@tanstack/db/dist/cjs/query/optimizer.cjs.map

A reactive client store for building super fast apps on sync

{"version":3,"file":"optimizer.cjs","sources":["../../../src/query/optimizer.ts"],"sourcesContent":["/**\n * # Query Optimizer\n *\n * The query optimizer improves query performance by implementing predicate pushdown optimization.\n * It rewrites the intermediate representation (IR) to push WHERE clauses as close to the data\n * source as possible, reducing the amount of data processed during joins.\n *\n * ## How It Works\n *\n * The optimizer follows a 4-step process:\n *\n * ### 1. AND Clause Splitting\n * Splits AND clauses at the root level into separate WHERE clauses for granular optimization.\n * ```javascript\n * // Before: WHERE and(eq(users.department_id, 1), gt(users.age, 25))\n * // After:  WHERE eq(users.department_id, 1) + WHERE gt(users.age, 25)\n * ```\n *\n * ### 2. Source Analysis\n * Analyzes each WHERE clause to determine which table sources it references:\n * - Single-source clauses: Touch only one table (e.g., `users.department_id = 1`)\n * - Multi-source clauses: Touch multiple tables (e.g., `users.id = posts.user_id`)\n *\n * ### 3. Clause Grouping\n * Groups WHERE clauses by the sources they touch:\n * - Single-source clauses are grouped by their respective table\n * - Multi-source clauses are combined for the main query\n *\n * ### 4. Subquery Creation\n * Lifts single-source WHERE clauses into subqueries that wrap the original table references.\n *\n * ## Safety & Edge Cases\n *\n * The optimizer includes targeted safety checks to prevent predicate pushdown when it could\n * break query semantics:\n *\n * ### Always Safe Operations\n * - **Creating new subqueries**: Wrapping collection references in subqueries with WHERE clauses\n * - **Main query optimizations**: Moving single-source WHERE clauses from main query to subqueries\n * - **Queries with aggregates/ORDER BY/HAVING**: Can still create new filtered subqueries\n *\n * ### Unsafe Operations (blocked by safety checks)\n * Pushing WHERE clauses **into existing subqueries** that have:\n * - **Aggregates**: GROUP BY, HAVING, or aggregate functions in SELECT (would change aggregation)\n * - **Ordering + Limits**: ORDER BY combined with LIMIT/OFFSET (would change result set)\n * - **Functional Operations**: fnSelect, fnWhere, fnHaving (potential side effects)\n *\n * The optimizer tracks which clauses were actually optimized and only removes those from the\n * main query. Subquery reuse is handled safely through immutable query copies.\n *\n * ## Example Optimizations\n *\n * ### Basic Query with Joins\n * **Original Query:**\n * ```javascript\n * query\n *   .from({ users: usersCollection })\n *   .join({ posts: postsCollection }, ({users, posts}) => eq(users.id, posts.user_id))\n *   .where(({users}) => eq(users.department_id, 1))\n *   .where(({posts}) => gt(posts.views, 100))\n *   .where(({users, posts}) => eq(users.id, posts.author_id))\n * ```\n *\n * **Optimized Query:**\n * ```javascript\n * query\n *   .from({\n *     users: subquery\n *       .from({ users: usersCollection })\n *       .where(({users}) => eq(users.department_id, 1))\n *   })\n *   .join({\n *     posts: subquery\n *       .from({ posts: postsCollection })\n *       .where(({posts}) => gt(posts.views, 100))\n *   }, ({users, posts}) => eq(users.id, posts.user_id))\n *   .where(({users, posts}) => eq(users.id, posts.author_id))\n * ```\n *\n * ### Query with Aggregates (Now Optimizable!)\n * **Original Query:**\n * ```javascript\n * query\n *   .from({ users: usersCollection })\n *   .join({ posts: postsCollection }, ({users, posts}) => eq(users.id, posts.user_id))\n *   .where(({users}) => eq(users.department_id, 1))\n *   .groupBy(['users.department_id'])\n *   .select({ count: agg('count', '*') })\n * ```\n *\n * **Optimized Query:**\n * ```javascript\n * query\n *   .from({\n *     users: subquery\n *       .from({ users: usersCollection })\n *       .where(({users}) => eq(users.department_id, 1))\n *   })\n *   .join({ posts: postsCollection }, ({users, posts}) => eq(users.id, posts.user_id))\n *   .groupBy(['users.department_id'])\n *   .select({ count: agg('count', '*') })\n * ```\n *\n * ## Benefits\n *\n * - **Reduced Data Processing**: Filters applied before joins reduce intermediate result size\n * - **Better Performance**: Smaller datasets lead to faster query execution\n * - **Automatic Optimization**: No manual query rewriting required\n * - **Preserves Semantics**: Optimized queries return identical results\n * - **Safe by Design**: Comprehensive checks prevent semantic-breaking optimizations\n *\n * ## Integration\n *\n * The optimizer is automatically called during query compilation before the IR is\n * transformed into a D2Mini pipeline.\n */\n\nimport { deepEquals } from \"../utils.js\"\nimport { CannotCombineEmptyExpressionListError } from \"../errors.js\"\nimport {\n  CollectionRef as CollectionRefClass,\n  Func,\n  QueryRef as QueryRefClass,\n} from \"./ir.js\"\nimport { isConvertibleToCollectionFilter } from \"./compiler/expressions.js\"\nimport type { BasicExpression, From, QueryIR } from \"./ir.js\"\n\n/**\n * Represents a WHERE clause after source analysis\n */\nexport interface AnalyzedWhereClause {\n  /** The WHERE expression */\n  expression: BasicExpression<boolean>\n  /** Set of table/source aliases that this WHERE clause touches */\n  touchedSources: Set<string>\n}\n\n/**\n * Represents WHERE clauses grouped by the sources they touch\n */\nexport interface GroupedWhereClauses {\n  /** WHERE clauses that touch only a single source, grouped by source alias */\n  singleSource: Map<string, BasicExpression<boolean>>\n  /** WHERE clauses that touch multiple sources, combined into one expression */\n  multiSource?: BasicExpression<boolean>\n}\n\n/**\n * Result of query optimization including both the optimized query and collection-specific WHERE clauses\n */\nexport interface OptimizationResult {\n  /** The optimized query with WHERE clauses potentially moved to subqueries */\n  optimizedQuery: QueryIR\n  /** Map of collection aliases to their extracted WHERE clauses for index optimization */\n  collectionWhereClauses: Map<string, BasicExpression<boolean>>\n}\n\n/**\n * Main query optimizer entry point that lifts WHERE clauses into subqueries.\n *\n * This function implements multi-level predicate pushdown optimization by recursively\n * moving WHERE clauses through nested subqueries to get them as close to the data\n * sources as possible, then removing redundant subqueries.\n *\n * @param query - The QueryIR to optimize\n * @returns An OptimizationResult with the optimized query and collection WHERE clause mapping\n *\n * @example\n * ```typescript\n * const originalQuery = {\n *   from: new CollectionRef(users, 'u'),\n *   join: [{ from: new CollectionRef(posts, 'p'), ... }],\n *   where: [eq(u.dept_id, 1), gt(p.views, 100)]\n * }\n *\n * const { optimizedQuery, collectionWhereClauses } = optimizeQuery(originalQuery)\n * // Result: Single-source clauses moved to deepest possible subqueries\n * // collectionWhereClauses: Map { 'u' => eq(u.dept_id, 1), 'p' => gt(p.views, 100) }\n * ```\n */\nexport function optimizeQuery(query: QueryIR): OptimizationResult {\n  // First, extract collection WHERE clauses before optimization\n  const collectionWhereClauses = extractCollectionWhereClauses(query)\n\n  // Apply multi-level predicate pushdown with iterative convergence\n  let optimized = query\n  let previousOptimized: QueryIR | undefined\n  let iterations = 0\n  const maxIterations = 10 // Prevent infinite loops\n\n  // Keep optimizing until no more changes occur or max iterations reached\n  while (\n    iterations < maxIterations &&\n    !deepEquals(optimized, previousOptimized)\n  ) {\n    previousOptimized = optimized\n    optimized = applyRecursiveOptimization(optimized)\n    iterations++\n  }\n\n  // Remove redundant subqueries\n  const cleaned = removeRedundantSubqueries(optimized)\n\n  return {\n    optimizedQuery: cleaned,\n    collectionWhereClauses,\n  }\n}\n\n/**\n * Extracts collection-specific WHERE clauses from a query for index optimization.\n * This analyzes the original query to identify WHERE clauses that can be pushed down\n * to specific collections, but only for simple queries without joins.\n *\n * @param query - The original QueryIR to analyze\n * @returns Map of collection aliases to their WHERE clauses\n */\nfunction extractCollectionWhereClauses(\n  query: QueryIR\n): Map<string, BasicExpression<boolean>> {\n  const collectionWhereClauses = new Map<string, BasicExpression<boolean>>()\n\n  // Only analyze queries that have WHERE clauses\n  if (!query.where || query.where.length === 0) {\n    return collectionWhereClauses\n  }\n\n  // Split all AND clauses at the root level for granular analysis\n  const splitWhereClauses = splitAndClauses(query.where)\n\n  // Analyze each WHERE clause to determine which sources it touches\n  const analyzedClauses = splitWhereClauses.map((clause) =>\n    analyzeWhereClause(clause)\n  )\n\n  // Group clauses by single-source vs multi-source\n  const groupedClauses = groupWhereClauses(analyzedClauses)\n\n  // Only include single-source clauses that reference collections directly\n  // and can be converted to BasicExpression format for collection indexes\n  for (const [sourceAlias, whereClause] of groupedClauses.singleSource) {\n    // Check if this source alias corresponds to a collection reference\n    if (isCollectionReference(query, sourceAlias)) {\n      // Check if the WHERE clause can be converted to collection-compatible format\n      if (isConvertibleToCollectionFilter(whereClause)) {\n        collectionWhereClauses.set(sourceAlias, whereClause)\n      }\n    }\n  }\n\n  return collectionWhereClauses\n}\n\n/**\n * Determines if a source alias refers to a collection reference (not a subquery).\n * This is used to identify WHERE clauses that can be pushed down to collection subscriptions.\n *\n * @param query - The query to analyze\n * @param sourceAlias - The source alias to check\n * @returns True if the alias refers to a collection reference\n */\nfunction isCollectionReference(query: QueryIR, sourceAlias: string): boolean {\n  // Check the FROM clause\n  if (query.from.alias === sourceAlias) {\n    return query.from.type === `collectionRef`\n  }\n\n  // Check JOIN clauses\n  if (query.join) {\n    for (const joinClause of query.join) {\n      if (joinClause.from.alias === sourceAlias) {\n        return joinClause.from.type === `collectionRef`\n      }\n    }\n  }\n\n  return false\n}\n\n/**\n * Applies recursive predicate pushdown optimization.\n *\n * @param query - The QueryIR to optimize\n * @returns A new QueryIR with optimizations applied\n */\nfunction applyRecursiveOptimization(query: QueryIR): QueryIR {\n  // First, recursively optimize any existing subqueries\n  const subqueriesOptimized = {\n    ...query,\n    from:\n      query.from.type === `queryRef`\n        ? new QueryRefClass(\n            applyRecursiveOptimization(query.from.query),\n            query.from.alias\n          )\n        : query.from,\n    join: query.join?.map((joinClause) => ({\n      ...joinClause,\n      from:\n        joinClause.from.type === `queryRef`\n          ? new QueryRefClass(\n              applyRecursiveOptimization(joinClause.from.query),\n              joinClause.from.alias\n            )\n          : joinClause.from,\n    })),\n  }\n\n  // Then apply single-level optimization to this query\n  return applySingleLevelOptimization(subqueriesOptimized)\n}\n\n/**\n * Applies single-level predicate pushdown optimization (existing logic)\n */\nfunction applySingleLevelOptimization(query: QueryIR): QueryIR {\n  // Skip optimization if no WHERE clauses exist\n  if (!query.where || query.where.length === 0) {\n    return query\n  }\n\n  // Skip optimization if there are no joins - predicate pushdown only benefits joins\n  // Single-table queries don't benefit from this optimization\n  if (!query.join || query.join.length === 0) {\n    return query\n  }\n\n  // Step 1: Split all AND clauses at the root level for granular optimization\n  const splitWhereClauses = splitAndClauses(query.where)\n\n  // Step 2: Analyze each WHERE clause to determine which sources it touches\n  const analyzedClauses = splitWhereClauses.map((clause) =>\n    analyzeWhereClause(clause)\n  )\n\n  // Step 3: Group clauses by single-source vs multi-source\n  const groupedClauses = groupWhereClauses(analyzedClauses)\n\n  // Step 4: Apply optimizations by lifting single-source clauses into subqueries\n  return applyOptimizations(query, groupedClauses)\n}\n\n/**\n * Removes redundant subqueries that don't add value.\n * A subquery is redundant if it only wraps another query without adding\n * WHERE, SELECT, GROUP BY, HAVING, ORDER BY, or LIMIT/OFFSET clauses.\n *\n * @param query - The QueryIR to process\n * @returns A new QueryIR with redundant subqueries removed\n */\nfunction removeRedundantSubqueries(query: QueryIR): QueryIR {\n  return {\n    ...query,\n    from: removeRedundantFromClause(query.from),\n    join: query.join?.map((joinClause) => ({\n      ...joinClause,\n      from: removeRedundantFromClause(joinClause.from),\n    })),\n  }\n}\n\n/**\n * Removes redundant subqueries from a FROM clause.\n *\n * @param from - The FROM clause to process\n * @returns A FROM clause with redundant subqueries removed\n */\nfunction removeRedundantFromClause(from: From): From {\n  if (from.type === `collectionRef`) {\n    return from\n  }\n\n  const processedQuery = removeRedundantSubqueries(from.query)\n\n  // Check if this subquery is redundant\n  if (isRedundantSubquery(processedQuery)) {\n    // Return the inner query's FROM clause with this alias\n    const innerFrom = removeRedundantFromClause(processedQuery.from)\n    if (innerFrom.type === `collectionRef`) {\n      return new CollectionRefClass(innerFrom.collection, from.alias)\n    } else {\n      return new QueryRefClass(innerFrom.query, from.alias)\n    }\n  }\n\n  return new QueryRefClass(processedQuery, from.alias)\n}\n\n/**\n * Determines if a subquery is redundant (adds no value).\n *\n * @param query - The query to check\n * @returns True if the query is redundant and can be removed\n */\nfunction isRedundantSubquery(query: QueryIR): boolean {\n  return (\n    (!query.where || query.where.length === 0) &&\n    !query.select &&\n    (!query.groupBy || query.groupBy.length === 0) &&\n    (!query.having || query.having.length === 0) &&\n    (!query.orderBy || query.orderBy.length === 0) &&\n    (!query.join || query.join.length === 0) &&\n    query.limit === undefined &&\n    query.offset === undefined &&\n    !query.fnSelect &&\n    (!query.fnWhere || query.fnWhere.length === 0) &&\n    (!query.fnHaving || query.fnHaving.length === 0)\n  )\n}\n\n/**\n * Step 1: Split all AND clauses recursively into separate WHERE clauses.\n *\n * This enables more granular optimization by treating each condition independently.\n * OR clauses are preserved as they cannot be split without changing query semantics.\n *\n * @param whereClauses - Array of WHERE expressions to split\n * @returns Flattened array with AND clauses split into separate expressions\n *\n * @example\n * ```typescript\n * // Input: [and(eq(a, 1), gt(b, 2)), eq(c, 3)]\n * // Output: [eq(a, 1), gt(b, 2), eq(c, 3)]\n * ```\n */\nfunction splitAndClauses(\n  whereClauses: Array<BasicExpression<boolean>>\n): Array<BasicExpression<boolean>> {\n  const result: Array<BasicExpression<boolean>> = []\n\n  for (const clause of whereClauses) {\n    if (clause.type === `func` && clause.name === `and`) {\n      // Recursively split nested AND clauses to handle complex expressions\n      const splitArgs = splitAndClauses(\n        clause.args as Array<BasicExpression<boolean>>\n      )\n      result.push(...splitArgs)\n    } else {\n      // Preserve non-AND clauses as-is (including OR clauses)\n      result.push(clause)\n    }\n  }\n\n  return result\n}\n\n/**\n * Step 2: Analyze which table sources a WHERE clause touches.\n *\n * This determines whether a clause can be pushed down to a specific table\n * or must remain in the main query (for multi-source clauses like join conditions).\n *\n * @param clause - The WHERE expression to analyze\n * @returns Analysis result with the expression and touched source aliases\n *\n * @example\n * ```typescript\n * // eq(users.department_id, 1) -> touches ['users']\n * // eq(users.id, posts.user_id) -> touches ['users', 'posts']\n * ```\n */\nfunction analyzeWhereClause(\n  clause: BasicExpression<boolean>\n): AnalyzedWhereClause {\n  const touchedSources = new Set<string>()\n\n  /**\n   * Recursively collect all table aliases referenced in an expression\n   */\n  function collectSources(expr: BasicExpression | any): void {\n    switch (expr.type) {\n      case `ref`:\n        // PropRef path has the table alias as the first element\n        if (expr.path && expr.path.length > 0) {\n          const firstElement = expr.path[0]\n          if (firstElement) {\n            touchedSources.add(firstElement)\n          }\n        }\n        break\n      case `func`:\n        // Recursively analyze function arguments (e.g., eq, gt, and, or)\n        if (expr.args) {\n          expr.args.forEach(collectSources)\n        }\n        break\n      case `val`:\n        // Values don't reference any sources\n        break\n      case `agg`:\n        // Aggregates can reference sources in their arguments\n        if (expr.args) {\n          expr.args.forEach(collectSources)\n        }\n        break\n    }\n  }\n\n  collectSources(clause)\n\n  return {\n    expression: clause,\n    touchedSources,\n  }\n}\n\n/**\n * Step 3: Group WHERE clauses by the sources they touch.\n *\n * Single-source clauses can be pushed down to subqueries for optimization.\n * Multi-source clauses must remain in the main query to preserve join semantics.\n *\n * @param analyzedClauses - Array of analyzed WHERE clauses\n * @returns Grouped clauses ready for optimization\n */\nfunction groupWhereClauses(\n  analyzedClauses: Array<AnalyzedWhereClause>\n): GroupedWhereClauses {\n  const singleSource = new Map<string, Array<BasicExpression<boolean>>>()\n  const multiSource: Array<BasicExpression<boolean>> = []\n\n  // Categorize each clause based on how many sources it touches\n  for (const clause of analyzedClauses) {\n    if (clause.touchedSources.size === 1) {\n      // Single source clause - can be optimized\n      const source = Array.from(clause.touchedSources)[0]!\n      if (!singleSource.has(source)) {\n        singleSource.set(source, [])\n      }\n      singleSource.get(source)!.push(clause.expression)\n    } else if (clause.touchedSources.size > 1) {\n      // Multi-source clause - must stay in main query\n      multiSource.push(clause.expression)\n    }\n    // Skip clauses that touch no sources (constants) - they don't need optimization\n  }\n\n  // Combine multiple clauses for each source with AND\n  const combinedSingleSource = new Map<string, BasicExpression<boolean>>()\n  for (const [source, clauses] of singleSource) {\n    combinedSingleSource.set(source, combineWithAnd(clauses))\n  }\n\n  // Combine multi-source clauses with AND\n  const combinedMultiSource =\n    multiSource.length > 0 ? combineWithAnd(multiSource) : undefined\n\n  return {\n    singleSource: combinedSingleSource,\n    multiSource: combinedMultiSource,\n  }\n}\n\n/**\n * Step 4: Apply optimizations by lifting single-source clauses into subqueries.\n *\n * Creates a new QueryIR with single-source WHERE clauses moved to subqueries\n * that wrap the original table references. This ensures immutability and prevents\n * infinite recursion issues.\n *\n * @param query - Original QueryIR to optimize\n * @param groupedClauses - WHERE clauses grouped by optimization strategy\n * @returns New QueryIR with optimizations applied\n */\nfunction applyOptimizations(\n  query: QueryIR,\n  groupedClauses: GroupedWhereClauses\n): QueryIR {\n  // Track which single-source clauses were actually optimized\n  const actuallyOptimized = new Set<string>()\n\n  // Optimize the main FROM clause and track what was optimized\n  const optimizedFrom = optimizeFromWithTracking(\n    query.from,\n    groupedClauses.singleSource,\n    actuallyOptimized\n  )\n\n  // Optimize JOIN clauses and track what was optimized\n  const optimizedJoins = query.join\n    ? query.join.map((joinClause) => ({\n        ...joinClause,\n        from: optimizeFromWithTracking(\n          joinClause.from,\n          groupedClauses.singleSource,\n          actuallyOptimized\n        ),\n      }))\n    : undefined\n\n  // Build the remaining WHERE clauses: multi-source + any single-source that weren't optimized\n  const remainingWhereClauses: Array<BasicExpression<boolean>> = []\n\n  // Add multi-source clauses\n  if (groupedClauses.multiSource) {\n    remainingWhereClauses.push(groupedClauses.multiSource)\n  }\n\n  // Add single-source clauses that weren't actually optimized\n  for (const [source, clause] of groupedClauses.singleSource) {\n    if (!actuallyOptimized.has(source)) {\n      remainingWhereClauses.push(clause)\n    }\n  }\n\n  // Create a completely new query object to ensure immutability\n  const optimizedQuery: QueryIR = {\n    // Copy all non-optimized fields as-is\n    select: query.select,\n    groupBy: query.groupBy ? [...query.groupBy] : undefined,\n    having: query.having ? [...query.having] : undefined,\n    orderBy: query.orderBy ? [...query.orderBy] : undefined,\n    limit: query.limit,\n    offset: query.offset,\n    fnSelect: query.fnSelect,\n    fnWhere: query.fnWhere ? [...query.fnWhere] : undefined,\n    fnHaving: query.fnHaving ? [...query.fnHaving] : undefined,\n\n    // Use the optimized FROM and JOIN clauses\n    from: optimizedFrom,\n    join: optimizedJoins,\n\n    // Only include WHERE clauses that weren't successfully optimized\n    where: remainingWhereClauses.length > 0 ? remainingWhereClauses : [],\n  }\n\n  return optimizedQuery\n}\n\n/**\n * Helper function to create a deep copy of a QueryIR object for immutability.\n *\n * This ensures that all optimizations create new objects rather than modifying\n * existing ones, preventing infinite recursion and shared reference issues.\n *\n * @param query - QueryIR to deep copy\n * @returns New QueryIR object with all nested objects copied\n */\nfunction deepCopyQuery(query: QueryIR): QueryIR {\n  return {\n    // Recursively copy the FROM clause\n    from:\n      query.from.type === `collectionRef`\n        ? new CollectionRefClass(query.from.collection, query.from.alias)\n        : new QueryRefClass(deepCopyQuery(query.from.query), query.from.alias),\n\n    // Copy all other fields, creating new arrays where necessary\n    select: query.select,\n    join: query.join\n      ? query.join.map((joinClause) => ({\n          type: joinClause.type,\n          left: joinClause.left,\n          right: joinClause.right,\n          from:\n            joinClause.from.type === `collectionRef`\n              ? new CollectionRefClass(\n                  joinClause.from.collection,\n                  joinClause.from.alias\n                )\n              : new QueryRefClass(\n                  deepCopyQuery(joinClause.from.query),\n                  joinClause.from.alias\n                ),\n        }))\n      : undefined,\n    where: query.where ? [...query.where] : undefined,\n    groupBy: query.groupBy ? [...query.groupBy] : undefined,\n    having: query.having ? [...query.having] : undefined,\n    orderBy: query.orderBy ? [...query.orderBy] : undefined,\n    limit: query.limit,\n    offset: query.offset,\n    fnSelect: query.fnSelect,\n    fnWhere: query.fnWhere ? [...query.fnWhere] : undefined,\n    fnHaving: query.fnHaving ? [...query.fnHaving] : undefined,\n  }\n}\n\n/**\n * Helper function to optimize a FROM clause while tracking what was actually optimized.\n *\n * @param from - FROM clause to optimize\n * @param singleSourceClauses - Map of source aliases to their WHERE clauses\n * @param actuallyOptimized - Set to track which sources were actually optimized\n * @returns New FROM clause, potentially wrapped in a subquery\n */\nfunction optimizeFromWithTracking(\n  from: From,\n  singleSourceClauses: Map<string, BasicExpression<boolean>>,\n  actuallyOptimized: Set<string>\n): From {\n  const whereClause = singleSourceClauses.get(from.alias)\n\n  if (!whereClause) {\n    // No optimization needed, but return a copy to maintain immutability\n    if (from.type === `collectionRef`) {\n      return new CollectionRefClass(from.collection, from.alias)\n    }\n    // Must be queryRef due to type system\n    return new QueryRefClass(deepCopyQuery(from.query), from.alias)\n  }\n\n  if (from.type === `collectionRef`) {\n    // Create a new subquery with the WHERE clause for the collection\n    // This is always safe since we're creating a new subquery\n    const subQuery: QueryIR = {\n      from: new CollectionRefClass(from.collection, from.alias),\n      where: [whereClause],\n    }\n    actuallyOptimized.add(from.alias) // Mark as successfully optimized\n    return new QueryRefClass(subQuery, from.alias)\n  }\n\n  // Must be queryRef due to type system\n\n  // SAFETY CHECK: Only check safety when pushing WHERE clauses into existing subqueries\n  // We need to be careful about pushing WHERE clauses into subqueries that already have\n  // aggregates, HAVING, or ORDER BY + LIMIT since that could change their semantics\n  if (!isSafeToPushIntoExistingSubquery(from.query)) {\n    // Return a copy without optimization to maintain immutability\n    // Do NOT mark as optimized since we didn't actually optimize it\n    return new QueryRefClass(deepCopyQuery(from.query), from.alias)\n  }\n\n  // Add the WHERE clause to the existing subquery\n  // Create a deep copy to ensure immutability\n  const existingWhere = from.query.where || []\n  const optimizedSubQuery: QueryIR = {\n    ...deepCopyQuery(from.query),\n    where: [...existingWhere, whereClause],\n  }\n  actuallyOptimized.add(from.alias) // Mark as successfully optimized\n  return new QueryRefClass(optimizedSubQuery, from.alias)\n}\n\n/**\n * Determines if it's safe to push WHERE clauses into an existing subquery.\n *\n * Pushing WHERE clauses into existing subqueries can break semantics in several cases:\n *\n * 1. **Aggregates**: Pushing predicates before GROUP BY changes what gets aggregated\n * 2. **ORDER BY + LIMIT/OFFSET**: Pushing predicates before sorting+limiting changes the result set\n * 3. **HAVING clauses**: These operate on aggregated data, predicates should not be pushed past them\n * 4. **Functional operations**: fnSelect, fnWhere, fnHaving could have side effects\n *\n * Note: This safety check only applies when pushing WHERE clauses into existing subqueries.\n * Creating new subqueries from collection references is always safe.\n *\n * @param query - The existing subquery to check for safety\n * @returns True if it's safe to push WHERE clauses into this subquery, false otherwise\n *\n * @example\n * ```typescript\n * // UNSAFE: has GROUP BY - pushing WHERE could change aggregation\n * { from: users, groupBy: [dept], select: { count: agg('count', '*') } }\n *\n * // UNSAFE: has ORDER BY + LIMIT - pushing WHERE could change \"top 10\"\n * { from: users, orderBy: [salary desc], limit: 10 }\n *\n * // SAFE: plain SELECT without aggregates/limits\n * { from: users, select: { id, name } }\n * ```\n */\nfunction isSafeToPushIntoExistingSubquery(query: QueryIR): boolean {\n  // Check for aggregates in SELECT clause\n  if (query.select) {\n    const hasAggregates = Object.values(query.select).some(\n      (expr) => expr.type === `agg`\n    )\n    if (hasAggregates) {\n      return false\n    }\n  }\n\n  // Check for GROUP BY clause\n  if (query.groupBy && query.groupBy.length > 0) {\n    return false\n  }\n\n  // Check for HAVING clause\n  if (query.having && query.having.length > 0) {\n    return false\n  }\n\n  // Check for ORDER BY with LIMIT or OFFSET (dangerous combination)\n  if (query.orderBy && query.orderBy.length > 0) {\n    if (query.limit !== undefined || query.offset !== undefined) {\n      return false\n    }\n  }\n\n  // Check for functional variants that might have side effects\n  if (\n    query.fnSelect ||\n    (query.fnWhere && query.fnWhere.length > 0) ||\n    (query.fnHaving && query.fnHaving.length > 0)\n  ) {\n    return false\n  }\n\n  // If none of the unsafe conditions are present, it's safe to optimize\n  return true\n}\n\n/**\n * Helper function to combine multiple expressions with AND.\n *\n * If there's only one expression, it's returned as-is.\n * If there are multiple expressions, they're combined with an AND function.\n *\n * 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