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* Measure Builder
* Handles all measure-related SQL generation:
* - Measure expression building with aggregations (count, sum, avg, etc.)
* - Statistical functions (stddev, variance, percentile)
* - Window functions (lag, lead, rank, etc.)
* - Calculated measure resolution and template substitution
* - CTE-specific measure handling
*/
import {
sql,
and,
count,
sum,
min,
max,
countDistinct,
SQL,
type AnyColumn
} from 'drizzle-orm'
import type {
Cube,
QueryContext,
QueryPlan
} from '../types'
import { resolveSqlExpression } from '../cube-utils'
import type { DatabaseAdapter } from '../adapters/base-adapter'
import { CalculatedMeasureResolver } from '../calculated-measure-resolver'
import { substituteTemplate, getMemberReferences, type ResolvedMeasures } from '../template-substitution'
export class MeasureBuilder {
constructor(private databaseAdapter: DatabaseAdapter) {}
/**
* Build resolvedMeasures map for a set of measures
* This centralizes the logic for building both regular and calculated measures
* in dependency order, avoiding duplication across main queries and CTEs
*
* @param measureNames - Array of measure names to resolve (e.g., ["Employees.count", "Employees.activePercentage"])
* @param cubeMap - Map of all cubes involved in the query
* @param context - Query context with database and security context
* @param customMeasureBuilder - Optional function to override how individual measures are built
* @returns Map of measure names to SQL builder functions
*/
buildResolvedMeasures(
measureNames: string[],
cubeMap: Map<string, Cube>,
context: QueryContext,
customMeasureBuilder?: (measureName: string, measure: any, cube: Cube) => SQL
): ResolvedMeasures {
const resolvedMeasures: ResolvedMeasures = new Map()
const regularMeasures: string[] = []
const calculatedMeasures: string[] = []
const allMeasuresToResolve = new Set<string>(measureNames)
// Build dependency graph
const resolver = new CalculatedMeasureResolver(cubeMap)
for (const cube of cubeMap.values()) {
resolver.buildGraph(cube)
}
// First pass: classify user-requested measures and collect dependencies
// Post-aggregation window measures are handled separately in the executor
const postAggWindowMeasures: string[] = []
for (const measureName of measureNames) {
const [cubeName, fieldName] = measureName.split('.')
const cube = cubeMap.get(cubeName)
if (cube && cube.measures && cube.measures[fieldName]) {
const measure = cube.measures[fieldName]
// Post-aggregation window functions are handled separately
// They don't go through buildMeasureExpression
if (MeasureBuilder.isPostAggregationWindow(measure)) {
postAggWindowMeasures.push(measureName)
// Add the base measure as a dependency
const baseMeasure = MeasureBuilder.getWindowBaseMeasure(measure, cubeName)
Eif (baseMeasure) {
allMeasuresToResolve.add(baseMeasure)
}
continue
}
if (CalculatedMeasureResolver.isCalculatedMeasure(measure)) {
calculatedMeasures.push(measureName)
// Add all dependencies to measures that need to be resolved
const deps = getMemberReferences(measure.calculatedSql!, cubeName)
deps.forEach(dep => allMeasuresToResolve.add(dep))
// Also add transitive calculated measure dependencies
const calculatedDeps = resolver.getAllDependencies(measureName)
calculatedDeps.forEach(dep => {
const [depCubeName, depFieldName] = dep.split('.')
const depCube = cubeMap.get(depCubeName)
Eif (depCube && depCube.measures[depFieldName]) {
const depMeasure = depCube.measures[depFieldName]
if (CalculatedMeasureResolver.isCalculatedMeasure(depMeasure)) {
const nestedDeps = getMemberReferences(depMeasure.calculatedSql!, depCubeName)
nestedDeps.forEach(nestedDep => allMeasuresToResolve.add(nestedDep))
}
}
})
} else {
regularMeasures.push(measureName)
}
}
}
// Second pass: classify all measures that need to be resolved (including dependencies)
// Skip post-aggregation window measures - they're handled separately
for (const measureName of allMeasuresToResolve) {
const [cubeName, fieldName] = measureName.split('.')
const cube = cubeMap.get(cubeName)
if (cube && cube.measures && cube.measures[fieldName]) {
const measure = cube.measures[fieldName]
// Skip post-aggregation window measures
if (MeasureBuilder.isPostAggregationWindow(measure)) {
continue
}
if (!CalculatedMeasureResolver.isCalculatedMeasure(measure)) {
if (!regularMeasures.includes(measureName)) {
regularMeasures.push(measureName)
}
} else {
if (!calculatedMeasures.includes(measureName)) {
calculatedMeasures.push(measureName)
}
}
}
}
// Build regular measures first
for (const measureName of regularMeasures) {
const [cubeName, fieldName] = measureName.split('.')
const cube = cubeMap.get(cubeName)!
const measure = cube.measures[fieldName]
// Use custom builder if provided, otherwise use default
if (customMeasureBuilder) {
const builtExpr = customMeasureBuilder(measureName, measure, cube)
resolvedMeasures.set(measureName, () => builtExpr)
} else {
// Store a FUNCTION that builds the SQL expression to avoid mutation issues
// Pass cube for window function dimension resolution
resolvedMeasures.set(measureName, () => this.buildMeasureExpression(measure, context, cube))
}
}
// Build calculated measures in dependency order
if (calculatedMeasures.length > 0) {
const sortedCalculated = resolver.topologicalSort(calculatedMeasures)
for (const measureName of sortedCalculated) {
const [cubeName, fieldName] = measureName.split('.')
const cube = cubeMap.get(cubeName)!
const measure = cube.measures[fieldName]
// Store a FUNCTION that builds the calculated measure SQL
resolvedMeasures.set(measureName, () => this.buildCalculatedMeasure(
measure,
cube,
cubeMap,
resolvedMeasures,
context
))
}
}
return resolvedMeasures
}
/**
* Build calculated measure expression by substituting {member} references
* with resolved SQL expressions
*/
buildCalculatedMeasure(
measure: any,
cube: Cube,
allCubes: Map<string, Cube>,
resolvedMeasures: ResolvedMeasures,
context: QueryContext
): SQL {
if (!measure.calculatedSql) {
throw new Error(
`Calculated measure '${cube.name}.${measure.name}' missing calculatedSql property`
)
}
// Preprocess template for database-specific transformations (e.g., SQLite float division)
const preprocessedSql = this.databaseAdapter.preprocessCalculatedTemplate(measure.calculatedSql)
// Substitute {member} references with resolved SQL
const substitutedSql = substituteTemplate(preprocessedSql, {
cube,
allCubes,
resolvedMeasures,
queryContext: context
})
return substitutedSql
}
/**
* Build resolved measures map for a calculated measure from CTE columns
* This handles re-aggregating pre-aggregated CTE columns for calculated measures
*
* IMPORTANT: For calculated measures in CTEs, we cannot sum/avg pre-computed ratios.
* We must recalculate from the base measures that were pre-aggregated in the CTE.
*
* @param measure - The calculated measure to build
* @param cube - The cube containing this measure
* @param cteInfo - CTE metadata (alias, measures, cube reference)
* @param allCubes - Map of all cubes in the query
* @param context - Query context
* @returns SQL expression for the calculated measure using CTE column references
*/
buildCTECalculatedMeasure(
measure: any,
cube: Cube,
cteInfo: { cteAlias: string; measures: string[]; cube: Cube },
allCubes: Map<string, Cube>,
context: QueryContext
): SQL {
if (!measure.calculatedSql) {
throw new Error(
`Calculated measure '${cube.name}.${measure.name || 'unknown'}' missing calculatedSql property`
)
}
// Build a resolvedMeasures map with CTE column references
const cteResolvedMeasures = new Map<string, () => SQL>()
// Get all dependencies for this calculated measure
const deps = getMemberReferences(measure.calculatedSql, cube.name)
for (const depMeasureName of deps) {
const [depCubeName, depFieldName] = depMeasureName.split('.')
const depCube = allCubes.get(depCubeName)
Eif (depCube && depCube.measures[depFieldName]) {
const depMeasure = depCube.measures[depFieldName]
// Check if this dependency is also in the CTE
Eif (cteInfo.measures.includes(depMeasureName)) {
// Reference the CTE column and apply appropriate aggregation
const cteDepColumn = sql`${sql.identifier(cteInfo.cteAlias)}.${sql.identifier(depFieldName)}`
// Apply aggregation based on the dependency's type
// For pre-aggregated values in CTEs, we need to re-aggregate them properly:
// - count/sum values should be summed
// - avg values should be averaged (though ideally weighted average)
// - min/max values should take min/max
let aggregatedDep: SQL
switch (depMeasure.type) {
case 'count':
case 'countDistinct':
case 'sum':
aggregatedDep = sum(cteDepColumn)
break
case 'avg':
aggregatedDep = this.databaseAdapter.buildAvg(cteDepColumn)
break
case 'min':
aggregatedDep = min(cteDepColumn)
break
case 'max':
aggregatedDep = max(cteDepColumn)
break
case 'number':
aggregatedDep = sum(cteDepColumn)
break
default:
aggregatedDep = sum(cteDepColumn)
}
// Store the aggregated CTE column as a builder function
cteResolvedMeasures.set(depMeasureName, () => aggregatedDep)
}
}
}
// Re-apply the calculated measure template with CTE-based dependencies
return this.buildCalculatedMeasure(
measure,
cube,
allCubes,
cteResolvedMeasures,
context
)
}
/**
* Build measure expression for HAVING clause, handling CTE references correctly
*/
buildHavingMeasureExpression(
cubeName: string,
fieldKey: string,
measure: any,
context: QueryContext,
queryPlan?: QueryPlan
): SQL {
// Check if this measure is from a CTE cube
if (queryPlan && queryPlan.preAggregationCTEs) {
const cteInfo = queryPlan.preAggregationCTEs.find(cte => cte.cube.name === cubeName)
if (cteInfo && cteInfo.measures.includes(`${cubeName}.${fieldKey}`)) {
// This measure is from a CTE - reference the CTE alias instead of the original table
if (measure.type === 'calculated' && measure.calculatedSql) {
// Get the cube for this measure
const cube = queryPlan.primaryCube.name === cubeName
? queryPlan.primaryCube
: queryPlan.joinCubes?.find(jc => jc.cube.name === cubeName)?.cube
if (!cube) {
throw new Error(`Cube ${cubeName} not found in query plan`)
}
// Build a cubeMap for the calculated measure builder
const cubeMap = new Map<string, Cube>([[queryPlan.primaryCube.name, queryPlan.primaryCube]])
Eif (queryPlan.joinCubes) {
for (const jc of queryPlan.joinCubes) {
cubeMap.set(jc.cube.name, jc.cube)
}
}
// Use the shared helper to build calculated measure from CTE columns
return this.buildCTECalculatedMeasure(
measure,
cube,
cteInfo,
cubeMap,
context
)
} else {
// For non-calculated measures, aggregate the CTE column directly
const cteColumn = sql`${sql.identifier(cteInfo.cteAlias)}.${sql.identifier(fieldKey)}`
// Apply aggregation function based on measure type
switch (measure.type) {
case 'count':
case 'countDistinct':
case 'sum':
return sum(cteColumn)
case 'avg':
// For average of averages, we should use a weighted average, but for now use simple avg
return this.databaseAdapter.buildAvg(cteColumn)
case 'min':
return min(cteColumn)
case 'max':
return max(cteColumn)
case 'number':
// For number type, use sum to combine values
return sum(cteColumn)
default:
return sum(cteColumn)
}
}
}
}
// Not from CTE - use regular measure expression
return this.buildMeasureExpression(measure, context)
}
/**
* Build measure expression with aggregation and filters
* Note: This should NOT be called for calculated measures
*
* @param measure - The measure definition
* @param context - Query context with security context and database info
* @param cube - Optional cube reference for resolving dimension references (window functions)
*/
buildMeasureExpression(
measure: any,
context: QueryContext,
cube?: Cube
): SQL {
// Calculated measures should be built via buildCalculatedMeasure
if (measure.type === 'calculated') {
throw new Error(
`Cannot build calculated measure '${measure.name}' directly. ` +
`Use buildCalculatedMeasure instead.`
)
}
// Post-aggregation window functions don't use sql property - they reference another measure
// These are handled in the executor's buildPostAggregationWindowExpression method
Iif (MeasureBuilder.isPostAggregationWindow(measure)) {
throw new Error(
`Post-aggregation window measure '${measure.name}' should be built via ` +
`buildPostAggregationWindowExpression, not buildMeasureExpression.`
)
}
// Non-calculated, non-post-agg-window measures must have sql property
if (!measure.sql) {
throw new Error(
`Measure '${measure.name}' of type '${measure.type}' is missing required 'sql' property. ` +
`Only calculated measures and post-aggregation window functions can omit 'sql'.`
)
}
// resolveSqlExpression already applies isolation via isolateSqlExpression()
// This protects against Drizzle SQL object mutation during reuse
let baseExpr = resolveSqlExpression(measure.sql, context)
// Apply measure filters if they exist
if (measure.filters && measure.filters.length > 0) {
const filterConditions = measure.filters.map((filter: (ctx: QueryContext) => SQL) => {
const filterResult = filter(context)
// Single wrap is OK here - we're creating fresh SQL for grouping in parentheses
// The filter function itself should handle isolation if needed
return filterResult ? sql`(${filterResult})` : undefined
}).filter(Boolean) // Remove any undefined conditions
Eif (filterConditions.length > 0) {
// Use CASE WHEN for conditional aggregation via adapter
const andCondition = filterConditions.length === 1 ? filterConditions[0] : and(...filterConditions)
const caseExpr = this.databaseAdapter.buildCaseWhen([
{ when: andCondition!, then: baseExpr }
])
baseExpr = caseExpr
}
}
// Apply aggregation function based on measure type
switch (measure.type) {
case 'count':
return count(baseExpr)
case 'countDistinct':
return countDistinct(baseExpr)
case 'sum':
return sum(baseExpr)
case 'avg':
return this.databaseAdapter.buildAvg(baseExpr)
case 'min':
return min(baseExpr)
case 'max':
return max(baseExpr)
case 'number':
return baseExpr as SQL
// Statistical functions (Phase 1)
case 'stddev':
case 'stddevSamp': {
const useSample = measure.type === 'stddevSamp' || measure.statisticalConfig?.useSample
const result = this.databaseAdapter.buildStddev(baseExpr, useSample)
if (result === null) {
console.warn(`[drizzle-cube] ${measure.type} not supported on ${this.databaseAdapter.getEngineType()}, returning NULL`)
// Use MAX(NULL) to ensure proper aggregation behavior
return sql`MAX(NULL)`
}
return result
}
case 'variance':
case 'varianceSamp': {
const useSample = measure.type === 'varianceSamp' || measure.statisticalConfig?.useSample
const result = this.databaseAdapter.buildVariance(baseExpr, useSample)
if (result === null) {
console.warn(`[drizzle-cube] ${measure.type} not supported on ${this.databaseAdapter.getEngineType()}, returning NULL`)
// Use MAX(NULL) to ensure proper aggregation behavior
return sql`MAX(NULL)`
}
return result
}
case 'percentile':
case 'median':
case 'p95':
case 'p99': {
// Determine percentile value based on type
let pct: number
switch (measure.type) {
case 'median':
pct = 50
break
case 'p95':
pct = 95
break
case 'p99':
pct = 99
break
default:
pct = measure.statisticalConfig?.percentile ?? 50
}
const result = this.databaseAdapter.buildPercentile(baseExpr, pct)
if (result === null) {
console.warn(`[drizzle-cube] ${measure.type} not supported on ${this.databaseAdapter.getEngineType()}, returning NULL`)
// Use MAX(NULL) to ensure proper aggregation behavior
return sql`MAX(NULL)`
}
return result
}
// Window functions (Phase 2) - now with dimension resolution
case 'lag':
case 'lead':
case 'rank':
case 'denseRank':
case 'rowNumber':
case 'ntile':
case 'firstValue':
case 'lastValue':
case 'movingAvg':
case 'movingSum': {
const windowConfig = measure.windowConfig || {}
// Resolve partitionBy dimension references to SQL expressions
let partitionByExprs: (AnyColumn | SQL)[] | undefined
if (windowConfig.partitionBy && windowConfig.partitionBy.length > 0 && cube) {
const resolvedPartitions = windowConfig.partitionBy
.map((dimRef: string) => {
// Handle both "dimensionName" and "CubeName.dimensionName" formats
const dimName = dimRef.includes('.') ? dimRef.split('.')[1] : dimRef
const dimension = cube.dimensions?.[dimName]
if (dimension) {
return resolveSqlExpression(dimension.sql, context)
}
console.warn(`[drizzle-cube] Window function partition dimension '${dimRef}' not found in cube '${cube.name}'`)
return null
})
.filter((expr: AnyColumn | SQL | null): expr is AnyColumn | SQL => expr !== null)
if (resolvedPartitions.length > 0) {
partitionByExprs = resolvedPartitions
}
}
// Resolve orderBy dimension/measure references to SQL expressions
type OrderByExpr = { field: AnyColumn | SQL; direction: 'asc' | 'desc' }
let orderByExprs: OrderByExpr[] | undefined
if (windowConfig.orderBy && windowConfig.orderBy.length > 0 && cube) {
const resolvedOrders = windowConfig.orderBy
.map((orderSpec: { field: string; direction: 'asc' | 'desc' }): OrderByExpr | null => {
// Handle both "fieldName" and "CubeName.fieldName" formats
const fieldName = orderSpec.field.includes('.') ? orderSpec.field.split('.')[1] : orderSpec.field
// First check dimensions, then measures
const dimension = cube.dimensions?.[fieldName]
if (dimension) {
return {
field: resolveSqlExpression(dimension.sql, context),
direction: orderSpec.direction
}
}
const measureDef = cube.measures?.[fieldName]
if (measureDef && measureDef.sql) {
return {
field: resolveSqlExpression(measureDef.sql, context),
direction: orderSpec.direction
}
}
console.warn(`[drizzle-cube] Window function order field '${orderSpec.field}' not found in cube '${cube.name}'`)
return null
})
.filter((expr: OrderByExpr | null): expr is OrderByExpr => expr !== null)
if (resolvedOrders.length > 0) {
orderByExprs = resolvedOrders
}
}
const result = this.databaseAdapter.buildWindowFunction(
measure.type,
['rank', 'denseRank', 'rowNumber'].includes(measure.type) ? null : baseExpr,
partitionByExprs,
orderByExprs,
{
offset: windowConfig.offset,
defaultValue: windowConfig.defaultValue,
nTile: windowConfig.nTile,
frame: windowConfig.frame
}
)
if (result === null) {
console.warn(`[drizzle-cube] ${measure.type} not supported on ${this.databaseAdapter.getEngineType()}, returning NULL`)
return sql`NULL`
}
return result
}
default:
return count(baseExpr)
}
}
/**
* List of measure types that are window functions
* Window functions require special handling in CTEs:
* - No GROUP BY in the CTE
* - No re-aggregation in outer query
* - Return individual rows, not grouped results
*/
static WINDOW_FUNCTION_TYPES = [
'lag', 'lead', 'rank', 'denseRank', 'rowNumber',
'ntile', 'firstValue', 'lastValue', 'movingAvg', 'movingSum'
] as const
/**
* Check if a measure type is a window function
* @param measureType - The measure type string
* @returns true if this is a window function type
*/
static isWindowFunction(measureType: string): boolean {
return (MeasureBuilder.WINDOW_FUNCTION_TYPES as readonly string[]).includes(measureType)
}
/**
* Categorize measures into window functions and regular aggregates
* Used by query planner to create separate CTEs for each category
*
* @param measureNames - Array of measure names (e.g., ["Productivity.rank", "Productivity.totalLines"])
* @param cubeMap - Map of cubes to look up measure definitions
* @returns Object with windowMeasures and aggregateMeasures arrays
*/
static categorizeMeasures(
measureNames: string[],
cubeMap: Map<string, Cube>
): { windowMeasures: string[]; aggregateMeasures: string[] } {
const windowMeasures: string[] = []
const aggregateMeasures: string[] = []
for (const measureName of measureNames) {
const [cubeName, fieldName] = measureName.split('.')
const cube = cubeMap.get(cubeName)
if (cube?.measures?.[fieldName]) {
const measure = cube.measures[fieldName]
if (MeasureBuilder.isWindowFunction(measure.type)) {
windowMeasures.push(measureName)
} else {
aggregateMeasures.push(measureName)
}
}
}
return { windowMeasures, aggregateMeasures }
}
/**
* Check if a query contains any window function measures
* @param measureNames - Array of measure names
* @param cubeMap - Map of cubes
* @returns true if any measure is a window function
*/
static hasWindowFunctions(
measureNames: string[],
cubeMap: Map<string, Cube>
): boolean {
const { windowMeasures } = MeasureBuilder.categorizeMeasures(measureNames, cubeMap)
return windowMeasures.length > 0
}
// ============================================================================
// Post-Aggregation Window Functions
// ============================================================================
/**
* Check if a measure is a post-aggregation window function.
* Post-aggregation windows have a `measure` reference in their windowConfig,
* indicating they should operate on aggregated data rather than raw rows.
*
* @param measure - The measure definition
* @returns true if this is a post-aggregation window function
*/
static isPostAggregationWindow(measure: any): boolean {
return (
MeasureBuilder.isWindowFunction(measure.type) &&
measure.windowConfig?.measure !== undefined
)
}
/**
* Get the base measure reference for a post-aggregation window function.
* Resolves simple names (e.g., 'totalRevenue') to fully qualified names ('Sales.totalRevenue').
*
* @param measure - The measure definition
* @param cubeName - The name of the cube containing this measure
* @returns Fully qualified base measure name, or null if not a post-agg window
*/
static getWindowBaseMeasure(measure: any, cubeName: string): string | null {
if (!measure.windowConfig?.measure) {
return null
}
const ref = measure.windowConfig.measure
return ref.includes('.') ? ref : `${cubeName}.${ref}`
}
/**
* Get the default operation for a window function type.
* - lag/lead default to 'difference' (compare current vs previous/next)
* - rank/rowNumber/ntile/firstValue/lastValue default to 'raw'
* - movingAvg/movingSum default to 'raw'
*
* @param windowType - The window function type
* @returns Default operation for the window type
*/
static getDefaultWindowOperation(windowType: string): 'raw' | 'difference' | 'ratio' | 'percentChange' {
switch (windowType) {
case 'lag':
case 'lead':
return 'difference'
default:
return 'raw'
}
}
/**
* Categorize measures for post-aggregation window function handling.
* Separates measures into:
* - aggregateMeasures: Regular aggregates (count, sum, avg, etc.)
* - postAggWindowMeasures: Window functions that reference a base measure
* - requiredBaseMeasures: Base measures needed by window functions (auto-added to query)
*
* @param measureNames - Array of measure names from the query
* @param cubeMap - Map of cubes to look up measure definitions
* @returns Categorized measures with base measure dependencies
*/
static categorizeForPostAggregation(
measureNames: string[],
cubeMap: Map<string, Cube>
): {
aggregateMeasures: string[]
postAggWindowMeasures: string[]
requiredBaseMeasures: Set<string>
} {
const aggregateMeasures: string[] = []
const postAggWindowMeasures: string[] = []
const requiredBaseMeasures = new Set<string>()
for (const measureName of measureNames) {
const [cubeName, fieldName] = measureName.split('.')
const cube = cubeMap.get(cubeName)
Eif (cube?.measures?.[fieldName]) {
const measure = cube.measures[fieldName]
if (MeasureBuilder.isPostAggregationWindow(measure)) {
postAggWindowMeasures.push(measureName)
// Extract and add the base measure as a required dependency
const baseMeasure = MeasureBuilder.getWindowBaseMeasure(measure, cubeName)
Eif (baseMeasure) {
requiredBaseMeasures.add(baseMeasure)
}
E} else if (!MeasureBuilder.isWindowFunction(measure.type)) {
// Regular aggregate measure (not a window function)
aggregateMeasures.push(measureName)
}
// Note: Pre-aggregation window functions (no windowConfig.measure) are no longer supported
// They should be updated to use the new post-aggregation pattern
}
}
return { aggregateMeasures, postAggWindowMeasures, requiredBaseMeasures }
}
/**
* Check if any measures in the query are post-aggregation window functions.
*
* @param measureNames - Array of measure names
* @param cubeMap - Map of cubes
* @returns true if any measure is a post-aggregation window function
*/
static hasPostAggregationWindows(
measureNames: string[],
cubeMap: Map<string, Cube>
): boolean {
const { postAggWindowMeasures } = MeasureBuilder.categorizeForPostAggregation(
measureNames,
cubeMap
)
return postAggWindowMeasures.length > 0
}
}
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