hyparquet-writer/test/write.buffer.test.js
2025-05-31 23:06:17 -07:00

305 lines
12 KiB
JavaScript

import { parquetMetadata, parquetReadObjects } from 'hyparquet'
import { describe, expect, it } from 'vitest'
import { parquetWriteBuffer } from '../src/index.js'
import { exampleData, exampleMetadata } from './example.js'
/**
* Utility to encode a parquet file and then read it back into a JS object.
*
* @import {ColumnSource} from '../src/types.js'
* @param {ColumnSource[]} columnData
* @param {import('hyparquet').SchemaElement[]} [schema]
* @returns {Promise<Record<string, any>>}
*/
async function roundTripDeserialize(columnData, schema) {
const file = parquetWriteBuffer({ columnData, schema })
return await parquetReadObjects({ file, utf8: false })
}
describe('parquetWriteBuffer', () => {
it('writes expected metadata', () => {
const file = parquetWriteBuffer({ columnData: exampleData })
const metadata = parquetMetadata(file)
expect(metadata).toEqual(exampleMetadata)
})
it('serializes basic types', async () => {
const result = await roundTripDeserialize(exampleData)
expect(result).toEqual([
{ bool: true, int: 0, bigint: 0n, float: 0, double: 0, string: 'a', nullable: true },
{ bool: false, int: 127, bigint: 127n, float: 0.00009999999747378752, double: 0.0001, string: 'b', nullable: false },
{ bool: true, int: 0x7fff, bigint: 0x7fffn, float: 123.45600128173828, double: 123.456, string: 'c', nullable: null },
{ bool: false, int: 0x7fffffff, bigint: 0x7fffffffffffffffn, float: Infinity, double: 1e100, string: 'd', nullable: null },
])
})
it('serializes a string as a BYTE_ARRAY', () => {
const data = ['string1', 'string2', 'string3']
const file = parquetWriteBuffer({ columnData: [{ name: 'string', data, type: 'BYTE_ARRAY' }] })
expect(file.byteLength).toBe(164)
})
it('serializes booleans as RLE', async () => {
const data = Array(100).fill(true)
const file = parquetWriteBuffer({ columnData: [{ name: 'bool', data }] })
expect(file.byteLength).toBe(131)
const metadata = parquetMetadata(file)
expect(metadata.row_groups[0].columns[0].meta_data?.encodings).toEqual(['RLE'])
const result = await parquetReadObjects({ file })
expect(result).toEqual(data.map(bool => ({ bool })))
})
it('efficiently serializes sparse booleans', async () => {
const data = Array(10000).fill(null)
data[10] = true
data[100] = false
data[500] = true
data[9999] = false
const file = parquetWriteBuffer({ columnData: [{ name: 'bool', data }] })
expect(file.byteLength).toBe(159)
const metadata = parquetMetadata(file)
expect(metadata.metadata_length).toBe(92)
const result = await parquetReadObjects({ file })
expect(result.length).toBe(10000)
expect(result[0]).toEqual({ bool: null })
expect(result[9]).toEqual({ bool: null })
expect(result[10]).toEqual({ bool: true })
expect(result[100]).toEqual({ bool: false })
expect(result[500]).toEqual({ bool: true })
expect(result[9999]).toEqual({ bool: false })
})
it('efficiently serializes long string', () => {
const str = 'a'.repeat(10000)
const file = parquetWriteBuffer({ columnData: [{ name: 'string', data: [str] }] })
expect(file.byteLength).toBe(638)
})
it('less efficiently serializes string without compression', () => {
const str = 'a'.repeat(10000)
const columnData = [{ name: 'string', data: [str] }]
const file = parquetWriteBuffer({ columnData, compressed: false })
expect(file.byteLength).toBe(10168)
})
it('efficiently serializes column with few distinct values', async () => {
const data = Array(100000)
.fill('aaaa', 0, 50000)
.fill('bbbb', 50000, 100000)
const file = parquetWriteBuffer({ columnData: [{ name: 'string', data }], statistics: false })
expect(file.byteLength).toBe(170)
// round trip
const result = await parquetReadObjects({ file })
expect(result.length).toBe(100000)
expect(result[0]).toEqual({ string: 'aaaa' })
expect(result[50000]).toEqual({ string: 'bbbb' })
})
it('writes statistics when enabled', () => {
const withStats = parquetWriteBuffer({ columnData: exampleData, statistics: true })
const noStats = parquetWriteBuffer({ columnData: exampleData, statistics: false })
expect(withStats.byteLength).toBe(721)
expect(noStats.byteLength).toBe(611)
})
it('serializes list types', async () => {
const result = await roundTripDeserialize([{
name: 'list',
data: [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]],
}])
expect(result).toEqual([
{ list: [1, 2, 3] },
{ list: [4, 5, 6] },
{ list: [7, 8, 9] },
{ list: [10, 11, 12] },
])
})
it('serializes object types', async () => {
const result = await roundTripDeserialize([{
name: 'obj',
data: [{ a: 1, b: 2 }, { a: 3, b: 4 }, { a: 5, b: 6 }, { a: 7, b: 8 }],
}])
expect(result).toEqual([
{ obj: { a: 1, b: 2 } },
{ obj: { a: 3, b: 4 } },
{ obj: { a: 5, b: 6 } },
{ obj: { a: 7, b: 8 } },
])
})
it('serializes date types', async () => {
const result = await roundTripDeserialize([{
name: 'date',
data: [new Date(0), new Date(100000), new Date(200000), new Date(300000)],
}])
expect(result).toEqual([
{ date: new Date(0) },
{ date: new Date(100000) },
{ date: new Date(200000) },
{ date: new Date(300000) },
])
})
it('serializes time types', async () => {
const result = await roundTripDeserialize(
[
{
name: 'time32',
data: [100000, 200000, 300000],
},
{
name: 'time64',
data: [100000000n, 200000000n, 300000000n],
},
{
name: 'interval',
data: [1000000000n, 2000000000n, 3000000000n],
},
],
[
{ name: 'root', num_children: 3 },
{ name: 'time32', repetition_type: 'OPTIONAL', type: 'INT32', logical_type: { type: 'TIME', isAdjustedToUTC: false, unit: 'MILLIS' } },
{ name: 'time64', repetition_type: 'OPTIONAL', type: 'INT64', logical_type: { type: 'TIME', isAdjustedToUTC: false, unit: 'MICROS' } },
{ name: 'interval', repetition_type: 'OPTIONAL', type: 'INT64', logical_type: { type: 'INTERVAL' } },
]
)
expect(result).toEqual([
{ time32: 100000, time64: 100000000n, interval: 1000000000n },
{ time32: 200000, time64: 200000000n, interval: 2000000000n },
{ time32: 300000, time64: 300000000n, interval: 3000000000n },
])
})
it('serializes byte array types', async () => {
const result = await roundTripDeserialize([{
name: 'bytes',
data: [Uint8Array.of(1, 2, 3), Uint8Array.of(4, 5, 6), Uint8Array.of(7, 8, 9), Uint8Array.of(10, 11, 12)],
}])
expect(result).toEqual([
{ bytes: Uint8Array.of(1, 2, 3) },
{ bytes: Uint8Array.of(4, 5, 6) },
{ bytes: Uint8Array.of(7, 8, 9) },
{ bytes: Uint8Array.of(10, 11, 12) },
])
})
it('serializes uuid types', async () => {
const result = await roundTripDeserialize([
{
name: 'uuid',
data: [
new Uint8Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]),
new Uint8Array([17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]),
],
type: 'UUID',
},
{
name: 'string',
data: [
'00000000-0000-0000-0000-000000000001',
'00010002-0003-0004-0005-000600070008',
],
type: 'UUID',
},
])
expect(result).toEqual([
{
uuid: new Uint8Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]),
string: new Uint8Array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),
},
{
uuid: new Uint8Array([17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]),
string: new Uint8Array([0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8]),
},
])
})
it('serializes empty column', async () => {
const result = await roundTripDeserialize([{
name: 'empty',
data: [null, null, null, null],
type: 'BOOLEAN',
}])
expect(result).toEqual([
{ empty: null },
{ empty: null },
{ empty: null },
{ empty: null },
])
})
it('serializes empty table', async () => {
const result = await roundTripDeserialize([])
expect(result).toEqual([])
})
it('handles special numeric values', async () => {
const data = [
{ name: 'double', data: [NaN, Infinity, -Infinity, 42, 0, -0] },
]
const result = await roundTripDeserialize(data)
expect(result[0].double).toBeNaN()
expect(result[1].double).toEqual(Infinity)
expect(result[2].double).toEqual(-Infinity)
expect(result[3].double).toEqual(42)
expect(result[4].double).toEqual(0)
expect(result[5].double).toEqual(-0)
expect(result[5].double).not.toEqual(0)
})
it('splits row groups', async () => {
const data = Array(200).fill(13)
const file = parquetWriteBuffer({ columnData: [{ name: 'int', data }], rowGroupSize: 100 })
const metadata = parquetMetadata(file)
expect(metadata.row_groups.length).toBe(2)
expect(metadata.row_groups[0].num_rows).toBe(100n)
expect(metadata.row_groups[1].num_rows).toBe(100n)
// round trip
const result = await parquetReadObjects({ file })
expect(result.length).toBe(200)
expect(result[0]).toEqual({ int: 13 })
expect(result[99]).toEqual({ int: 13 })
expect(result[100]).toEqual({ int: 13 })
expect(result[199]).toEqual({ int: 13 })
})
it('throws for wrong type specified', () => {
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1, 2, 3], type: 'INT64' }] }))
.toThrow('parquet expected bigint value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1n, 2n, 3n], type: 'INT32' }] }))
.toThrow('parquet expected integer value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1, 2, 3n], type: 'INT32' }] }))
.toThrow('parquet expected integer value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1, 2, 3.5], type: 'INT32' }] }))
.toThrow('parquet expected integer value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1n, 2n, 3n], type: 'FLOAT' }] }))
.toThrow('parquet expected number value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1n, 2n, 3n], type: 'DOUBLE' }] }))
.toThrow('parquet expected number value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'int', data: [1, 2, 3], type: 'BYTE_ARRAY' }] }))
.toThrow('parquet expected Uint8Array value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'float16', data: [1n, 2n, 3n], type: 'FLOAT16' }] }))
.toThrow('parquet float16 expected number value')
expect(() => parquetWriteBuffer({ columnData: [{ name: 'uuid', data: [new Uint8Array(4)], type: 'UUID' }] }))
.toThrow('parquet expected Uint8Array of length 16')
})
it('throws for mixed types', () => {
expect(() => parquetWriteBuffer({ columnData: [{ name: 'mixed', data: [1, 2, 3, 'boom'] }] }))
.toThrow('mixed types not supported')
})
it('throws error when columns have mismatched lengths', () => {
expect(() => parquetWriteBuffer({ columnData: [
{ name: 'col1', data: [1, 2, 3] },
{ name: 'col2', data: [4, 5] },
] })).toThrow('columns must have the same length')
})
it('throws error for unsupported data types', () => {
expect(() => parquetWriteBuffer({ columnData: [{ name: 'func', data: [() => {}] }] }))
.toThrow('cannot determine parquet type for: () => {}')
})
})