@tanstack/db-ivm/dist/cjs/operators/groupBy.cjs.map

Incremental View Maintenance for TanStack DB based on Differential Dataflow

{"version":3,"file":"groupBy.cjs","sources":["../../../src/operators/groupBy.ts"],"sourcesContent":["import { map } from \"./map.js\"\nimport { reduce } from \"./reduce.js\"\nimport type { IStreamBuilder, KeyValue } from \"../types.js\"\n\ntype GroupKey = Record<string, unknown>\n\ntype BasicAggregateFunction<T, R, V = unknown> = {\n  preMap: (data: T) => V\n  reduce: (values: Array<[V, number]>) => V\n  postMap?: (result: V) => R\n}\n\ntype PipedAggregateFunction<T, R> = {\n  pipe: (stream: IStreamBuilder<T>) => IStreamBuilder<KeyValue<string, R>>\n}\n\ntype AggregateFunction<T, R, V = unknown> =\n  | BasicAggregateFunction<T, R, V>\n  | PipedAggregateFunction<T, R>\n\ntype ExtractAggregateReturnType<T, A> =\n  A extends AggregateFunction<T, infer R, any> ? R : never\n\ntype AggregatesReturnType<T, A> = {\n  [K in keyof A]: ExtractAggregateReturnType<T, A[K]>\n}\n\nfunction isPipedAggregateFunction<T, R>(\n  aggregate: AggregateFunction<T, R>\n): aggregate is PipedAggregateFunction<T, R> {\n  return `pipe` in aggregate\n}\n\n/**\n * Groups data by key and applies multiple aggregate operations\n * @param keyExtractor Function to extract grouping key from data\n * @param aggregates Object mapping aggregate names to aggregate functions\n */\nexport function groupBy<\n  T,\n  K extends GroupKey,\n  A extends Record<string, AggregateFunction<T, any, any>>,\n>(keyExtractor: (data: T) => K, aggregates: A = {} as A) {\n  type ResultType = K & AggregatesReturnType<T, A>\n\n  const basicAggregates = Object.fromEntries(\n    Object.entries(aggregates).filter(\n      ([_, aggregate]) => !isPipedAggregateFunction(aggregate)\n    )\n  ) as Record<string, BasicAggregateFunction<T, any, any>>\n\n  // @ts-expect-error - TODO: we don't use this yet, but we will\n  // eslint-disable-next-line @typescript-eslint/no-unused-vars\n  const pipedAggregates = Object.fromEntries(\n    Object.entries(aggregates).filter(([_, aggregate]) =>\n      isPipedAggregateFunction(aggregate)\n    )\n  ) as Record<string, PipedAggregateFunction<T, any>>\n\n  return (\n    stream: IStreamBuilder<T>\n  ): IStreamBuilder<KeyValue<string, ResultType>> => {\n    // Special key to store the original key object\n    const KEY_SENTINEL = `__original_key__`\n\n    // First map to extract keys and pre-aggregate values\n    const withKeysAndValues = stream.pipe(\n      map((data) => {\n        const key = keyExtractor(data)\n        const keyString = JSON.stringify(key)\n\n        // Create values object with pre-aggregated values\n        const values: Record<string, unknown> = {}\n\n        // Store the original key object\n        values[KEY_SENTINEL] = key\n\n        // Add pre-aggregated values\n        for (const [name, aggregate] of Object.entries(basicAggregates)) {\n          values[name] = aggregate.preMap(data)\n        }\n\n        return [keyString, values] as KeyValue<string, Record<string, unknown>>\n      })\n    )\n\n    // Then reduce to compute aggregates\n    const reduced = withKeysAndValues.pipe(\n      reduce((values) => {\n        // Calculate total multiplicity to check if the group should exist\n        let totalMultiplicity = 0\n        for (const [_, multiplicity] of values) {\n          totalMultiplicity += multiplicity\n        }\n\n        // If total multiplicity is 0 or negative, the group should be removed completely\n        if (totalMultiplicity <= 0) {\n          return []\n        }\n\n        const result: Record<string, unknown> = {}\n\n        // Get the original key from first value in group\n        const originalKey = values[0]?.[0]?.[KEY_SENTINEL]\n        result[KEY_SENTINEL] = originalKey\n\n        // Apply each aggregate function\n        for (const [name, aggregate] of Object.entries(basicAggregates)) {\n          const preValues = values.map(\n            ([v, m]) => [v[name], m] as [any, number]\n          )\n          result[name] = aggregate.reduce(preValues)\n        }\n\n        return [[result, 1]]\n      })\n    )\n\n    // Finally map to extract the key and include all values\n    return reduced.pipe(\n      map(([keyString, values]) => {\n        // Extract the original key\n        const key = values[KEY_SENTINEL] as K\n\n        // Create intermediate result with key values and aggregate results\n        const result: Record<string, unknown> = {}\n\n        // Add key properties to result\n        Object.assign(result, key)\n\n        // Apply postMap if provided\n        for (const [name, aggregate] of Object.entries(basicAggregates)) {\n          if (aggregate.postMap) {\n            result[name] = aggregate.postMap(values[name])\n          } else {\n            result[name] = values[name]\n          }\n        }\n\n        // Return with the string key instead of the object\n        return [keyString, result] as KeyValue<string, ResultType>\n      })\n    )\n  }\n}\n\n/**\n * Creates a sum aggregate function\n */\nexport function sum<T>(\n  valueExtractor: (value: T) => number = (v) => v as unknown as number\n): AggregateFunction<T, number, number> {\n  return {\n    preMap: (data: T) => valueExtractor(data),\n    reduce: (values: Array<[number, number]>) => {\n      let total = 0\n      for (const [value, multiplicity] of values) {\n        total += value * multiplicity\n      }\n      return total\n    },\n  }\n}\n\n/**\n * Creates a count aggregate function\n */\nexport function count<T>(): AggregateFunction<T, number, number> {\n  return {\n    preMap: () => 1,\n    reduce: (values: Array<[number, number]>) => {\n      let totalCount = 0\n      for (const [_, multiplicity] of values) {\n        totalCount += multiplicity\n      }\n      return totalCount\n    },\n  }\n}\n\n/**\n * Creates an average aggregate function\n */\nexport function avg<T>(\n  valueExtractor: (value: T) => number = (v) => v as unknown as number\n): AggregateFunction<T, number, { sum: number; count: number }> {\n  return {\n    preMap: (data: T) => ({\n      sum: valueExtractor(data),\n      count: 0,\n    }),\n    reduce: (values: Array<[{ sum: number; count: number }, number]>) => {\n      let totalSum = 0\n      let totalCount = 0\n      for (const [value, multiplicity] of values) {\n        totalSum += value.sum * multiplicity\n        totalCount += multiplicity\n      }\n      return {\n        sum: totalSum,\n        count: totalCount,\n      }\n    },\n    postMap: (result: { sum: number; count: number }) => {\n      return result.sum / result.count\n    },\n  }\n}\n\n/**\n * Creates a min aggregate function that computes the minimum value in a group\n * @param valueExtractor Function to extract a numeric value from each data entry\n */\nexport function min<T>(\n  valueExtractor: (value: T) => number = (v) => v as unknown as number\n): AggregateFunction<T, number, number> {\n  return {\n    preMap: (data: T) => valueExtractor(data),\n    reduce: (values: Array<[number, number]>) => {\n      let minValue = Number.POSITIVE_INFINITY\n      for (const [value, _multiplicity] of values) {\n        if (value < minValue) {\n          minValue = value\n        }\n      }\n      return minValue === Number.POSITIVE_INFINITY ? 0 : minValue\n    },\n  }\n}\n\n/**\n * Creates a max aggregate function that computes the maximum value in a group\n * @param valueExtractor Function to extract a numeric value from each data entry\n */\nexport function max<T>(\n  valueExtractor: (value: T) => number = (v) => v as unknown as number\n): AggregateFunction<T, number, number> {\n  return {\n    preMap: (data: T) => valueExtractor(data),\n    reduce: (values: Array<[number, number]>) => {\n      let maxValue = Number.NEGATIVE_INFINITY\n      for (const [value, _multiplicity] of values) {\n        if (value > maxValue) {\n          maxValue = value\n        }\n      }\n      return maxValue === Number.NEGATIVE_INFINITY ? 0 : maxValue\n    },\n  }\n}\n\n/**\n * Creates a median aggregate function that computes the middle value in a sorted group\n * If there's an even number of values, returns the average of the two middle values\n * @param valueExtractor Function to extract a numeric value from each data entry\n */\nexport function median<T>(\n  valueExtractor: (value: T) => number = (v) => v as unknown as number\n): AggregateFunction<T, number, Array<number>> {\n  return {\n    preMap: (data: T) => [valueExtractor(data)],\n    reduce: (values: Array<[Array<number>, number]>) => {\n      // Flatten all values, taking multiplicity into account\n      const allValues: Array<number> = []\n      for (const [valueArray, multiplicity] of values) {\n        for (const value of valueArray) {\n          // Add each value multiple times based on multiplicity\n          for (let i = 0; i < multiplicity; i++) {\n            allValues.push(value)\n          }\n        }\n      }\n\n      // Return empty array if no values\n      if (allValues.length === 0) {\n        return []\n      }\n\n      // Sort values\n      allValues.sort((a, b) => a - b)\n\n      return allValues\n    },\n    postMap: (result: Array<number>) => {\n      if (result.length === 0) return 0\n\n      const mid = Math.floor(result.length / 2)\n\n      // If even number of values, average the two middle values\n      if (result.length % 2 === 0) {\n        return (result[mid - 1]! + result[mid]!) / 2\n      }\n\n      // If odd number of values, return the middle value\n      return result[mid]!\n    },\n  }\n}\n\n/**\n * Creates a mode aggregate function that computes the most frequent value in a group\n * If multiple values have the same highest frequency, returns the first one encountered\n * @param valueExtractor Function to extract a value from each data entry\n */\nexport function mode<T>(\n  valueExtractor: (value: T) 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  if (frequency > maxFrequency) {\n          maxFrequency = frequency\n          modeValue = value\n        }\n      }\n\n      return modeValue\n    },\n  }\n}\n\nexport const groupByOperators = {\n  sum,\n  count,\n  avg,\n  min,\n  max,\n  median,\n  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