1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
|
% Tests for the arrow.tabular.Table class and the associated arrow.table
% construction function.
% 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.
classdef tTable < hTabular
properties
FromArraysFcn = @arrow.tabular.Table.fromArrays
ConstructionFcn = @arrow.table
ClassName = "arrow.tabular.Table"
end
methods(Test)
function FromRecordBatchesZeroInputsError(testCase)
% Verify the arrow.tabular.Table.fromRecordBatches function
% throws an `arrow:Table:FromRecordBatches:ZeroBatches`
% exception if called with zero input arguments.
import arrow.tabular.Table
fcn = @() Table.fromRecordBatches();
testCase.verifyError(fcn, "arrow:Table:FromRecordBatches:ZeroBatches");
end
function FromRecordBatchesOneInput(testCase)
% Verify the arrow.tabular.Table.fromRecordBatches function
% returns the expected arrow.tabular.Table instance when
% provided a single RecordBatch as input.
import arrow.tabular.Table
import arrow.type.traits.traits
matlabTable = table([1; 2], ["A"; "B"], VariableNames=["Number" "Letter"]);
recordBatch = arrow.recordBatch(matlabTable);
arrowTable = Table.fromRecordBatches(recordBatch);
expectedColumnTraits = varfun(@(var) traits(string(class(var))), ...
matlabTable, OutputFormat="cell");
testCase.verifyTabularObject(arrowTable, ["Number", "Letter"], expectedColumnTraits, matlabTable);
end
function FromRecordBatchesMultipleInputs(testCase)
% Verify the arrow.tabular.Table.fromRecordBatches function
% returns the expected arrow.tabular.Table instance when
% provided mulitple RecordBatches as input.
import arrow.tabular.Table
import arrow.type.traits.traits
matlabTable1 = table([1; 2], ["A"; "B"], VariableNames=["Number" "Letter"]);
matlabTable2 = table([10; 20; 30], ["A1"; "B1"; "C1"], VariableNames=["Number" "Letter"]);
matlabTable3 = table([100; 200], ["A2"; "B2"], VariableNames=["Number" "Letter"]);
recordBatch1 = arrow.recordBatch(matlabTable1);
recordBatch2 = arrow.recordBatch(matlabTable2);
recordBatch3 = arrow.recordBatch(matlabTable3);
arrowTable = Table.fromRecordBatches(recordBatch1, recordBatch2, recordBatch3);
expectedColumnTraits = varfun(@(var) traits(string(class(var))), ...
matlabTable1, OutputFormat="cell");
testCase.verifyTabularObject(arrowTable, ["Number", "Letter"], expectedColumnTraits, [matlabTable1; matlabTable2; matlabTable3]);
end
function FromRecordBatchesInconsistentSchemaError(testCase)
% Verify the arrow.tabular.Table.fromRecordBatches function
% throws an `arrow:Table:FromRecordBatches:InconsistentSchema`
% exception if the Schemas of the provided RecordBatches are
% inconsistent.
import arrow.tabular.Table
matlabTable1 = table("A", 1);
matlabTable2 = table(2, "B");
recordBatch1 = arrow.recordBatch(matlabTable1);
recordBatch2 = arrow.recordBatch(matlabTable2);
fcn = @() Table.fromRecordBatches(recordBatch1, recordBatch2);
testCase.verifyError(fcn, "arrow:Table:FromRecordBatches:InconsistentSchema");
end
end
methods
function verifyTabularObject(tc, arrowTabularObj, columnNames, columnTraits, matlabTable)
tc.verifyInstanceOf(arrowTabularObj, tc.ClassName);
tc.verifyEqual(arrowTabularObj.NumColumns, int32(width(matlabTable)));
tc.verifyEqual(arrowTabularObj.ColumnNames, columnNames);
convertedTable = arrowTabularObj.table();
tc.verifyEqual(convertedTable, matlabTable);
for ii = 1:arrowTabularObj.NumColumns
column = arrowTabularObj.column(ii);
tc.verifyEqual(column.toMATLAB(), matlabTable{:, ii});
tc.verifyInstanceOf(column, "arrow.array.ChunkedArray");
tc.verifyInstanceOf(column.Type, columnTraits{ii}.TypeClassName);
end
end
function col = makeColumnFromArray(~, array)
% Each column in an arrow.tabular.Table is an
% arrow.array.ChunkedArray.
col = arrow.array.ChunkedArray.fromArrays(array);
end
end
end
|
