aboutsummaryrefslogtreecommitdiffstats
path: root/vespajlib/src/main/java/com/yahoo/tensor/functions/Join.java
blob: 4c92e1e57a28892f366ac2953cbe31793a2f15ba (plain) (blame)
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
// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.tensor.functions;

import com.google.common.collect.Sets;
import com.yahoo.tensor.DimensionSizes;
import com.yahoo.tensor.IndexedTensor;
import com.yahoo.tensor.PartialAddress;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorAddress;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.TypeResolver;
import com.yahoo.tensor.evaluation.EvaluationContext;
import com.yahoo.tensor.evaluation.Name;
import com.yahoo.tensor.evaluation.TypeContext;

import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Optional;
import java.util.Set;
import java.util.function.DoubleBinaryOperator;

/**
 * The <i>join</i> tensor operation produces a tensor from the argument tensors containing the set of cells
 * given by the cross product of the cells of the given tensors, having as values the value produced by
 * applying the given combinator function on the values from the two source cells.
 *
 * @author bratseth
 */
public class Join<NAMETYPE extends Name> extends PrimitiveTensorFunction<NAMETYPE> {

    private final TensorFunction<NAMETYPE> argumentA, argumentB;
    private final DoubleBinaryOperator combinator;

    public Join(TensorFunction<NAMETYPE> argumentA, TensorFunction<NAMETYPE> argumentB, DoubleBinaryOperator combinator) {
        Objects.requireNonNull(argumentA, "The first argument tensor cannot be null");
        Objects.requireNonNull(argumentB, "The second argument tensor cannot be null");
        Objects.requireNonNull(combinator, "The combinator function cannot be null");
        this.argumentA = argumentA;
        this.argumentB = argumentB;
        this.combinator = combinator;
    }

    /** Returns the type resulting from applying Join to the two given types */
    public static TensorType outputType(TensorType a, TensorType b) {
        try {
            return TypeResolver.join(a, b);
        }
        catch (IllegalArgumentException e) {
            throw new IllegalArgumentException("Can not join " + a + " and " + b, e);
        }
    }

    public DoubleBinaryOperator combinator() { return combinator; }

    @Override
    public List<TensorFunction<NAMETYPE>> arguments() { return List.of(argumentA, argumentB); }

    @Override
    public TensorFunction<NAMETYPE> withArguments(List<TensorFunction<NAMETYPE>> arguments) {
        if ( arguments.size() != 2)
            throw new IllegalArgumentException("Join must have 2 arguments, got " + arguments.size());
        return new Join<>(arguments.get(0), arguments.get(1), combinator);
    }

    @Override
    public PrimitiveTensorFunction<NAMETYPE> toPrimitive() {
        return new Join<>(argumentA.toPrimitive(), argumentB.toPrimitive(), combinator);
    }

    @Override
    public String toString(ToStringContext<NAMETYPE> context) {
        return "join(" + argumentA.toString(context) + ", " + argumentB.toString(context) + ", " + combinator + ")";
    }

    @Override
    public int hashCode() { return Objects.hash("join", argumentA, argumentB, combinator); }

    @Override
    public TensorType type(TypeContext<NAMETYPE> context) {
        return outputType(argumentA.type(context), argumentB.type(context));
    }

    @Override
    public Tensor evaluate(EvaluationContext<NAMETYPE> context) {
        Tensor a = argumentA.evaluate(context);
        Tensor b = argumentB.evaluate(context);
        TensorType joinedType = outputType(a.type(), b.type());
        return evaluate(a, b, joinedType, combinator);
    }

    static Tensor evaluate(Tensor a, Tensor b, TensorType joinedType, DoubleBinaryOperator combinator) {
        // Choose join algorithm
        if (hasSingleIndexedDimension(a) && hasSingleIndexedDimension(b) && a.type().dimensions().get(0).name().equals(b.type().dimensions().get(0).name()))
            return indexedVectorJoin((IndexedTensor)a, (IndexedTensor)b, joinedType, combinator);
        else if (joinedType.dimensions().size() == a.type().dimensions().size() && joinedType.dimensions().size() == b.type().dimensions().size())
            return singleSpaceJoin(a, b, joinedType, combinator);
        else if (a.type().dimensions().containsAll(b.type().dimensions()))
            return subspaceJoin(b, a, joinedType, true, combinator);
        else if (b.type().dimensions().containsAll(a.type().dimensions()))
            return subspaceJoin(a, b, joinedType, false, combinator);
        else
            return generalJoin(a, b, joinedType, combinator);

    }

    private static boolean hasSingleIndexedDimension(Tensor tensor) {
        return tensor.type().dimensions().size() == 1 && tensor.type().dimensions().get(0).isIndexed();
    }

    private static Tensor indexedVectorJoin(IndexedTensor a, IndexedTensor b, TensorType type, DoubleBinaryOperator combinator) {
        long joinedRank = Math.min(a.dimensionSizes().size(0), b.dimensionSizes().size(0));
        Iterator<Double> aIterator = a.valueIterator();
        Iterator<Double> bIterator = b.valueIterator();
        IndexedTensor.Builder builder = IndexedTensor.Builder.of(type, new DimensionSizes.Builder(1).set(0, joinedRank).build());
        for (int i = 0; i < joinedRank; i++)
            builder.cell(combinator.applyAsDouble(aIterator.next(), bIterator.next()), i);
        return builder.build();
    }

    /** When both tensors have the same dimensions, at most one cell matches a cell in the other tensor */
    private static Tensor singleSpaceJoin(Tensor a, Tensor b, TensorType joinedType, DoubleBinaryOperator combinator) {
        Tensor.Builder builder = Tensor.Builder.of(joinedType);
        for (Iterator<Tensor.Cell> i = a.cellIterator(); i.hasNext(); ) {
            Map.Entry<TensorAddress, Double> aCell = i.next();
            var key = aCell.getKey();
            if (b.has(key)) {
                builder.cell(key, combinator.applyAsDouble(aCell.getValue(), b.get(key)));
            }
        }
        return builder.build();
    }

    /** Join a tensor into a superspace */
    private static Tensor subspaceJoin(Tensor subspace, Tensor superspace, TensorType joinedType, boolean reversedArgumentOrder, DoubleBinaryOperator combinator) {
        if (subspace instanceof IndexedTensor && superspace instanceof IndexedTensor)
            return indexedSubspaceJoin((IndexedTensor) subspace, (IndexedTensor) superspace, joinedType, reversedArgumentOrder, combinator);
        else
            return generalSubspaceJoin(subspace, superspace, joinedType, reversedArgumentOrder, combinator);
    }

    private static Tensor indexedSubspaceJoin(IndexedTensor subspace, IndexedTensor superspace, TensorType joinedType, boolean reversedArgumentOrder, DoubleBinaryOperator combinator) {
        if (subspace.size() == 0 || superspace.size() == 0) // special case empty here to avoid doing it when finding sizes
            return Tensor.Builder.of(joinedType, new DimensionSizes.Builder(joinedType.dimensions().size()).build()).build();

        DimensionSizes joinedSizes = joinedSize(joinedType, subspace, superspace);

        IndexedTensor.Builder builder = (IndexedTensor.Builder)Tensor.Builder.of(joinedType, joinedSizes);

        // Find dimensions which are only in the supertype
        Set<String> superDimensionNames = new HashSet<>(superspace.type().dimensionNames());
        superDimensionNames.removeAll(subspace.type().dimensionNames());

        for (Iterator<IndexedTensor.SubspaceIterator> i = superspace.subspaceIterator(superDimensionNames, joinedSizes); i.hasNext(); ) {
            IndexedTensor.SubspaceIterator subspaceInSuper = i.next();
            joinSubspaces(subspace.valueIterator(), subspace.size(),
                    subspaceInSuper, subspaceInSuper.size(),
                    reversedArgumentOrder, builder, combinator);
        }

        return builder.build();
    }

    private static void joinSubspaces(Iterator<Double> subspace, long subspaceSize,
                                      Iterator<Tensor.Cell> superspace, long superspaceSize,
                                      boolean reversedArgumentOrder, IndexedTensor.Builder builder,
                                      DoubleBinaryOperator combinator) {
        long joinedLength = Math.min(subspaceSize, superspaceSize);
        if (reversedArgumentOrder) {
            for (int i = 0; i < joinedLength; i++) {
                Tensor.Cell supercell = superspace.next();
                builder.cell(supercell, combinator.applyAsDouble(supercell.getValue(), subspace.next()));
            }
        } else {
            for (int i = 0; i < joinedLength; i++) {
                Tensor.Cell supercell = superspace.next();
                builder.cell(supercell, combinator.applyAsDouble(subspace.next(), supercell.getValue()));
            }
        }
    }

    private static DimensionSizes joinedSize(TensorType joinedType, IndexedTensor a, IndexedTensor b) {
        DimensionSizes.Builder builder = new DimensionSizes.Builder(joinedType.dimensions().size());
        for (int i = 0; i < builder.dimensions(); i++) {
            String dimensionName = joinedType.dimensions().get(i).name();
            Optional<Integer> aIndex = a.type().indexOfDimension(dimensionName);
            Optional<Integer> bIndex = b.type().indexOfDimension(dimensionName);
            if (aIndex.isPresent() && bIndex.isPresent())
                builder.set(i, Math.min(b.dimensionSizes().size(bIndex.get()), a.dimensionSizes().size(aIndex.get())));
            else if (aIndex.isPresent())
                builder.set(i, a.dimensionSizes().size(aIndex.get()));
            else if (bIndex.isPresent())
                builder.set(i, b.dimensionSizes().size(bIndex.get()));
        }
        return builder.build();
    }

    private static Tensor generalSubspaceJoin(Tensor subspace, Tensor superspace, TensorType joinedType, boolean reversedArgumentOrder, DoubleBinaryOperator combinator) {
        int[] subspaceIndexes = subspaceIndexes(superspace.type(), subspace.type());
        Tensor.Builder builder = Tensor.Builder.of(joinedType);
        for (Iterator<Tensor.Cell> i = superspace.cellIterator(); i.hasNext(); ) {
            Map.Entry<TensorAddress, Double> supercell = i.next();
            TensorAddress subaddress = mapAddressToSubspace(supercell.getKey(), subspaceIndexes);
            if (subspace.has(subaddress)) {
                double subspaceValue = subspace.get(subaddress);
                builder.cell(supercell.getKey(),
                        reversedArgumentOrder ? combinator.applyAsDouble(supercell.getValue(), subspaceValue)
                             : combinator.applyAsDouble(subspaceValue, supercell.getValue()));
            }
        }
        return builder.build();
    }

    /** Returns the indexes in the superspace type which should be retained to create the subspace type */
    private static int[] subspaceIndexes(TensorType supertype, TensorType subtype) {
        int[] subspaceIndexes = new int[subtype.dimensions().size()];
        for (int i = 0; i < subtype.dimensions().size(); i++)
            subspaceIndexes[i] = supertype.indexOfDimension(subtype.dimensions().get(i).name()).get();
        return subspaceIndexes;
    }

    private static TensorAddress mapAddressToSubspace(TensorAddress superAddress, int[] subspaceIndexes) {
        String[] subspaceLabels = new String[subspaceIndexes.length];
        for (int i = 0; i < subspaceIndexes.length; i++)
            subspaceLabels[i] = superAddress.label(subspaceIndexes[i]);
        return TensorAddress.of(subspaceLabels);
    }

    /** Slow join which works for any two tensors */
    private static Tensor generalJoin(Tensor a, Tensor b, TensorType joinedType, DoubleBinaryOperator combinator) {
        if (a instanceof IndexedTensor && b instanceof IndexedTensor)
            return indexedGeneralJoin((IndexedTensor) a, (IndexedTensor) b, joinedType, combinator);
        else
            return mappedHashJoin(a, b, joinedType, combinator);
    }

    private static Tensor indexedGeneralJoin(IndexedTensor a, IndexedTensor b, TensorType joinedType, DoubleBinaryOperator combinator) {
        DimensionSizes joinedSize = joinedSize(joinedType, a, b);
        Tensor.Builder builder = Tensor.Builder.of(joinedType, joinedSize);
        int[] aToIndexes = mapIndexes(a.type(), joinedType);
        int[] bToIndexes = mapIndexes(b.type(), joinedType);
        joinTo(a, b, joinedType, joinedSize, aToIndexes, bToIndexes, builder, combinator);
        return builder.build();
    }

    private static void joinTo(IndexedTensor a, IndexedTensor b, TensorType joinedType, DimensionSizes joinedSize,
                               int[] aToIndexes, int[] bToIndexes, Tensor.Builder builder,
                               DoubleBinaryOperator combinator) {
        Set<String> sharedDimensions = Sets.intersection(a.type().dimensionNames(), b.type().dimensionNames());
        Set<String> dimensionsOnlyInA = Sets.difference(a.type().dimensionNames(), b.type().dimensionNames());

        DimensionSizes aIterateSize = joinedSizeOf(a.type(), joinedType, joinedSize);
        DimensionSizes bIterateSize = joinedSizeOf(b.type(), joinedType, joinedSize);

        // for each combination of dimensions only in a
        for (Iterator<IndexedTensor.SubspaceIterator> ia = a.subspaceIterator(dimensionsOnlyInA, aIterateSize); ia.hasNext(); ) {
            IndexedTensor.SubspaceIterator aSubspace = ia.next();
            // for each combination of dimensions in a which is also in b
            while (aSubspace.hasNext()) {
                Tensor.Cell aCell = aSubspace.next();
                PartialAddress matchingBCells = partialAddress(a.type(), aSubspace.address(), sharedDimensions);
                // for each matching combination of dimensions ony in b
                for (IndexedTensor.SubspaceIterator bSubspace = b.cellIterator(matchingBCells, bIterateSize); bSubspace.hasNext(); ) {
                    Tensor.Cell bCell = bSubspace.next();
                    TensorAddress joinedAddress = joinAddresses(aCell.getKey(), aToIndexes, bCell.getKey(), bToIndexes, joinedType);
                    double joinedValue = combinator.applyAsDouble(aCell.getValue(), bCell.getValue());
                    builder.cell(joinedAddress, joinedValue);
                }
            }
        }
    }

    private static PartialAddress partialAddress(TensorType addressType, TensorAddress address, Set<String> retainDimensions) {
        PartialAddress.Builder builder = new PartialAddress.Builder(retainDimensions.size());
        for (int i = 0; i < addressType.dimensions().size(); i++)
            if (retainDimensions.contains(addressType.dimensions().get(i).name()))
                builder.add(addressType.dimensions().get(i).name(), address.numericLabel(i));
        return builder.build();
    }

    /** Returns the sizes from the joined sizes which are present in the type argument */
    private static DimensionSizes joinedSizeOf(TensorType type, TensorType joinedType, DimensionSizes joinedSizes) {
        DimensionSizes.Builder builder = new DimensionSizes.Builder(type.dimensions().size());
        int dimensionIndex = 0;
        for (int i = 0; i < joinedType.dimensions().size(); i++) {
            if (type.dimensionNames().contains(joinedType.dimensions().get(i).name()))
                builder.set(dimensionIndex++, joinedSizes.size(i));
        }
        return builder.build();
    }

    private static Tensor mappedGeneralJoin(Tensor a, Tensor b, TensorType joinedType, DoubleBinaryOperator combinator) {
        int[] aToIndexes = mapIndexes(a.type(), joinedType);
        int[] bToIndexes = mapIndexes(b.type(), joinedType);
        Tensor.Builder builder = Tensor.Builder.of(joinedType);
        for (Iterator<Tensor.Cell> aIterator = a.cellIterator(); aIterator.hasNext(); ) {
            Map.Entry<TensorAddress, Double> aCell = aIterator.next();
            for (Iterator<Tensor.Cell> bIterator = b.cellIterator(); bIterator.hasNext(); ) {
                Map.Entry<TensorAddress, Double> bCell = bIterator.next();
                TensorAddress combinedAddress = joinAddresses(aCell.getKey(), aToIndexes,
                                                              bCell.getKey(), bToIndexes, joinedType);
                if (combinedAddress == null) continue; // not combinable
                builder.cell(combinedAddress, combinator.applyAsDouble(aCell.getValue(), bCell.getValue()));
            }
        }
        return builder.build();
    }

    private static Tensor mappedHashJoin(Tensor a, Tensor b, TensorType joinedType, DoubleBinaryOperator combinator) {
        TensorType commonDimensionType = commonDimensions(a, b);
        if (commonDimensionType.dimensions().isEmpty()) {
            return mappedGeneralJoin(a, b, joinedType, combinator); // fallback
        }

        boolean swapTensors = a.size() > b.size();
        if (swapTensors) {
            Tensor temp = a;
            a = b;
            b = temp;
        }

        // Map dimension indexes to common and joined type
        int[] aIndexesInCommon = mapIndexes(commonDimensionType, a.type());
        int[] bIndexesInCommon = mapIndexes(commonDimensionType, b.type());
        int[] aIndexesInJoined = mapIndexes(a.type(), joinedType);
        int[] bIndexesInJoined = mapIndexes(b.type(), joinedType);

        // Iterate once through the smaller tensor and construct a hash map for common dimensions
        Map<TensorAddress, List<Tensor.Cell>> aCellsByCommonAddress = new HashMap<>();
        for (Iterator<Tensor.Cell> cellIterator = a.cellIterator(); cellIterator.hasNext(); ) {
            Tensor.Cell aCell = cellIterator.next();
            TensorAddress partialCommonAddress = partialCommonAddress(aCell, aIndexesInCommon);
            aCellsByCommonAddress.putIfAbsent(partialCommonAddress, new ArrayList<>());
            aCellsByCommonAddress.get(partialCommonAddress).add(aCell);
        }

        // Iterate once through the larger tensor and use the hash map to find joinable cells
        Tensor.Builder builder = Tensor.Builder.of(joinedType);
        for (Iterator<Tensor.Cell> cellIterator = b.cellIterator(); cellIterator.hasNext(); ) {
            Tensor.Cell bCell = cellIterator.next();
            TensorAddress partialCommonAddress = partialCommonAddress(bCell, bIndexesInCommon);
            for (Tensor.Cell aCell : aCellsByCommonAddress.getOrDefault(partialCommonAddress, List.of())) {
                TensorAddress combinedAddress = joinAddresses(aCell.getKey(), aIndexesInJoined,
                                                              bCell.getKey(), bIndexesInJoined, joinedType);
                if (combinedAddress == null) continue; // not combinable
                double combinedValue = swapTensors ?
                        combinator.applyAsDouble(bCell.getValue(), aCell.getValue()) :
                        combinator.applyAsDouble(aCell.getValue(), bCell.getValue());
                builder.cell(combinedAddress, combinedValue);
            }
        }

        return builder.build();
    }

    /**
     * Returns the an array having one entry in order for each dimension of fromType
     * containing the index at which toType contains the same dimension name.
     * That is, if the returned array contains n at index i then
     * fromType.dimensions().get(i).name.equals(toType.dimensions().get(n).name())
     * If some dimension in fromType is not present in toType, the corresponding index will be -1
     */
    static int[] mapIndexes(TensorType fromType, TensorType toType) {
        int[] toIndexes = new int[fromType.dimensions().size()];
        for (int i = 0; i < fromType.dimensions().size(); i++)
            toIndexes[i] = toType.indexOfDimension(fromType.dimensions().get(i).name()).orElse(-1);
        return toIndexes;
    }

    private static TensorAddress joinAddresses(TensorAddress a, int[] aToIndexes, TensorAddress b, int[] bToIndexes,
                                               TensorType joinedType) {
        String[] joinedLabels = new String[joinedType.dimensions().size()];
        mapContent(a, joinedLabels, aToIndexes);
        boolean compatible = mapContent(b, joinedLabels, bToIndexes);
        if ( ! compatible) return null;
        return TensorAddress.of(joinedLabels);
    }

    /**
     * Maps the content in the given list to the given array, using the given index map.
     *
     * @return true if the mapping was successful, false if one of the destination positions was
     *         occupied by a different value
     */
    private static boolean mapContent(TensorAddress from, String[] to, int[] indexMap) {
        for (int i = 0; i < from.size(); i++) {
            int toIndex = indexMap[i];
            if (to[toIndex] != null && ! to[toIndex].equals(from.label(i))) return false;
            to[toIndex] = from.label(i);
        }
        return true;
    }

    /** Returns common dimension of a and b as a new tensor type */
    private static TensorType commonDimensions(Tensor a, Tensor b) {
        TensorType aType = a.type();
        TensorType bType = b.type();
        TensorType.Builder typeBuilder = new TensorType.Builder(TensorType.combinedValueType(aType, bType));
        for (int i = 0; i < aType.dimensions().size(); ++i) {
            TensorType.Dimension aDim = aType.dimensions().get(i);
            for (int j = 0; j < bType.dimensions().size(); ++j) {
                TensorType.Dimension bDim = bType.dimensions().get(j);
                if (aDim.equals(bDim)) {
                    typeBuilder.set(bDim);
                }
            }
        }
        return typeBuilder.build();
    }

    private static TensorAddress partialCommonAddress(Tensor.Cell cell, int[] indexMap) {
        TensorAddress address = cell.getKey();
        String[] labels = new String[indexMap.length];
        for (int i = 0; i < labels.length; ++i) {
            labels[i] = address.label(indexMap[i]);
        }
        return TensorAddress.of(labels);
    }

}