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/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
import React, { useMemo } from 'react';
import PropTypes from 'prop-types';
import Mustache from 'mustache';
import { scaleLinear } from 'd3-scale';
import TableView from 'src/components/TableView';
import { formatNumber, formatTime, styled } from '@superset-ui/core';
import {
InfoTooltipWithTrigger,
MetricOption,
} from '@superset-ui/chart-controls';
import moment from 'moment';
import FormattedNumber from './FormattedNumber';
import SparklineCell from './SparklineCell';
import './TimeTable.less';
const ACCESSIBLE_COLOR_BOUNDS = ['#ca0020', '#0571b0'];
function colorFromBounds(value, bounds, colorBounds = ACCESSIBLE_COLOR_BOUNDS) {
if (bounds) {
const [min, max] = bounds;
const [minColor, maxColor] = colorBounds;
if (min !== null && max !== null) {
const colorScale = scaleLinear()
.domain([min, (max + min) / 2, max])
.range([minColor, 'grey', maxColor]);
return colorScale(value);
}
if (min !== null) {
return value >= min ? maxColor : minColor;
}
if (max !== null) {
return value < max ? maxColor : minColor;
}
}
return null;
}
const propTypes = {
className: PropTypes.string,
height: PropTypes.number,
// Example
// {'2018-04-14 00:00:00': { 'SUM(metric_value)': 80031779.40047 }}
data: PropTypes.objectOf(PropTypes.objectOf(PropTypes.number)).isRequired,
columnConfigs: PropTypes.arrayOf(
PropTypes.shape({
colType: PropTypes.string,
comparisonType: PropTypes.string,
d3format: PropTypes.string,
key: PropTypes.string,
label: PropTypes.string,
timeLag: PropTypes.number,
}),
).isRequired,
rows: PropTypes.arrayOf(
PropTypes.oneOfType([
PropTypes.shape({
label: PropTypes.string,
}),
PropTypes.shape({
metric_name: PropTypes.string,
}),
]),
).isRequired,
rowType: PropTypes.oneOf(['column', 'metric']).isRequired,
url: PropTypes.string,
};
const defaultProps = {
className: '',
height: undefined,
url: '',
};
const TimeTableStyles = styled.div`
height: ${props => props.height}px;
th {
z-index: 1; // to cover sparkline
}
`;
const TimeTable = ({
className,
height,
data,
columnConfigs,
rowType,
rows,
url,
}) => {
const memoizedColumns = useMemo(
() => [
{ accessor: 'metric', Header: 'Metric' },
...columnConfigs.map((columnConfig, i) => ({
accessor: columnConfig.key,
cellProps: columnConfig.colType === 'spark' && {
style: { width: '1%' },
},
Header: () => (
<>
{columnConfig.label}{' '}
{columnConfig.tooltip && (
<InfoTooltipWithTrigger
tooltip={columnConfig.tooltip}
label={`tt-col-${i}`}
placement="top"
/>
)}
</>
),
sortType: (rowA, rowB, columnId) => {
const rowAVal = rowA.values[columnId].props['data-value'];
const rowBVal = rowB.values[columnId].props['data-value'];
return rowAVal - rowBVal;
},
})),
],
[columnConfigs],
);
const memoizedRows = useMemo(() => {
const renderSparklineCell = (valueField, column, entries) => {
let sparkData;
if (column.timeRatio) {
// Period ratio sparkline
sparkData = [];
for (let i = column.timeRatio; i < entries.length; i += 1) {
const prevData = entries[i - column.timeRatio][valueField];
if (prevData && prevData !== 0) {
sparkData.push(entries[i][valueField] / prevData);
} else {
sparkData.push(null);
}
}
} else {
sparkData = entries.map(d => d[valueField]);
}
return (
<SparklineCell
width={parseInt(column.width, 10) || 300}
height={parseInt(column.height, 10) || 50}
data={sparkData}
data-value={sparkData[sparkData.length - 1]}
ariaLabel={`spark-${valueField}`}
numberFormat={column.d3format}
yAxisBounds={column.yAxisBounds}
showYAxis={column.showYAxis}
renderTooltip={({ index }) => (
<div>
<strong>{formatNumber(column.d3format, sparkData[index])}</strong>
<div>
{formatTime(
column.dateFormat,
moment.utc(entries[index].time).toDate(),
)}
</div>
</div>
)}
/>
);
};
const renderValueCell = (valueField, column, reversedEntries) => {
const recent = reversedEntries[0][valueField];
let v;
let errorMsg;
if (column.colType === 'time') {
// Time lag ratio
const timeLag = column.timeLag || 0;
const totalLag = Object.keys(reversedEntries).length;
if (timeLag >= totalLag) {
errorMsg = `The time lag set at ${timeLag} is too large for the length of data at ${reversedEntries.length}. No data available.`;
} else {
v = reversedEntries[timeLag][valueField];
}
if (column.comparisonType === 'diff') {
v = recent - v;
} else if (column.comparisonType === 'perc') {
v = recent / v;
} else if (column.comparisonType === 'perc_change') {
v = recent / v - 1;
}
v = v || 0;
} else if (column.colType === 'contrib') {
// contribution to column total
v =
recent /
Object.keys(reversedEntries[0])
.map(k => (k !== 'time' ? reversedEntries[0][k] : null))
.reduce((a, b) => a + b);
} else if (column.colType === 'avg') {
// Average over the last {timeLag}
v =
reversedEntries
.map((k, i) => (i < column.timeLag ? k[valueField] : 0))
.reduce((a, b) => a + b) / column.timeLag;
}
const color = colorFromBounds(v, column.bounds);
return (
<span
key={column.key}
data-value={v}
style={
color && {
boxShadow: `inset 0px -2.5px 0px 0px ${color}`,
borderRight: '2px solid #fff',
}
}
>
{errorMsg || (
<span style={{ color }}>
<FormattedNumber num={v} format={column.d3format} />
</span>
)}
</span>
);
};
const renderLeftCell = row => {
const context = { metric: row };
const fullUrl = url ? Mustache.render(url, context) : null;
if (rowType === 'column') {
const column = row;
if (fullUrl) {
return (
<a href={fullUrl} rel="noopener noreferrer" target="_blank">
{column.label}
</a>
);
}
return column.label;
}
return (
<MetricOption
metric={row}
url={fullUrl}
showFormula={false}
openInNewWindow
/>
);
};
const entries = Object.keys(data)
.sort()
.map(time => ({ ...data[time], time }));
const reversedEntries = entries.concat().reverse();
return rows.map(row => {
const valueField = row.label || row.metric_name;
const cellValues = columnConfigs.reduce((acc, columnConfig) => {
if (columnConfig.colType === 'spark') {
return {
...acc,
[columnConfig.key]: renderSparklineCell(
valueField,
columnConfig,
entries,
),
};
}
return {
...acc,
[columnConfig.key]: renderValueCell(
valueField,
columnConfig,
reversedEntries,
),
};
}, {});
return { ...row, ...cellValues, metric: renderLeftCell(row) };
});
}, [columnConfigs, data, rowType, rows, url]);
const defaultSort =
rowType === 'column' && columnConfigs.length
? [
{
id: columnConfigs[0].key,
desc: 'true',
},
]
: [];
return (
<TimeTableStyles className={`time-table ${className}`} height={height}>
<TableView
className="table-no-hover"
columns={memoizedColumns}
data={memoizedRows}
initialSortBy={defaultSort}
withPagination={false}
/>
</TimeTableStyles>
);
};
TimeTable.propTypes = propTypes;
TimeTable.defaultProps = defaultProps;
export default TimeTable;