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Author SHA1 Message Date
Tushar Vats
dbbb4b6998 fix: modularize query range function 2026-06-18 19:22:24 +05:30
21 changed files with 759 additions and 1574 deletions

View File

@@ -1,29 +1,67 @@
/* eslint-disable sonarjs/no-identical-functions */
import { Fragment, useMemo, useState } from 'react';
import { Input } from '@signozhq/ui/input';
import { Skeleton } from 'antd';
import { Button, Skeleton } from 'antd';
import { Checkbox } from '@signozhq/ui/checkbox';
import { Typography } from '@signozhq/ui/typography';
import cx from 'classnames';
import { removeKeysFromExpression } from 'components/QueryBuilderV2/utils';
import {
IQuickFiltersConfig,
QuickFiltersSource,
} from 'components/QuickFilters/types';
import { OPERATORS } from 'constants/antlrQueryConstants';
import {
DATA_TYPE_VS_ATTRIBUTE_VALUES_KEY,
PANEL_TYPES,
} from 'constants/queryBuilder';
import { DEBOUNCE_DELAY } from 'constants/queryBuilderFilterConfig';
import { getOperatorValue } from 'container/QueryBuilder/filters/QueryBuilderSearch/utils';
import { useGetAggregateValues } from 'hooks/queryBuilder/useGetAggregateValues';
import { useQueryBuilder } from 'hooks/queryBuilder/useQueryBuilder';
import { useGetQueryKeyValueSuggestions } from 'hooks/querySuggestions/useGetQueryKeyValueSuggestions';
import useDebouncedFn from 'hooks/useDebouncedFunction';
import { Query } from 'types/api/queryBuilder/queryBuilderData';
import { cloneDeep, isArray, isFunction } from 'lodash-es';
import { ChevronDown, ChevronRight } from '@signozhq/icons';
import { DataTypes } from 'types/api/queryBuilder/queryAutocompleteResponse';
import { Query, TagFilterItem } from 'types/api/queryBuilder/queryBuilderData';
import { DataSource } from 'types/common/queryBuilder';
import { v4 as uuid } from 'uuid';
import CheckboxFilterHeader from './CheckboxFilterHeader';
import CheckboxValueRow from './CheckboxValueRow';
import LogsQuickFilterEmptyState from './LogsQuickFilterEmptyState';
import useActiveQueryIndex from './useActiveQueryIndex';
import useCheckboxDisclosure from './useCheckboxDisclosure';
import useCheckboxFilterActions from './useCheckboxFilterActions';
import useCheckboxFilterState from './useCheckboxFilterState';
import useCheckboxFilterValues from './useCheckboxFilterValues';
import { isKeyMatch } from './utils';
import './Checkbox.styles.scss';
const SELECTED_OPERATORS = [OPERATORS['='], 'in'];
const NON_SELECTED_OPERATORS = [OPERATORS['!='], 'not in', 'nin'];
const SOURCES_WITH_EMPTY_STATE_ENABLED = [QuickFiltersSource.LOGS_EXPLORER];
// Sources that use backend APIs expecting short operator format (e.g., 'nin' instead of 'not in')
const SOURCES_WITH_SHORT_OPERATORS = [QuickFiltersSource.INFRA_MONITORING];
/**
* Returns the correct NOT_IN operator value based on source.
* InfraMonitoring backend expects 'nin', others expect 'not in'.
*/
function getNotInOperator(source: QuickFiltersSource): string {
if (SOURCES_WITH_SHORT_OPERATORS.includes(source)) {
return 'nin';
}
return getOperatorValue('NOT_IN');
}
function setDefaultValues(
values: string[],
trueOrFalse: boolean,
): Record<string, boolean> {
const defaultState: Record<string, boolean> = {};
values.forEach((val) => {
defaultState[val] = trueOrFalse;
});
return defaultState;
}
interface ICheckboxProps {
filter: IQuickFiltersConfig;
source: QuickFiltersSource;
@@ -34,39 +72,194 @@ interface ICheckboxProps {
export default function CheckboxFilter(props: ICheckboxProps): JSX.Element {
const { source, filter, onFilterChange } = props;
const [searchText, setSearchText] = useState<string>('');
const activeQueryIndex = useActiveQueryIndex(source);
// null = no user action, true = user opened, false = user closed
const [userToggleState, setUserToggleState] = useState<boolean | null>(null);
const [visibleItemsCount, setVisibleItemsCount] = useState<number>(10);
const {
isOpen,
lastUsedQuery,
currentQuery,
redirectWithQueryBuilderData,
panelType,
} = useQueryBuilder();
// Determine if we're in ListView mode
const isListView = panelType === PANEL_TYPES.LIST;
// In ListView mode, use index 0 for most sources; for TRACES_EXPLORER, use lastUsedQuery
// Otherwise use lastUsedQuery for non-ListView modes
const activeQueryIndex = useMemo(() => {
if (isListView) {
return source === QuickFiltersSource.TRACES_EXPLORER
? lastUsedQuery || 0
: 0;
}
return lastUsedQuery || 0;
}, [isListView, source, lastUsedQuery]);
// Check if this filter has active filters in the query
const isSomeFilterPresentForCurrentAttribute = useMemo(
() =>
currentQuery.builder.queryData?.[activeQueryIndex]?.filters?.items?.some(
(item) => isKeyMatch(item.key?.key, filter.attributeKey.key),
),
[currentQuery.builder.queryData, activeQueryIndex, filter.attributeKey.key],
);
// Derive isOpen from filter state + user action
const isOpen = useMemo(() => {
// If user explicitly toggled, respect that
if (userToggleState !== null) {
return userToggleState;
}
// Auto-open if this filter has active filters in the query
if (isSomeFilterPresentForCurrentAttribute) {
return true;
}
// Otherwise use default behavior (first 2 filters open)
return filter.defaultOpen;
}, [
userToggleState,
isSomeFilterPresentForCurrentAttribute,
visibleItemsCount,
onToggleOpen,
onShowMore,
} = useCheckboxDisclosure({ filter, activeQueryIndex });
filter.defaultOpen,
]);
const { attributeValues, isLoading } = useCheckboxFilterValues({
filter,
source,
searchText,
isOpen,
});
const { data, isLoading } = useGetAggregateValues(
{
aggregateOperator: filter.aggregateOperator || 'noop',
dataSource: filter.dataSource || DataSource.LOGS,
aggregateAttribute: filter.aggregateAttribute || '',
attributeKey: filter.attributeKey.key,
filterAttributeKeyDataType: filter.attributeKey.dataType || DataTypes.EMPTY,
tagType: filter.attributeKey.type || '',
searchText: searchText ?? '',
},
{
enabled: isOpen && source !== QuickFiltersSource.METER_EXPLORER,
keepPreviousData: true,
},
);
const { currentFilterState, isFilterDisabled, isMultipleValuesTrueForTheKey } =
useCheckboxFilterState({ filter, attributeValues, activeQueryIndex });
const { data: keyValueSuggestions, isLoading: isLoadingKeyValueSuggestions } =
useGetQueryKeyValueSuggestions({
key: filter.attributeKey.key,
signal: filter.dataSource || DataSource.LOGS,
signalSource: 'meter',
options: {
enabled: isOpen && source === QuickFiltersSource.METER_EXPLORER,
keepPreviousData: true,
},
});
const { onChange, onClear } = useCheckboxFilterActions({
filter,
source,
attributeValues,
activeQueryIndex,
onFilterChange,
});
const attributeValues: string[] = useMemo(() => {
const dataType = filter.attributeKey.dataType || DataTypes.String;
if (source === QuickFiltersSource.METER_EXPLORER && keyValueSuggestions) {
// Process the response data
const responseData = keyValueSuggestions?.data as any;
const values = responseData.data?.values || {};
const stringValues = values.stringValues || [];
const numberValues = values.numberValues || [];
// Generate options from string values - explicitly handle empty strings
const stringOptions = stringValues
// Strict filtering for empty string - we'll handle it as a special case if needed
.filter(
(value: string | null | undefined): value is string =>
value !== null && value !== undefined && value !== '',
);
// Generate options from number values
const numberOptions = numberValues
.filter(
(value: number | null | undefined): value is number =>
value !== null && value !== undefined,
)
.map((value: number) => value.toString());
// Combine all options and make sure we don't have duplicate labels
return [...stringOptions, ...numberOptions];
}
const key = DATA_TYPE_VS_ATTRIBUTE_VALUES_KEY[dataType];
return (data?.payload?.[key] || []).filter(
(val) => val !== undefined && val !== null,
);
}, [data?.payload, filter.attributeKey.dataType, keyValueSuggestions, source]);
const setSearchTextDebounced = useDebouncedFn((...args) => {
setSearchText(args[0] as string);
}, DEBOUNCE_DELAY);
// derive the state of each filter key here in the renderer itself and keep it in sync with current query
// also we need to keep a note of last focussed query.
// eslint-disable-next-line sonarjs/cognitive-complexity
const currentFilterState = useMemo(() => {
let filterState: Record<string, boolean> = setDefaultValues(
attributeValues,
false,
);
const filterSync = currentQuery?.builder.queryData?.[
activeQueryIndex
]?.filters?.items.find((item) =>
isKeyMatch(item.key?.key, filter.attributeKey.key),
);
if (filterSync) {
if (SELECTED_OPERATORS.includes(filterSync.op)) {
if (isArray(filterSync.value)) {
filterSync.value.forEach((val) => {
filterState[String(val)] = true;
});
} else if (typeof filterSync.value === 'string') {
filterState[filterSync.value] = true;
} else if (typeof filterSync.value === 'boolean') {
filterState[String(filterSync.value)] = true;
} else if (typeof filterSync.value === 'number') {
filterState[String(filterSync.value)] = true;
}
} else if (NON_SELECTED_OPERATORS.includes(filterSync.op)) {
filterState = setDefaultValues(attributeValues, true);
if (isArray(filterSync.value)) {
filterSync.value.forEach((val) => {
filterState[String(val)] = false;
});
} else if (typeof filterSync.value === 'string') {
filterState[filterSync.value] = false;
} else if (typeof filterSync.value === 'boolean') {
filterState[String(filterSync.value)] = false;
} else if (typeof filterSync.value === 'number') {
filterState[String(filterSync.value)] = false;
}
}
} else {
filterState = setDefaultValues(attributeValues, true);
}
return filterState;
}, [
attributeValues,
currentQuery?.builder.queryData,
filter.attributeKey,
activeQueryIndex,
]);
// disable the filter when there are multiple entries of the same attribute key present in the filter bar
const isFilterDisabled = useMemo(
() =>
(currentQuery?.builder?.queryData?.[
activeQueryIndex
]?.filters?.items?.filter((item) =>
isKeyMatch(item.key?.key, filter.attributeKey.key),
)?.length || 0) > 1,
[currentQuery?.builder?.queryData, activeQueryIndex, filter.attributeKey],
);
// variable to check if the current filter has multiple values to its name in the key op value section
const isMultipleValuesTrueForTheKey =
Object.values(currentFilterState).filter((val) => val).length > 1;
// Sort checked items to the top, then unchecked items
const currentAttributeKeys = useMemo(() => {
const checkedValues = attributeValues.filter(
@@ -84,6 +277,293 @@ export default function CheckboxFilter(props: ICheckboxProps): JSX.Element {
[currentAttributeKeys, currentFilterState],
);
const handleClearFilterAttribute = (): void => {
const preparedQuery: Query = {
...currentQuery,
builder: {
...currentQuery.builder,
queryData: currentQuery.builder.queryData.map((item, idx) => ({
...item,
filter: {
expression: removeKeysFromExpression(item.filter?.expression ?? '', [
filter.attributeKey.key,
]),
},
filters: {
...item.filters,
items:
idx === activeQueryIndex
? item.filters?.items?.filter(
(fil) => !isKeyMatch(fil.key?.key, filter.attributeKey.key),
) || []
: [...(item.filters?.items || [])],
op: item.filters?.op || 'AND',
},
})),
},
};
if (onFilterChange && isFunction(onFilterChange)) {
onFilterChange(preparedQuery);
} else {
redirectWithQueryBuilderData(preparedQuery);
}
};
const onChange = (
value: string,
checked: boolean,
isOnlyOrAllClicked: boolean,
// eslint-disable-next-line sonarjs/cognitive-complexity
): void => {
const query = cloneDeep(currentQuery.builder.queryData?.[activeQueryIndex]);
// if only or all are clicked we do not need to worry about anything just override whatever we have
// by either adding a new IN operator value clause in case of ONLY or remove everything we have for ALL.
if (isOnlyOrAllClicked && query?.filters?.items) {
const isOnlyOrAll = isSomeFilterPresentForCurrentAttribute
? currentFilterState[value] && !isMultipleValuesTrueForTheKey
? 'All'
: 'Only'
: 'Only';
query.filters.items = query.filters.items.filter(
(q) => !isKeyMatch(q.key?.key, filter.attributeKey.key),
);
if (query.filter?.expression) {
query.filter.expression = removeKeysFromExpression(
query.filter.expression,
[filter.attributeKey.key],
);
}
if (isOnlyOrAll === 'Only') {
const newFilterItem: TagFilterItem = {
id: uuid(),
op: getOperatorValue(OPERATORS.IN),
key: filter.attributeKey,
value,
};
query.filters.items = [...query.filters.items, newFilterItem];
}
} else if (query?.filters?.items) {
if (
query.filters?.items?.some((item) =>
isKeyMatch(item.key?.key, filter.attributeKey.key),
)
) {
// if there is already a running filter for the current attribute key then
// we split the cases by which particular operator is present right now!
const currentFilter = query.filters?.items?.find((q) =>
isKeyMatch(q.key?.key, filter.attributeKey.key),
);
if (currentFilter) {
const runningOperator = currentFilter?.op;
switch (runningOperator) {
case 'in':
if (checked) {
// if it's an IN operator then if we are checking another value it get's added to the
// filter clause. example - key IN [value1, currentSelectedValue]
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: [...currentFilter.value, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else {
// if the current state wasn't an array we make it one and add our value
const newFilter = {
...currentFilter,
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else if (!checked) {
// if we are removing some value when the running operator is IN we filter.
// example - key IN [value1,currentSelectedValue] becomes key IN [value1] in case of array
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: currentFilter.value.filter((val) => val !== value),
};
if (newFilter.value.length === 0) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
} else {
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else {
// if not an array remove the whole thing altogether!
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
}
break;
case 'nin':
case 'not in':
// if the current running operator is NIN then when unchecking the value it gets
// added to the clause like key NIN [value1 , currentUnselectedValue]
if (!checked) {
// in case of array add the currentUnselectedValue to the list.
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: [...currentFilter.value, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else {
// in case of not an array make it one!
const newFilter = {
...currentFilter,
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else if (checked) {
// opposite of above!
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: currentFilter.value.filter((val) => val !== value),
};
if (newFilter.value.length === 0) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
if (query.filter?.expression) {
query.filter.expression = removeKeysFromExpression(
query.filter.expression,
[filter.attributeKey.key],
);
}
} else {
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else {
const newFilter = {
...currentFilter,
value: currentFilter.value === value ? null : currentFilter.value,
};
if (newFilter.value === null && query.filter?.expression) {
query.filter.expression = removeKeysFromExpression(
query.filter.expression,
[filter.attributeKey.key],
);
}
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
}
break;
case '=':
if (checked) {
const newFilter = {
...currentFilter,
op: getOperatorValue(OPERATORS.IN),
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else if (!checked) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
break;
case '!=':
if (!checked) {
const newFilter = {
...currentFilter,
op: getNotInOperator(source),
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else if (checked) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
break;
default:
break;
}
}
} else {
// case - when there is no filter for the current key that means all are selected right now.
const newFilterItem: TagFilterItem = {
id: uuid(),
op: getNotInOperator(source),
key: filter.attributeKey,
value,
};
query.filters.items = [...query.filters.items, newFilterItem];
}
}
const finalQuery = {
...currentQuery,
builder: {
...currentQuery.builder,
queryData: [
...currentQuery.builder.queryData.map((q, idx) => {
if (idx === activeQueryIndex) {
return query;
}
return q;
}),
],
},
};
if (onFilterChange && isFunction(onFilterChange)) {
onFilterChange(finalQuery);
} else {
redirectWithQueryBuilderData(finalQuery);
}
};
const isEmptyStateWithDocsEnabled =
SOURCES_WITH_EMPTY_STATE_ENABLED.includes(source) &&
!searchText &&
@@ -91,19 +571,48 @@ export default function CheckboxFilter(props: ICheckboxProps): JSX.Element {
return (
<div className="checkbox-filter">
<CheckboxFilterHeader
title={filter.title}
isOpen={isOpen}
showClearAll={!!attributeValues.length}
onToggleOpen={onToggleOpen}
onClear={onClear}
/>
{isOpen && isLoading && !attributeValues.length && (
<section className="loading">
<Skeleton paragraph={{ rows: 4 }} />
<section
className="filter-header-checkbox"
onClick={(): void => {
if (isOpen) {
setUserToggleState(false);
setVisibleItemsCount(10);
} else {
setUserToggleState(true);
}
}}
>
<section className="left-action">
{isOpen ? (
<ChevronDown size={13} cursor="pointer" />
) : (
<ChevronRight size={13} cursor="pointer" />
)}
<Typography.Text className="title">{filter.title}</Typography.Text>
</section>
)}
{isOpen && !isLoading && (
<section className="right-action">
{isOpen && !!attributeValues.length && (
<Typography.Text
className="clear-all"
onClick={(e): void => {
e.stopPropagation();
e.preventDefault();
handleClearFilterAttribute();
}}
>
Clear All
</Typography.Text>
)}
</section>
</section>
{isOpen &&
(isLoading || isLoadingKeyValueSuggestions) &&
!attributeValues.length && (
<section className="loading">
<Skeleton paragraph={{ rows: 4 }} />
</section>
)}
{isOpen && !isLoading && !isLoadingKeyValueSuggestions && (
<>
{!isEmptyStateWithDocsEnabled && (
<section className="search">
@@ -125,24 +634,48 @@ export default function CheckboxFilter(props: ICheckboxProps): JSX.Element {
data-testid="filter-separator"
/>
)}
<CheckboxValueRow
value={value}
checked={currentFilterState[value]}
disabled={isFilterDisabled}
title={filter.title}
onlyButtonLabel={
isSomeFilterPresentForCurrentAttribute
? currentFilterState[value] && !isMultipleValuesTrueForTheKey
? 'All'
: 'Only'
: 'Only'
}
customRendererForValue={filter.customRendererForValue}
onCheckboxChange={(checked): void => onChange(value, checked, false)}
onOnlyOrAllClick={(): void =>
onChange(value, currentFilterState[value], true)
}
/>
<div className="value">
<Checkbox
onChange={(checked): void =>
onChange(value, checked === true, false)
}
value={currentFilterState[value]}
disabled={isFilterDisabled}
className="check-box"
/>
<div
className={cx(
'checkbox-value-section',
isFilterDisabled ? 'filter-disabled' : '',
)}
onClick={(): void => {
if (isFilterDisabled) {
return;
}
onChange(value, currentFilterState[value], true);
}}
>
<div className={`${filter.title} label-${value}`} />
{filter.customRendererForValue ? (
filter.customRendererForValue(value)
) : (
<Typography.Text className="value-string" truncate={1}>
{String(value)}
</Typography.Text>
)}
<Button type="text" className="only-btn">
{isSomeFilterPresentForCurrentAttribute
? currentFilterState[value] && !isMultipleValuesTrueForTheKey
? 'All'
: 'Only'
: 'Only'}
</Button>
<Button type="text" className="toggle-btn">
Toggle
</Button>
</div>
</div>
</Fragment>
))}
</section>
@@ -155,7 +688,10 @@ export default function CheckboxFilter(props: ICheckboxProps): JSX.Element {
)}
{visibleItemsCount < attributeValues?.length && (
<section className="show-more">
<Typography.Text className="show-more-text" onClick={onShowMore}>
<Typography.Text
className="show-more-text"
onClick={(): void => setVisibleItemsCount((prev) => prev + 10)}
>
Show More...
</Typography.Text>
</section>

View File

@@ -1,47 +0,0 @@
import { Typography } from '@signozhq/ui/typography';
import { ChevronDown, ChevronRight } from '@signozhq/icons';
interface CheckboxFilterHeaderProps {
title: string;
isOpen: boolean;
showClearAll: boolean;
onToggleOpen: () => void;
onClear: () => void;
}
function CheckboxFilterHeader({
title,
isOpen,
showClearAll,
onToggleOpen,
onClear,
}: CheckboxFilterHeaderProps): JSX.Element {
return (
<section className="filter-header-checkbox" onClick={onToggleOpen}>
<section className="left-action">
{isOpen ? (
<ChevronDown size={13} cursor="pointer" />
) : (
<ChevronRight size={13} cursor="pointer" />
)}
<Typography.Text className="title">{title}</Typography.Text>
</section>
<section className="right-action">
{isOpen && showClearAll && (
<Typography.Text
className="clear-all"
onClick={(e): void => {
e.stopPropagation();
e.preventDefault();
onClear();
}}
>
Clear All
</Typography.Text>
)}
</section>
</section>
);
}
export default CheckboxFilterHeader;

View File

@@ -1,68 +0,0 @@
import { Button } from 'antd';
import { Checkbox } from '@signozhq/ui/checkbox';
import { Typography } from '@signozhq/ui/typography';
import cx from 'classnames';
interface CheckboxValueRowProps {
value: string;
checked: boolean;
disabled: boolean;
title: string;
onlyButtonLabel: string;
customRendererForValue?: (value: string) => JSX.Element;
onCheckboxChange: (checked: boolean) => void;
onOnlyOrAllClick: () => void;
}
function CheckboxValueRow({
value,
checked,
disabled,
title,
onlyButtonLabel,
customRendererForValue,
onCheckboxChange,
onOnlyOrAllClick,
}: CheckboxValueRowProps): JSX.Element {
return (
<div className="value">
<Checkbox
onChange={(isChecked): void => onCheckboxChange(isChecked === true)}
value={checked}
disabled={disabled}
className="check-box"
/>
<div
className={cx('checkbox-value-section', disabled ? 'filter-disabled' : '')}
onClick={(): void => {
if (disabled) {
return;
}
onOnlyOrAllClick();
}}
>
<div className={`${title} label-${value}`} />
{customRendererForValue ? (
customRendererForValue(value)
) : (
<Typography.Text className="value-string" truncate={1}>
{String(value)}
</Typography.Text>
)}
<Button type="text" className="only-btn">
{onlyButtonLabel}
</Button>
<Button type="text" className="toggle-btn">
Toggle
</Button>
</div>
</div>
);
}
CheckboxValueRow.defaultProps = {
customRendererForValue: undefined,
};
export default CheckboxValueRow;

View File

@@ -1,417 +0,0 @@
/* eslint-disable sonarjs/no-identical-functions */
import { removeKeysFromExpression } from 'components/QueryBuilderV2/utils';
import {
IQuickFiltersConfig,
QuickFiltersSource,
} from 'components/QuickFilters/types';
import { OPERATORS } from 'constants/antlrQueryConstants';
import { getOperatorValue } from 'container/QueryBuilder/filters/QueryBuilderSearch/utils';
import { cloneDeep, isArray } from 'lodash-es';
import { Query, TagFilterItem } from 'types/api/queryBuilder/queryBuilderData';
import { v4 as uuid } from 'uuid';
import { isKeyMatch } from './utils';
export const SELECTED_OPERATORS = [OPERATORS['='], 'in'];
export const NON_SELECTED_OPERATORS = [OPERATORS['!='], 'not in', 'nin'];
// Sources that use backend APIs expecting short operator format (e.g., 'nin' instead of 'not in')
const SOURCES_WITH_SHORT_OPERATORS = [QuickFiltersSource.INFRA_MONITORING];
/**
* Returns the correct NOT_IN operator value based on source.
* InfraMonitoring backend expects 'nin', others expect 'not in'.
*/
export function getNotInOperator(source: QuickFiltersSource): string {
if (SOURCES_WITH_SHORT_OPERATORS.includes(source)) {
return 'nin';
}
return getOperatorValue('NOT_IN');
}
function setDefaultValues(
values: string[],
trueOrFalse: boolean,
): Record<string, boolean> {
const defaultState: Record<string, boolean> = {};
values.forEach((val) => {
defaultState[val] = trueOrFalse;
});
return defaultState;
}
/**
* Derives the checked/unchecked state for each attribute value by reading the
* active filter clause for this attribute key out of the query.
*
* - No matching clause -> every value is checked (all selected).
* - IN / `=` clause -> only the listed values are checked.
* - NOT IN / `!=` clause -> every value is checked except the excluded ones.
*/
// eslint-disable-next-line sonarjs/cognitive-complexity
export function deriveCheckboxState({
attributeValues,
filterItems,
filterKey,
}: {
attributeValues: string[];
filterItems: TagFilterItem[] | undefined;
filterKey: string;
}): Record<string, boolean> {
let filterState: Record<string, boolean> = setDefaultValues(
attributeValues,
false,
);
const filterSync = filterItems?.find((item) =>
isKeyMatch(item.key?.key, filterKey),
);
if (filterSync) {
if (SELECTED_OPERATORS.includes(filterSync.op)) {
if (isArray(filterSync.value)) {
filterSync.value.forEach((val) => {
filterState[String(val)] = true;
});
} else if (typeof filterSync.value === 'string') {
filterState[filterSync.value] = true;
} else if (typeof filterSync.value === 'boolean') {
filterState[String(filterSync.value)] = true;
} else if (typeof filterSync.value === 'number') {
filterState[String(filterSync.value)] = true;
}
} else if (NON_SELECTED_OPERATORS.includes(filterSync.op)) {
filterState = setDefaultValues(attributeValues, true);
if (isArray(filterSync.value)) {
filterSync.value.forEach((val) => {
filterState[String(val)] = false;
});
} else if (typeof filterSync.value === 'string') {
filterState[filterSync.value] = false;
} else if (typeof filterSync.value === 'boolean') {
filterState[String(filterSync.value)] = false;
} else if (typeof filterSync.value === 'number') {
filterState[String(filterSync.value)] = false;
}
}
} else {
filterState = setDefaultValues(attributeValues, true);
}
return filterState;
}
/**
* Returns a new query with every clause for this attribute key removed, both
* from the structured filter items and the raw filter expression.
*/
export function clearFilterFromQuery({
currentQuery,
filter,
activeQueryIndex,
}: {
currentQuery: Query;
filter: IQuickFiltersConfig;
activeQueryIndex: number;
}): Query {
return {
...currentQuery,
builder: {
...currentQuery.builder,
queryData: currentQuery.builder.queryData.map((item, idx) => ({
...item,
filter: {
expression: removeKeysFromExpression(item.filter?.expression ?? '', [
filter.attributeKey.key,
]),
},
filters: {
...item.filters,
items:
idx === activeQueryIndex
? item.filters?.items?.filter(
(fil) => !isKeyMatch(fil.key?.key, filter.attributeKey.key),
) || []
: [...(item.filters?.items || [])],
op: item.filters?.op || 'AND',
},
})),
},
};
}
// eslint-disable-next-line sonarjs/cognitive-complexity
export function applyCheckboxToggle({
currentQuery,
activeQueryIndex,
filter,
source,
attributeValues,
value,
checked,
isOnlyOrAllClicked,
}: {
currentQuery: Query;
activeQueryIndex: number;
filter: IQuickFiltersConfig;
source: QuickFiltersSource;
attributeValues: string[];
value: string;
checked: boolean;
isOnlyOrAllClicked: boolean;
}): Query {
const activeItems =
currentQuery.builder.queryData?.[activeQueryIndex]?.filters?.items;
const isSomeFilterPresentForCurrentAttribute = !!activeItems?.some((item) =>
isKeyMatch(item.key?.key, filter.attributeKey.key),
);
const currentFilterState = deriveCheckboxState({
attributeValues,
filterItems: activeItems,
filterKey: filter.attributeKey.key,
});
const isMultipleValuesTrueForTheKey =
Object.values(currentFilterState).filter((val) => val).length > 1;
const query = cloneDeep(currentQuery.builder.queryData?.[activeQueryIndex]);
// if only or all are clicked we do not need to worry about anything just override whatever we have
// by either adding a new IN operator value clause in case of ONLY or remove everything we have for ALL.
if (isOnlyOrAllClicked && query?.filters?.items) {
const isOnlyOrAll = isSomeFilterPresentForCurrentAttribute
? currentFilterState[value] && !isMultipleValuesTrueForTheKey
? 'All'
: 'Only'
: 'Only';
query.filters.items = query.filters.items.filter(
(q) => !isKeyMatch(q.key?.key, filter.attributeKey.key),
);
if (query.filter?.expression) {
query.filter.expression = removeKeysFromExpression(query.filter.expression, [
filter.attributeKey.key,
]);
}
if (isOnlyOrAll === 'Only') {
const newFilterItem: TagFilterItem = {
id: uuid(),
op: getOperatorValue(OPERATORS.IN),
key: filter.attributeKey,
value,
};
query.filters.items = [...query.filters.items, newFilterItem];
}
} else if (query?.filters?.items) {
if (
query.filters?.items?.some((item) =>
isKeyMatch(item.key?.key, filter.attributeKey.key),
)
) {
// if there is already a running filter for the current attribute key then
// we split the cases by which particular operator is present right now!
const currentFilter = query.filters?.items?.find((q) =>
isKeyMatch(q.key?.key, filter.attributeKey.key),
);
if (currentFilter) {
const runningOperator = currentFilter?.op;
switch (runningOperator) {
case 'in':
if (checked) {
// if it's an IN operator then if we are checking another value it get's added to the
// filter clause. example - key IN [value1, currentSelectedValue]
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: [...currentFilter.value, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else {
// if the current state wasn't an array we make it one and add our value
const newFilter = {
...currentFilter,
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else if (!checked) {
// if we are removing some value when the running operator is IN we filter.
// example - key IN [value1,currentSelectedValue] becomes key IN [value1] in case of array
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: currentFilter.value.filter((val) => val !== value),
};
if (newFilter.value.length === 0) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
} else {
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else {
// if not an array remove the whole thing altogether!
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
}
break;
case 'nin':
case 'not in':
// if the current running operator is NIN then when unchecking the value it gets
// added to the clause like key NIN [value1 , currentUnselectedValue]
if (!checked) {
// in case of array add the currentUnselectedValue to the list.
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: [...currentFilter.value, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else {
// in case of not an array make it one!
const newFilter = {
...currentFilter,
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else if (checked) {
// opposite of above!
if (isArray(currentFilter.value)) {
const newFilter = {
...currentFilter,
value: currentFilter.value.filter((val) => val !== value),
};
if (newFilter.value.length === 0) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
if (query.filter?.expression) {
query.filter.expression = removeKeysFromExpression(
query.filter.expression,
[filter.attributeKey.key],
);
}
} else {
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
}
} else {
const newFilter = {
...currentFilter,
value: currentFilter.value === value ? null : currentFilter.value,
};
if (newFilter.value === null && query.filter?.expression) {
query.filter.expression = removeKeysFromExpression(
query.filter.expression,
[filter.attributeKey.key],
);
}
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
}
break;
case '=':
if (checked) {
const newFilter = {
...currentFilter,
op: getOperatorValue(OPERATORS.IN),
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else if (!checked) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
break;
case '!=':
if (!checked) {
const newFilter = {
...currentFilter,
op: getNotInOperator(source),
value: [currentFilter.value as string, value],
};
query.filters.items = query.filters.items.map((item) => {
if (isKeyMatch(item.key?.key, filter.attributeKey.key)) {
return newFilter;
}
return item;
});
} else if (checked) {
query.filters.items = query.filters.items.filter(
(item) => !isKeyMatch(item.key?.key, filter.attributeKey.key),
);
}
break;
default:
break;
}
}
} else {
// case - when there is no filter for the current key that means all are selected right now.
const newFilterItem: TagFilterItem = {
id: uuid(),
op: getNotInOperator(source),
key: filter.attributeKey,
value,
};
query.filters.items = [...query.filters.items, newFilterItem];
}
}
return {
...currentQuery,
builder: {
...currentQuery.builder,
queryData: [
...currentQuery.builder.queryData.map((q, idx) => {
if (idx === activeQueryIndex) {
return query;
}
return q;
}),
],
},
};
}

View File

@@ -1,27 +0,0 @@
import { useMemo } from 'react';
import { QuickFiltersSource } from 'components/QuickFilters/types';
import { PANEL_TYPES } from 'constants/queryBuilder';
import { useQueryBuilder } from 'hooks/queryBuilder/useQueryBuilder';
/**
* Resolves which query-builder query index the checkbox filter reads from and
* writes to.
*
* In ListView most sources use index 0; TRACES_EXPLORER and every non-ListView
* mode track the last focused query.
*/
function useActiveQueryIndex(source: QuickFiltersSource): number {
const { lastUsedQuery, panelType } = useQueryBuilder();
const isListView = panelType === PANEL_TYPES.LIST;
return useMemo(() => {
if (isListView) {
return source === QuickFiltersSource.TRACES_EXPLORER
? lastUsedQuery || 0
: 0;
}
return lastUsedQuery || 0;
}, [isListView, source, lastUsedQuery]);
}
export default useActiveQueryIndex;

View File

@@ -1,90 +0,0 @@
import { useMemo, useState } from 'react';
import { IQuickFiltersConfig } from 'components/QuickFilters/types';
import { useQueryBuilder } from 'hooks/queryBuilder/useQueryBuilder';
import { isKeyMatch } from './utils';
const DEFAULT_VISIBLE_ITEMS_COUNT = 10;
interface UseCheckboxDisclosureProps {
filter: IQuickFiltersConfig;
activeQueryIndex: number;
}
interface UseCheckboxDisclosureReturn {
isOpen: boolean;
isSomeFilterPresentForCurrentAttribute: boolean;
visibleItemsCount: number;
onToggleOpen: () => void;
onShowMore: () => void;
}
/**
* Owns the open/collapsed state of a checkbox filter section and how many
* values are visible.
*
* Auto-opens when the query already has a clause for this attribute, otherwise
* falls back to `filter.defaultOpen`. An explicit user toggle always wins.
* Collapsing resets the visible count.
*/
function useCheckboxDisclosure({
filter,
activeQueryIndex,
}: UseCheckboxDisclosureProps): UseCheckboxDisclosureReturn {
const { currentQuery } = useQueryBuilder();
// null = no user action, true = user opened, false = user closed
const [userToggleState, setUserToggleState] = useState<boolean | null>(null);
const [visibleItemsCount, setVisibleItemsCount] = useState<number>(
DEFAULT_VISIBLE_ITEMS_COUNT,
);
const isSomeFilterPresentForCurrentAttribute = useMemo(
() =>
!!currentQuery.builder.queryData?.[activeQueryIndex]?.filters?.items?.some(
(item) => isKeyMatch(item.key?.key, filter.attributeKey.key),
),
[currentQuery.builder.queryData, activeQueryIndex, filter.attributeKey.key],
);
const isOpen = useMemo(() => {
// If user explicitly toggled, respect that
if (userToggleState !== null) {
return userToggleState;
}
// Auto-open if this filter has active filters in the query
if (isSomeFilterPresentForCurrentAttribute) {
return true;
}
// Otherwise use default behavior (first 2 filters open)
return filter.defaultOpen;
}, [
userToggleState,
isSomeFilterPresentForCurrentAttribute,
filter.defaultOpen,
]);
const onToggleOpen = (): void => {
if (isOpen) {
setUserToggleState(false);
setVisibleItemsCount(DEFAULT_VISIBLE_ITEMS_COUNT);
} else {
setUserToggleState(true);
}
};
const onShowMore = (): void => {
setVisibleItemsCount((prev) => prev + DEFAULT_VISIBLE_ITEMS_COUNT);
};
return {
isOpen,
isSomeFilterPresentForCurrentAttribute,
visibleItemsCount,
onToggleOpen,
onShowMore,
};
}
export default useCheckboxDisclosure;

View File

@@ -1,78 +0,0 @@
import {
IQuickFiltersConfig,
QuickFiltersSource,
} from 'components/QuickFilters/types';
import { useQueryBuilder } from 'hooks/queryBuilder/useQueryBuilder';
import { isFunction } from 'lodash-es';
import { Query } from 'types/api/queryBuilder/queryBuilderData';
import {
applyCheckboxToggle,
clearFilterFromQuery,
} from './checkboxFilterQuery';
interface UseCheckboxFilterActionsProps {
filter: IQuickFiltersConfig;
source: QuickFiltersSource;
attributeValues: string[];
activeQueryIndex: number;
onFilterChange?: ((query: Query) => void) | null;
}
interface UseCheckboxFilterActionsReturn {
onChange: (
value: string,
checked: boolean,
isOnlyOrAllClicked: boolean,
) => void;
onClear: () => void;
}
/**
* Wires the pure checkbox query algebra to query-builder dispatch: the
* caller-provided `onFilterChange` when present, otherwise a URL redirect.
*/
function useCheckboxFilterActions({
filter,
source,
attributeValues,
activeQueryIndex,
onFilterChange,
}: UseCheckboxFilterActionsProps): UseCheckboxFilterActionsReturn {
const { currentQuery, redirectWithQueryBuilderData } = useQueryBuilder();
const dispatch = (query: Query): void => {
if (onFilterChange && isFunction(onFilterChange)) {
onFilterChange(query);
} else {
redirectWithQueryBuilderData(query);
}
};
const onChange = (
value: string,
checked: boolean,
isOnlyOrAllClicked: boolean,
): void => {
dispatch(
applyCheckboxToggle({
currentQuery,
activeQueryIndex,
filter,
source,
attributeValues,
value,
checked,
isOnlyOrAllClicked,
}),
);
};
const onClear = (): void => {
dispatch(clearFilterFromQuery({ currentQuery, filter, activeQueryIndex }));
};
return { onChange, onClear };
}
export default useCheckboxFilterActions;

View File

@@ -1,71 +0,0 @@
import { useMemo } from 'react';
import { IQuickFiltersConfig } from 'components/QuickFilters/types';
import { useQueryBuilder } from 'hooks/queryBuilder/useQueryBuilder';
import { deriveCheckboxState } from './checkboxFilterQuery';
import { isKeyMatch } from './utils';
interface UseCheckboxFilterStateProps {
filter: IQuickFiltersConfig;
attributeValues: string[];
activeQueryIndex: number;
}
interface UseCheckboxFilterStateReturn {
currentFilterState: Record<string, boolean>;
isFilterDisabled: boolean;
isMultipleValuesTrueForTheKey: boolean;
}
/**
* Reads the active query and derives the per-value checked state for this
* attribute, whether the filter is disabled (same key used more than once in
* the filter bar), and whether more than one value is currently selected.
*/
function useCheckboxFilterState({
filter,
attributeValues,
activeQueryIndex,
}: UseCheckboxFilterStateProps): UseCheckboxFilterStateReturn {
const { currentQuery } = useQueryBuilder();
// derive the state of each filter key here and keep it in sync with current query
const currentFilterState = useMemo(
() =>
deriveCheckboxState({
attributeValues,
filterItems:
currentQuery?.builder.queryData?.[activeQueryIndex]?.filters?.items,
filterKey: filter.attributeKey.key,
}),
[
attributeValues,
currentQuery?.builder.queryData,
filter.attributeKey,
activeQueryIndex,
],
);
// disable the filter when there are multiple entries of the same attribute key present in the filter bar
const isFilterDisabled = useMemo(
() =>
(currentQuery?.builder?.queryData?.[
activeQueryIndex
]?.filters?.items?.filter((item) =>
isKeyMatch(item.key?.key, filter.attributeKey.key),
)?.length || 0) > 1,
[currentQuery?.builder?.queryData, activeQueryIndex, filter.attributeKey],
);
// whether the current filter has multiple values to its name in the key op value section
const isMultipleValuesTrueForTheKey =
Object.values(currentFilterState).filter((val) => val).length > 1;
return {
currentFilterState,
isFilterDisabled,
isMultipleValuesTrueForTheKey,
};
}
export default useCheckboxFilterState;

View File

@@ -1,99 +0,0 @@
import { useMemo } from 'react';
import {
IQuickFiltersConfig,
QuickFiltersSource,
} from 'components/QuickFilters/types';
import { DATA_TYPE_VS_ATTRIBUTE_VALUES_KEY } from 'constants/queryBuilder';
import { useGetAggregateValues } from 'hooks/queryBuilder/useGetAggregateValues';
import { useGetQueryKeyValueSuggestions } from 'hooks/querySuggestions/useGetQueryKeyValueSuggestions';
import { DataTypes } from 'types/api/queryBuilder/queryAutocompleteResponse';
import { DataSource } from 'types/common/queryBuilder';
interface UseCheckboxFilterValuesProps {
filter: IQuickFiltersConfig;
source: QuickFiltersSource;
searchText: string;
isOpen: boolean;
}
interface UseCheckboxFilterValuesReturn {
attributeValues: string[];
isLoading: boolean;
}
function useCheckboxFilterValues({
filter,
source,
searchText,
isOpen,
}: UseCheckboxFilterValuesProps): UseCheckboxFilterValuesReturn {
const { data, isLoading } = useGetAggregateValues(
{
aggregateOperator: filter.aggregateOperator || 'noop',
dataSource: filter.dataSource || DataSource.LOGS,
aggregateAttribute: filter.aggregateAttribute || '',
attributeKey: filter.attributeKey.key,
filterAttributeKeyDataType: filter.attributeKey.dataType || DataTypes.EMPTY,
tagType: filter.attributeKey.type || '',
searchText: searchText ?? '',
},
{
enabled: isOpen && source !== QuickFiltersSource.METER_EXPLORER,
keepPreviousData: true,
},
);
const { data: keyValueSuggestions, isLoading: isLoadingKeyValueSuggestions } =
useGetQueryKeyValueSuggestions({
key: filter.attributeKey.key,
signal: filter.dataSource || DataSource.LOGS,
signalSource: 'meter',
options: {
enabled: isOpen && source === QuickFiltersSource.METER_EXPLORER,
keepPreviousData: true,
},
});
const attributeValues: string[] = useMemo(() => {
const dataType = filter.attributeKey.dataType || DataTypes.String;
if (source === QuickFiltersSource.METER_EXPLORER && keyValueSuggestions) {
// Process the response data
const responseData = keyValueSuggestions?.data as any;
const values = responseData.data?.values || {};
const stringValues = values.stringValues || [];
const numberValues = values.numberValues || [];
// Generate options from string values - explicitly handle empty strings
const stringOptions = stringValues
// Strict filtering for empty string - we'll handle it as a special case if needed
.filter(
(value: string | null | undefined): value is string =>
value !== null && value !== undefined && value !== '',
);
// Generate options from number values
const numberOptions = numberValues
.filter(
(value: number | null | undefined): value is number =>
value !== null && value !== undefined,
)
.map((value: number) => value.toString());
// Combine all options and make sure we don't have duplicate labels
return [...stringOptions, ...numberOptions];
}
const key = DATA_TYPE_VS_ATTRIBUTE_VALUES_KEY[dataType];
return (data?.payload?.[key] || []).filter(
(val) => val !== undefined && val !== null,
);
}, [data?.payload, filter.attributeKey.dataType, keyValueSuggestions, source]);
return {
attributeValues,
isLoading: isLoading || isLoadingKeyValueSuggestions,
};
}
export default useCheckboxFilterValues;

View File

@@ -3,16 +3,15 @@ package flagger
import "github.com/SigNoz/signoz/pkg/types/featuretypes"
var (
FeatureUseSpanMetrics = featuretypes.MustNewName("use_span_metrics")
FeatureKafkaSpanEval = featuretypes.MustNewName("kafka_span_eval")
FeatureHideRootUser = featuretypes.MustNewName("hide_root_user")
FeatureGetMetersFromZeus = featuretypes.MustNewName("get_meters_from_zeus")
FeaturePutMetersInZeus = featuretypes.MustNewName("put_meters_in_zeus")
FeatureUseMeterReporter = featuretypes.MustNewName("use_meter_reporter")
FeatureUseJSONBody = featuretypes.MustNewName("use_json_body")
FeatureUseFineGrainedAuthz = featuretypes.MustNewName("use_fine_grained_authz")
FeatureUseDashboardV2 = featuretypes.MustNewName("use_dashboard_v2")
FeatureEnableMetricsReduction = featuretypes.MustNewName("enable_metrics_reduction")
FeatureUseSpanMetrics = featuretypes.MustNewName("use_span_metrics")
FeatureKafkaSpanEval = featuretypes.MustNewName("kafka_span_eval")
FeatureHideRootUser = featuretypes.MustNewName("hide_root_user")
FeatureGetMetersFromZeus = featuretypes.MustNewName("get_meters_from_zeus")
FeaturePutMetersInZeus = featuretypes.MustNewName("put_meters_in_zeus")
FeatureUseMeterReporter = featuretypes.MustNewName("use_meter_reporter")
FeatureUseJSONBody = featuretypes.MustNewName("use_json_body")
FeatureUseFineGrainedAuthz = featuretypes.MustNewName("use_fine_grained_authz")
FeatureUseDashboardV2 = featuretypes.MustNewName("use_dashboard_v2")
)
func MustNewRegistry() featuretypes.Registry {
@@ -89,14 +88,6 @@ func MustNewRegistry() featuretypes.Registry {
DefaultVariant: featuretypes.MustNewName("disabled"),
Variants: featuretypes.NewBooleanVariants(),
},
&featuretypes.Feature{
Name: FeatureEnableMetricsReduction,
Kind: featuretypes.KindBoolean,
Stage: featuretypes.StageExperimental,
Description: "Controls whether metrics cardinality reduction (buffer/reduced tables) is read by the querier",
DefaultVariant: featuretypes.MustNewName("disabled"),
Variants: featuretypes.NewBooleanVariants(),
},
)
if err != nil {
panic(err)

View File

@@ -341,12 +341,12 @@ func alignedMetricWindow(startMs, endMs int64) (
}
tsAdjustedStartMs, _, distributedTSTable, localTSTable := telemetrymetrics.WhichTSTableToUse(
samplesAdjustedStartMs, flooredEndMs, false, nil,
samplesAdjustedStartMs, flooredEndMs, nil,
)
distributedSamplesTable, localSamplesTable := telemetrymetrics.WhichSamplesTableToUse(
samplesAdjustedStartMs, flooredEndMs,
metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, false, nil,
metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil,
)
return samplesAdjustedStartMs, flooredEndMs, tsAdjustedStartMs, distributedTSTable, localTSTable, distributedSamplesTable, localSamplesTable

View File

@@ -141,7 +141,7 @@ func (m *module) listMetrics(ctx context.Context, orgID valuer.UUID, params *met
sb.Select("DISTINCT metric_name")
if params.Start != nil && params.End != nil {
start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(*params.Start), uint64(*params.End), false, nil)
start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(*params.Start), uint64(*params.End), nil)
sb.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedTsTable))
sb.Where(sb.Between("unix_milli", start, end))
} else {
@@ -527,7 +527,7 @@ func (m *module) InspectMetrics(
return nil, err
}
tsStart, _, tsTable, _ := telemetrymetrics.WhichTSTableToUse(start, end, false, nil)
tsStart, _, tsTable, _ := telemetrymetrics.WhichTSTableToUse(start, end, nil)
tsSb := sqlbuilder.NewSelectBuilder()
tsSb.Select("fingerprint", "labels")
tsSb.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, tsTable))
@@ -971,8 +971,8 @@ func (m *module) fetchMetricsStatsWithSamples(
}
}
start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), false, nil)
distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, false, nil)
start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
countExp := telemetrymetrics.CountExpressionForSamplesTable(distributedSamplesTable)
// Timeseries counts per metric
@@ -1100,7 +1100,7 @@ func (m *module) computeTimeseriesTreemap(ctx context.Context, req *metricsexplo
}
}
start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), false, nil)
start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
totalTSBuilder := sqlbuilder.NewSelectBuilder()
totalTSBuilder.Select("uniq(fingerprint) AS total_time_series")
@@ -1176,8 +1176,8 @@ func (m *module) computeSamplesTreemap(ctx context.Context, req *metricsexplorer
}
}
start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), false, nil)
distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, false, nil)
start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
countExp := telemetrymetrics.CountExpressionForSamplesTable(distributedSamplesTable)
candidateLimit := req.Limit + 50

View File

@@ -91,22 +91,13 @@ func (q *builderQuery[T]) Fingerprint() string {
if a.ComparisonSpaceAggregationParam != nil {
spaceAggParamStr = a.ComparisonSpaceAggregationParam.StringValue()
}
part := fmt.Sprintf("%s:%s:%s:%s:%s",
aggParts = append(aggParts, fmt.Sprintf("%s:%s:%s:%s:%s",
a.MetricName,
a.Temporality.StringValue(),
a.TimeAggregation.StringValue(),
a.SpaceAggregation.StringValue(),
spaceAggParamStr,
)
if a.Reduced {
oneDay := uint64(24 * time.Hour.Milliseconds())
route := "reduced"
if q.toMS-q.fromMS < oneDay && q.fromMS >= uint64(time.Now().UnixMilli())-oneDay {
route = "buffer"
}
part += ":" + route
}
aggParts = append(aggParts, part)
))
}
}
parts = append(parts, fmt.Sprintf("aggs=[%s]", strings.Join(aggParts, ",")))

View File

@@ -92,11 +92,6 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
req.Start = querybuilder.ToMilliSecs(req.Start)
req.End = querybuilder.ToMilliSecs(req.End)
tmplVars := req.Variables
if tmplVars == nil {
tmplVars = make(map[string]qbtypes.VariableItem)
}
event := &qbtypes.QBEvent{
Version: "v5",
NumberOfQueries: len(req.CompositeQuery.Queries),
@@ -116,10 +111,7 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
// We need to set if it is unspecified or adjust it if value is not within recommended range
intervalWarnings := q.adjustStepInterval(req.CompositeQuery.Queries, req.Start, req.End)
queries := make(map[string]qbtypes.Query)
steps := make(map[string]qbtypes.Step)
missingMetricQueries, metricWarnings, err := q.resolveMetricMetadata(ctx, orgID, req.CompositeQuery.Queries, req.Start, req.End)
missingMetricQueries, metricWarnings, err := q.resolveMetricMetadata(ctx, req.CompositeQuery.Queries, req.Start, req.End)
if err != nil {
return nil, err
}
@@ -128,6 +120,64 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
missingMetricQuerySet[name] = true
}
queries, steps, err := q.buildQueries(req, dependencyQueries, missingMetricQuerySet, event)
if err != nil {
return nil, err
}
preseededResults := make(map[string]any)
for _, name := range missingMetricQueries {
switch req.RequestType {
case qbtypes.RequestTypeTimeSeries:
preseededResults[name] = &qbtypes.TimeSeriesData{QueryName: name}
case qbtypes.RequestTypeScalar:
preseededResults[name] = &qbtypes.ScalarData{QueryName: name}
case qbtypes.RequestTypeRaw:
preseededResults[name] = &qbtypes.RawData{QueryName: name}
}
}
qbResp, qbErr := q.run(ctx, orgID, queries, req, steps, event, preseededResults)
if qbResp != nil {
qbResp.QBEvent = event
if len(intervalWarnings) != 0 && req.RequestType == qbtypes.RequestTypeTimeSeries {
if qbResp.Warning == nil {
qbResp.Warning = &qbtypes.QueryWarnData{
Warnings: make([]qbtypes.QueryWarnDataAdditional, len(intervalWarnings)),
}
for idx := range intervalWarnings {
qbResp.Warning.Warnings[idx] = qbtypes.QueryWarnDataAdditional{Message: intervalWarnings[idx]}
}
}
}
if len(metricWarnings) > 0 {
if qbResp.Warning == nil {
qbResp.Warning = &qbtypes.QueryWarnData{}
}
for _, w := range metricWarnings {
qbResp.Warning.Warnings = append(qbResp.Warning.Warnings, qbtypes.QueryWarnDataAdditional{
Message: w,
})
}
}
}
return qbResp, qbErr
}
func (q *querier) buildQueries(
req *qbtypes.QueryRangeRequest,
dependencyQueries map[string]bool,
missingMetricQuerySet map[string]bool,
event *qbtypes.QBEvent,
) (map[string]qbtypes.Query, map[string]qbtypes.Step, error) {
tmplVars := req.Variables
if tmplVars == nil {
tmplVars = make(map[string]qbtypes.VariableItem)
}
queries := make(map[string]qbtypes.Query)
steps := make(map[string]qbtypes.Step)
for _, query := range req.CompositeQuery.Queries {
queryName := query.GetQueryName()
@@ -140,7 +190,7 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
case qbtypes.QueryTypePromQL:
promQuery, ok := query.Spec.(qbtypes.PromQuery)
if !ok {
return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid promql query spec %T", query.Spec)
return nil, nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid promql query spec %T", query.Spec)
}
promqlQuery := newPromqlQuery(q.logger, q.promEngine, promQuery, qbtypes.TimeRange{From: req.Start, To: req.End}, req.RequestType, tmplVars)
queries[promQuery.Name] = promqlQuery
@@ -148,14 +198,14 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
case qbtypes.QueryTypeClickHouseSQL:
chQuery, ok := query.Spec.(qbtypes.ClickHouseQuery)
if !ok {
return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid clickhouse query spec %T", query.Spec)
return nil, nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid clickhouse query spec %T", query.Spec)
}
chSQLQuery := newchSQLQuery(q.logger, q.telemetryStore, chQuery, nil, qbtypes.TimeRange{From: req.Start, To: req.End}, req.RequestType, tmplVars)
queries[chQuery.Name] = chSQLQuery
case qbtypes.QueryTypeTraceOperator:
traceOpQuery, ok := query.Spec.(qbtypes.QueryBuilderTraceOperator)
if !ok {
return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid trace operator query spec %T", query.Spec)
return nil, nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid trace operator query spec %T", query.Spec)
}
toq := &traceOperatorQuery{
telemetryStore: q.telemetryStore,
@@ -208,46 +258,12 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
queries[spec.Name] = bq
steps[spec.Name] = spec.StepInterval
default:
return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "unsupported builder spec type %T", query.Spec)
return nil, nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "unsupported builder spec type %T", query.Spec)
}
}
}
preseededResults := make(map[string]any)
for _, name := range missingMetricQueries {
switch req.RequestType {
case qbtypes.RequestTypeTimeSeries:
preseededResults[name] = &qbtypes.TimeSeriesData{QueryName: name}
case qbtypes.RequestTypeScalar:
preseededResults[name] = &qbtypes.ScalarData{QueryName: name}
case qbtypes.RequestTypeRaw:
preseededResults[name] = &qbtypes.RawData{QueryName: name}
}
}
qbResp, qbErr := q.run(ctx, orgID, queries, req, steps, event, preseededResults)
if qbResp != nil {
qbResp.QBEvent = event
if len(intervalWarnings) != 0 && req.RequestType == qbtypes.RequestTypeTimeSeries {
if qbResp.Warning == nil {
qbResp.Warning = &qbtypes.QueryWarnData{
Warnings: make([]qbtypes.QueryWarnDataAdditional, len(intervalWarnings)),
}
for idx := range intervalWarnings {
qbResp.Warning.Warnings[idx] = qbtypes.QueryWarnDataAdditional{Message: intervalWarnings[idx]}
}
}
}
if len(metricWarnings) > 0 {
if qbResp.Warning == nil {
qbResp.Warning = &qbtypes.QueryWarnData{}
}
for _, w := range metricWarnings {
qbResp.Warning.Warnings = append(qbResp.Warning.Warnings, qbtypes.QueryWarnDataAdditional{
Message: w,
})
}
}
}
return qbResp, qbErr
return queries, steps, nil
}
func (q *querier) populateQBEvent(event *qbtypes.QBEvent, queries []qbtypes.QueryEnvelope) {
@@ -304,7 +320,7 @@ func (q *querier) populateQBEvent(event *qbtypes.QBEvent, queries []qbtypes.Quer
// resolved: never-seen metrics and dormant metrics (seen but no data in
// the query window).
// - err: Internal when a metadata fetch fails.
func (q *querier) resolveMetricMetadata(ctx context.Context, orgID valuer.UUID, queries []qbtypes.QueryEnvelope, start, end uint64) (missingMetricQueries []string, metricWarnings []string, err error) {
func (q *querier) resolveMetricMetadata(ctx context.Context, queries []qbtypes.QueryEnvelope, start, end uint64) (missingMetricQueries []string, metricWarnings []string, err error) {
metricNames := make([]string, 0)
for idx := range queries {
if queries[idx].Type != qbtypes.QueryTypeBuilder {
@@ -325,7 +341,7 @@ func (q *querier) resolveMetricMetadata(ctx context.Context, orgID valuer.UUID,
return nil, nil, nil
}
metricTemporality, metricTypes, reducedMetricsSet, err := q.metadataStore.FetchTemporalityAndTypeMulti(ctx, orgID, start, end, metricNames...)
metricTemporality, metricTypes, err := q.metadataStore.FetchTemporalityAndTypeMulti(ctx, start, end, metricNames...)
if err != nil {
q.logger.WarnContext(ctx, "failed to fetch metric temporality", errors.Attr(err), slog.Any("metrics", metricNames))
return nil, nil, errors.NewInternalf(errors.CodeInternal, "failed to fetch metrics temporality")
@@ -362,9 +378,6 @@ func (q *querier) resolveMetricMetadata(ctx context.Context, orgID valuer.UUID,
if err := spec.Aggregations[i].ValidateForType(); err != nil {
return nil, nil, err
}
if reducedMetricsSet[spec.Aggregations[i].MetricName] {
spec.Aggregations[i].Reduced = true
}
presentAggregations = append(presentAggregations, spec.Aggregations[i])
}
if len(presentAggregations) == 0 {

View File

@@ -2136,12 +2136,12 @@ func (t *telemetryMetaStore) GetAllValues(ctx context.Context, fieldValueSelecto
return values, complete, nil
}
func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
if metricName == "" {
return metrictypes.Unknown, errors.Newf(errors.TypeInternal, errors.CodeInternal, "metric name cannot be empty")
}
temporalityMap, err := t.FetchTemporalityMulti(ctx, orgID, queryTimeRangeStartTs, queryTimeRangeEndTs, metricName)
temporalityMap, err := t.FetchTemporalityMulti(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricName)
if err != nil {
return metrictypes.Unknown, err
}
@@ -2154,27 +2154,25 @@ func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, orgID valuer.
return temporality, nil
}
func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
temporalities, _, _, err := t.FetchTemporalityAndTypeMulti(ctx, orgID, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
temporalities, _, err := t.FetchTemporalityAndTypeMulti(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
return temporalities, err
}
func (t *telemetryMetaStore) FetchTemporalityAndTypeMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error) {
func (t *telemetryMetaStore) FetchTemporalityAndTypeMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {
if len(metricNames) == 0 {
return make(map[string]metrictypes.Temporality), make(map[string]metrictypes.Type), make(map[string]bool), nil
return make(map[string]metrictypes.Temporality), make(map[string]metrictypes.Type), nil
}
reductionEnabled := t.fl.BooleanOrEmpty(ctx, flagger.FeatureEnableMetricsReduction, featuretypes.NewFlaggerEvaluationContext(orgID))
temporalities := make(map[string]metrictypes.Temporality)
types := make(map[string]metrictypes.Type)
metricsTemporality, metricTypes, reduced, err := t.fetchMetricsTemporalityAndType(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, reductionEnabled, metricNames...)
metricsTemporality, metricTypes, err := t.fetchMetricsTemporalityAndType(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
if err != nil {
return nil, nil, nil, err
return nil, nil, err
}
meterMetricsTemporality, meterMetricsTypes, err := t.fetchMeterSourceMetricsTemporalityAndType(ctx, metricNames...)
if err != nil {
return nil, nil, nil, err
return nil, nil, err
}
// For metrics not found in the database, set to Unknown
@@ -2199,10 +2197,10 @@ func (t *telemetryMetaStore) FetchTemporalityAndTypeMulti(ctx context.Context, o
}
}
return temporalities, types, reduced, nil
return temporalities, types, nil
}
func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, reductionEnabled bool, metricNames ...string) (map[string][]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error) {
func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string][]metrictypes.Temporality, map[string]metrictypes.Type, error) {
ctx = ctxtypes.NewContextWithCommentVals(ctx, map[string]string{
instrumentationtypes.TelemetrySignal: telemetrytypes.SignalMetrics.StringValue(),
instrumentationtypes.CodeNamespace: "metadata",
@@ -2210,58 +2208,48 @@ func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context,
})
temporalities := make(map[string][]metrictypes.Temporality)
types := make(map[string]metrictypes.Type)
reduced := make(map[string]bool)
adjustedStartTs, adjustedEndTs, tsTableName, _ := telemetrymetrics.WhichTSTableToUse(queryTimeRangeStartTs, queryTimeRangeEndTs, false, nil)
adjustedStartTs, adjustedEndTs, tsTableName, _ := telemetrymetrics.WhichTSTableToUse(queryTimeRangeStartTs, queryTimeRangeEndTs, nil)
cols := []string{"metric_name", "temporality", "any(type) AS type", "any(is_monotonic) as is_monotonic"}
// Build query to fetch temporality for all metrics
// We use attr_string_value where attr_name = '__temporality__'
// Note: The columns are mixed in the current data - temporality column contains metric_name
// and metric_name column contains temporality value, so we use the correct mapping
sb := sqlbuilder.Select(
"metric_name",
"temporality",
"any(type) AS type",
"any(is_monotonic) as is_monotonic",
).
From(t.metricsDBName + "." + tsTableName)
// When reduction is enabled, fold the reduced-catalog presence check into the
// same query so a metric's reduced status comes back in one round trip.
var reducedArgs []any
if reductionEnabled {
rs := sqlbuilder.NewSelectBuilder()
rs.Select("metric_name")
rs.From(t.metricsDBName + "." + telemetrymetrics.TimeseriesV4ReducedTableName)
rs.Where(rs.In("metric_name", metricNames), rs.GTE("unix_milli", adjustedStartTs), rs.LT("unix_milli", adjustedEndTs))
rs.GroupBy("metric_name")
rsQuery, rsArgs := rs.BuildWithFlavor(sqlbuilder.ClickHouse)
cols = append(cols, fmt.Sprintf("metric_name GLOBAL IN (%s) AS reduced", rsQuery))
reducedArgs = rsArgs
}
sb := sqlbuilder.NewSelectBuilder()
sb.Select(cols...)
sb.From(t.metricsDBName + "." + tsTableName)
// Filter by metric names (in the temporality column due to data mix-up)
sb.Where(
sb.In("metric_name", metricNames),
sb.GTE("unix_milli", adjustedStartTs),
sb.LT("unix_milli", adjustedEndTs),
)
sb.GroupBy("metric_name", "temporality")
query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, reducedArgs...)
query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
t.logger.DebugContext(ctx, "fetching metric temporality", slog.String("query", query), slog.Any("args", args))
rows, err := t.telemetrystore.ClickhouseDB().Query(ctx, query, args...)
if err != nil {
return nil, nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch metric temporality")
return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch metric temporality")
}
defer rows.Close()
// Process results
for rows.Next() {
var metricName string
var temporality metrictypes.Temporality
var metricType metrictypes.Type
var isMonotonic bool
var isReduced uint8
dest := []any{&metricName, &temporality, &metricType, &isMonotonic}
if reductionEnabled {
dest = append(dest, &isReduced)
}
if err := rows.Scan(dest...); err != nil {
return nil, nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
if err := rows.Scan(&metricName, &temporality, &metricType, &isMonotonic); err != nil {
return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
}
if temporality != metrictypes.Unknown {
temporalities[metricName] = append(temporalities[metricName], temporality)
@@ -2270,15 +2258,12 @@ func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context,
metricType = metrictypes.GaugeType
}
types[metricName] = metricType
if isReduced != 0 {
reduced[metricName] = true
}
}
if err := rows.Err(); err != nil {
return nil, nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
}
return temporalities, types, reduced, nil
return temporalities, types, nil
}
func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporalityAndType(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {

View File

@@ -1,157 +0,0 @@
package telemetrymetrics
import (
"context"
"testing"
"time"
"github.com/SigNoz/signoz/pkg/flagger"
"github.com/SigNoz/signoz/pkg/instrumentation/instrumentationtest"
"github.com/SigNoz/signoz/pkg/types/metrictypes"
qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes/telemetrytypestest"
"github.com/stretchr/testify/require"
)
func reducedQuery(metric string, ty metrictypes.Type, temp metrictypes.Temporality, ta metrictypes.TimeAggregation, sa metrictypes.SpaceAggregation) qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation] {
return qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
Signal: telemetrytypes.SignalMetrics,
StepInterval: qbtypes.Step{Duration: 5 * time.Minute},
Aggregations: []qbtypes.MetricAggregation{{
MetricName: metric,
Type: ty,
Temporality: temp,
TimeAggregation: ta,
SpaceAggregation: sa,
Reduced: true,
}},
}
}
func TestReducedStatementBuilder(t *testing.T) {
cases := []struct {
name string
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]
expected qbtypes.Statement
}{
{
name: "gauge_sum_latest",
query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, anyLast(last) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, argMax(value, unix_milli) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
},
},
{
name: "gauge_avg_avg",
query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationAvg, metrictypes.SpaceAggregationAvg),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
},
},
{
name: "gauge_min_min",
query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationMin, metrictypes.SpaceAggregationMin),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(min) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(value) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`min`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
},
},
{
name: "gauge_max_max",
query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationMax, metrictypes.SpaceAggregationMax),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(value) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`max`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
},
},
{
name: "counter_sum_rate",
query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationSum),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) / 300 AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0, "test.metric", uint64(1746999600000), uint64(1747172760000), "test.metric", uint64(1746999600000), uint64(1747172760000), false},
},
},
{
name: "counter_avg_increase",
query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationIncrease, metrictypes.SpaceAggregationAvg),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0, "test.metric", uint64(1746999600000), uint64(1747172760000), "test.metric", uint64(1746999600000), uint64(1747172760000), false},
},
},
{
name: "counter_min_omitted",
query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationMin),
expected: qbtypes.Statement{
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0},
},
},
{
name: "counter_max_omitted",
query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationMax),
expected: qbtypes.Statement{
Query: "WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0},
},
},
{
name: "histogram_p99",
query: reducedQuery("test.metric", metrictypes.HistogramType, metrictypes.Cumulative, metrictypes.TimeAggregationUnspecified, metrictypes.SpaceAggregationPercentile99),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, `le`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, sum(value) / 300 AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts, `le`), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
},
},
{
name: "summary_avg",
query: reducedQuery("test.metric", metrictypes.SummaryType, metrictypes.Unspecified, metrictypes.TimeAggregationAvg, metrictypes.SpaceAggregationAvg),
expected: qbtypes.Statement{
Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
Args: []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
},
},
}
fm := NewFieldMapper()
cb := NewConditionBuilder(fm)
fl, err := flagger.New(context.Background(), instrumentationtest.New().ToProviderSettings(), flagger.Config{}, flagger.MustNewRegistry())
require.NoError(t, err)
sb := NewMetricQueryStatementBuilder(instrumentationtest.New().ToProviderSettings(), telemetrytypestest.NewMockMetadataStore(), fm, cb, fl)
const start, end = uint64(1747000000000), uint64(1747172800000)
for _, c := range cases {
t.Run(c.name, func(t *testing.T) {
got, err := sb.Build(context.Background(), start, end, qbtypes.RequestTypeTimeSeries, c.query, nil)
require.NoError(t, err)
require.Equal(t, c.expected.Query, got.Query)
require.Equal(t, c.expected.Args, got.Args)
})
}
t.Run("buffer_recent_window", func(t *testing.T) {
now := time.Now().UnixMilli()
q := reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum)
got, err := sb.Build(context.Background(), uint64(now-2*time.Hour.Milliseconds()), uint64(now), qbtypes.RequestTypeTimeSeries, q, nil)
require.NoError(t, err)
require.Contains(t, got.Query, "signoz_metrics.distributed_samples_v4_buffer")
require.Contains(t, got.Query, "signoz_metrics.time_series_v4_buffer")
require.Contains(t, got.Query, "is_reduced")
require.NotContains(t, got.Query, "UNION ALL")
})
t.Run("not_reduced", func(t *testing.T) {
q := reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum)
q.Aggregations[0].Reduced = false
got, err := sb.Build(context.Background(), start, end, qbtypes.RequestTypeTimeSeries, q, nil)
require.NoError(t, err)
require.NotContains(t, got.Query, "UNION ALL")
require.NotContains(t, got.Query, "reduced")
require.NotContains(t, got.Query, "buffer")
})
}

View File

@@ -4,7 +4,6 @@ import (
"context"
"fmt"
"log/slog"
"time"
"github.com/SigNoz/signoz/pkg/factory"
"github.com/SigNoz/signoz/pkg/flagger"
@@ -181,30 +180,19 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
query.Aggregations[0].SpaceAggregation = metrictypes.SpaceAggregationSum
}
agg := query.Aggregations[0]
// A reduced metric reads the raw buffer for recent short windows, and
// samples_v4/agg (unioned with the reduced tables) otherwise. The buffer is
// shaped exactly like samples_v4 / time_series_v4, so once the table names are
// chosen the rest of the pipeline is unchanged.
useBuffer := agg.Reduced &&
end-start < oneDayInMilliseconds &&
start >= uint64(time.Now().UnixMilli())-oneDayInMilliseconds
samplesTable, _ := WhichSamplesTableToUse(start, end, agg.Type, agg.TimeAggregation, useBuffer, agg.TableHints)
tsStart, tsEnd, _, tsTable := WhichTSTableToUse(start, end, useBuffer, agg.TableHints)
var timeSeriesCTE string
var timeSeriesCTEArgs []any
var err error
if timeSeriesCTE, timeSeriesCTEArgs, err = b.buildTimeSeriesCTE(ctx, tsStart, tsEnd, query, keys, variables, tsTable); err != nil {
// time_series_cte
// this is applicable for all the queries
if timeSeriesCTE, timeSeriesCTEArgs, err = b.buildTimeSeriesCTE(ctx, start, end, query, keys, variables); err != nil {
return nil, err
}
if qbtypes.CanShortCircuitDelta(query.Aggregations[0]) {
// spatial_aggregation_cte directly for certain delta queries
if frag, args, err := b.buildTemporalAggDeltaFastPath(start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
if frag, args, err := b.buildTemporalAggDeltaFastPath(start, end, query, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
return nil, err
} else if frag != "" {
cteFragments = append(cteFragments, frag)
@@ -212,7 +200,7 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
}
} else {
// temporal_aggregation_cte
if frag, args, err := b.buildTemporalAggregationCTE(ctx, start, end, query, keys, samplesTable, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
if frag, args, err := b.buildTemporalAggregationCTE(ctx, start, end, query, keys, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
return nil, err
} else if frag != "" {
cteFragments = append(cteFragments, frag)
@@ -226,188 +214,18 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
}
}
var reducedFragments []string
var reducedArgs [][]any
if agg.Reduced && !useBuffer {
var tsCTE string
var tsArgs []any
if tsCTE, tsArgs, err = b.buildReducedTimeSeriesCTE(ctx, start, end, query, keys, variables); err != nil {
return nil, err
}
if temporalFrag, temporalArgs, ok := b.buildReducedTemporalAggregationCTE(start, end, query, tsCTE, tsArgs); ok {
spatialFrag, spatialArgs := b.buildReducedSpatialAggregationCTE(query)
reducedFragments = []string{temporalFrag, spatialFrag}
reducedArgs = [][]any{temporalArgs, spatialArgs}
}
}
// reset the query to the original state
query.Aggregations[0].SpaceAggregation = origSpaceAgg
query.Aggregations[0].TimeAggregation = origTimeAgg
query.GroupBy = origGroupBy
mainStmt, err := b.BuildFinalSelect(cteFragments, cteArgs, query)
if err != nil {
return nil, err
}
if reducedFragments == nil {
return mainStmt, nil
}
reducedStmt, err := b.BuildFinalSelect(reducedFragments, reducedArgs, query)
if err != nil {
return nil, err
}
return unionStatements(mainStmt, reducedStmt, query)
}
func unionStatements(main, reduced *qbtypes.Statement, query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]) (*qbtypes.Statement, error) {
orderBy := "ts"
for _, g := range query.GroupBy {
orderBy = fmt.Sprintf("`%s`, ", g.Name) + orderBy
}
q := fmt.Sprintf("SELECT * FROM (%s) UNION ALL SELECT * FROM (%s) ORDER BY %s", main.Query, reduced.Query, orderBy)
args := append(append([]any{}, main.Args...), reduced.Args...)
warnings := append(append([]string{}, main.Warnings...), reduced.Warnings...)
return &qbtypes.Statement{Query: q, Args: args, Warnings: warnings}, nil
}
func (b *MetricQueryStatementBuilder) buildReducedTimeSeriesCTE(
ctx context.Context,
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
keys map[string][]*telemetrytypes.TelemetryFieldKey,
variables map[string]qbtypes.VariableItem,
) (string, []any, error) {
sb := sqlbuilder.NewSelectBuilder()
var preparedWhereClause querybuilder.PreparedWhereClause
var err error
if query.Filter != nil && query.Filter.Expression != "" {
preparedWhereClause, err = querybuilder.PrepareWhereClause(query.Filter.Expression, querybuilder.FilterExprVisitorOpts{
Context: ctx,
Logger: b.logger,
FieldMapper: b.fm,
ConditionBuilder: b.cb,
FieldKeys: keys,
FullTextColumn: &telemetrytypes.TelemetryFieldKey{Name: "labels"},
Variables: variables,
StartNs: start,
EndNs: end,
})
if err != nil {
return "", nil, err
}
}
sb.From(fmt.Sprintf("%s.%s", DBName, TimeseriesV4ReducedTableName))
sb.Select("fingerprint")
for _, g := range query.GroupBy {
col, err := b.fm.ColumnExpressionFor(ctx, start, end, &g.TelemetryFieldKey, keys)
if err != nil {
return "", nil, err
}
sb.SelectMore(col)
}
sb.Where(
sb.In("metric_name", query.Aggregations[0].MetricName),
sb.GTE("unix_milli", start),
sb.LTE("unix_milli", end),
sb.EQ("__normalized", false),
)
if !preparedWhereClause.IsEmpty() {
sb.AddWhereClause(preparedWhereClause.WhereClause)
}
sb.GroupBy("fingerprint")
sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
return fmt.Sprintf("(%s) AS filtered_time_series", q), args, nil
}
func (b *MetricQueryStatementBuilder) buildReducedTemporalAggregationCTE(
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
timeSeriesCTE string,
timeSeriesCTEArgs []any,
) (string, []any, bool) {
agg := query.Aggregations[0]
stepSec := int64(query.StepInterval.Seconds())
value, weight, ok := ReducedValueColumn(agg.Type, agg.SpaceAggregation)
if !ok {
return "", nil, false
}
// dedup recomputed buckets: latest computed_at wins per (series, 60s bucket)
dedup := sqlbuilder.NewSelectBuilder()
dedup.Select("reduced_fingerprint AS fingerprint", "unix_milli")
dedup.SelectMore(fmt.Sprintf("argMax(%s, computed_at) AS value", value))
if weight != "" {
dedup.SelectMore(fmt.Sprintf("argMax(%s, computed_at) AS weight", weight))
}
dedup.From(fmt.Sprintf("%s.%s", DBName, WhichReducedSamplesTableToUse(agg.Type)))
dedup.Where(
dedup.In("metric_name", agg.MetricName),
dedup.GTE("unix_milli", start),
dedup.LT("unix_milli", end),
)
dedup.GroupBy("reduced_fingerprint", "unix_milli")
dedupQuery, dedupArgs := dedup.BuildWithFlavor(sqlbuilder.ClickHouse)
sb := sqlbuilder.NewSelectBuilder()
sb.Select("fingerprint")
sb.SelectMore(fmt.Sprintf("toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(%d)) AS ts", stepSec))
for _, g := range query.GroupBy {
sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
}
sb.SelectMore(fmt.Sprintf("%s AS per_series_value", ReducedTimeAggregationColumn(agg.TimeAggregation, stepSec)))
if weight != "" {
// count_series is a series count, not additive over time, so the avg
// denominator is reduced with avg
sb.SelectMore("avg(weight) AS per_series_weight")
}
sb.From(fmt.Sprintf("(%s) AS points", dedupQuery))
sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
sb.GroupBy("fingerprint", "ts")
sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
initArgs := append(append([]any{}, dedupArgs...), timeSeriesCTEArgs...)
q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, initArgs...)
return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, true
}
func (b *MetricQueryStatementBuilder) buildReducedSpatialAggregationCTE(
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
) (string, []any) {
spatial := "sum(per_series_value)"
switch query.Aggregations[0].SpaceAggregation {
case metrictypes.SpaceAggregationAvg:
spatial = "sum(per_series_value) / sum(per_series_weight)"
case metrictypes.SpaceAggregationMin:
spatial = "min(per_series_value)"
case metrictypes.SpaceAggregationMax:
spatial = "max(per_series_value)"
}
sb := sqlbuilder.NewSelectBuilder()
sb.Select("ts")
for _, g := range query.GroupBy {
sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
}
sb.SelectMore(spatial + " AS value")
sb.From("__temporal_aggregation_cte")
sb.GroupBy("ts")
sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args
// final SELECT
return b.BuildFinalSelect(cteFragments, cteArgs, query)
}
func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
samplesTable string,
timeSeriesCTE string,
timeSeriesCTEArgs []any,
) (string, []any, error) {
@@ -424,7 +242,8 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
}
aggCol, err := AggregationColumnForSamplesTable(
samplesTable, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation,
start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality,
query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints,
)
if err != nil {
return "", nil, err
@@ -441,7 +260,8 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
sb.SelectMore(fmt.Sprintf("%s AS value", aggCol))
sb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
sb.Where(
sb.In("metric_name", query.Aggregations[0].MetricName),
@@ -461,7 +281,6 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
keys map[string][]*telemetrytypes.TelemetryFieldKey,
variables map[string]qbtypes.VariableItem,
tsTable string,
) (string, []any, error) {
sb := sqlbuilder.NewSelectBuilder()
@@ -485,7 +304,8 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
}
}
sb.From(fmt.Sprintf("%s.%s", DBName, tsTable))
start, end, _, tbl := WhichTSTableToUse(start, end, query.Aggregations[0].TableHints)
sb.From(fmt.Sprintf("%s.%s", DBName, tbl))
sb.Select("fingerprint")
for _, g := range query.GroupBy {
@@ -511,12 +331,6 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
sb.EQ("__normalized", false),
)
// the buffer holds both raw rows and the reduced catalog rows; the raw read
// only wants the original series
if tsTable == TimeseriesV4BufferLocalTableName {
sb.Where(sb.EQ("is_reduced", false))
}
if !preparedWhereClause.IsEmpty() {
sb.AddWhereClause(preparedWhereClause.WhereClause)
}
@@ -533,23 +347,21 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggregationCTE(
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
_ map[string][]*telemetrytypes.TelemetryFieldKey,
samplesTable string,
timeSeriesCTE string,
timeSeriesCTEArgs []any,
) (string, []any, error) {
if query.Aggregations[0].Temporality == metrictypes.Delta {
return b.buildTemporalAggDelta(ctx, start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs)
return b.buildTemporalAggDelta(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
} else if query.Aggregations[0].Temporality != metrictypes.Multiple {
return b.buildTemporalAggCumulativeOrUnspecified(ctx, start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs)
return b.buildTemporalAggCumulativeOrUnspecified(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
}
return b.buildTemporalAggForMultipleTemporalities(ctx, start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs)
return b.buildTemporalAggForMultipleTemporalities(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
}
func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
_ context.Context,
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
samplesTable string,
timeSeriesCTE string,
timeSeriesCTEArgs []any,
) (string, []any, error) {
@@ -566,7 +378,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
}
aggCol, err := AggregationColumnForSamplesTable(samplesTable, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation)
aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
if err != nil {
return "", nil, err
}
@@ -577,7 +389,8 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
sb.SelectMore(fmt.Sprintf("%s AS per_series_value", aggCol))
sb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
sb.Where(
sb.In("metric_name", query.Aggregations[0].MetricName),
@@ -596,7 +409,6 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
_ context.Context,
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
samplesTable string,
timeSeriesCTE string,
timeSeriesCTEArgs []any,
) (string, []any, error) {
@@ -612,13 +424,14 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
baseSb.SelectMore(fmt.Sprintf("`%s`", g.Name))
}
aggCol, err := AggregationColumnForSamplesTable(samplesTable, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation)
aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
if err != nil {
return "", nil, err
}
baseSb.SelectMore(fmt.Sprintf("%s AS per_series_value", aggCol))
baseSb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
baseSb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
baseSb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
baseSb.Where(
baseSb.In("metric_name", query.Aggregations[0].MetricName),
@@ -662,7 +475,6 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
_ context.Context,
start, end uint64,
query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
samplesTable string,
timeSeriesCTE string,
timeSeriesCTEArgs []any,
) (string, []any, error) {
@@ -677,11 +489,11 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
}
aggForDeltaTemporality, err := AggregationColumnForSamplesTable(samplesTable, metrictypes.Delta, query.Aggregations[0].TimeAggregation)
aggForDeltaTemporality, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Delta, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
if err != nil {
return "", nil, err
}
aggForCumulativeTemporality, err := AggregationColumnForSamplesTable(samplesTable, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation)
aggForCumulativeTemporality, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
if err != nil {
return "", nil, err
}
@@ -709,7 +521,8 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
sb.SelectMore(expr)
}
sb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
sb.Where(
sb.In("metric_name", query.Aggregations[0].MetricName),

View File

@@ -30,17 +30,6 @@ const (
TimeseriesV41weekLocalTableName = "time_series_v4_1week"
AttributesMetadataTableName = "distributed_metadata"
AttributesMetadataLocalTableName = "metadata"
// The buffer holds raw points for ~24h; the reduced tables hold 60s
// aggregates of dropped-label series.
SamplesV4BufferTableName = "distributed_samples_v4_buffer"
SamplesV4BufferLocalTableName = "samples_v4_buffer"
TimeseriesV4BufferTableName = "distributed_time_series_v4_buffer"
TimeseriesV4BufferLocalTableName = "time_series_v4_buffer"
SamplesV4ReducedLastTableName = "distributed_samples_v4_reduced_last_60s"
SamplesV4ReducedSumTableName = "distributed_samples_v4_reduced_sum_60s"
TimeseriesV4ReducedTableName = "distributed_time_series_v4_reduced"
TimeseriesV4ReducedLocalTableName = "time_series_v4_reduced"
)
var (
@@ -60,16 +49,8 @@ var (
// in that order.
func WhichTSTableToUse(
start, end uint64,
useBuffer bool,
tableHints *metrictypes.MetricTableHints,
) (uint64, uint64, string, string) {
// the buffer holds the recent raw window for reduced metrics and has the same
// shape as time_series_v4; round the start to the hour like the v4 table.
if useBuffer {
start = start - (start % (oneHourInMilliseconds))
return start, end, TimeseriesV4BufferTableName, TimeseriesV4BufferLocalTableName
}
// if we have a hint for the table, we need to use it
// the hint will be used to override the default table selection logic
if tableHints != nil {
@@ -168,20 +149,14 @@ func WhichSamplesTableToUse(
start, end uint64,
metricType metrictypes.Type,
timeAggregation metrictypes.TimeAggregation,
useBuffer bool,
tableHints *metrictypes.MetricTableHints,
) (string, string) {
// the buffer holds the recent raw window for reduced metrics; same shape as samples_v4
if useBuffer {
return SamplesV4BufferTableName, SamplesV4BufferLocalTableName
}
// if we have a hint for the table, we need to use it
// the hint will be used to override the default table selection logic.
// SamplesTableName is the distributed name; derive the local via switch.
if tableHints != nil && tableHints.SamplesTableName != "" {
switch tableHints.SamplesTableName {
case SamplesV4TableName, SamplesV4BufferTableName:
case SamplesV4TableName:
return SamplesV4TableName, SamplesV4LocalTableName
case SamplesV4Agg5mTableName:
return SamplesV4Agg5mTableName, SamplesV4Agg5mLocalTableName
@@ -213,10 +188,13 @@ func WhichSamplesTableToUse(
}
func AggregationColumnForSamplesTable(
tableName string,
start, end uint64,
metricType metrictypes.Type,
temporality metrictypes.Temporality,
timeAggregation metrictypes.TimeAggregation,
tableHints *metrictypes.MetricTableHints,
) (string, error) {
tableName, _ := WhichSamplesTableToUse(start, end, metricType, timeAggregation, tableHints)
var aggregationColumn string
switch temporality {
case metrictypes.Delta:
@@ -224,7 +202,7 @@ func AggregationColumnForSamplesTable(
// although it doesn't make sense to use anyLast, avg, min, max, count on delta metrics,
// we are keeping it here to make sure that query will not be invalid
switch tableName {
case SamplesV4TableName, SamplesV4BufferTableName:
case SamplesV4TableName:
switch timeAggregation {
case metrictypes.TimeAggregationLatest:
aggregationColumn = "anyLast(value)"
@@ -266,7 +244,7 @@ func AggregationColumnForSamplesTable(
// for cumulative metrics, we only support `RATE`/`INCREASE`. The max value in window is
// used to calculate the sum which is then divided by the window size to get the rate
switch tableName {
case SamplesV4TableName, SamplesV4BufferTableName:
case SamplesV4TableName:
switch timeAggregation {
case metrictypes.TimeAggregationLatest:
aggregationColumn = "anyLast(value)"
@@ -306,7 +284,7 @@ func AggregationColumnForSamplesTable(
}
case metrictypes.Unspecified:
switch tableName {
case SamplesV4TableName, SamplesV4BufferTableName:
case SamplesV4TableName:
switch timeAggregation {
case metrictypes.TimeAggregationLatest:
aggregationColumn = "anyLast(value)"
@@ -354,65 +332,6 @@ func AggregationColumnForSamplesTable(
return aggregationColumn, nil
}
// WhichReducedSamplesTableToUse returns the 60s reduced samples table for a metric
// type: the last_60s table for gauge-like series, the sum_60s table for counters
// and histograms.
func WhichReducedSamplesTableToUse(metricType metrictypes.Type) string {
if metricType == metrictypes.SumType || metricType == metrictypes.HistogramType {
return SamplesV4ReducedSumTableName
}
return SamplesV4ReducedLastTableName
}
// ReducedValueColumn returns the reduced value column (and the avg-denominator
// weight) for a space aggregation. The reduced columns are pre-aggregated across
// the original series, so the space aggregation picks the underlying value; the
// sum table only has `sum`, so min/max across series have no column (ok=false).
func ReducedValueColumn(metricType metrictypes.Type, space metrictypes.SpaceAggregation) (value, weight string, ok bool) {
if metricType == metrictypes.SumType || metricType == metrictypes.HistogramType {
switch space {
case metrictypes.SpaceAggregationSum:
return "`sum`", "", true
case metrictypes.SpaceAggregationAvg:
return "`sum`", "`count_series`", true
}
return "", "", false
}
switch space {
case metrictypes.SpaceAggregationSum:
return "`sum_last`", "", true
case metrictypes.SpaceAggregationAvg:
return "`sum_last`", "`count_series`", true
case metrictypes.SpaceAggregationMin:
return "`min`", "", true
case metrictypes.SpaceAggregationMax:
return "`max`", "", true
}
return "", "", false
}
// ReducedTimeAggregationColumn applies the time aggregation to the reduced `value`
// column over the step's 60s buckets. latest uses argMax over the bucket timestamp
// (the buckets have no read order); rate divides the per-step sum by the step.
func ReducedTimeAggregationColumn(timeAggregation metrictypes.TimeAggregation, stepSec int64) string {
switch timeAggregation {
case metrictypes.TimeAggregationLatest:
return "argMax(value, unix_milli)"
case metrictypes.TimeAggregationAvg:
return "avg(value)"
case metrictypes.TimeAggregationMin:
return "min(value)"
case metrictypes.TimeAggregationMax:
return "max(value)"
case metrictypes.TimeAggregationCount:
return "count(value)"
case metrictypes.TimeAggregationRate:
return fmt.Sprintf("sum(value) / %d", stepSec)
default: // sum, increase
return "sum(value)"
}
}
func AggregationQueryForHistogramCountWithParams(param *metrictypes.ComparisonSpaceAggregationParam) (string, error) {
if param == nil {
return "", errors.NewInvalidInputf(errors.CodeInvalidInput, "no aggregation param provided for histogram count")

View File

@@ -480,9 +480,7 @@ type MetricAggregation struct {
// value filter to apply to the query
ValueFilter *metrictypes.MetricValueFilter `json:"-"`
// reduce to operator for metric scalar requests
ReduceTo ReduceTo `json:"reduceTo,omitzero"`
Reduced bool `json:"-"`
ReduceTo ReduceTo `json:"reduceTo,omitempty"`
}
// Copy creates a deep copy of MetricAggregation.

View File

@@ -4,7 +4,6 @@ import (
"context"
"github.com/SigNoz/signoz/pkg/types/metrictypes"
"github.com/SigNoz/signoz/pkg/valuer"
)
// MetadataStore is the interface for the telemetry metadata store.
@@ -27,12 +26,12 @@ type MetadataStore interface {
GetAllValues(ctx context.Context, fieldValueSelector *FieldValueSelector) (*TelemetryFieldValues, bool, error)
// FetchTemporality fetches the temporality for metric
FetchTemporality(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error)
FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error)
// FetchTemporalityMulti fetches the temporality for multiple metrics
FetchTemporalityMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error)
FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error)
FetchTemporalityAndTypeMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error)
FetchTemporalityAndTypeMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error)
// ListLogsJSONIndexes lists the JSON indexes for the logs table.
ListLogsJSONIndexes(ctx context.Context, filters ...string) ([]TelemetryFieldKeySkipIndex, error)

View File

@@ -6,7 +6,6 @@ import (
"github.com/SigNoz/signoz/pkg/types/metrictypes"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
"github.com/SigNoz/signoz/pkg/valuer"
)
// MockMetadataStore implements the MetadataStore interface for testing purposes.
@@ -17,7 +16,6 @@ type MockMetadataStore struct {
AllValuesMap map[string]*telemetrytypes.TelemetryFieldValues
TemporalityMap map[string]metrictypes.Temporality
TypeMap map[string]metrictypes.Type
ReducedMap map[string]bool
PromotedPathsMap map[string]bool
LogsJSONIndexes []telemetrytypes.TelemetryFieldKeySkipIndex
ColumnEvolutionMetadataMap map[string][]*telemetrytypes.EvolutionEntry
@@ -308,7 +306,7 @@ func (m *MockMetadataStore) SetAllValues(lookupKey string, values *telemetrytype
}
// FetchTemporality fetches the temporality for a metric.
func (m *MockMetadataStore) FetchTemporality(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
func (m *MockMetadataStore) FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
if temporality, exists := m.TemporalityMap[metricName]; exists {
return temporality, nil
}
@@ -316,7 +314,7 @@ func (m *MockMetadataStore) FetchTemporality(ctx context.Context, orgID valuer.U
}
// FetchTemporalityMulti fetches the temporality for multiple metrics.
func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
result := make(map[string]metrictypes.Temporality)
for _, metricName := range metricNames {
@@ -331,10 +329,9 @@ func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, orgID val
}
// FetchTemporalityMulti fetches the temporality for multiple metrics.
func (m *MockMetadataStore) FetchTemporalityAndTypeMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error) {
func (m *MockMetadataStore) FetchTemporalityAndTypeMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {
temporalities := make(map[string]metrictypes.Temporality)
types := make(map[string]metrictypes.Type)
reduced := make(map[string]bool)
for _, metricName := range metricNames {
if temporality, exists := m.TemporalityMap[metricName]; exists {
@@ -347,12 +344,9 @@ func (m *MockMetadataStore) FetchTemporalityAndTypeMulti(ctx context.Context, or
} else {
types[metricName] = metrictypes.UnspecifiedType
}
if m.ReducedMap[metricName] {
reduced[metricName] = true
}
}
return temporalities, types, reduced, nil
return temporalities, types, nil
}
// SetTemporality sets the temporality for a metric in the mock store.