.spacing.lg}; &:last-child { margin-bottom: 0; } `, bucket: css` display: flex; margin-bottom: ${theme.spacing.sm}; border-radius: ${theme.border.radius.sm}; `, bucketInterval: css` flex-grow: 0; width: 60px; `, bucketRetention: css` background: linear-gradient(0deg, ${theme.palette.blue85}, ${theme.palette.blue95}); text-align: center; color: ${theme.palette.white}; margin-right: ${theme.spacing.md}; border-radius: ${theme.border.radius.sm}; `, bucketRetentionActive: css` background: linear-gradient(0deg, ${theme.palette.greenBase}, ${theme.palette.greenShade}); `, }; });