-
Notifications
You must be signed in to change notification settings - Fork 1.3k
/
Copy pathscalar.rs
1984 lines (1890 loc) · 79.7 KB
/
scalar.rs
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
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
// 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.
//! This module provides ScalarValue, an enum that can be used for storage of single elements
use crate::error::{DataFusionError, Result};
use arrow::{
array::*,
compute::kernels::cast::{cast, cast_with_options, CastOptions},
datatypes::{
ArrowDictionaryKeyType, ArrowNativeType, DataType, Field, Float32Type,
Float64Type, Int16Type, Int32Type, Int64Type, Int8Type, IntervalUnit, TimeUnit,
TimestampMicrosecondType, TimestampMillisecondType, TimestampNanosecondType,
TimestampSecondType, UInt16Type, UInt32Type, UInt64Type, UInt8Type,
DECIMAL_MAX_PRECISION,
},
util::decimal::{BasicDecimal, Decimal128},
};
use ordered_float::OrderedFloat;
use std::cmp::Ordering;
use std::convert::{Infallible, TryInto};
use std::str::FromStr;
use std::{convert::TryFrom, fmt, iter::repeat, sync::Arc};
/// Represents a dynamically typed, nullable single value.
/// This is the single-valued counter-part of arrow’s `Array`.
#[derive(Clone)]
pub enum ScalarValue {
/// represents `DataType::Null` (castable to/from any other type)
Null,
/// true or false value
Boolean(Option<bool>),
/// 32bit float
Float32(Option<f32>),
/// 64bit float
Float64(Option<f64>),
/// 128bit decimal, using the i128 to represent the decimal
Decimal128(Option<i128>, usize, usize),
/// signed 8bit int
Int8(Option<i8>),
/// signed 16bit int
Int16(Option<i16>),
/// signed 32bit int
Int32(Option<i32>),
/// signed 64bit int
Int64(Option<i64>),
/// unsigned 8bit int
UInt8(Option<u8>),
/// unsigned 16bit int
UInt16(Option<u16>),
/// unsigned 32bit int
UInt32(Option<u32>),
/// unsigned 64bit int
UInt64(Option<u64>),
/// utf-8 encoded string.
Utf8(Option<String>),
/// utf-8 encoded string representing a LargeString's arrow type.
LargeUtf8(Option<String>),
/// binary
Binary(Option<Vec<u8>>),
/// large binary
LargeBinary(Option<Vec<u8>>),
/// list of nested ScalarValue
List(Option<Vec<ScalarValue>>, Box<DataType>),
/// Date stored as a signed 32bit int
Date32(Option<i32>),
/// Date stored as a signed 64bit int
Date64(Option<i64>),
/// Timestamp Second
TimestampSecond(Option<i64>, Option<String>),
/// Timestamp Milliseconds
TimestampMillisecond(Option<i64>, Option<String>),
/// Timestamp Microseconds
TimestampMicrosecond(Option<i64>, Option<String>),
/// Timestamp Nanoseconds
TimestampNanosecond(Option<i64>, Option<String>),
/// Interval with YearMonth unit
IntervalYearMonth(Option<i32>),
/// Interval with DayTime unit
IntervalDayTime(Option<i64>),
/// Interval with MonthDayNano unit
IntervalMonthDayNano(Option<i128>),
/// struct of nested ScalarValue
Struct(Option<Vec<ScalarValue>>, Box<Vec<Field>>),
}
// manual implementation of `PartialEq` that uses OrderedFloat to
// get defined behavior for floating point
impl PartialEq for ScalarValue {
fn eq(&self, other: &Self) -> bool {
use ScalarValue::*;
// This purposely doesn't have a catch-all "(_, _)" so that
// any newly added enum variant will require editing this list
// or else face a compile error
match (self, other) {
(Decimal128(v1, p1, s1), Decimal128(v2, p2, s2)) => {
v1.eq(v2) && p1.eq(p2) && s1.eq(s2)
}
(Decimal128(_, _, _), _) => false,
(Boolean(v1), Boolean(v2)) => v1.eq(v2),
(Boolean(_), _) => false,
(Float32(v1), Float32(v2)) => {
let v1 = v1.map(OrderedFloat);
let v2 = v2.map(OrderedFloat);
v1.eq(&v2)
}
(Float32(_), _) => false,
(Float64(v1), Float64(v2)) => {
let v1 = v1.map(OrderedFloat);
let v2 = v2.map(OrderedFloat);
v1.eq(&v2)
}
(Float64(_), _) => false,
(Int8(v1), Int8(v2)) => v1.eq(v2),
(Int8(_), _) => false,
(Int16(v1), Int16(v2)) => v1.eq(v2),
(Int16(_), _) => false,
(Int32(v1), Int32(v2)) => v1.eq(v2),
(Int32(_), _) => false,
(Int64(v1), Int64(v2)) => v1.eq(v2),
(Int64(_), _) => false,
(UInt8(v1), UInt8(v2)) => v1.eq(v2),
(UInt8(_), _) => false,
(UInt16(v1), UInt16(v2)) => v1.eq(v2),
(UInt16(_), _) => false,
(UInt32(v1), UInt32(v2)) => v1.eq(v2),
(UInt32(_), _) => false,
(UInt64(v1), UInt64(v2)) => v1.eq(v2),
(UInt64(_), _) => false,
(Utf8(v1), Utf8(v2)) => v1.eq(v2),
(Utf8(_), _) => false,
(LargeUtf8(v1), LargeUtf8(v2)) => v1.eq(v2),
(LargeUtf8(_), _) => false,
(Binary(v1), Binary(v2)) => v1.eq(v2),
(Binary(_), _) => false,
(LargeBinary(v1), LargeBinary(v2)) => v1.eq(v2),
(LargeBinary(_), _) => false,
(List(v1, t1), List(v2, t2)) => v1.eq(v2) && t1.eq(t2),
(List(_, _), _) => false,
(Date32(v1), Date32(v2)) => v1.eq(v2),
(Date32(_), _) => false,
(Date64(v1), Date64(v2)) => v1.eq(v2),
(Date64(_), _) => false,
(TimestampSecond(v1, _), TimestampSecond(v2, _)) => v1.eq(v2),
(TimestampSecond(_, _), _) => false,
(TimestampMillisecond(v1, _), TimestampMillisecond(v2, _)) => v1.eq(v2),
(TimestampMillisecond(_, _), _) => false,
(TimestampMicrosecond(v1, _), TimestampMicrosecond(v2, _)) => v1.eq(v2),
(TimestampMicrosecond(_, _), _) => false,
(TimestampNanosecond(v1, _), TimestampNanosecond(v2, _)) => v1.eq(v2),
(TimestampNanosecond(_, _), _) => false,
(IntervalYearMonth(v1), IntervalYearMonth(v2)) => v1.eq(v2),
(IntervalYearMonth(_), _) => false,
(IntervalDayTime(v1), IntervalDayTime(v2)) => v1.eq(v2),
(IntervalDayTime(_), _) => false,
(IntervalMonthDayNano(v1), IntervalMonthDayNano(v2)) => v1.eq(v2),
(IntervalMonthDayNano(_), _) => false,
(Struct(v1, t1), Struct(v2, t2)) => v1.eq(v2) && t1.eq(t2),
(Struct(_, _), _) => false,
(Null, Null) => true,
(Null, _) => false,
}
}
}
// manual implementation of `PartialOrd` that uses OrderedFloat to
// get defined behavior for floating point
impl PartialOrd for ScalarValue {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
use ScalarValue::*;
// This purposely doesn't have a catch-all "(_, _)" so that
// any newly added enum variant will require editing this list
// or else face a compile error
match (self, other) {
(Decimal128(v1, p1, s1), Decimal128(v2, p2, s2)) => {
if p1.eq(p2) && s1.eq(s2) {
v1.partial_cmp(v2)
} else {
// Two decimal values can be compared if they have the same precision and scale.
None
}
}
(Decimal128(_, _, _), _) => None,
(Boolean(v1), Boolean(v2)) => v1.partial_cmp(v2),
(Boolean(_), _) => None,
(Float32(v1), Float32(v2)) => {
let v1 = v1.map(OrderedFloat);
let v2 = v2.map(OrderedFloat);
v1.partial_cmp(&v2)
}
(Float32(_), _) => None,
(Float64(v1), Float64(v2)) => {
let v1 = v1.map(OrderedFloat);
let v2 = v2.map(OrderedFloat);
v1.partial_cmp(&v2)
}
(Float64(_), _) => None,
(Int8(v1), Int8(v2)) => v1.partial_cmp(v2),
(Int8(_), _) => None,
(Int16(v1), Int16(v2)) => v1.partial_cmp(v2),
(Int16(_), _) => None,
(Int32(v1), Int32(v2)) => v1.partial_cmp(v2),
(Int32(_), _) => None,
(Int64(v1), Int64(v2)) => v1.partial_cmp(v2),
(Int64(_), _) => None,
(UInt8(v1), UInt8(v2)) => v1.partial_cmp(v2),
(UInt8(_), _) => None,
(UInt16(v1), UInt16(v2)) => v1.partial_cmp(v2),
(UInt16(_), _) => None,
(UInt32(v1), UInt32(v2)) => v1.partial_cmp(v2),
(UInt32(_), _) => None,
(UInt64(v1), UInt64(v2)) => v1.partial_cmp(v2),
(UInt64(_), _) => None,
(Utf8(v1), Utf8(v2)) => v1.partial_cmp(v2),
(Utf8(_), _) => None,
(LargeUtf8(v1), LargeUtf8(v2)) => v1.partial_cmp(v2),
(LargeUtf8(_), _) => None,
(Binary(v1), Binary(v2)) => v1.partial_cmp(v2),
(Binary(_), _) => None,
(LargeBinary(v1), LargeBinary(v2)) => v1.partial_cmp(v2),
(LargeBinary(_), _) => None,
(List(v1, t1), List(v2, t2)) => {
if t1.eq(t2) {
v1.partial_cmp(v2)
} else {
None
}
}
(List(_, _), _) => None,
(Date32(v1), Date32(v2)) => v1.partial_cmp(v2),
(Date32(_), _) => None,
(Date64(v1), Date64(v2)) => v1.partial_cmp(v2),
(Date64(_), _) => None,
(TimestampSecond(v1, _), TimestampSecond(v2, _)) => v1.partial_cmp(v2),
(TimestampSecond(_, _), _) => None,
(TimestampMillisecond(v1, _), TimestampMillisecond(v2, _)) => {
v1.partial_cmp(v2)
}
(TimestampMillisecond(_, _), _) => None,
(TimestampMicrosecond(v1, _), TimestampMicrosecond(v2, _)) => {
v1.partial_cmp(v2)
}
(TimestampMicrosecond(_, _), _) => None,
(TimestampNanosecond(v1, _), TimestampNanosecond(v2, _)) => {
v1.partial_cmp(v2)
}
(TimestampNanosecond(_, _), _) => None,
(IntervalYearMonth(v1), IntervalYearMonth(v2)) => v1.partial_cmp(v2),
(IntervalYearMonth(_), _) => None,
(IntervalDayTime(v1), IntervalDayTime(v2)) => v1.partial_cmp(v2),
(IntervalDayTime(_), _) => None,
(IntervalMonthDayNano(v1), IntervalMonthDayNano(v2)) => v1.partial_cmp(v2),
(IntervalMonthDayNano(_), _) => None,
(Struct(v1, t1), Struct(v2, t2)) => {
if t1.eq(t2) {
v1.partial_cmp(v2)
} else {
None
}
}
(Struct(_, _), _) => None,
(Null, Null) => Some(Ordering::Equal),
(Null, _) => None,
}
}
}
impl Eq for ScalarValue {}
// manual implementation of `Hash` that uses OrderedFloat to
// get defined behavior for floating point
impl std::hash::Hash for ScalarValue {
fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
use ScalarValue::*;
match self {
Decimal128(v, p, s) => {
v.hash(state);
p.hash(state);
s.hash(state)
}
Boolean(v) => v.hash(state),
Float32(v) => {
let v = v.map(OrderedFloat);
v.hash(state)
}
Float64(v) => {
let v = v.map(OrderedFloat);
v.hash(state)
}
Int8(v) => v.hash(state),
Int16(v) => v.hash(state),
Int32(v) => v.hash(state),
Int64(v) => v.hash(state),
UInt8(v) => v.hash(state),
UInt16(v) => v.hash(state),
UInt32(v) => v.hash(state),
UInt64(v) => v.hash(state),
Utf8(v) => v.hash(state),
LargeUtf8(v) => v.hash(state),
Binary(v) => v.hash(state),
LargeBinary(v) => v.hash(state),
List(v, t) => {
v.hash(state);
t.hash(state);
}
Date32(v) => v.hash(state),
Date64(v) => v.hash(state),
TimestampSecond(v, _) => v.hash(state),
TimestampMillisecond(v, _) => v.hash(state),
TimestampMicrosecond(v, _) => v.hash(state),
TimestampNanosecond(v, _) => v.hash(state),
IntervalYearMonth(v) => v.hash(state),
IntervalDayTime(v) => v.hash(state),
IntervalMonthDayNano(v) => v.hash(state),
Struct(v, t) => {
v.hash(state);
t.hash(state);
}
// stable hash for Null value
Null => 1.hash(state),
}
}
}
// return the index into the dictionary values for array@index as well
// as a reference to the dictionary values array. Returns None for the
// index if the array is NULL at index
#[inline]
fn get_dict_value<K: ArrowDictionaryKeyType>(
array: &ArrayRef,
index: usize,
) -> Result<(&ArrayRef, Option<usize>)> {
let dict_array = array.as_any().downcast_ref::<DictionaryArray<K>>().unwrap();
// look up the index in the values dictionary
let keys_col = dict_array.keys();
if !keys_col.is_valid(index) {
return Ok((dict_array.values(), None));
}
let values_index = keys_col.value(index).to_usize().ok_or_else(|| {
DataFusionError::Internal(format!(
"Can not convert index to usize in dictionary of type creating group by value {:?}",
keys_col.data_type()
))
})?;
Ok((dict_array.values(), Some(values_index)))
}
macro_rules! typed_cast_tz {
($array:expr, $index:expr, $ARRAYTYPE:ident, $SCALAR:ident, $TZ:expr) => {{
let array = $array.as_any().downcast_ref::<$ARRAYTYPE>().unwrap();
ScalarValue::$SCALAR(
match array.is_null($index) {
true => None,
false => Some(array.value($index).into()),
},
$TZ.clone(),
)
}};
}
macro_rules! typed_cast {
($array:expr, $index:expr, $ARRAYTYPE:ident, $SCALAR:ident) => {{
let array = $array.as_any().downcast_ref::<$ARRAYTYPE>().unwrap();
ScalarValue::$SCALAR(match array.is_null($index) {
true => None,
false => Some(array.value($index).into()),
})
}};
}
macro_rules! build_list {
($VALUE_BUILDER_TY:ident, $SCALAR_TY:ident, $VALUES:expr, $SIZE:expr) => {{
match $VALUES {
// the return on the macro is necessary, to short-circuit and return ArrayRef
None => {
return new_null_array(
&DataType::List(Box::new(Field::new(
"item",
DataType::$SCALAR_TY,
true,
))),
$SIZE,
)
}
Some(values) => {
build_values_list!($VALUE_BUILDER_TY, $SCALAR_TY, values, $SIZE)
}
}
}};
}
macro_rules! build_timestamp_list {
($TIME_UNIT:expr, $TIME_ZONE:expr, $VALUES:expr, $SIZE:expr) => {{
match $VALUES {
// the return on the macro is necessary, to short-circuit and return ArrayRef
None => {
return new_null_array(
&DataType::List(Box::new(Field::new(
"item",
DataType::Timestamp($TIME_UNIT, $TIME_ZONE),
true,
))),
$SIZE,
)
}
Some(values) => match $TIME_UNIT {
TimeUnit::Second => {
build_values_list_tz!(
TimestampSecondBuilder,
TimestampSecond,
values,
$SIZE
)
}
TimeUnit::Microsecond => build_values_list_tz!(
TimestampMillisecondBuilder,
TimestampMillisecond,
values,
$SIZE
),
TimeUnit::Millisecond => build_values_list_tz!(
TimestampMicrosecondBuilder,
TimestampMicrosecond,
values,
$SIZE
),
TimeUnit::Nanosecond => build_values_list_tz!(
TimestampNanosecondBuilder,
TimestampNanosecond,
values,
$SIZE
),
},
}
}};
}
macro_rules! build_values_list {
($VALUE_BUILDER_TY:ident, $SCALAR_TY:ident, $VALUES:expr, $SIZE:expr) => {{
let mut builder = ListBuilder::new($VALUE_BUILDER_TY::new($VALUES.len()));
for _ in 0..$SIZE {
for scalar_value in $VALUES {
match scalar_value {
ScalarValue::$SCALAR_TY(Some(v)) => {
builder.values().append_value(v.clone()).unwrap()
}
ScalarValue::$SCALAR_TY(None) => {
builder.values().append_null().unwrap();
}
_ => panic!("Incompatible ScalarValue for list"),
};
}
builder.append(true).unwrap();
}
builder.finish()
}};
}
macro_rules! build_values_list_tz {
($VALUE_BUILDER_TY:ident, $SCALAR_TY:ident, $VALUES:expr, $SIZE:expr) => {{
let mut builder = ListBuilder::new($VALUE_BUILDER_TY::new($VALUES.len()));
for _ in 0..$SIZE {
for scalar_value in $VALUES {
match scalar_value {
ScalarValue::$SCALAR_TY(Some(v), _) => {
builder.values().append_value(v.clone()).unwrap()
}
ScalarValue::$SCALAR_TY(None, _) => {
builder.values().append_null().unwrap();
}
_ => panic!("Incompatible ScalarValue for list"),
};
}
builder.append(true).unwrap();
}
builder.finish()
}};
}
macro_rules! build_array_from_option {
($DATA_TYPE:ident, $ARRAY_TYPE:ident, $EXPR:expr, $SIZE:expr) => {{
match $EXPR {
Some(value) => Arc::new($ARRAY_TYPE::from_value(*value, $SIZE)),
None => new_null_array(&DataType::$DATA_TYPE, $SIZE),
}
}};
($DATA_TYPE:ident, $ENUM:expr, $ARRAY_TYPE:ident, $EXPR:expr, $SIZE:expr) => {{
match $EXPR {
Some(value) => Arc::new($ARRAY_TYPE::from_value(*value, $SIZE)),
None => new_null_array(&DataType::$DATA_TYPE($ENUM), $SIZE),
}
}};
($DATA_TYPE:ident, $ENUM:expr, $ENUM2:expr, $ARRAY_TYPE:ident, $EXPR:expr, $SIZE:expr) => {{
match $EXPR {
Some(value) => {
let array: ArrayRef = Arc::new($ARRAY_TYPE::from_value(*value, $SIZE));
// Need to call cast to cast to final data type with timezone/extra param
cast(&array, &DataType::$DATA_TYPE($ENUM, $ENUM2))
.expect("cannot do temporal cast")
}
None => new_null_array(&DataType::$DATA_TYPE($ENUM, $ENUM2), $SIZE),
}
}};
}
macro_rules! eq_array_primitive {
($array:expr, $index:expr, $ARRAYTYPE:ident, $VALUE:expr) => {{
let array = $array.as_any().downcast_ref::<$ARRAYTYPE>().unwrap();
let is_valid = array.is_valid($index);
match $VALUE {
Some(val) => is_valid && &array.value($index) == val,
None => !is_valid,
}
}};
}
impl ScalarValue {
/// Create a decimal Scalar from value/precision and scale.
pub fn try_new_decimal128(
value: i128,
precision: usize,
scale: usize,
) -> Result<Self> {
// make sure the precision and scale is valid
if precision <= DECIMAL_MAX_PRECISION && scale <= precision {
return Ok(ScalarValue::Decimal128(Some(value), precision, scale));
}
Err(DataFusionError::Internal(format!(
"Can not new a decimal type ScalarValue for precision {} and scale {}",
precision, scale
)))
}
/// Getter for the `DataType` of the value
pub fn get_datatype(&self) -> DataType {
match self {
ScalarValue::Boolean(_) => DataType::Boolean,
ScalarValue::UInt8(_) => DataType::UInt8,
ScalarValue::UInt16(_) => DataType::UInt16,
ScalarValue::UInt32(_) => DataType::UInt32,
ScalarValue::UInt64(_) => DataType::UInt64,
ScalarValue::Int8(_) => DataType::Int8,
ScalarValue::Int16(_) => DataType::Int16,
ScalarValue::Int32(_) => DataType::Int32,
ScalarValue::Int64(_) => DataType::Int64,
ScalarValue::Decimal128(_, precision, scale) => {
DataType::Decimal(*precision, *scale)
}
ScalarValue::TimestampSecond(_, tz_opt) => {
DataType::Timestamp(TimeUnit::Second, tz_opt.clone())
}
ScalarValue::TimestampMillisecond(_, tz_opt) => {
DataType::Timestamp(TimeUnit::Millisecond, tz_opt.clone())
}
ScalarValue::TimestampMicrosecond(_, tz_opt) => {
DataType::Timestamp(TimeUnit::Microsecond, tz_opt.clone())
}
ScalarValue::TimestampNanosecond(_, tz_opt) => {
DataType::Timestamp(TimeUnit::Nanosecond, tz_opt.clone())
}
ScalarValue::Float32(_) => DataType::Float32,
ScalarValue::Float64(_) => DataType::Float64,
ScalarValue::Utf8(_) => DataType::Utf8,
ScalarValue::LargeUtf8(_) => DataType::LargeUtf8,
ScalarValue::Binary(_) => DataType::Binary,
ScalarValue::LargeBinary(_) => DataType::LargeBinary,
ScalarValue::List(_, data_type) => DataType::List(Box::new(Field::new(
"item",
data_type.as_ref().clone(),
true,
))),
ScalarValue::Date32(_) => DataType::Date32,
ScalarValue::Date64(_) => DataType::Date64,
ScalarValue::IntervalYearMonth(_) => {
DataType::Interval(IntervalUnit::YearMonth)
}
ScalarValue::IntervalDayTime(_) => DataType::Interval(IntervalUnit::DayTime),
ScalarValue::IntervalMonthDayNano(_) => {
DataType::Interval(IntervalUnit::MonthDayNano)
}
ScalarValue::Struct(_, fields) => DataType::Struct(fields.as_ref().clone()),
ScalarValue::Null => DataType::Null,
}
}
/// Calculate arithmetic negation for a scalar value
pub fn arithmetic_negate(&self) -> Self {
match self {
ScalarValue::Boolean(None)
| ScalarValue::Int8(None)
| ScalarValue::Int16(None)
| ScalarValue::Int32(None)
| ScalarValue::Int64(None)
| ScalarValue::Float32(None) => self.clone(),
ScalarValue::Float64(Some(v)) => ScalarValue::Float64(Some(-v)),
ScalarValue::Float32(Some(v)) => ScalarValue::Float32(Some(-v)),
ScalarValue::Int8(Some(v)) => ScalarValue::Int8(Some(-v)),
ScalarValue::Int16(Some(v)) => ScalarValue::Int16(Some(-v)),
ScalarValue::Int32(Some(v)) => ScalarValue::Int32(Some(-v)),
ScalarValue::Int64(Some(v)) => ScalarValue::Int64(Some(-v)),
ScalarValue::Decimal128(Some(v), precision, scale) => {
ScalarValue::Decimal128(Some(-v), *precision, *scale)
}
_ => panic!("Cannot run arithmetic negate on scalar value: {:?}", self),
}
}
/// whether this value is null or not.
pub fn is_null(&self) -> bool {
match self {
ScalarValue::Boolean(v) => v.is_none(),
ScalarValue::Null => true,
ScalarValue::Float32(v) => v.is_none(),
ScalarValue::Float64(v) => v.is_none(),
ScalarValue::Decimal128(v, _, _) => v.is_none(),
ScalarValue::Int8(v) => v.is_none(),
ScalarValue::Int16(v) => v.is_none(),
ScalarValue::Int32(v) => v.is_none(),
ScalarValue::Int64(v) => v.is_none(),
ScalarValue::UInt8(v) => v.is_none(),
ScalarValue::UInt16(v) => v.is_none(),
ScalarValue::UInt32(v) => v.is_none(),
ScalarValue::UInt64(v) => v.is_none(),
ScalarValue::Utf8(v) => v.is_none(),
ScalarValue::LargeUtf8(v) => v.is_none(),
ScalarValue::Binary(v) => v.is_none(),
ScalarValue::LargeBinary(v) => v.is_none(),
ScalarValue::List(v, _) => v.is_none(),
ScalarValue::Date32(v) => v.is_none(),
ScalarValue::Date64(v) => v.is_none(),
ScalarValue::TimestampSecond(v, _) => v.is_none(),
ScalarValue::TimestampMillisecond(v, _) => v.is_none(),
ScalarValue::TimestampMicrosecond(v, _) => v.is_none(),
ScalarValue::TimestampNanosecond(v, _) => v.is_none(),
ScalarValue::IntervalYearMonth(v) => v.is_none(),
ScalarValue::IntervalDayTime(v) => v.is_none(),
ScalarValue::IntervalMonthDayNano(v) => v.is_none(),
ScalarValue::Struct(v, _) => v.is_none(),
}
}
/// Converts a scalar value into an 1-row array.
pub fn to_array(&self) -> ArrayRef {
self.to_array_of_size(1)
}
/// Converts an iterator of references [`ScalarValue`] into an [`ArrayRef`]
/// corresponding to those values. For example,
///
/// Returns an error if the iterator is empty or if the
/// [`ScalarValue`]s are not all the same type
///
/// Example
/// ```
/// use datafusion_common::ScalarValue;
/// use arrow::array::{ArrayRef, BooleanArray};
///
/// let scalars = vec![
/// ScalarValue::Boolean(Some(true)),
/// ScalarValue::Boolean(None),
/// ScalarValue::Boolean(Some(false)),
/// ];
///
/// // Build an Array from the list of ScalarValues
/// let array = ScalarValue::iter_to_array(scalars.into_iter())
/// .unwrap();
///
/// let expected: ArrayRef = std::sync::Arc::new(
/// BooleanArray::from(vec![
/// Some(true),
/// None,
/// Some(false)
/// ]
/// ));
///
/// assert_eq!(&array, &expected);
/// ```
pub fn iter_to_array(
scalars: impl IntoIterator<Item = ScalarValue>,
) -> Result<ArrayRef> {
let mut scalars = scalars.into_iter().peekable();
// figure out the type based on the first element
let data_type = match scalars.peek() {
None => {
return Err(DataFusionError::Internal(
"Empty iterator passed to ScalarValue::iter_to_array".to_string(),
));
}
Some(sv) => sv.get_datatype(),
};
/// Creates an array of $ARRAY_TY by unpacking values of
/// SCALAR_TY for primitive types
macro_rules! build_array_primitive {
($ARRAY_TY:ident, $SCALAR_TY:ident) => {{
{
let array = scalars.map(|sv| {
if let ScalarValue::$SCALAR_TY(v) = sv {
Ok(v)
} else {
Err(DataFusionError::Internal(format!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected {:?}, got {:?}",
data_type, sv
)))
}
})
.collect::<Result<$ARRAY_TY>>()?;
Arc::new(array)
}
}};
}
macro_rules! build_array_primitive_tz {
($ARRAY_TY:ident, $SCALAR_TY:ident) => {{
{
let array = scalars.map(|sv| {
if let ScalarValue::$SCALAR_TY(v, _) = sv {
Ok(v)
} else {
Err(DataFusionError::Internal(format!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected {:?}, got {:?}",
data_type, sv
)))
}
})
.collect::<Result<$ARRAY_TY>>()?;
Arc::new(array)
}
}};
}
/// Creates an array of $ARRAY_TY by unpacking values of
/// SCALAR_TY for "string-like" types.
macro_rules! build_array_string {
($ARRAY_TY:ident, $SCALAR_TY:ident) => {{
{
let array = scalars.map(|sv| {
if let ScalarValue::$SCALAR_TY(v) = sv {
Ok(v)
} else {
Err(DataFusionError::Internal(format!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected {:?}, got {:?}",
data_type, sv
)))
}
})
.collect::<Result<$ARRAY_TY>>()?;
Arc::new(array)
}
}};
}
macro_rules! build_array_list_primitive {
($ARRAY_TY:ident, $SCALAR_TY:ident, $NATIVE_TYPE:ident) => {{
Arc::new(ListArray::from_iter_primitive::<$ARRAY_TY, _, _>(
scalars.into_iter().map(|x| match x {
ScalarValue::List(xs, _) => xs.map(|x| {
x.iter().map(|x| match x {
ScalarValue::$SCALAR_TY(i) => *i,
sv => panic!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected {:?}, got {:?}",
data_type, sv
),
})
.collect::<Vec<Option<$NATIVE_TYPE>>>()
}),
sv => panic!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected {:?}, got {:?}",
data_type, sv
),
}),
))
}};
}
macro_rules! build_array_list_string {
($BUILDER:ident, $SCALAR_TY:ident) => {{
let mut builder = ListBuilder::new($BUILDER::new(0));
for scalar in scalars.into_iter() {
match scalar {
ScalarValue::List(Some(xs), _) => {
for s in xs {
match s {
ScalarValue::$SCALAR_TY(Some(val)) => {
builder.values().append_value(val)?;
}
ScalarValue::$SCALAR_TY(None) => {
builder.values().append_null()?;
}
sv => {
return Err(DataFusionError::Internal(format!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected Utf8, got {:?}",
sv
)))
}
}
}
builder.append(true)?;
}
ScalarValue::List(None, _) => {
builder.append(false)?;
}
sv => {
return Err(DataFusionError::Internal(format!(
"Inconsistent types in ScalarValue::iter_to_array. \
Expected List, got {:?}",
sv
)))
}
}
}
Arc::new(builder.finish())
}};
}
let array: ArrayRef = match &data_type {
DataType::Decimal(precision, scale) => {
let decimal_array =
ScalarValue::iter_to_decimal_array(scalars, precision, scale)?;
Arc::new(decimal_array)
}
DataType::Null => ScalarValue::iter_to_null_array(scalars),
DataType::Boolean => build_array_primitive!(BooleanArray, Boolean),
DataType::Float32 => build_array_primitive!(Float32Array, Float32),
DataType::Float64 => build_array_primitive!(Float64Array, Float64),
DataType::Int8 => build_array_primitive!(Int8Array, Int8),
DataType::Int16 => build_array_primitive!(Int16Array, Int16),
DataType::Int32 => build_array_primitive!(Int32Array, Int32),
DataType::Int64 => build_array_primitive!(Int64Array, Int64),
DataType::UInt8 => build_array_primitive!(UInt8Array, UInt8),
DataType::UInt16 => build_array_primitive!(UInt16Array, UInt16),
DataType::UInt32 => build_array_primitive!(UInt32Array, UInt32),
DataType::UInt64 => build_array_primitive!(UInt64Array, UInt64),
DataType::Utf8 => build_array_string!(StringArray, Utf8),
DataType::LargeUtf8 => build_array_string!(LargeStringArray, LargeUtf8),
DataType::Binary => build_array_string!(BinaryArray, Binary),
DataType::LargeBinary => build_array_string!(LargeBinaryArray, LargeBinary),
DataType::Date32 => build_array_primitive!(Date32Array, Date32),
DataType::Date64 => build_array_primitive!(Date64Array, Date64),
DataType::Timestamp(TimeUnit::Second, _) => {
build_array_primitive_tz!(TimestampSecondArray, TimestampSecond)
}
DataType::Timestamp(TimeUnit::Millisecond, _) => {
build_array_primitive_tz!(TimestampMillisecondArray, TimestampMillisecond)
}
DataType::Timestamp(TimeUnit::Microsecond, _) => {
build_array_primitive_tz!(TimestampMicrosecondArray, TimestampMicrosecond)
}
DataType::Timestamp(TimeUnit::Nanosecond, _) => {
build_array_primitive_tz!(TimestampNanosecondArray, TimestampNanosecond)
}
DataType::Interval(IntervalUnit::DayTime) => {
build_array_primitive!(IntervalDayTimeArray, IntervalDayTime)
}
DataType::Interval(IntervalUnit::YearMonth) => {
build_array_primitive!(IntervalYearMonthArray, IntervalYearMonth)
}
DataType::List(fields) if fields.data_type() == &DataType::Int8 => {
build_array_list_primitive!(Int8Type, Int8, i8)
}
DataType::List(fields) if fields.data_type() == &DataType::Int16 => {
build_array_list_primitive!(Int16Type, Int16, i16)
}
DataType::List(fields) if fields.data_type() == &DataType::Int32 => {
build_array_list_primitive!(Int32Type, Int32, i32)
}
DataType::List(fields) if fields.data_type() == &DataType::Int64 => {
build_array_list_primitive!(Int64Type, Int64, i64)
}
DataType::List(fields) if fields.data_type() == &DataType::UInt8 => {
build_array_list_primitive!(UInt8Type, UInt8, u8)
}
DataType::List(fields) if fields.data_type() == &DataType::UInt16 => {
build_array_list_primitive!(UInt16Type, UInt16, u16)
}
DataType::List(fields) if fields.data_type() == &DataType::UInt32 => {
build_array_list_primitive!(UInt32Type, UInt32, u32)
}
DataType::List(fields) if fields.data_type() == &DataType::UInt64 => {
build_array_list_primitive!(UInt64Type, UInt64, u64)
}
DataType::List(fields) if fields.data_type() == &DataType::Float32 => {
build_array_list_primitive!(Float32Type, Float32, f32)
}
DataType::List(fields) if fields.data_type() == &DataType::Float64 => {
build_array_list_primitive!(Float64Type, Float64, f64)
}
DataType::List(fields) if fields.data_type() == &DataType::Utf8 => {
build_array_list_string!(StringBuilder, Utf8)
}
DataType::List(fields) if fields.data_type() == &DataType::LargeUtf8 => {
build_array_list_string!(LargeStringBuilder, LargeUtf8)
}
DataType::List(_) => {
// Fallback case handling homogeneous lists with any ScalarValue element type
let list_array = ScalarValue::iter_to_array_list(scalars, &data_type)?;
Arc::new(list_array)
}
DataType::Struct(fields) => {
// Initialize a Vector to store the ScalarValues for each column
let mut columns: Vec<Vec<ScalarValue>> =
(0..fields.len()).map(|_| Vec::new()).collect();
// Iterate over scalars to populate the column scalars for each row
for scalar in scalars {
if let ScalarValue::Struct(values, fields) = scalar {
match values {
Some(values) => {
// Push value for each field
for (column, value) in columns.iter_mut().zip(values) {
column.push(value.clone());
}
}
None => {
// Push NULL of the appropriate type for each field
for (column, field) in
columns.iter_mut().zip(fields.as_ref())
{
column
.push(ScalarValue::try_from(field.data_type())?);
}
}
};
} else {
return Err(DataFusionError::Internal(format!(
"Expected Struct but found: {}",
scalar
)));
};
}
// Call iter_to_array recursively to convert the scalars for each column into Arrow arrays
let field_values = fields
.iter()
.zip(columns)
.map(|(field, column)| -> Result<(Field, ArrayRef)> {
Ok((field.clone(), Self::iter_to_array(column)?))
})
.collect::<Result<Vec<_>>>()?;
Arc::new(StructArray::from(field_values))
}
_ => {
return Err(DataFusionError::Internal(format!(
"Unsupported creation of {:?} array from ScalarValue {:?}",
data_type,
scalars.peek()
)));
}
};
Ok(array)
}
fn iter_to_null_array(scalars: impl IntoIterator<Item = ScalarValue>) -> ArrayRef {
let length =
scalars
.into_iter()
.fold(0usize, |r, element: ScalarValue| match element {
ScalarValue::Null => r + 1,
_ => unreachable!(),
});
new_null_array(&DataType::Null, length)
}
fn iter_to_decimal_array(
scalars: impl IntoIterator<Item = ScalarValue>,
precision: &usize,
scale: &usize,
) -> Result<DecimalArray> {
let array = scalars
.into_iter()
.map(|element: ScalarValue| match element {
ScalarValue::Decimal128(v1, _, _) => v1,