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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-21 11:54:28 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-21 11:54:28 +0000 |
commit | e6918187568dbd01842d8d1d2c808ce16a894239 (patch) | |
tree | 64f88b554b444a49f656b6c656111a145cbbaa28 /src/arrow/js/test/data | |
parent | Initial commit. (diff) | |
download | ceph-e6918187568dbd01842d8d1d2c808ce16a894239.tar.xz ceph-e6918187568dbd01842d8d1d2c808ce16a894239.zip |
Adding upstream version 18.2.2.upstream/18.2.2
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'src/arrow/js/test/data')
-rw-r--r-- | src/arrow/js/test/data/tables.ts | 84 |
1 files changed, 84 insertions, 0 deletions
diff --git a/src/arrow/js/test/data/tables.ts b/src/arrow/js/test/data/tables.ts new file mode 100644 index 000000000..6ce2c861d --- /dev/null +++ b/src/arrow/js/test/data/tables.ts @@ -0,0 +1,84 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +import { vecs } from '../generate-test-data'; +import * as generate from '../generate-test-data'; +import { Schema, Field, Dictionary } from '../Arrow'; + +const listVectorGeneratorNames = ['list', 'fixedSizeList']; +const nestedVectorGeneratorNames = [ 'struct', 'denseUnion', 'sparseUnion', 'map' ]; +const dictionaryKeyGeneratorNames = ['int8' ,'int16' ,'int32' ,'uint8' ,'uint16' ,'uint32']; +const valueVectorGeneratorNames = [ + 'null_', 'bool', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64', + 'float16', 'float32', 'float64', 'utf8', 'binary', 'fixedSizeBinary', 'dateDay', 'dateMillisecond', + 'timestampSecond', 'timestampMillisecond', 'timestampMicrosecond', 'timestampNanosecond', + 'timeSecond', 'timeMillisecond', 'timeMicrosecond', 'timeNanosecond', 'decimal', + 'dictionary', 'intervalDayTime', 'intervalYearMonth' +]; + +const vectorGeneratorNames = [...valueVectorGeneratorNames, ...listVectorGeneratorNames, ...nestedVectorGeneratorNames]; + +export function* generateRandomTables(batchLengths = [1000, 2000, 3000], minCols = 1, maxCols = 5) { + + let numCols = 0; + let allNames = shuffle(vectorGeneratorNames); + + do { + numCols = Math.max(Math.min( + Math.random() * maxCols | 0, allNames.length), minCols); + + let names = allNames.slice(0, numCols); + let types = names.map((fn) => vecs[fn](0).vector.type); + let schema = new Schema(names.map((name, i) => new Field(name, types[i]))); + + yield generate.table(batchLengths, schema).table; + + } while ((allNames = allNames.slice(numCols)).length > 0); +} + +/** + * Yields a series of tables containing a single Dictionary-encoded column. + * Each yielded table will be a unique combination of dictionary and indexType, + * such that consuming all tables ensures all Arrow types dictionary-encode. + * + * @param batchLengths number[] Number and length of recordbatches to generate + */ +export function* generateDictionaryTables(batchLengths = [100, 200, 300]) { + for (const dictName of valueVectorGeneratorNames) { + if (dictName === 'dictionary') { continue; } + const dictionary = vecs[dictName](100).vector; + for (const keys of dictionaryKeyGeneratorNames) { + const valsType = dictionary.type; + const keysType = vecs[keys](0).vector.type; + const dictType = new Dictionary(valsType, keysType); + const schema = new Schema([new Field(`dict[${keys}]`, dictType, true)]); + yield generate.table(batchLengths, schema).table; + } + } +} + +function shuffle(input: any[]) { + const result = input.slice(); + let j, tmp, i = result.length; + while (--i > 0) { + j = (Math.random() * (i + 1)) | 0; + tmp = result[i]; + result[i] = result[j]; + result[j] = tmp; + } + return result; +} |