blob: 96bd2dd500a34e4329b449dbe5ab691ef1d6d88c [file]
/*
* 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.
*/
#include "paimon_vindex.hpp"
#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstdio>
#include <cstring>
#include <vector>
#define ASSERT_EQ(a, b) do { \
if ((a) != (b)) { \
fprintf(stderr, "FAIL %s:%d: %s != %s\n", __FILE__, __LINE__, #a, #b); \
abort(); \
} \
} while (0)
#define ASSERT_TRUE(x) do { \
if (!(x)) { \
fprintf(stderr, "FAIL %s:%d: %s\n", __FILE__, __LINE__, #x); \
abort(); \
} \
} while (0)
struct MemBuffer {
std::vector<uint8_t> data;
size_t pos = 0;
};
constexpr size_t kRoundtripDimension = 2;
constexpr size_t kRoundtripNlist = 4;
constexpr size_t kRoundtripPerList = 128;
constexpr size_t kRoundtripVectorCount = kRoundtripNlist * kRoundtripPerList;
static paimon::vindex::OutputFile make_output(MemBuffer& buf) {
paimon::vindex::OutputFile out;
out.write_fn = [&buf](const uint8_t* data, size_t len) -> int {
buf.data.insert(buf.data.end(), data, data + len);
buf.pos += len;
return 0;
};
out.flush_fn = []() -> int { return 0; };
out.get_pos_fn = [&buf]() -> int64_t { return static_cast<int64_t>(buf.pos); };
return out;
}
static paimon::vindex::InputFile make_input(const MemBuffer& buf) {
paimon::vindex::InputFile in;
in.read_at_fn = [&buf](uint64_t offset, uint8_t* dst, size_t len) -> int {
if (offset + len > buf.data.size()) return -1;
memcpy(dst, buf.data.data() + offset, len);
return 0;
};
return in;
}
static int64_t cluster_base_id(size_t cluster) {
return static_cast<int64_t>((cluster + 1) * 100000);
}
static std::vector<float> roundtrip_data() {
std::vector<float> data(kRoundtripVectorCount * kRoundtripDimension);
for (size_t i = 0; i < kRoundtripVectorCount; i++) {
size_t cluster = i / kRoundtripPerList;
size_t local = i % kRoundtripPerList;
float center = static_cast<float>(cluster) * 20.0f;
data[i * kRoundtripDimension] = center + static_cast<float>(local % 16) * 0.001f;
data[i * kRoundtripDimension + 1] = center + static_cast<float>(local / 16) * 0.001f;
}
return data;
}
static std::vector<int64_t> roundtrip_ids() {
std::vector<int64_t> ids(kRoundtripVectorCount);
for (size_t i = 0; i < kRoundtripVectorCount; i++) {
size_t cluster = i / kRoundtripPerList;
size_t local = i % kRoundtripPerList;
ids[i] = cluster_base_id(cluster) + static_cast<int64_t>(local);
}
return ids;
}
static void assert_id_in_cluster(int64_t id, size_t cluster) {
int64_t base = cluster_base_id(cluster);
ASSERT_TRUE(id >= base);
ASSERT_TRUE(id < base + static_cast<int64_t>(kRoundtripPerList));
}
static void run_roundtrip(
const char* name,
const std::vector<std::pair<std::string, std::string>>& options,
uint32_t expected_index_type,
size_t expected_pq_m,
size_t expected_hnsw_m) {
paimon::vindex::Writer writer(options);
ASSERT_EQ(writer.dimension(), 2);
std::vector<float> data = roundtrip_data();
std::vector<int64_t> ids = roundtrip_ids();
writer.train(data.data(), kRoundtripVectorCount);
writer.add_vectors(ids.data(), data.data(), kRoundtripVectorCount);
MemBuffer buf;
writer.write_index(make_output(buf));
ASSERT_TRUE(!buf.data.empty());
paimon::vindex::Reader reader(make_input(buf));
auto metadata = reader.metadata();
ASSERT_EQ(metadata.index_type, expected_index_type);
ASSERT_EQ(metadata.dimension, 2);
ASSERT_EQ(metadata.nlist, 4);
ASSERT_EQ(metadata.metric, PAIMON_VINDEX_METRIC_L2);
ASSERT_EQ(metadata.total_vectors, kRoundtripVectorCount);
ASSERT_EQ(metadata.pq_m, expected_pq_m);
ASSERT_EQ(metadata.hnsw_m, expected_hnsw_m);
reader.optimize_for_search();
const float query[] = {0.0f, 0.0f};
auto result = reader.search(query, 2, 4, 16);
ASSERT_EQ(result.ids.size(), 2);
assert_id_in_cluster(result.ids[0], 0);
ASSERT_TRUE(std::isfinite(result.distances[0]));
const float queries[] = {0.0f, 0.0f, 20.0f, 20.0f};
auto batch = reader.search_batch(queries, 2, 1, 4, 16);
ASSERT_EQ(batch.ids.size(), 2);
assert_id_in_cluster(batch.ids[0], 0);
assert_id_in_cluster(batch.ids[1], 1);
printf("PASS %s\n", name);
}
static void test_supported_index_roundtrips() {
run_roundtrip(
"ivf_flat_roundtrip",
{
{"index.type", "ivf_flat"},
{"dimension", "2"},
{"nlist", "4"},
{"metric", "l2"},
},
PAIMON_VINDEX_INDEX_TYPE_IVF_FLAT,
0,
0);
run_roundtrip(
"ivf_pq_roundtrip",
{
{"index.type", "ivf_pq"},
{"dimension", "2"},
{"nlist", "4"},
{"metric", "l2"},
{"pq.m", "1"},
},
PAIMON_VINDEX_INDEX_TYPE_IVF_PQ,
1,
0);
run_roundtrip(
"ivf_hnsw_flat_roundtrip",
{
{"index.type", "ivf_hnsw_flat"},
{"dimension", "2"},
{"nlist", "4"},
{"metric", "l2"},
{"hnsw.m", "4"},
},
PAIMON_VINDEX_INDEX_TYPE_IVF_HNSW_FLAT,
0,
4);
run_roundtrip(
"ivf_hnsw_sq_roundtrip",
{
{"index.type", "ivf_hnsw_sq"},
{"dimension", "2"},
{"nlist", "4"},
{"metric", "l2"},
{"hnsw.m", "4"},
},
PAIMON_VINDEX_INDEX_TYPE_IVF_HNSW_SQ,
0,
4);
}
int main() {
test_supported_index_roundtrips();
return 0;
}