diff --git a/README_CN.md b/README_CN.md
index ef7df1b..1b4195c 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -1,5 +1,5 @@
- English | 简体中文
+ English | 中文
diff --git a/python/tests/test_embedding.py b/python/tests/test_embedding.py
index e0a57a1..1b0622b 100644
--- a/python/tests/test_embedding.py
+++ b/python/tests/test_embedding.py
@@ -1168,8 +1168,8 @@ class TestDefaultLocalDenseEmbedding:
return_value="/path/to/model",
):
mock_ms = Mock()
- mock_require_module.side_effect = (
- lambda m: mock_st if m == "sentence_transformers" else mock_ms
+ mock_require_module.side_effect = lambda m: (
+ mock_st if m == "sentence_transformers" else mock_ms
)
emb_func_ms = DefaultLocalDenseEmbedding(model_source="modelscope")
assert (
@@ -1635,8 +1635,8 @@ class TestDefaultLocalSparseEmbedding:
"modelscope.hub.snapshot_download.snapshot_download",
return_value="/cache/splade-cocondenser",
):
- mock_require_module.side_effect = (
- lambda m: mock_st if m == "sentence_transformers" else mock_ms
+ mock_require_module.side_effect = lambda m: (
+ mock_st if m == "sentence_transformers" else mock_ms
)
sparse_emb = DefaultLocalSparseEmbedding(model_source="modelscope")
diff --git a/src/db/common/constants.h b/src/db/common/constants.h
index 39aa834..f987aa2 100644
--- a/src/db/common/constants.h
+++ b/src/db/common/constants.h
@@ -52,7 +52,7 @@ constexpr uint32_t kMaxScalarFieldSize = 1024;
constexpr uint32_t kMaxVectorFieldSize = 5;
-constexpr uint32_t kMaxQueryTopk = 1024;
+constexpr uint32_t kMaxQueryTopk = 100000;
constexpr uint32_t kMaxOutputFieldSize = 1024;
diff --git a/src/db/index/common/doc.cc b/src/db/index/common/doc.cc
index 35271f3..deb4a58 100644
--- a/src/db/index/common/doc.cc
+++ b/src/db/index/common/doc.cc
@@ -1203,53 +1203,61 @@ bool Doc::operator==(const Doc &other) const {
Status VectorQuery::validate(const FieldSchema *schema) const {
if ((uint32_t)topk_ > kMaxQueryTopk) {
- return Status::InvalidArgument("query validate failed: topk[", topk_,
- "] is too large, max is ", kMaxQueryTopk);
+ return Status::InvalidArgument("Invalid query: topk[", topk_,
+ "] exceeds the maximum allowed value of ",
+ kMaxQueryTopk);
}
if (output_fields_.has_value() &&
output_fields_->size() > kMaxOutputFieldSize) {
return Status::InvalidArgument(
- "query validate failed: output_fields is too large, max is ",
+ "Invalid query: too many output fields, the maximum allowed is ",
kMaxOutputFieldSize);
}
if (schema == nullptr) {
- // support query with vector
if (query_vector_.empty() && query_sparse_indices_.empty()) {
+ // No vector provided — this is a scalar-only filter query.
return Status::OK();
+ } else {
+ // If a query vector was provided, the field must exist as a vector field
+ // since we are doing vector similarity search.
+ return Status::InvalidArgument(
+ "Invalid query: query vector is provided, but query field[",
+ field_name_,
+ "] does not exist or is not a vector field in the collection");
}
-
- return Status::InvalidArgument("query validate failed: vector_field[",
- field_name_,
- "] not defined in the collection schema");
}
// validate dense/sparse vector
if (schema->is_dense_vector()) {
- // validate dimension
+ // Validate dimension
auto dim = schema->dimension();
switch (schema->data_type()) {
case DataType::VECTOR_FP16:
if (dim * sizeof(float16_t) != query_vector_.size()) {
return Status::InvalidArgument(
- "query validate failed: dimension is invalid");
+ "Invalid query: dimension mismatch, expected ", dim, " but got ",
+ query_vector_.size() / sizeof(float16_t), " (FP16)");
}
break;
case DataType::VECTOR_FP32:
if (dim * sizeof(float) != query_vector_.size()) {
return Status::InvalidArgument(
- "query validate failed: dimension is invalid");
+ "Invalid query: dimension mismatch, expected ", dim, " but got ",
+ query_vector_.size() / sizeof(float), " (FP32)");
}
break;
case DataType::VECTOR_FP64:
if (dim * sizeof(double) != query_vector_.size()) {
return Status::InvalidArgument(
- "query validate failed: dimension is invalid");
+ "Invalid query: dimension mismatch, expected ", dim, " but got ",
+ query_vector_.size() / sizeof(double), " (FP64)");
}
break;
case DataType::VECTOR_INT8:
if (dim * sizeof(int8_t) != query_vector_.size()) {
return Status::InvalidArgument(
- "query validate failed: dimension is invalid");
+ "Invalid query: dimension mismatch, expected ", dim, " but got ",
+ query_vector_.size() / sizeof(int8_t), " (INT8)");
}
break;
case DataType::VECTOR_INT16:
@@ -1257,22 +1265,22 @@ Status VectorQuery::validate(const FieldSchema *schema) const {
case DataType::VECTOR_BINARY32:
case DataType::VECTOR_BINARY64:
return Status::NotSupported(
- "query validate failed: unsupported dense vector type");
+ "Invalid query: dense vector type of field[", field_name_,
+ "] is not supported");
default:
- return Status::InvalidArgument(
- "query validate failed: field is not dense vector");
+ return Status::InvalidArgument("Invalid query: field[", field_name_,
+ "] is not a dense vector field");
}
} else if (schema->is_sparse_vector()) {
- // validate sparse indices size
+ // Validate sparse indices size
if (query_sparse_indices_.size() > kSparseMaxDimSize * sizeof(uint32_t)) {
return Status::InvalidArgument(
- "query validate failed: the number of sparse indices exceeds the "
- "maximum limit ",
+ "Invalid query: too many sparse indices, the maximum allowed is ",
kSparseMaxDimSize);
}
} else {
- return Status::InvalidArgument(
- "query validate failed: field is not vector");
+ return Status::InvalidArgument("Invalid query: field[", field_name_,
+ "] is not a vector field");
}
return Status::OK();
}
diff --git a/tests/db/collection_test.cc b/tests/db/collection_test.cc
index 486b740..d50701d 100644
--- a/tests/db/collection_test.cc
+++ b/tests/db/collection_test.cc
@@ -30,7 +30,6 @@
#include "db/index/common/type_helper.h"
#include "index/utils/utils.h"
#include "zvec/ailego/utility/float_helper.h"
-#include "zvec/db/config.h"
#include "zvec/db/doc.h"
#include "zvec/db/index_params.h"
#include "zvec/db/options.h"
@@ -2110,7 +2109,8 @@ TEST_F(CollectionTest, Feature_CreateIndex_Vector) {
TEST_F(CollectionTest, Feature_CreateIndex_Scalar) {
#ifdef __ANDROID__
- GTEST_SKIP() << "Skipped on Android: emulator filesystem lacks hardlink support (needed by RocksDB checkpoint)";
+ GTEST_SKIP() << "Skipped on Android: emulator filesystem lacks hardlink "
+ "support (needed by RocksDB checkpoint)";
#endif
auto func = [&](std::string field_name, bool enable_optimize,
IndexParams::Ptr scalar_index_params = nullptr) {
@@ -2387,7 +2387,8 @@ TEST_F(CollectionTest, Feature_DropIndex_Vector) {
TEST_F(CollectionTest, Feature_DropIndex_Scalar) {
#ifdef __ANDROID__
- GTEST_SKIP() << "Skipped on Android: emulator filesystem lacks hardlink support (needed by RocksDB checkpoint)";
+ GTEST_SKIP() << "Skipped on Android: emulator filesystem lacks hardlink "
+ "support (needed by RocksDB checkpoint)";
#endif
auto func = [&](std::string field_name, bool enable_optimize) {
FileHelper::RemoveDirectory(col_path);
@@ -3266,7 +3267,7 @@ TEST_F(CollectionTest, Feature_Query_Validate) {
{
VectorQuery query;
- query.topk_ = 1025;
+ query.topk_ = 100001;
query.field_name_ = field_name;
auto field_scheama = schema->get_vector_field(field_name);
diff --git a/tests/db/crash_recovery/CMakeLists.txt b/tests/db/crash_recovery/CMakeLists.txt
index 32b5f56..f737b40 100644
--- a/tests/db/crash_recovery/CMakeLists.txt
+++ b/tests/db/crash_recovery/CMakeLists.txt
@@ -50,6 +50,7 @@ cc_binary(
INCS .. ../../src
LDFLAGS ${APPLE_FRAMEWORK_LIBS}
)
+set_target_properties(data_generator PROPERTIES EXCLUDE_FROM_ALL TRUE)
# Build collection_optimizer executable
@@ -60,6 +61,7 @@ cc_binary(
INCS .. ../../src
LDFLAGS ${APPLE_FRAMEWORK_LIBS}
)
+set_target_properties(collection_optimizer PROPERTIES EXCLUDE_FROM_ALL TRUE)
# Build test executables