mirror of
https://github.com/asadbek064/hyparquet.git
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215 lines
9.0 KiB
JavaScript
215 lines
9.0 KiB
JavaScript
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import { assembleNested } from './assemble.js'
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import { getColumnRange, readColumn } from './column.js'
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import { parquetMetadataAsync } from './metadata.js'
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import { getSchemaPath } from './schema.js'
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import { concat } from './utils.js'
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/**
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* Read parquet data rows from a file-like object.
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* Reads the minimal number of row groups and columns to satisfy the request.
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*
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* Returns a void promise when complete, and to throw errors.
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* Data is returned in onComplete, not the return promise, because
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* if onComplete is undefined, we parse the data, and emit chunks, but skip
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* computing the row view directly. This saves on allocation if the caller
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* wants to cache the full chunks, and make their own view of the data from
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* the chunks.
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*
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* @typedef {import('./hyparquet.js').ColumnData} ColumnData
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* @typedef {import('./types.js').Compressors} Compressors
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* @typedef {import('./types.js').AsyncBuffer} AsyncBuffer
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* @typedef {import('./types.js').FileMetaData} FileMetaData
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* @param {object} options read options
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* @param {AsyncBuffer} options.file file-like object containing parquet data
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* @param {FileMetaData} [options.metadata] parquet file metadata
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* @param {string[]} [options.columns] columns to read, all columns if undefined
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* @param {number} [options.rowStart] first requested row index (inclusive)
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* @param {number} [options.rowEnd] last requested row index (exclusive)
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* @param {(chunk: ColumnData) => void} [options.onChunk] called when a column chunk is parsed. chunks may include row data outside the requested range.
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* @param {(rows: any[][]) => void} [options.onComplete] called when all requested rows and columns are parsed
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* @param {Compressors} [options.compressors] custom decompressors
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* @returns {Promise<void>} resolves when all requested rows and columns are parsed
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*/
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export async function parquetRead(options) {
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if (!options.file) throw new Error('parquet file is required')
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// load metadata if not provided
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options.metadata ||= await parquetMetadataAsync(options.file)
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if (!options.metadata) throw new Error('parquet metadata not found')
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const { metadata, onComplete, rowEnd } = options
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const rowStart = options.rowStart || 0
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/** @type {any[][]} */
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const rowData = []
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// find which row groups to read
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let groupStart = 0 // first row index of the current group
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for (const rowGroup of metadata.row_groups) {
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// number of rows in this row group
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const groupRows = Number(rowGroup.num_rows)
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// if row group overlaps with row range, read it
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if (groupStart + groupRows >= rowStart && (rowEnd === undefined || groupStart < rowEnd)) {
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// read row group
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const rowLimit = rowEnd && rowEnd - groupStart
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const groupData = await readRowGroup(options, rowGroup, groupStart, rowLimit)
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if (onComplete) {
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// filter to rows in range
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const start = Math.max(rowStart - groupStart, 0)
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const end = rowEnd === undefined ? undefined : rowEnd - groupStart
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concat(rowData, groupData.slice(start, end))
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}
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}
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groupStart += groupRows
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}
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if (onComplete) onComplete(rowData)
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}
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/**
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* Read a row group from a file-like object.
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*
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* @typedef {import('./types.js').RowGroup} RowGroup
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* @param {object} options read options
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* @param {AsyncBuffer} options.file file-like object containing parquet data
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* @param {FileMetaData} [options.metadata] parquet file metadata
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* @param {string[]} [options.columns] columns to read, all columns if undefined
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* @param {(chunk: ColumnData) => void} [options.onChunk] called when a column chunk is parsed. chunks may include row data outside the requested range.
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* @param {(rows: any[][]) => void} [options.onComplete] called when all requested rows and columns are parsed
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* @param {Compressors} [options.compressors]
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* @param {RowGroup} rowGroup row group to read
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* @param {number} groupStart row index of the first row in the group
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* @param {number} [rowLimit] max rows to read from this group
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* @returns {Promise<any[][]>} resolves to row data
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*/
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export async function readRowGroup(options, rowGroup, groupStart, rowLimit) {
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const { file, metadata, columns } = options
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if (!metadata) throw new Error('parquet metadata not found')
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if (rowLimit === undefined || rowLimit > rowGroup.num_rows) rowLimit = Number(rowGroup.num_rows)
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// loop through metadata to find min/max bytes to read
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let [groupStartByte, groupEndByte] = [file.byteLength, 0]
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rowGroup.columns.forEach(({ meta_data: columnMetadata }) => {
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if (!columnMetadata) throw new Error('parquet column metadata is undefined')
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// skip columns that are not requested
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if (columns && !columns.includes(columnMetadata.path_in_schema[0])) return
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const [columnStartByte, columnEndByte] = getColumnRange(columnMetadata).map(Number)
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groupStartByte = Math.min(groupStartByte, columnStartByte)
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groupEndByte = Math.max(groupEndByte, columnEndByte)
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})
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if (groupStartByte >= groupEndByte && columns?.length) {
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// TODO: should throw if any column is missing
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throw new Error(`parquet columns not found: ${columns.join(', ')}`)
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}
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// if row group size is less than 32mb, pre-load in one read
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let groupBuffer
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if (groupEndByte - groupStartByte <= 1 << 25) {
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// pre-load row group byte data in one big read,
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// otherwise read column data individually
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groupBuffer = await file.slice(groupStartByte, groupEndByte)
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}
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/** @type {any[][]} */
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const groupColumnData = []
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const promises = []
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// Top-level columns to assemble
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const { children } = getSchemaPath(metadata.schema, [])[0]
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const subcolumnNames = new Map(children.map(child => [child.element.name, getSubcolumns(child)]))
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const subcolumnData = new Map() // columns to assemble as maps
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// read column data
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for (let columnIndex = 0; columnIndex < rowGroup.columns.length; columnIndex++) {
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const columnMetadata = rowGroup.columns[columnIndex].meta_data
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if (!columnMetadata) throw new Error('parquet column metadata is undefined')
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// skip columns that are not requested
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const columnName = columnMetadata.path_in_schema[0]
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if (columns && !columns.includes(columnName)) continue
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const [columnStartByte, columnEndByte] = getColumnRange(columnMetadata).map(Number)
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const columnBytes = columnEndByte - columnStartByte
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// skip columns larger than 1gb
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// TODO: stream process the data, returning only the requested rows
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if (columnBytes > 1 << 30) {
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console.warn(`parquet skipping huge column "${columnMetadata.path_in_schema}" ${columnBytes.toLocaleString()} bytes`)
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// TODO: set column to new Error('parquet column too large')
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continue
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}
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// use pre-loaded row group byte data if available, else read column data
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/** @type {Promise<ArrayBuffer>} */
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let buffer
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let bufferOffset = 0
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if (groupBuffer) {
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buffer = Promise.resolve(groupBuffer)
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bufferOffset = columnStartByte - groupStartByte
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} else {
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// wrap awaitable to ensure it's a promise
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buffer = Promise.resolve(file.slice(columnStartByte, columnEndByte))
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}
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// read column data async
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promises.push(buffer.then(arrayBuffer => {
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const schemaPath = getSchemaPath(metadata.schema, columnMetadata.path_in_schema)
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const reader = { view: new DataView(arrayBuffer), offset: bufferOffset }
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/** @type {any[] | undefined} */
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let columnData = readColumn(reader, rowLimit, columnMetadata, schemaPath, options)
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// assert(columnData.length === Number(rowGroup.num_rows)
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// TODO: fast path for non-nested columns
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// Save column data for assembly
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const subcolumn = columnMetadata.path_in_schema.join('.')
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subcolumnData.set(subcolumn, columnData)
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columnData = undefined
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const subcolumns = subcolumnNames.get(columnName)
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if (subcolumns?.every(name => subcolumnData.has(name))) {
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// We have all data needed to assemble a top level column
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assembleNested(subcolumnData, schemaPath[1])
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columnData = subcolumnData.get(columnName)
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if (!columnData) {
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throw new Error(`parquet column data not assembled: ${columnName}`)
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}
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}
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// do not emit column data until structs are fully parsed
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if (!columnData) return
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// notify caller of column data
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options.onChunk?.({
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columnName,
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columnData,
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rowStart: groupStart,
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rowEnd: groupStart + columnData.length,
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})
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// save column data only if onComplete is defined
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if (options.onComplete) groupColumnData.push(columnData)
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}))
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}
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await Promise.all(promises)
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if (options.onComplete) {
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// transpose columns into rows
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return groupColumnData[0].map((_, row) => groupColumnData.map(col => col[row]))
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}
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return []
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}
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/**
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* Return a list of sub-columns needed to construct a top-level column.
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*
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* @param {import('./types.js').SchemaTree} schema
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* @param {string[]} output
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* @returns {string[]}
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*/
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function getSubcolumns(schema, output = []) {
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if (schema.children.length) {
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for (const child of schema.children) {
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getSubcolumns(child, output)
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}
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} else {
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output.push(schema.path.join('.'))
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}
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return output
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}
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