mirror of
https://github.com/hyperdxio/hyperdx
synced 2026-04-21 13:37:15 +00:00
fix: update sum metric query based on v1 integration test (#650)
Fix the sum query to produce the correct results from the min/max test case from v1. Ref: HDX-1421
This commit is contained in:
Dan Hable
GitHub
parent
7f1a5a0b09
commit
99b60d50b2
6 changed files with 251 additions and 97 deletions
6
.changeset/silent-dolphins-call.md
Normal file
6
.changeset/silent-dolphins-call.md
Normal file
|
|
@ -0,0 +1,6 @@
|
|||
---
|
||||
"@hyperdx/common-utils": patch
|
||||
"@hyperdx/api": patch
|
||||
---
|
||||
|
||||
Fixed sum metric query to pass integration test case from v1.
|
||||
|
|
@ -21,15 +21,41 @@ Array [
|
|||
]
|
||||
`;
|
||||
|
||||
exports[`renderChartConfig Query Metrics calculates min_rate/max_rate correctly for sum metrics: maxSum 1`] = `
|
||||
Array [
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:00:00Z",
|
||||
"max(toFloat64OrNull(toString(Value)))": 24,
|
||||
},
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:10:00Z",
|
||||
"max(toFloat64OrNull(toString(Value)))": 134,
|
||||
},
|
||||
]
|
||||
`;
|
||||
|
||||
exports[`renderChartConfig Query Metrics calculates min_rate/max_rate correctly for sum metrics: minSum 1`] = `
|
||||
Array [
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:00:00Z",
|
||||
"min(toFloat64OrNull(toString(Value)))": 15,
|
||||
},
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:10:00Z",
|
||||
"min(toFloat64OrNull(toString(Value)))": 52,
|
||||
},
|
||||
]
|
||||
`;
|
||||
|
||||
exports[`renderChartConfig Query Metrics handles counter resets correctly for sum metrics 1`] = `
|
||||
Array [
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:00:00Z",
|
||||
"sum(toFloat64OrNull(toString(Rate)))": 15,
|
||||
"sum(toFloat64OrNull(toString(Value)))": 15,
|
||||
},
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:10:00Z",
|
||||
"sum(toFloat64OrNull(toString(Rate)))": 52,
|
||||
"sum(toFloat64OrNull(toString(Value)))": 52,
|
||||
},
|
||||
]
|
||||
`;
|
||||
|
|
@ -115,19 +141,19 @@ exports[`renderChartConfig Query Metrics single sum rate 1`] = `
|
|||
Array [
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:00:00Z",
|
||||
"sum(toFloat64OrNull(toString(Rate)))": 19,
|
||||
"sum(toFloat64OrNull(toString(Value)))": 19,
|
||||
},
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:05:00Z",
|
||||
"sum(toFloat64OrNull(toString(Rate)))": 79,
|
||||
"sum(toFloat64OrNull(toString(Value)))": 79,
|
||||
},
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:10:00Z",
|
||||
"sum(toFloat64OrNull(toString(Rate)))": 5813,
|
||||
"sum(toFloat64OrNull(toString(Value)))": 5813,
|
||||
},
|
||||
Object {
|
||||
"__hdx_time_bucket": "2022-01-05T00:15:00Z",
|
||||
"sum(toFloat64OrNull(toString(Rate)))": 78754,
|
||||
"sum(toFloat64OrNull(toString(Value)))": 78754,
|
||||
},
|
||||
]
|
||||
`;
|
||||
|
|
|
|||
|
|
@ -532,12 +532,23 @@ describe('renderChartConfig', () => {
|
|||
expect(await queryData(query)).toMatchSnapshot();
|
||||
});
|
||||
|
||||
// FIXME: here are the expected values
|
||||
// [0, 1, 8, 8, 15, 15, 23, 25, 25, 67]
|
||||
// [0, 2, 9, 9, 24, 34, 44, 66, 66, 158]
|
||||
// min -> [15, 52]
|
||||
// max -> [24, 134]
|
||||
it.skip('calculates min_rate/max_rate correctly for sum metrics', async () => {
|
||||
it('calculates min_rate/max_rate correctly for sum metrics', async () => {
|
||||
// Based on the data inserted in the fixture, the expected stream of values
|
||||
// for each series after adjusting for the zero reset should be:
|
||||
// MIN_VARIANT_0: [0, 1, 8, 8, 15, 15, 23, 25, 25, 67]
|
||||
// MIN_VARIANT_1: [0, 2, 9, 9, 24, 34, 44, 66, 66, 158]
|
||||
//
|
||||
// At the 10 minute buckets, should result in three buckets for each where
|
||||
// the first bucket is outside the query window.
|
||||
// MIN_VARIANT_0: [0], [1, 8, 8, 15], [15, 23, 25, 25, 67]]
|
||||
// MIN_VARIANT_1: [0], [2, 9, 9, 24], [34, 44, 66, 66, 158]]
|
||||
//
|
||||
// When comparing the value at the end of the buckets over the filtered
|
||||
// time frame it should result in the following counts added per bucket as:
|
||||
// MIN_VARIANT_0: [15, 52]
|
||||
// MIN_VARIANT_1: [24, 134]
|
||||
//
|
||||
// These values are what we apply the aggregation functions to.
|
||||
const minQuery = await renderChartConfig(
|
||||
{
|
||||
select: [
|
||||
|
|
@ -562,6 +573,7 @@ describe('renderChartConfig', () => {
|
|||
},
|
||||
metadata,
|
||||
);
|
||||
expect(await queryData(minQuery)).toMatchSnapshot('minSum');
|
||||
|
||||
const maxQuery = await renderChartConfig(
|
||||
{
|
||||
|
|
@ -587,6 +599,7 @@ describe('renderChartConfig', () => {
|
|||
},
|
||||
metadata,
|
||||
);
|
||||
expect(await queryData(maxQuery)).toMatchSnapshot('maxSum');
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -27,3 +27,78 @@ exports[`renderChartConfig should generate sql for a single gauge metric 1`] = `
|
|||
TO toUnixTimestamp(toStartOfInterval(fromUnixTimestamp64Milli(1765670400000), INTERVAL 1 minute))
|
||||
STEP 60 LIMIT 10"
|
||||
`;
|
||||
|
||||
exports[`renderChartConfig should generate sql for a single histogram metric 1`] = `
|
||||
"WITH HistRate AS (SELECT *, any(BucketCounts) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevBucketCounts,
|
||||
any(CountLength) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevCountLength,
|
||||
any(AttributesHash) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevAttributesHash,
|
||||
IF(AggregationTemporality = 1,
|
||||
BucketCounts,
|
||||
IF(AttributesHash = PrevAttributesHash AND CountLength = PrevCountLength,
|
||||
arrayMap((prev, curr) -> IF(curr < prev, curr, toUInt64(toInt64(curr) - toInt64(prev))), PrevBucketCounts, BucketCounts),
|
||||
BucketCounts)) as BucketRates
|
||||
FROM (
|
||||
SELECT *, cityHash64(mapConcat(ScopeAttributes, ResourceAttributes, Attributes)) AS AttributesHash,
|
||||
length(BucketCounts) as CountLength
|
||||
FROM default.otel_metrics_histogram)
|
||||
WHERE MetricName = 'http.server.duration'
|
||||
ORDER BY Attributes, TimeUnix ASC
|
||||
),RawHist AS (
|
||||
SELECT *, toUInt64( 0.5 * arraySum(BucketRates)) AS Rank,
|
||||
arrayCumSum(BucketRates) as CumRates,
|
||||
arrayFirstIndex(x -> if(x > Rank, 1, 0), CumRates) AS BucketLowIdx,
|
||||
IF(BucketLowIdx = length(BucketRates),
|
||||
ExplicitBounds[length(ExplicitBounds)], -- if the low bound is the last bucket, use the last bound value
|
||||
IF(BucketLowIdx > 1, -- indexes are 1-based
|
||||
ExplicitBounds[BucketLowIdx] + (ExplicitBounds[BucketLowIdx + 1] - ExplicitBounds[BucketLowIdx]) *
|
||||
intDivOrZero(
|
||||
Rank - CumRates[BucketLowIdx - 1],
|
||||
CumRates[BucketLowIdx] - CumRates[BucketLowIdx - 1]),
|
||||
arrayElement(ExplicitBounds, BucketLowIdx + 1) * intDivOrZero(Rank, CumRates[BucketLowIdx]))) as Rate
|
||||
FROM HistRate) SELECT sum(
|
||||
toFloat64OrNull(toString(Rate))
|
||||
) FROM RawHist WHERE (TimeUnix >= fromUnixTimestamp64Milli(1739318400000) AND TimeUnix <= fromUnixTimestamp64Milli(1765670400000)) LIMIT 10"
|
||||
`;
|
||||
|
||||
exports[`renderChartConfig should generate sql for a single sum metric 1`] = `
|
||||
"WITH Source AS (
|
||||
SELECT
|
||||
*,
|
||||
cityHash64(mapConcat(ScopeAttributes, ResourceAttributes, Attributes)) AS AttributesHash,
|
||||
IF(AggregationTemporality = 1,
|
||||
SUM(Value) OVER (PARTITION BY AttributesHash ORDER BY AttributesHash, TimeUnix ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW),
|
||||
deltaSum(Value) OVER (PARTITION BY AttributesHash ORDER BY AttributesHash, TimeUnix ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
|
||||
) AS Value
|
||||
FROM default.otel_metrics_sum
|
||||
WHERE (TimeUnix >= toStartOfInterval(fromUnixTimestamp64Milli(1739318400000), INTERVAL 5 minute) - INTERVAL 5 minute AND TimeUnix <= toStartOfInterval(fromUnixTimestamp64Milli(1765670400000), INTERVAL 5 minute) + INTERVAL 5 minute) AND ((MetricName = 'db.client.connections.usage'))),Bucketed AS (
|
||||
SELECT
|
||||
toStartOfInterval(toDateTime(TimeUnix), INTERVAL 5 minute) AS \`__hdx_time_bucket2\`,
|
||||
AttributesHash,
|
||||
last_value(Source.Value) AS \`__hdx_value_high\`,
|
||||
any(\`__hdx_value_high\`) OVER(PARTITION BY AttributesHash ORDER BY \`__hdx_time_bucket2\` ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS \`__hdx_value_high_prev\`,
|
||||
\`__hdx_value_high\` - \`__hdx_value_high_prev\` AS Value,
|
||||
any(ResourceAttributes) AS ResourceAttributes,
|
||||
any(ResourceSchemaUrl) AS ResourceSchemaUrl,
|
||||
any(ScopeName) AS ScopeName,
|
||||
any(ScopeVersion) AS ScopeVersion,
|
||||
any(ScopeAttributes) AS ScopeAttributes,
|
||||
any(ScopeDroppedAttrCount) AS ScopeDroppedAttrCount,
|
||||
any(ScopeSchemaUrl) AS ScopeSchemaUrl,
|
||||
any(ServiceName) AS ServiceName,
|
||||
any(MetricName) AS MetricName,
|
||||
any(MetricDescription) AS MetricDescription,
|
||||
any(MetricUnit) AS MetricUnit,
|
||||
any(Attributes) AS Attributes,
|
||||
any(StartTimeUnix) AS StartTimeUnix,
|
||||
any(Flags) AS Flags,
|
||||
any(AggregationTemporality) AS AggregationTemporality,
|
||||
any(IsMonotonic) AS IsMonotonic
|
||||
FROM Source
|
||||
GROUP BY AttributesHash, \`__hdx_time_bucket2\`
|
||||
ORDER BY AttributesHash, \`__hdx_time_bucket2\`
|
||||
) SELECT avg(
|
||||
toFloat64OrNull(toString(Value))
|
||||
),toStartOfInterval(toDateTime(\`__hdx_time_bucket2\`), INTERVAL 5 minute) AS \`__hdx_time_bucket\` FROM Bucketed WHERE (\`__hdx_time_bucket2\` >= fromUnixTimestamp64Milli(1739318400000) AND \`__hdx_time_bucket2\` <= fromUnixTimestamp64Milli(1765670400000)) GROUP BY toStartOfInterval(toDateTime(\`__hdx_time_bucket2\`), INTERVAL 5 minute) AS \`__hdx_time_bucket\` ORDER BY toStartOfInterval(toDateTime(\`__hdx_time_bucket2\`), INTERVAL 5 minute) AS \`__hdx_time_bucket\` WITH FILL FROM toUnixTimestamp(toStartOfInterval(fromUnixTimestamp64Milli(1739318400000), INTERVAL 5 minute))
|
||||
TO toUnixTimestamp(toStartOfInterval(fromUnixTimestamp64Milli(1765670400000), INTERVAL 5 minute))
|
||||
STEP 300 LIMIT 10"
|
||||
`;
|
||||
|
|
|
|||
|
|
@ -94,29 +94,33 @@ describe('renderChartConfig', () => {
|
|||
|
||||
const generatedSql = await renderChartConfig(config, mockMetadata);
|
||||
const actual = parameterizedQueryToSql(generatedSql);
|
||||
expect(actual).toBe(
|
||||
'WITH RawSum AS (SELECT *,\n' +
|
||||
' any(Value) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevValue,\n' +
|
||||
' any(AttributesHash) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevAttributesHash,\n' +
|
||||
' IF(AggregationTemporality = 1,\n' +
|
||||
' Value,IF(Value - PrevValue < 0 AND AttributesHash = PrevAttributesHash, Value,\n' +
|
||||
' IF(AttributesHash != PrevAttributesHash, 0, Value - PrevValue))) as Rate\n' +
|
||||
' FROM (\n' +
|
||||
' SELECT *, \n' +
|
||||
' cityHash64(mapConcat(ScopeAttributes, ResourceAttributes, Attributes)) AS AttributesHash\n' +
|
||||
' FROM default.otel_metrics_sum\n' +
|
||||
" WHERE MetricName = 'db.client.connections.usage'\n" +
|
||||
' ORDER BY AttributesHash, TimeUnix ASC\n' +
|
||||
' ) ) SELECT avg(\n' +
|
||||
' toFloat64OrNull(toString(Rate))\n' +
|
||||
' ),toStartOfInterval(toDateTime(TimeUnix), INTERVAL 5 minute) AS `__hdx_time_bucket`' +
|
||||
' FROM RawSum WHERE (TimeUnix >= fromUnixTimestamp64Milli(1739318400000) AND TimeUnix <= fromUnixTimestamp64Milli(1765670400000))' +
|
||||
' GROUP BY toStartOfInterval(toDateTime(TimeUnix), INTERVAL 5 minute) AS `__hdx_time_bucket`' +
|
||||
' ORDER BY toStartOfInterval(toDateTime(TimeUnix), INTERVAL 5 minute) AS `__hdx_time_bucket`' +
|
||||
' WITH FILL FROM toUnixTimestamp(toStartOfInterval(fromUnixTimestamp64Milli(1739318400000), INTERVAL 5 minute))\n' +
|
||||
' TO toUnixTimestamp(toStartOfInterval(fromUnixTimestamp64Milli(1765670400000), INTERVAL 5 minute))\n' +
|
||||
' STEP 300' +
|
||||
' LIMIT 10',
|
||||
expect(actual).toMatchSnapshot();
|
||||
});
|
||||
|
||||
it('should throw error for string select on sum metric', async () => {
|
||||
const config: ChartConfigWithOptDateRange = {
|
||||
displayType: DisplayType.Line,
|
||||
connection: 'test-connection',
|
||||
metricTables: {
|
||||
gauge: 'otel_metrics_gauge',
|
||||
histogram: 'otel_metrics_histogram',
|
||||
sum: 'otel_metrics_sum',
|
||||
},
|
||||
from: {
|
||||
databaseName: 'default',
|
||||
tableName: '',
|
||||
},
|
||||
select: 'Value',
|
||||
where: '',
|
||||
whereLanguage: 'sql',
|
||||
timestampValueExpression: 'TimeUnix',
|
||||
dateRange: [new Date('2025-02-12'), new Date('2025-12-14')],
|
||||
granularity: '5 minute',
|
||||
limit: { limit: 10 },
|
||||
};
|
||||
|
||||
await expect(renderChartConfig(config, mockMetadata)).rejects.toThrow(
|
||||
'multi select or string select on metrics not supported',
|
||||
);
|
||||
});
|
||||
|
||||
|
|
@ -152,39 +156,6 @@ describe('renderChartConfig', () => {
|
|||
|
||||
const generatedSql = await renderChartConfig(config, mockMetadata);
|
||||
const actual = parameterizedQueryToSql(generatedSql);
|
||||
expect(actual).toBe(
|
||||
'WITH HistRate AS (SELECT *, any(BucketCounts) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevBucketCounts,\n' +
|
||||
' any(CountLength) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevCountLength,\n' +
|
||||
' any(AttributesHash) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevAttributesHash,\n' +
|
||||
' IF(AggregationTemporality = 1,\n' +
|
||||
' BucketCounts,\n' +
|
||||
' IF(AttributesHash = PrevAttributesHash AND CountLength = PrevCountLength,\n' +
|
||||
' arrayMap((prev, curr) -> IF(curr < prev, curr, toUInt64(toInt64(curr) - toInt64(prev))), PrevBucketCounts, BucketCounts),\n' +
|
||||
' BucketCounts)) as BucketRates\n' +
|
||||
' FROM (\n' +
|
||||
' SELECT *, cityHash64(mapConcat(ScopeAttributes, ResourceAttributes, Attributes)) AS AttributesHash,\n' +
|
||||
' length(BucketCounts) as CountLength\n' +
|
||||
' FROM default.otel_metrics_histogram)\n' +
|
||||
" WHERE MetricName = 'http.server.duration'\n " +
|
||||
' ORDER BY Attributes, TimeUnix ASC\n' +
|
||||
' ),RawHist AS (\n' +
|
||||
' SELECT *, toUInt64( 0.5 * arraySum(BucketRates)) AS Rank,\n' +
|
||||
' arrayCumSum(BucketRates) as CumRates,\n' +
|
||||
' arrayFirstIndex(x -> if(x > Rank, 1, 0), CumRates) AS BucketLowIdx,\n' +
|
||||
' IF(BucketLowIdx = length(BucketRates),\n' +
|
||||
' ExplicitBounds[length(ExplicitBounds)], -- if the low bound is the last bucket, use the last bound value\n' +
|
||||
' IF(BucketLowIdx > 1, -- indexes are 1-based\n' +
|
||||
' ExplicitBounds[BucketLowIdx] + (ExplicitBounds[BucketLowIdx + 1] - ExplicitBounds[BucketLowIdx]) *\n' +
|
||||
' intDivOrZero(\n' +
|
||||
' Rank - CumRates[BucketLowIdx - 1],\n' +
|
||||
' CumRates[BucketLowIdx] - CumRates[BucketLowIdx - 1]),\n' +
|
||||
' arrayElement(ExplicitBounds, BucketLowIdx + 1) * intDivOrZero(Rank, CumRates[BucketLowIdx]))) as Rate\n' +
|
||||
' FROM HistRate) SELECT sum(\n' +
|
||||
' toFloat64OrNull(toString(Rate))\n' +
|
||||
' )' +
|
||||
' FROM RawHist' +
|
||||
' WHERE (TimeUnix >= fromUnixTimestamp64Milli(1739318400000) AND TimeUnix <= fromUnixTimestamp64Milli(1765670400000))' +
|
||||
' LIMIT 10',
|
||||
);
|
||||
expect(actual).toMatchSnapshot();
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -407,6 +407,7 @@ async function timeFilterExpr({
|
|||
metadata,
|
||||
connectionId,
|
||||
with: withClauses,
|
||||
includedDataInterval,
|
||||
}: {
|
||||
timestampValueExpression: string;
|
||||
dateRange: [Date, Date];
|
||||
|
|
@ -416,6 +417,7 @@ async function timeFilterExpr({
|
|||
databaseName: string;
|
||||
tableName: string;
|
||||
with?: { name: string; sql: ChSql }[];
|
||||
includedDataInterval?: string;
|
||||
}) {
|
||||
const valueExpressions = timestampValueExpression.split(',');
|
||||
const startTime = dateRange[0].getTime();
|
||||
|
|
@ -443,23 +445,23 @@ async function timeFilterExpr({
|
|||
);
|
||||
}
|
||||
|
||||
const startTimeCond = includedDataInterval
|
||||
? chSql`toStartOfInterval(fromUnixTimestamp64Milli(${{ Int64: startTime }}), INTERVAL ${includedDataInterval}) - INTERVAL ${includedDataInterval}`
|
||||
: chSql`fromUnixTimestamp64Milli(${{ Int64: startTime }})`;
|
||||
|
||||
const endTimeCond = includedDataInterval
|
||||
? chSql`toStartOfInterval(fromUnixTimestamp64Milli(${{ Int64: endTime }}), INTERVAL ${includedDataInterval}) + INTERVAL ${includedDataInterval}`
|
||||
: chSql`fromUnixTimestamp64Milli(${{ Int64: endTime }})`;
|
||||
|
||||
// If it's a date type
|
||||
if (columnMeta?.type === 'Date') {
|
||||
return chSql`(${unsafeTimestampValueExpression} ${
|
||||
dateRangeStartInclusive ? '>=' : '>'
|
||||
} toDate(fromUnixTimestamp64Milli(${{
|
||||
Int64: startTime,
|
||||
}})) AND ${unsafeTimestampValueExpression} <= toDate(fromUnixTimestamp64Milli(${{
|
||||
Int64: endTime,
|
||||
}})))`;
|
||||
} toDate(${startTimeCond}) AND ${unsafeTimestampValueExpression} <= toDate(${endTimeCond}))`;
|
||||
} else {
|
||||
return chSql`(${unsafeTimestampValueExpression} ${
|
||||
dateRangeStartInclusive ? '>=' : '>'
|
||||
} fromUnixTimestamp64Milli(${{
|
||||
Int64: startTime,
|
||||
}}) AND ${unsafeTimestampValueExpression} <= fromUnixTimestamp64Milli(${{
|
||||
Int64: endTime,
|
||||
}}))`;
|
||||
} ${startTimeCond} AND ${unsafeTimestampValueExpression} <= ${endTimeCond})`;
|
||||
}
|
||||
}),
|
||||
);
|
||||
|
|
@ -654,6 +656,7 @@ async function renderWhere(
|
|||
databaseName: chartConfig.from.databaseName,
|
||||
tableName: chartConfig.from.tableName,
|
||||
with: chartConfig.with,
|
||||
includedDataInterval: chartConfig.includedDataInterval,
|
||||
})
|
||||
: [],
|
||||
whereSearchCondition,
|
||||
|
|
@ -732,6 +735,7 @@ function renderLimit(
|
|||
// for metric SQL generation.
|
||||
type ChartConfigWithOptDateRangeEx = ChartConfigWithOptDateRange & {
|
||||
with?: { name: string; sql: ChSql }[];
|
||||
includedDataInterval?: string;
|
||||
};
|
||||
|
||||
function renderWith(
|
||||
|
|
@ -872,36 +876,95 @@ async function translateMetricChartConfig(
|
|||
timestampValueExpression: timeBucketCol,
|
||||
};
|
||||
} else if (metricType === MetricsDataType.Sum && metricName) {
|
||||
const timeBucketCol = '__hdx_time_bucket2';
|
||||
const valueHighCol = '`__hdx_value_high`';
|
||||
const valueHighPrevCol = '`__hdx_value_high_prev`';
|
||||
const timeExpr = timeBucketExpr({
|
||||
interval: chartConfig.granularity || 'auto',
|
||||
timestampValueExpression:
|
||||
chartConfig.timestampValueExpression || 'TimeUnix',
|
||||
dateRange: chartConfig.dateRange,
|
||||
alias: timeBucketCol,
|
||||
});
|
||||
|
||||
// Render the where clause to limit data selection on the source CTE but also search forward/back one
|
||||
// bucket window to ensure that there is enough data to compute a reasonable value on the ends of the
|
||||
// series.
|
||||
const where = await renderWhere(
|
||||
{
|
||||
...chartConfig,
|
||||
from: {
|
||||
...from,
|
||||
tableName: metricTables[MetricsDataType.Gauge],
|
||||
},
|
||||
filters: [
|
||||
{
|
||||
type: 'sql',
|
||||
condition: `MetricName = '${metricName}'`,
|
||||
},
|
||||
],
|
||||
includedDataInterval:
|
||||
chartConfig.granularity === 'auto' &&
|
||||
Array.isArray(chartConfig.dateRange)
|
||||
? convertDateRangeToGranularityString(chartConfig.dateRange, 60)
|
||||
: chartConfig.granularity,
|
||||
},
|
||||
metadata,
|
||||
);
|
||||
|
||||
return {
|
||||
...restChartConfig,
|
||||
with: [
|
||||
{
|
||||
name: 'RawSum',
|
||||
sql: chSql`SELECT *,
|
||||
any(Value) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevValue,
|
||||
any(AttributesHash) OVER (ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS PrevAttributesHash,
|
||||
IF(AggregationTemporality = 1,
|
||||
Value,IF(Value - PrevValue < 0 AND AttributesHash = PrevAttributesHash, Value,
|
||||
IF(AttributesHash != PrevAttributesHash, 0, Value - PrevValue))) as Rate
|
||||
FROM (
|
||||
SELECT *,
|
||||
cityHash64(mapConcat(ScopeAttributes, ResourceAttributes, Attributes)) AS AttributesHash
|
||||
name: 'Source',
|
||||
sql: chSql`
|
||||
SELECT
|
||||
*,
|
||||
cityHash64(mapConcat(ScopeAttributes, ResourceAttributes, Attributes)) AS AttributesHash,
|
||||
IF(AggregationTemporality = 1,
|
||||
SUM(Value) OVER (PARTITION BY AttributesHash ORDER BY AttributesHash, TimeUnix ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW),
|
||||
deltaSum(Value) OVER (PARTITION BY AttributesHash ORDER BY AttributesHash, TimeUnix ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
|
||||
) AS Value
|
||||
FROM ${renderFrom({ from: { ...from, tableName: metricTables[MetricsDataType.Sum] } })}
|
||||
WHERE MetricName = '${metricName}'
|
||||
ORDER BY AttributesHash, TimeUnix ASC
|
||||
) `,
|
||||
WHERE ${where}`,
|
||||
},
|
||||
],
|
||||
select: [
|
||||
{
|
||||
..._select,
|
||||
valueExpression: 'Rate',
|
||||
name: 'Bucketed',
|
||||
sql: chSql`
|
||||
SELECT
|
||||
${timeExpr},
|
||||
AttributesHash,
|
||||
last_value(Source.Value) AS ${valueHighCol},
|
||||
any(${valueHighCol}) OVER(PARTITION BY AttributesHash ORDER BY \`${timeBucketCol}\` ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS ${valueHighPrevCol},
|
||||
${valueHighCol} - ${valueHighPrevCol} AS Value,
|
||||
any(ResourceAttributes) AS ResourceAttributes,
|
||||
any(ResourceSchemaUrl) AS ResourceSchemaUrl,
|
||||
any(ScopeName) AS ScopeName,
|
||||
any(ScopeVersion) AS ScopeVersion,
|
||||
any(ScopeAttributes) AS ScopeAttributes,
|
||||
any(ScopeDroppedAttrCount) AS ScopeDroppedAttrCount,
|
||||
any(ScopeSchemaUrl) AS ScopeSchemaUrl,
|
||||
any(ServiceName) AS ServiceName,
|
||||
any(MetricName) AS MetricName,
|
||||
any(MetricDescription) AS MetricDescription,
|
||||
any(MetricUnit) AS MetricUnit,
|
||||
any(Attributes) AS Attributes,
|
||||
any(StartTimeUnix) AS StartTimeUnix,
|
||||
any(Flags) AS Flags,
|
||||
any(AggregationTemporality) AS AggregationTemporality,
|
||||
any(IsMonotonic) AS IsMonotonic
|
||||
FROM Source
|
||||
GROUP BY AttributesHash, \`${timeBucketCol}\`
|
||||
ORDER BY AttributesHash, \`${timeBucketCol}\`
|
||||
`,
|
||||
},
|
||||
],
|
||||
select,
|
||||
from: {
|
||||
databaseName: '',
|
||||
tableName: 'RawSum',
|
||||
tableName: 'Bucketed',
|
||||
},
|
||||
timestampValueExpression: `\`${timeBucketCol}\``,
|
||||
};
|
||||
} else if (metricType === MetricsDataType.Histogram && metricName) {
|
||||
// histograms are only valid for quantile selections
|
||||
|
|
|
|||
Loading…
Reference in a new issue