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* Shared Query Builder
* Contains all SQL building logic that was previously duplicated between executor and multi-cube-builder
* Single source of truth for all SQL generation
*/
import {
sql,
and,
or,
count,
asc,
desc,
SQL,
type AnyColumn
} from 'drizzle-orm'
import type {
SemanticQuery,
FilterOperator,
Filter,
FilterCondition,
LogicalFilter,
Cube,
QueryContext,
QueryPlan
} from './types'
import { resolveSqlExpression } from './cube-utils'
import type { DatabaseAdapter } from './adapters/base-adapter'
import { getFilterKey, getTimeDimensionFilterKey } from './filter-cache'
import { DateTimeBuilder, FilterBuilder, GroupByBuilder, MeasureBuilder } from './builders'
import type { ResolvedMeasures } from './template-substitution'
export class QueryBuilder {
private dateTimeBuilder: DateTimeBuilder
private filterBuilder: FilterBuilder
private groupByBuilder: GroupByBuilder
private measureBuilder: MeasureBuilder
constructor(databaseAdapter: DatabaseAdapter) {
this.dateTimeBuilder = new DateTimeBuilder(databaseAdapter)
this.filterBuilder = new FilterBuilder(databaseAdapter, this.dateTimeBuilder)
this.groupByBuilder = new GroupByBuilder(this.dateTimeBuilder)
this.measureBuilder = new MeasureBuilder(databaseAdapter)
}
/**
* Build resolvedMeasures map for a set of measures
* Delegates to MeasureBuilder
*/
buildResolvedMeasures(
measureNames: string[],
cubeMap: Map<string, Cube>,
context: QueryContext,
customMeasureBuilder?: (measureName: string, measure: any, cube: Cube) => SQL
): ResolvedMeasures {
return this.measureBuilder.buildResolvedMeasures(measureNames, cubeMap, context, customMeasureBuilder)
}
/**
* Build dynamic selections for measures, dimensions, and time dimensions
* Works for both single and multi-cube queries
* Handles calculated measures with dependency resolution
*/
buildSelections(
cubes: Map<string, Cube> | Cube,
query: SemanticQuery,
context: QueryContext
): Record<string, SQL | AnyColumn> {
const selections: Record<string, SQL | AnyColumn> = {}
// Convert single cube to map for consistent handling
const cubeMap = cubes instanceof Map ? cubes : new Map([[cubes.name, cubes]])
// Add dimensions
if (query.dimensions) {
for (const dimensionName of query.dimensions) {
const [cubeName, fieldName] = dimensionName.split('.')
const cube = cubeMap.get(cubeName)
if (cube && cube.dimensions && cube.dimensions[fieldName]) {
const dimension = cube.dimensions[fieldName]
const sqlExpr = resolveSqlExpression(dimension.sql, context)
// Use explicit alias for dimension expressions so they can be referenced in ORDER BY
selections[dimensionName] = sql`${sqlExpr}`.as(dimensionName) as unknown as SQL
}
}
}
// Add measures with aggregations using the centralized helper
if (query.measures) {
const resolvedMeasures = this.buildResolvedMeasures(
query.measures,
cubeMap,
context
)
// Add user-requested measures to selections
for (const measureName of query.measures) {
const measureBuilder = resolvedMeasures.get(measureName)
if (measureBuilder) {
const measureExpr = measureBuilder()
selections[measureName] = sql`${measureExpr}`.as(measureName) as unknown as SQL
}
}
}
// Add time dimensions with granularity
if (query.timeDimensions) {
for (const timeDim of query.timeDimensions) {
const [cubeName, fieldName] = timeDim.dimension.split('.')
const cube = cubeMap.get(cubeName)
Eif (cube && cube.dimensions && cube.dimensions[fieldName]) {
const dimension = cube.dimensions[fieldName]
const timeExpr = this.buildTimeDimensionExpression(
dimension.sql,
timeDim.granularity,
context
)
// Use explicit alias for time dimension expressions so they can be referenced in ORDER BY
selections[timeDim.dimension] = sql`${timeExpr}`.as(timeDim.dimension) as unknown as SQL
}
}
}
// Default to COUNT(*) if no selections
if (Object.keys(selections).length === 0) {
selections.count = count()
}
return selections
}
/**
* Build calculated measure expression by substituting {member} references
* Delegates to MeasureBuilder
*/
public buildCalculatedMeasure(
measure: any,
cube: Cube,
allCubes: Map<string, Cube>,
resolvedMeasures: ResolvedMeasures,
context: QueryContext
): SQL {
return this.measureBuilder.buildCalculatedMeasure(measure, cube, allCubes, resolvedMeasures, context)
}
/**
* Build resolved measures map for a calculated measure from CTE columns
* Delegates to MeasureBuilder
*/
public buildCTECalculatedMeasure(
measure: any,
cube: Cube,
cteInfo: { cteAlias: string; measures: string[]; cube: Cube },
allCubes: Map<string, Cube>,
context: QueryContext
): SQL {
return this.measureBuilder.buildCTECalculatedMeasure(measure, cube, cteInfo, allCubes, context)
}
/**
* Build measure expression for HAVING clause, handling CTE references correctly
* Delegates to MeasureBuilder
*/
private buildHavingMeasureExpression(
cubeName: string,
fieldKey: string,
measure: any,
context: QueryContext,
queryPlan?: QueryPlan
): SQL {
return this.measureBuilder.buildHavingMeasureExpression(cubeName, fieldKey, measure, context, queryPlan)
}
/**
* Build measure expression with aggregation and filters
* Delegates to MeasureBuilder
*/
buildMeasureExpression(
measure: any,
context: QueryContext,
cube?: Cube
): SQL {
return this.measureBuilder.buildMeasureExpression(measure, context, cube)
}
/**
* Build time dimension expression with granularity using database adapter
* Delegates to DateTimeBuilder
*/
buildTimeDimensionExpression(
dimensionSql: any,
granularity: string | undefined,
context: QueryContext
): SQL {
return this.dateTimeBuilder.buildTimeDimensionExpression(dimensionSql, granularity, context)
}
/**
* Build WHERE conditions from semantic query filters (dimensions only)
* Works for both single and multi-cube queries
* @param preBuiltFilters - Optional map of cube name to pre-built filter SQL for parameter deduplication
*/
buildWhereConditions(
cubes: Map<string, Cube> | Cube,
query: SemanticQuery,
context: QueryContext,
queryPlan?: QueryPlan,
preBuiltFilters?: Map<string, SQL[]>
): SQL[] {
const conditions: SQL[] = []
// Convert single cube to map for consistent handling
const cubeMap = cubes instanceof Map ? cubes : new Map([[cubes.name, cubes]])
// Track which cubes have had their pre-built filters added
const cubesWithPreBuiltFiltersAdded = new Set<string>()
// Process regular filters (dimensions only for WHERE clause)
if (query.filters && query.filters.length > 0) {
for (const filter of query.filters) {
// Check if this filter's cube has pre-built filters we should use instead
// IMPORTANT: Only use pre-built filters if the filter's cube is in our current cubeMap
// This prevents using Employees filters in a Productivity CTE context
if (preBuiltFilters && 'member' in filter) {
const [cubeName] = (filter.member as string).split('.')
const cubeIsInContext = cubeMap.has(cubeName)
if (cubeIsInContext && preBuiltFilters.has(cubeName) && !cubesWithPreBuiltFiltersAdded.has(cubeName)) {
// Use the pre-built filter SQL instead of building fresh
// This deduplicates parameters between CTE subquery and main query
const preBuilt = preBuiltFilters.get(cubeName)!
conditions.push(...preBuilt)
cubesWithPreBuiltFiltersAdded.add(cubeName)
continue
} else if (cubesWithPreBuiltFiltersAdded.has(cubeName)) {
// Skip - already added pre-built filters for this cube
continue
}
}
const condition = this.processFilter(filter, cubeMap, context, 'where', queryPlan)
if (condition) {
conditions.push(condition)
}
}
}
// Process time dimension date range filters
if (query.timeDimensions) {
for (const timeDim of query.timeDimensions) {
const [cubeName, fieldName] = timeDim.dimension.split('.')
const cube = cubeMap.get(cubeName)
if (cube && cube.dimensions[fieldName] && timeDim.dateRange) {
// Check if this cube is in a pre-aggregation CTE - if so, skip this filter in WHERE clause
// The time dimension filter will be applied within the CTE itself during pre-aggregation
if (queryPlan?.preAggregationCTEs) {
const isInCTE = queryPlan.preAggregationCTEs.some((cte: any) => cte.cube.name === cubeName)
if (isInCTE) {
continue // Skip this filter - it's handled in the CTE
}
}
// Try to use cached time dimension filter for parameter deduplication
Eif (context.filterCache) {
const key = getTimeDimensionFilterKey(timeDim.dimension, timeDim.dateRange)
const cached = context.filterCache.get(key)
if (cached) {
conditions.push(cached)
continue
}
}
const dimension = cube.dimensions[fieldName]
// Use the raw field expression for date filtering (not the truncated version)
// This ensures we filter on the actual timestamp values before aggregation
const fieldExpr = resolveSqlExpression(dimension.sql, context)
const dateCondition = this.buildDateRangeCondition(fieldExpr, timeDim.dateRange)
Iif (dateCondition) {
conditions.push(dateCondition)
}
}
}
}
return conditions
}
/**
* Build HAVING conditions from semantic query filters (measures only)
* Works for both single and multi-cube queries
*/
buildHavingConditions(
cubes: Map<string, Cube> | Cube,
query: SemanticQuery,
context: QueryContext,
queryPlan?: QueryPlan
): SQL[] {
const conditions: SQL[] = []
// Convert single cube to map for consistent handling
const cubeMap = cubes instanceof Map ? cubes : new Map([[cubes.name, cubes]])
// Process regular filters (measures only for HAVING clause)
if (query.filters && query.filters.length > 0) {
for (const filter of query.filters) {
const condition = this.processFilter(filter, cubeMap, context, 'having', queryPlan)
if (condition) {
conditions.push(condition)
}
}
}
return conditions
}
/**
* Process a single filter (basic or logical)
* @param filterType - 'where' for dimension filters, 'having' for measure filters
*/
private processFilter(
filter: Filter,
cubes: Map<string, Cube>,
context: QueryContext,
filterType: 'where' | 'having',
queryPlan?: QueryPlan
): SQL | null {
// Handle logical filters (AND/OR)
// NOTE: We do NOT cache logical filters because they can contain mixed cube references.
// When some cubes are in CTEs, the cached version would reference wrong table contexts.
// Individual simple filters within logical filters are still cached for deduplication.
if ('and' in filter || 'or' in filter) {
const logicalFilter = filter as LogicalFilter
if (logicalFilter.and) {
const conditions = logicalFilter.and
.map(f => this.processFilter(f, cubes, context, filterType, queryPlan))
.filter((condition): condition is SQL => condition !== null)
return conditions.length > 0 ? and(...conditions) as SQL : null
}
Eif (logicalFilter.or) {
const conditions = logicalFilter.or
.map(f => this.processFilter(f, cubes, context, filterType, queryPlan))
.filter((condition): condition is SQL => condition !== null)
return conditions.length > 0 ? or(...conditions) as SQL : null
}
}
// Handle simple filter condition
const filterCondition = filter as FilterCondition
const [cubeName, fieldKey] = filterCondition.member.split('.')
const cube = cubes.get(cubeName)
if (!cube) return null
// Find the field in dimensions or measures
const dimension = cube.dimensions[fieldKey]
const measure = cube.measures[fieldKey]
const field = dimension || measure
Iif (!field) return null
// Apply filter based on type and what we're looking for
if (filterType === 'where' && dimension) {
// Check if this cube is in a pre-aggregation CTE - if so, skip this filter in WHERE clause
// The filter will be applied within the CTE itself
// IMPORTANT: This check MUST come before the cache check, because cached filters
// would reference the wrong table context (CTE table vs main query table)
if (queryPlan?.preAggregationCTEs) {
const isInCTE = queryPlan.preAggregationCTEs.some((cte: any) => cte.cube.name === cubeName)
if (isInCTE) {
return null // Skip this filter - it's handled in the CTE
}
}
// For array operators, we need the raw column (not isolated SQL)
// because Drizzle's array functions need column type metadata for proper encoding
// These CANNOT be cached because the raw column reference is required
const isArrayOperator = ['arrayContains', 'arrayOverlaps', 'arrayContained'].includes(filterCondition.operator)
// Try to use cached filter SQL for parameter deduplication
// This avoids creating duplicate parameters for the same filter values
// NOTE: Skip cache for array operators (they require raw column)
// NOTE: We only use cache for non-CTE cubes (checked above)
if (!isArrayOperator && context.filterCache) {
const key = getFilterKey(filter)
const cached = context.filterCache.get(key)
if (cached) {
return cached
}
}
const fieldExpr = isArrayOperator
? (typeof dimension.sql === 'function' ? dimension.sql(context) : dimension.sql)
: resolveSqlExpression(dimension.sql, context)
return this.buildFilterCondition(
fieldExpr,
filterCondition.operator,
filterCondition.values,
field,
filterCondition.dateRange
)
} else if (filterType === 'where' && measure) {
// NEVER apply measure filters in WHERE clause - they should only be in HAVING
// This prevents incorrect behavior where measure filters are applied before aggregation
return null
} else if (filterType === 'having' && measure) {
// HAVING clause: use aggregated measure expression
// Note: HAVING filters are NOT cached because they use aggregated expressions
// which may be different depending on the query context (CTE vs main query)
const measureExpr = this.buildHavingMeasureExpression(cubeName, fieldKey, measure, context, queryPlan)
return this.buildFilterCondition(
measureExpr,
filterCondition.operator,
filterCondition.values,
field,
filterCondition.dateRange
)
}
// Skip if this filter doesn't match the type we're processing
return null
}
/**
* Build filter condition using Drizzle operators
* Delegates to FilterBuilder
*/
private buildFilterCondition(
fieldExpr: AnyColumn | SQL,
operator: FilterOperator,
values: any[],
field?: any,
dateRange?: string | string[]
): SQL | null {
return this.filterBuilder.buildFilterCondition(fieldExpr, operator, values, field, dateRange)
}
/**
* Build date range condition for time dimensions
* Delegates to DateTimeBuilder
*/
buildDateRangeCondition(
fieldExpr: AnyColumn | SQL,
dateRange: string | string[]
): SQL | null {
return this.dateTimeBuilder.buildDateRangeCondition(fieldExpr, dateRange)
}
/**
* Build GROUP BY fields from dimensions and time dimensions
* Delegates to GroupByBuilder
*/
buildGroupByFields(
cubes: Map<string, Cube> | Cube,
query: SemanticQuery,
context: QueryContext,
queryPlan?: any
): (SQL | AnyColumn)[] {
return this.groupByBuilder.buildGroupByFields(cubes, query, context, queryPlan)
}
/**
* Build ORDER BY clause with automatic time dimension sorting
*/
buildOrderBy(query: SemanticQuery, selectedFields?: string[]): SQL[] {
const orderClauses: SQL[] = []
// Get all selected fields (measures + dimensions + timeDimensions)
const allSelectedFields = selectedFields || [
...(query.measures || []),
...(query.dimensions || []),
...(query.timeDimensions?.map(td => td.dimension) || [])
]
// First, add explicit ordering from query.order
if (query.order && Object.keys(query.order).length > 0) {
for (const [field, direction] of Object.entries(query.order)) {
// Validate that the field exists in the selected fields
if (!allSelectedFields.includes(field)) {
throw new Error(`Cannot order by '${field}': field is not selected in the query`)
}
// Use Drizzle's built-in asc/desc functions for proper ordering
const orderClause = direction === 'desc' ? desc(sql.identifier(field)) : asc(sql.identifier(field))
orderClauses.push(orderClause)
}
}
// Then, automatically add time dimension sorting for any time dimensions not explicitly ordered
if (query.timeDimensions && query.timeDimensions.length > 0) {
const explicitlyOrderedFields = new Set(Object.keys(query.order || {}))
// Sort time dimensions by their dimension name to ensure consistent ordering
const sortedTimeDimensions = [...query.timeDimensions].sort((a, b) =>
a.dimension.localeCompare(b.dimension)
)
for (const timeDim of sortedTimeDimensions) {
if (!explicitlyOrderedFields.has(timeDim.dimension)) {
// Automatically sort time dimensions in ascending order (earliest to latest)
orderClauses.push(asc(sql.identifier(timeDim.dimension)))
}
}
}
return orderClauses
}
/**
* Collect numeric field names (measures + numeric dimensions) for type conversion
* Works for both single and multi-cube queries
*/
collectNumericFields(cubes: Map<string, Cube> | Cube, query: SemanticQuery): string[] {
const numericFields: string[] = []
// Convert single cube to map for consistent handling
const cubeMap = cubes instanceof Map ? cubes : new Map([[cubes.name, cubes]])
// Add all measure fields (they are always numeric)
if (query.measures) {
numericFields.push(...query.measures)
}
// Add numeric dimension fields
if (query.dimensions) {
for (const dimensionName of query.dimensions) {
const [cubeName, fieldName] = dimensionName.split('.')
const cube = cubeMap.get(cubeName)
Eif (cube) {
const dimension = cube.dimensions[fieldName]
if (dimension && dimension.type === 'number') {
// Use the full name (with prefix) as it appears in the result
numericFields.push(dimensionName)
}
}
}
}
return numericFields
}
/**
* Apply LIMIT and OFFSET to a query with validation
* If offset is provided without limit, add a reasonable default limit
*/
applyLimitAndOffset<T>(query: T, semanticQuery: SemanticQuery): T {
// If offset is provided without limit, add a reasonable default limit
let effectiveLimit = semanticQuery.limit
if (semanticQuery.offset !== undefined && semanticQuery.offset > 0 && effectiveLimit === undefined) {
effectiveLimit = 50 // Default limit when offset is used
}
let result = query
if (effectiveLimit !== undefined) {
if (effectiveLimit < 0) {
throw new Error('Limit must be non-negative')
}
result = (result as any).limit(effectiveLimit)
}
if (semanticQuery.offset !== undefined) {
if (semanticQuery.offset < 0) {
throw new Error('Offset must be non-negative')
}
result = (result as any).offset(semanticQuery.offset)
}
return result
}
/**
* Public wrapper for buildFilterCondition - used by executor for cache preloading
* This allows pre-building filter SQL before query construction
*/
buildFilterConditionPublic(
fieldExpr: AnyColumn | SQL,
operator: FilterOperator,
values: any[],
field?: any,
dateRange?: string | string[]
): SQL | null {
return this.buildFilterCondition(fieldExpr, operator, values, field, dateRange)
}
/**
* Build a logical filter (AND/OR) - used by executor for cache preloading
* This handles nested filter structures and builds combined SQL
* Delegates to FilterBuilder
*/
buildLogicalFilter(
filter: Filter,
cubes: Map<string, Cube>,
context: QueryContext
): SQL | null {
return this.filterBuilder.buildLogicalFilter(filter, cubes, context)
}
} |