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
|
// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include "simple_join_count.h"
#include "generic_join.h"
#include <vespa/eval/eval/fast_value.hpp>
namespace vespalib::eval {
using namespace tensor_function;
using namespace operation;
using namespace instruction;
namespace {
size_t my_intersect_count_fallback(const Value::Index &lhs_idx, const Value::Index &rhs_idx) {
size_t result = 0.0;
SparseJoinPlan plan(1);
SparseJoinState sparse(plan, lhs_idx, rhs_idx);
auto outer = sparse.first_index.create_view({});
auto inner = sparse.second_index.create_view(sparse.second_view_dims);
outer->lookup({});
while (outer->next_result(sparse.first_address, sparse.first_subspace)) {
inner->lookup(sparse.address_overlap);
if (inner->next_result(sparse.second_only_address, sparse.second_subspace)) {
++result;
}
}
return result;
}
size_t my_fast_intersect_count(const FastAddrMap *small_map, const FastAddrMap *big_map) {
size_t result = 0;
if (big_map->size() < small_map->size()) {
std::swap(small_map, big_map);
}
const auto &labels = small_map->labels();
for (size_t i = 0; i < labels.size(); ++i) {
if (big_map->lookup_singledim(labels[i]) != FastAddrMap::npos()) {
++result;
}
}
return result;
}
void my_simple_join_count_op(InterpretedFunction::State &state, uint64_t dense_factor) {
const auto &lhs_idx = state.peek(1).index();
const auto &rhs_idx = state.peek(0).index();
double result = dense_factor * (__builtin_expect(are_fast(lhs_idx, rhs_idx), true)
? my_fast_intersect_count(&as_fast(lhs_idx).map, &as_fast(rhs_idx).map)
: my_intersect_count_fallback(lhs_idx, rhs_idx));
state.pop_pop_push(state.stash.create<DoubleValue>(result));
}
bool check_types(const ValueType &res, const ValueType &lhs, const ValueType &rhs) {
return ((res.is_double()) &&
(lhs.count_mapped_dimensions() == 1) &&
(lhs.mapped_dimensions() == rhs.mapped_dimensions()));
}
} // namespace <unnamed>
SimpleJoinCount::SimpleJoinCount(const TensorFunction &lhs_in,
const TensorFunction &rhs_in,
uint64_t dense_factor_in)
: tensor_function::Op2(ValueType::double_type(), lhs_in, rhs_in),
_dense_factor(dense_factor_in)
{
}
InterpretedFunction::Instruction
SimpleJoinCount::compile_self(const ValueBuilderFactory &, Stash &) const
{
return InterpretedFunction::Instruction(my_simple_join_count_op, _dense_factor);
}
const TensorFunction &
SimpleJoinCount::optimize(const TensorFunction &expr, Stash &stash)
{
auto reduce = as<Reduce>(expr);
if (reduce && (reduce->aggr() == Aggr::COUNT)) {
if (auto join = as<Join>(reduce->child())) {
const TensorFunction &lhs = join->lhs();
const TensorFunction &rhs = join->rhs();
if (check_types(expr.result_type(), lhs.result_type(), rhs.result_type())) {
return stash.create<SimpleJoinCount>(lhs, rhs, join->result_type().dense_subspace_size());
}
}
}
return expr;
}
} // namespace
|
