milvus/internal/core/src/common/FieldData.cpp
smellthemoon 44ddcb5a63
fix: not check has_value before get value in JSON (#37128)
https://github.com/milvus-io/milvus/issues/36236
also: https://github.com/milvus-io/milvus/issues/37113

Signed-off-by: lixinguo <xinguo.li@zilliz.com>
Co-authored-by: lixinguo <xinguo.li@zilliz.com>
2024-10-25 17:19:28 +08:00

325 lines
13 KiB
C++

// Licensed to the LF AI & Data foundation 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 "common/FieldData.h"
#include "arrow/array/array_binary.h"
#include "common/Array.h"
#include "common/EasyAssert.h"
#include "common/Exception.h"
#include "common/FieldDataInterface.h"
#include "common/Json.h"
#include "simdjson/padded_string.h"
namespace milvus {
template <typename Type, bool is_type_entire_row>
void
FieldDataImpl<Type, is_type_entire_row>::FillFieldData(const void* source,
ssize_t element_count) {
AssertInfo(!nullable_,
"need to fill valid_data, use the 3-argument version instead");
if (element_count == 0) {
return;
}
std::lock_guard lck(tell_mutex_);
if (length_ + element_count > get_num_rows()) {
resize_field_data(length_ + element_count);
}
std::copy_n(static_cast<const Type*>(source),
element_count * dim_,
data_.data() + length_ * dim_);
length_ += element_count;
}
template <typename Type, bool is_type_entire_row>
void
FieldDataImpl<Type, is_type_entire_row>::FillFieldData(
const void* field_data, const uint8_t* valid_data, ssize_t element_count) {
AssertInfo(
nullable_,
"no need to fill valid_data, use the 2-argument version instead");
if (element_count == 0) {
return;
}
std::lock_guard lck(tell_mutex_);
if (length_ + element_count > get_num_rows()) {
resize_field_data(length_ + element_count);
}
std::copy_n(static_cast<const Type*>(field_data),
element_count * dim_,
data_.data() + length_ * dim_);
ssize_t byte_count = (element_count + 7) / 8;
// Note: if 'nullable == true` and valid_data is nullptr
// means null_count == 0, will fill it with 0xFF
if (valid_data == nullptr) {
valid_data_.assign(byte_count, 0xFF);
} else {
std::copy_n(valid_data, byte_count, valid_data_.data());
}
length_ += element_count;
}
template <typename ArrayType, arrow::Type::type ArrayDataType>
std::pair<const void*, int64_t>
GetDataInfoFromArray(const std::shared_ptr<arrow::Array> array) {
AssertInfo(array->type()->id() == ArrayDataType,
"inconsistent data type, expected {}, actual {}",
ArrayDataType,
array->type()->id());
auto typed_array = std::dynamic_pointer_cast<ArrayType>(array);
auto element_count = array->length();
return std::make_pair(typed_array->raw_values(), element_count);
}
template <typename Type, bool is_type_entire_row>
void
FieldDataImpl<Type, is_type_entire_row>::FillFieldData(
const std::shared_ptr<arrow::Array> array) {
AssertInfo(array != nullptr, "null arrow array");
auto element_count = array->length();
if (element_count == 0) {
return;
}
null_count_ = array->null_count();
switch (data_type_) {
case DataType::BOOL: {
AssertInfo(array->type()->id() == arrow::Type::type::BOOL,
"inconsistent data type");
auto bool_array =
std::dynamic_pointer_cast<arrow::BooleanArray>(array);
FixedVector<bool> values(element_count);
for (size_t index = 0; index < element_count; ++index) {
values[index] = bool_array->Value(index);
}
if (nullable_) {
return FillFieldData(values.data(),
bool_array->null_bitmap_data(),
element_count);
}
return FillFieldData(values.data(), element_count);
}
case DataType::INT8: {
auto array_info =
GetDataInfoFromArray<arrow::Int8Array, arrow::Type::type::INT8>(
array);
if (nullable_) {
return FillFieldData(
array_info.first, array->null_bitmap_data(), element_count);
}
return FillFieldData(array_info.first, array_info.second);
}
case DataType::INT16: {
auto array_info =
GetDataInfoFromArray<arrow::Int16Array,
arrow::Type::type::INT16>(array);
if (nullable_) {
return FillFieldData(
array_info.first, array->null_bitmap_data(), element_count);
}
return FillFieldData(array_info.first, array_info.second);
}
case DataType::INT32: {
auto array_info =
GetDataInfoFromArray<arrow::Int32Array,
arrow::Type::type::INT32>(array);
if (nullable_) {
return FillFieldData(
array_info.first, array->null_bitmap_data(), element_count);
}
return FillFieldData(array_info.first, array_info.second);
}
case DataType::INT64: {
auto array_info =
GetDataInfoFromArray<arrow::Int64Array,
arrow::Type::type::INT64>(array);
if (nullable_) {
return FillFieldData(
array_info.first, array->null_bitmap_data(), element_count);
}
return FillFieldData(array_info.first, array_info.second);
}
case DataType::FLOAT: {
auto array_info =
GetDataInfoFromArray<arrow::FloatArray,
arrow::Type::type::FLOAT>(array);
if (nullable_) {
return FillFieldData(
array_info.first, array->null_bitmap_data(), element_count);
}
return FillFieldData(array_info.first, array_info.second);
}
case DataType::DOUBLE: {
auto array_info =
GetDataInfoFromArray<arrow::DoubleArray,
arrow::Type::type::DOUBLE>(array);
if (nullable_) {
return FillFieldData(
array_info.first, array->null_bitmap_data(), element_count);
}
return FillFieldData(array_info.first, array_info.second);
}
case DataType::STRING:
case DataType::VARCHAR: {
AssertInfo(array->type()->id() == arrow::Type::type::STRING,
"inconsistent data type");
auto string_array =
std::dynamic_pointer_cast<arrow::StringArray>(array);
std::vector<std::string> values(element_count);
for (size_t index = 0; index < element_count; ++index) {
values[index] = string_array->GetString(index);
}
if (nullable_) {
return FillFieldData(
values.data(), array->null_bitmap_data(), element_count);
}
return FillFieldData(values.data(), element_count);
}
case DataType::JSON: {
// The code here is not referenced.
// A subclass named FieldDataJsonImpl is implemented, which overloads this function.
AssertInfo(array->type()->id() == arrow::Type::type::BINARY,
"inconsistent data type");
auto json_array =
std::dynamic_pointer_cast<arrow::BinaryArray>(array);
std::vector<Json> values(element_count);
for (size_t index = 0; index < element_count; ++index) {
values[index] =
Json(simdjson::padded_string(json_array->GetString(index)));
}
if (nullable_) {
return FillFieldData(
values.data(), array->null_bitmap_data(), element_count);
}
return FillFieldData(values.data(), element_count);
}
case DataType::ARRAY: {
auto array_array =
std::dynamic_pointer_cast<arrow::BinaryArray>(array);
std::vector<Array> values(element_count);
int null_number = 0;
for (size_t index = 0; index < element_count; ++index) {
ScalarArray field_data;
if (array_array->GetString(index) == "") {
null_number++;
continue;
}
auto success =
field_data.ParseFromString(array_array->GetString(index));
AssertInfo(success, "parse from string failed");
values[index] = Array(field_data);
}
if (nullable_) {
return FillFieldData(
values.data(), array->null_bitmap_data(), element_count);
}
AssertInfo(null_number == 0, "get empty string when not nullable");
return FillFieldData(values.data(), element_count);
}
case DataType::VECTOR_FLOAT:
case DataType::VECTOR_FLOAT16:
case DataType::VECTOR_BFLOAT16:
case DataType::VECTOR_BINARY: {
auto array_info =
GetDataInfoFromArray<arrow::FixedSizeBinaryArray,
arrow::Type::type::FIXED_SIZE_BINARY>(
array);
return FillFieldData(array_info.first, array_info.second);
}
case DataType::VECTOR_SPARSE_FLOAT: {
AssertInfo(array->type()->id() == arrow::Type::type::BINARY,
"inconsistent data type");
auto arr = std::dynamic_pointer_cast<arrow::BinaryArray>(array);
std::vector<knowhere::sparse::SparseRow<float>> values;
for (size_t index = 0; index < element_count; ++index) {
auto view = arr->GetString(index);
values.push_back(
CopyAndWrapSparseRow(view.data(), view.size()));
}
return FillFieldData(values.data(), element_count);
}
default: {
PanicInfo(DataTypeInvalid,
GetName() + "::FillFieldData" +
" not support data type " +
GetDataTypeName(data_type_));
}
}
}
// scalar data
template class FieldDataImpl<bool, true>;
template class FieldDataImpl<unsigned char, false>;
template class FieldDataImpl<int8_t, true>;
template class FieldDataImpl<int16_t, true>;
template class FieldDataImpl<int32_t, true>;
template class FieldDataImpl<int64_t, true>;
template class FieldDataImpl<float, true>;
template class FieldDataImpl<double, true>;
template class FieldDataImpl<std::string, true>;
template class FieldDataImpl<Json, true>;
template class FieldDataImpl<Array, true>;
// vector data
template class FieldDataImpl<int8_t, false>;
template class FieldDataImpl<float, false>;
template class FieldDataImpl<float16, false>;
template class FieldDataImpl<bfloat16, false>;
template class FieldDataImpl<knowhere::sparse::SparseRow<float>, true>;
FieldDataPtr
InitScalarFieldData(const DataType& type, bool nullable, int64_t cap_rows) {
switch (type) {
case DataType::BOOL:
return std::make_shared<FieldData<bool>>(type, nullable, cap_rows);
case DataType::INT8:
return std::make_shared<FieldData<int8_t>>(
type, nullable, cap_rows);
case DataType::INT16:
return std::make_shared<FieldData<int16_t>>(
type, nullable, cap_rows);
case DataType::INT32:
return std::make_shared<FieldData<int32_t>>(
type, nullable, cap_rows);
case DataType::INT64:
return std::make_shared<FieldData<int64_t>>(
type, nullable, cap_rows);
case DataType::FLOAT:
return std::make_shared<FieldData<float>>(type, nullable, cap_rows);
case DataType::DOUBLE:
return std::make_shared<FieldData<double>>(
type, nullable, cap_rows);
case DataType::STRING:
case DataType::VARCHAR:
return std::make_shared<FieldData<std::string>>(
type, nullable, cap_rows);
case DataType::JSON:
return std::make_shared<FieldData<Json>>(type, nullable, cap_rows);
default:
PanicInfo(DataTypeInvalid,
"InitScalarFieldData not support data type " +
GetDataTypeName(type));
}
}
} // namespace milvus