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duckdb_deeplake_scan.cpp
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1136 lines (1032 loc) · 49 KB
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// Include libintl.h first to avoid conflicts with PostgreSQL's gettext macro
#include <libintl.h>
// DuckDB headers must come before PostgreSQL headers to avoid namespace pollution
#include "duckdb_deeplake_scan.hpp"
#include <duckdb.hpp>
#include <duckdb/catalog/catalog.hpp>
#include <duckdb/common/types/uuid.hpp>
#include <duckdb/parser/parsed_data/create_table_function_info.hpp>
#include <duckdb/planner/expression/bound_conjunction_expression.hpp>
#include <duckdb/planner/expression/bound_reference_expression.hpp>
#include <duckdb/planner/filter/in_filter.hpp>
#include "duckdb_deeplake_convert.hpp"
#include "pg_deeplake.hpp"
#include "table_data.hpp"
#include "table_storage.hpp"
#include "utils.hpp"
#include <base/function.hpp>
#include <heimdall_common/filtered_dataset.hpp>
#include <query_core/index_holder.hpp>
namespace {
struct deeplake_scan_bind_data final : public duckdb::TableFunctionData
{
pg::table_data& table_data;
duckdb::vector<duckdb::LogicalType> bind_types;
deeplake_scan_bind_data(pg::table_data& td_ref, duckdb::vector<duckdb::LogicalType> types)
: table_data(td_ref)
, bind_types(std::move(types))
{
}
~deeplake_scan_bind_data() override
{
}
};
struct deeplake_scan_global_state final : public duckdb::GlobalTableFunctionState
{
duckdb::vector<duckdb::column_t> column_ids;
icm::vector<base::function<async::promise<icm::vector<icm::roaring>>()>> index_searchers;
duckdb::unique_ptr<duckdb::Expression> filter_expr;
std::mutex index_search_mutex;
heimdall::dataset_view_ptr index_search_result;
std::atomic<int64_t> current_row = 0;
idx_t MaxThreads() const override
{
return std::min(base::system_report::cpu_cores(), pg::max_num_threads_for_global_state);
}
};
struct deeplake_scan_local_state final : public duckdb::LocalTableFunctionState
{
duckdb::unique_ptr<duckdb::ExpressionExecutor> filter_executor;
};
// Map PostgreSQL type OID to DuckDB LogicalType
duckdb::LogicalType pg_type_to_duckdb(Oid typid, int32_t typmod, int32_t ndims = 1)
{
using namespace duckdb;
// Resolve domain types to their base type
switch (typid) {
case BOOLOID:
return LogicalType::BOOLEAN;
case INT2OID:
return LogicalType::SMALLINT;
case INT4OID:
return LogicalType::INTEGER;
case INT8OID:
return LogicalType::BIGINT;
case FLOAT4OID:
return LogicalType::FLOAT;
case FLOAT8OID:
case NUMERICOID:
return LogicalType::DOUBLE;
case DATEOID:
return LogicalType::DATE;
case TIMEOID:
return LogicalType::TIME;
case TIMESTAMPOID:
return LogicalType::TIMESTAMP;
case TIMESTAMPTZOID:
return LogicalType::TIMESTAMP_TZ;
case CHAROID:
case BPCHAROID:
case VARCHAROID:
case TEXTOID:
return LogicalType::VARCHAR;
case JSONOID:
case JSONBOID: {
LogicalType res(LogicalType::VARCHAR);
res.SetAlias(LogicalType::JSON_TYPE_NAME);
return res;
}
case UUIDOID:
return LogicalType::UUID;
case BYTEAOID:
return LogicalType::BLOB;
// Array types - map to DuckDB LIST, with proper nesting for multi-dimensional arrays
case BOOLARRAYOID: {
LogicalType elem_type = LogicalType::BOOLEAN;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case INT2ARRAYOID: {
LogicalType elem_type = LogicalType::SMALLINT;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case INT4ARRAYOID: {
LogicalType elem_type = LogicalType::INTEGER;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case INT8ARRAYOID: {
LogicalType elem_type = LogicalType::BIGINT;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case FLOAT4ARRAYOID: {
LogicalType elem_type = LogicalType::FLOAT;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case FLOAT8ARRAYOID: {
LogicalType elem_type = LogicalType::DOUBLE;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case TEXTARRAYOID:
case VARCHARARRAYOID: {
LogicalType elem_type = LogicalType::VARCHAR;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case DATEARRAYOID: {
LogicalType elem_type = LogicalType::DATE;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case TIMESTAMPARRAYOID: {
LogicalType elem_type = LogicalType::TIMESTAMP;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case TIMESTAMPTZARRAYOID: {
LogicalType elem_type = LogicalType::TIMESTAMP_TZ;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
case BYTEAARRAYOID: {
LogicalType elem_type = LogicalType::BLOB;
for (int32_t i = 1; i < ndims; ++i)
elem_type = LogicalType::LIST(elem_type);
return LogicalType::LIST(elem_type);
}
default:
throw duckdb::NotImplementedException("Unsupported PostgreSQL type OID: " + std::to_string(typid) + " (" +
format_type_with_typemod(typid, typmod) + ")");
}
}
// Bind function: Define schema from table_data
duckdb::unique_ptr<duckdb::FunctionData> deeplake_scan_bind(duckdb::ClientContext& context,
duckdb::TableFunctionBindInput& input,
duckdb::vector<duckdb::LogicalType>& return_types,
duckdb::vector<duckdb::string>& names)
{
ASSERT(input.inputs.size() == 1);
// Extract table_data pointer passed as uint
const auto table_id = input.inputs[0].GetValue<Oid>();
ASSERT(table_id != InvalidOid);
auto& td = pg::table_storage::instance().get_table_data(table_id);
// Build schema from table_data's tuple descriptor
// Note: table_data.num_columns() returns only active (non-dropped) columns
for (int32_t i = 0; i < td.num_columns(); ++i) {
names.emplace_back(td.get_atttypename(i));
int32_t ndims = td.get_attndims(i);
// For array types, use attndims; for non-arrays, ndims is 0
if (ndims == 0 && type_is_array(td.get_base_atttypid(i))) {
ndims = 1; // Default to 1D if attndims not set but type is array
}
return_types.push_back(pg_type_to_duckdb(td.get_base_atttypid(i), td.get_atttypmod(i), ndims));
}
return duckdb::make_uniq<deeplake_scan_bind_data>(td, return_types);
}
base::function<async::promise<icm::vector<icm::roaring>>()>
try_get_index_searcher(heimdall::column_view_ptr column_view, const duckdb::ConstantFilter& filter)
{
base::function<async::promise<icm::vector<icm::roaring>>()> result;
auto index_holder = column_view->index_holder();
ASSERT(index_holder != nullptr);
auto constant = pg::to_deeplake_value(filter.constant);
if (nd::dtype_is_numeric(constant.dtype())) {
query_core::inverted_index_search_info info;
switch (filter.comparison_type) {
case duckdb::ExpressionType::COMPARE_EQUAL:
info.op = query_core::relational_operator::equals;
break;
case duckdb::ExpressionType::COMPARE_NOTEQUAL:
break;
case duckdb::ExpressionType::COMPARE_LESSTHAN:
info.op = query_core::relational_operator::less;
break;
case duckdb::ExpressionType::COMPARE_GREATERTHAN:
info.op = query_core::relational_operator::greater;
break;
case duckdb::ExpressionType::COMPARE_LESSTHANOREQUALTO:
info.op = query_core::relational_operator::less_eq;
break;
case duckdb::ExpressionType::COMPARE_GREATERTHANOREQUALTO:
info.op = query_core::relational_operator::greater_eq;
break;
default:
break;
}
if (info.op != query_core::relational_operator::invalid) {
info.column_name = column_view->name();
info.search_values.push_back(constant);
if (index_holder->can_run_query(info)) {
result = [index_holder, si = std::move(info)]() {
return index_holder->run_query(si);
};
}
}
} else if (constant.dtype() == nd::dtype::string) {
// handle duckdb::ExpressionType::COMPARE_NOTEQUAL ?
if (filter.comparison_type == duckdb::ExpressionType::COMPARE_EQUAL) {
query_core::text_search_info info;
info.column_name = column_view->name();
info.type = query_core::text_search_info::search_type::equals;
info.search_values.push_back(icm::vector<std::string>{filter.constant.ToString()});
if (index_holder->can_run_query(info)) {
result = [index_holder, si = std::move(info)]() {
return index_holder->run_query(si);
};
}
}
}
return result;
}
base::function<async::promise<icm::vector<icm::roaring>>()>
try_get_index_searcher(heimdall::column_view_ptr column_view, const duckdb::InFilter& filter)
{
query_core::inverted_index_search_info info;
info.column_name = column_view->name();
info.op = query_core::relational_operator::equals;
info.search_values.reserve(filter.values.size());
for (const duckdb::Value& v : filter.values) {
info.search_values.push_back(pg::to_deeplake_value(v));
}
ASSERT(column_view->index_holder() != nullptr);
return [h = column_view->index_holder(), si = std::move(info)]() {
return h->run_query(si);
};
}
base::function<async::promise<icm::vector<icm::roaring>>()>
try_get_index_searcher(heimdall::column_view_ptr column_view, const duckdb::TableFilter& filter)
{
base::function<async::promise<icm::vector<icm::roaring>>()> result;
ASSERT(column_view != nullptr);
if (column_view->index_holder() == nullptr) {
return result;
}
switch (filter.filter_type) {
case duckdb::TableFilterType::CONSTANT_COMPARISON: {
result = try_get_index_searcher(column_view, filter.Cast<const duckdb::ConstantFilter>());
break;
}
case duckdb::TableFilterType::IN_FILTER: {
result = try_get_index_searcher(column_view, filter.Cast<const duckdb::InFilter>());
break;
}
default:
break;
}
return result;
}
duckdb::unique_ptr<duckdb::GlobalTableFunctionState> deeplake_scan_init_global(duckdb::ClientContext& context,
duckdb::TableFunctionInitInput& input)
{
auto& bind_data = input.bind_data->Cast<deeplake_scan_bind_data>();
const auto& td = bind_data.table_data;
auto r = duckdb::make_uniq<deeplake_scan_global_state>();
r->column_ids = input.column_ids;
if (input.filters) {
duckdb::vector<duckdb::unique_ptr<duckdb::Expression>> filter_exprs;
for (auto& [output_col_idx, filter] : input.filters->filters) {
ASSERT(output_col_idx >= 0 && output_col_idx < input.column_ids.size());
const auto col_idx = input.column_ids[output_col_idx];
auto is = try_get_index_searcher(td.get_column_view(col_idx), *filter);
if (is) {
r->index_searchers.push_back(std::move(is));
} else {
duckdb::BoundReferenceExpression column_expr_ref(bind_data.bind_types[col_idx], output_col_idx);
filter_exprs.push_back(filter->ToExpression(column_expr_ref));
}
}
if (filter_exprs.size() == 1) {
r->filter_expr = std::move(filter_exprs[0]);
} else if (filter_exprs.size() > 1) {
// Create a conjunction from the select list.
auto c = duckdb::make_uniq<duckdb::BoundConjunctionExpression>(duckdb::ExpressionType::CONJUNCTION_AND);
for (auto& expr : filter_exprs) {
c->children.push_back(std::move(expr));
}
r->filter_expr = std::move(c);
}
}
return r;
}
duckdb::unique_ptr<duckdb::LocalTableFunctionState>
deeplake_scan_init_local(duckdb::ExecutionContext& context,
duckdb::TableFunctionInitInput& input,
duckdb::GlobalTableFunctionState* global_state)
{
auto& global = global_state->Cast<deeplake_scan_global_state>();
auto r = duckdb::make_uniq<deeplake_scan_local_state>();
// Handle other filter types similarly
if (global.filter_expr) {
r->filter_executor = duckdb::make_uniq<duckdb::ExpressionExecutor>(context.client, *global.filter_expr);
}
return r;
}
class deeplake_scan_function_helper
{
const deeplake_scan_bind_data& bind_data_;
deeplake_scan_global_state& global_state_;
deeplake_scan_local_state& local_state_;
duckdb::DataChunk& output_;
public:
deeplake_scan_function_helper(duckdb::ClientContext& context,
duckdb::TableFunctionInput& data,
duckdb::DataChunk& output)
: bind_data_(data.bind_data->Cast<deeplake_scan_bind_data>())
, global_state_(data.global_state->Cast<deeplake_scan_global_state>())
, local_state_(data.local_state->Cast<deeplake_scan_local_state>())
, output_(output)
{
}
void scan()
{
while (true) {
if (INTERRUPTS_PENDING_CONDITION()) {
return;
}
do_scan();
if (output_.size() == 0 || !local_state_.filter_executor) {
break;
}
duckdb::SelectionVector sel(output_.size());
const idx_t match_count = local_state_.filter_executor->SelectExpression(output_, sel);
if (match_count != 0) {
if (match_count != output_.size()) {
output_.Slice(sel, match_count);
}
break;
}
}
}
private:
bool has_index_search() const
{
return !global_state_.index_searchers.empty();
}
bool is_index_search_done() const
{
return global_state_.index_search_result != nullptr;
}
bool is_uuid_type(duckdb::column_t col_idx) const
{
auto att_type = bind_data_.table_data.get_atttypid(col_idx);
return att_type == UUIDOID;
}
bool is_bytea_type(duckdb::column_t col_idx) const
{
auto att_type = bind_data_.table_data.get_base_atttypid(col_idx);
return att_type == BYTEAOID;
}
bool is_array_type(duckdb::column_t col_idx) const
{
auto att_type = bind_data_.table_data.get_atttypid(col_idx);
switch (att_type) {
case BOOLARRAYOID:
case INT2ARRAYOID:
case INT4ARRAYOID:
case INT8ARRAYOID:
case FLOAT4ARRAYOID:
case FLOAT8ARRAYOID:
case TEXTARRAYOID:
case VARCHARARRAYOID:
case DATEARRAYOID:
case TIMESTAMPARRAYOID:
case TIMESTAMPTZARRAYOID:
case BYTEAARRAYOID:
return true;
default:
return false;
}
}
static duckdb::string_t add_string(duckdb::Vector& vector, const char* data, duckdb::idx_t len)
{
try {
return duckdb::StringVector::AddString(vector, data, len);
} catch (const duckdb::Exception& e) {
elog(ERROR,
"DuckDB exception while adding string '%s': %s",
std::string(std::string_view(data, len)).c_str(),
e.what());
} catch (const std::exception& e) {
elog(ERROR,
"STD exception while adding string '%s': %s",
std::string(std::string_view(data, len)).c_str(),
e.what());
} catch (...) {
elog(ERROR, "Unknown exception while adding string '%s'", std::string(std::string_view(data, len)).c_str());
}
}
void set_string_column_output(unsigned output_column_id, nd::array&& samples)
{
ASSERT(samples.dtype() == nd::dtype::string);
auto& output_vector = output_.data[output_column_id];
pg::impl::string_stream_array_holder string_holder(samples);
for (duckdb::idx_t row_in_batch = 0; row_in_batch < output_.size(); ++row_in_batch) {
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
std::string_view value;
if (string_holder.is_valid()) {
value = string_holder.data(row_in_batch);
} else {
value = base::string_view_cast<const unsigned char>(samples[row_in_batch].data());
}
duckdb_data[row_in_batch] = add_string(output_vector, value.data(), value.size());
}
}
void set_uuid_column_output(unsigned output_column_id, nd::array&& samples)
{
auto& output_vector = output_.data[output_column_id];
for (duckdb::idx_t row_in_batch = 0; row_in_batch < output_.size(); ++row_in_batch) {
auto sample = samples[row_in_batch];
if (sample.is_none()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
continue;
}
// UUID type - convert string to DuckDB UUID (hugeint/INT128)
auto value = base::string_view_cast<const unsigned char>(sample.data());
std::string uuid_str(reinterpret_cast<const char*>(value.data()), value.size());
// Treat empty string as NULL for UUID columns
if (uuid_str.empty()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
} else {
// Use DuckDB's UUID::FromString to parse UUID string
try {
auto uuid_value = duckdb::UUID::FromString(uuid_str);
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::hugeint_t>(output_vector);
duckdb_data[row_in_batch] = uuid_value;
} catch (...) {
// If parsing fails, set to NULL
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
}
}
}
}
void set_non_array_column_output(unsigned output_column_id, nd::array&& samples)
{
const auto col_idx = global_state_.column_ids[output_column_id];
auto& output_vector = output_.data[output_column_id];
for (duckdb::idx_t row_in_batch = 0; row_in_batch < output_.size(); ++row_in_batch) {
auto sample = samples[row_in_batch];
if (sample.is_none()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
continue;
}
// Non-array type
nd::switch_dtype(sample.dtype(), [&]<typename T>() {
if constexpr (std::is_arithmetic_v<T>) {
auto att_type = bind_data_.table_data.get_atttypid(col_idx);
if (att_type == VARCHAROID || att_type == CHAROID || att_type == BPCHAROID) {
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
auto value = *reinterpret_cast<const T*>(sample.data().data());
duckdb_data[row_in_batch] = add_string(output_vector, reinterpret_cast<const char*>(&value), 1);
return;
}
auto* duckdb_data = duckdb::FlatVector::GetData<T>(output_vector);
auto value = sample.data().data();
duckdb_data[row_in_batch] = *reinterpret_cast<const T*>(value);
} else if constexpr (std::is_same_v<T, std::span<const uint8_t>>) {
auto value = sample.data();
if (value.size() == 0) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
return;
}
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
duckdb_data[row_in_batch] = duckdb::StringVector::AddStringOrBlob(
output_vector, reinterpret_cast<const char*>(value.data()), value.size());
} else {
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
if (sample.dtype() == nd::dtype::object) {
if (sample.is_none()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
} else {
auto json_str = sample.dict_value(0).serialize();
duckdb_data[row_in_batch] = add_string(output_vector, json_str.data(), json_str.size());
}
} else {
auto value = base::string_view_cast<const unsigned char>(sample.data());
duckdb_data[row_in_batch] = add_string(output_vector, value.data(), value.size());
}
}
});
}
}
void set_empty_array_output(duckdb::Vector& output_vector, duckdb::idx_t row_in_batch)
{
auto list_entry = duckdb::ListVector::GetEntry(output_vector);
auto offset = duckdb::ListVector::GetListSize(output_vector);
duckdb::ListVector::SetListSize(output_vector, offset);
auto& list_data = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector)[row_in_batch];
list_data.offset = offset;
list_data.length = 0;
}
void set_2d_array_output(
duckdb::Vector& output_vector, duckdb::idx_t row_in_batch, nd::array&& sample, int64_t nrows, int64_t ncols)
{
// Get the child vector (type: LIST(T))
auto& child_vec = duckdb::ListVector::GetEntry(output_vector);
auto child_offset = duckdb::ListVector::GetListSize(output_vector);
elog(LOG,
" output_vector type=%s, child_vec type=%s, child_offset=%zu",
output_vector.GetType().ToString().c_str(),
child_vec.GetType().ToString().c_str(),
child_offset);
// Reserve space in output_vector for nrows list entries
duckdb::ListVector::Reserve(output_vector, child_offset + nrows);
duckdb::ListVector::SetListSize(output_vector, child_offset + nrows);
// Get the grandchild vector (type: T) - the actual data vector
auto& grandchild_vec = duckdb::ListVector::GetEntry(child_vec);
auto grandchild_offset = duckdb::ListVector::GetListSize(child_vec);
elog(LOG,
" grandchild_vec type=%s, grandchild_offset=%zu",
grandchild_vec.GetType().ToString().c_str(),
grandchild_offset);
// Reserve space in child_vec for nrows * ncols list entries
duckdb::ListVector::Reserve(child_vec, grandchild_offset + nrows * ncols);
duckdb::ListVector::SetListSize(child_vec, grandchild_offset + nrows * ncols);
// Fill the nested structure
nd::switch_dtype(sample.dtype(), [&]<typename T>() {
if constexpr (std::is_arithmetic_v<T>) {
// Copy actual data to grandchild vector
auto* data_ptr = duckdb::FlatVector::GetData<T>(grandchild_vec);
const T* array_data = reinterpret_cast<const T*>(sample.data().data());
std::memcpy(data_ptr + grandchild_offset, array_data, nrows * static_cast<size_t>(ncols) * sizeof(T));
// Log first few values being written
elog(
LOG, " WRITE: copying %ld elements to grandchild at offset %zu", nrows * ncols, grandchild_offset);
for (int64_t k = 0; k < std::min(nrows * ncols, (int64_t)6); ++k) {
if constexpr (std::is_integral_v<T>) {
elog(LOG, " grandchild[%zu] = %ld", grandchild_offset + k, (long)array_data[k]);
} else {
elog(LOG, " grandchild[%zu] = %f", grandchild_offset + k, (double)array_data[k]);
}
}
// Set up child_vec list entries (one per row, pointing to ranges in grandchild_vec)
auto* child_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(child_vec);
for (int64_t i = 0; i < nrows; ++i) {
child_entries[child_offset + i].offset = grandchild_offset + i * ncols;
child_entries[child_offset + i].length = ncols;
elog(LOG,
" child_entries[%zu]: offset=%zu, length=%zu",
child_offset + i,
child_entries[child_offset + i].offset,
child_entries[child_offset + i].length);
}
// Set up output_vector list entry (pointing to range in child_vec)
auto* output_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector);
output_entries[row_in_batch].offset = child_offset;
output_entries[row_in_batch].length = nrows;
elog(LOG,
" output_entries[%zu]: offset=%zu, length=%zu",
row_in_batch,
output_entries[row_in_batch].offset,
output_entries[row_in_batch].length);
} else {
// String or bytea arrays with 2D structure
auto* child_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(child_vec);
auto* output_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector);
for (int64_t i = 0; i < nrows; ++i) {
child_entries[child_offset + i].offset = grandchild_offset + i * ncols;
child_entries[child_offset + i].length = ncols;
for (int64_t j = 0; j < ncols; ++j) {
int64_t flat_idx = i * ncols + j;
auto elem = sample[flat_idx];
if constexpr (std::is_same_v<T, std::span<const uint8_t>>) {
auto value = elem.data();
auto* data_ptr = duckdb::FlatVector::GetData<duckdb::string_t>(grandchild_vec);
data_ptr[grandchild_offset + flat_idx] = duckdb::StringVector::AddStringOrBlob(
grandchild_vec, reinterpret_cast<const char*>(value.data()), value.size());
} else {
auto elem_view = base::string_view_cast<const unsigned char>(elem.data());
auto* data_ptr = duckdb::FlatVector::GetData<duckdb::string_t>(grandchild_vec);
data_ptr[grandchild_offset + flat_idx] =
add_string(grandchild_vec, elem_view.data(), elem_view.size());
}
}
}
output_entries[row_in_batch].offset = child_offset;
output_entries[row_in_batch].length = nrows;
}
});
}
void set_1d_array_output(duckdb::Vector& output_vector,
duckdb::idx_t row_in_batch,
nd::array&& sample,
int64_t array_len)
{
auto& list_entry_vec = duckdb::ListVector::GetEntry(output_vector);
auto offset = duckdb::ListVector::GetListSize(output_vector);
// Reserve space for array elements
duckdb::ListVector::Reserve(output_vector, offset + array_len);
duckdb::ListVector::SetListSize(output_vector, offset + array_len);
// Fill array elements
nd::switch_dtype(sample.dtype(), [&]<typename T>() {
if constexpr (std::is_arithmetic_v<T>) {
auto* list_data = duckdb::FlatVector::GetData<T>(list_entry_vec);
const T* array_data = reinterpret_cast<const T*>(sample.data().data());
std::memcpy(list_data + offset, array_data, static_cast<size_t>(array_len) * sizeof(T));
} else if constexpr (std::is_same_v<T, std::span<const uint8_t>>) {
auto* list_data = duckdb::FlatVector::GetData<duckdb::string_t>(list_entry_vec);
for (int64_t i = 0; i < array_len; ++i) {
auto value = sample[i].data();
list_data[offset + i] = duckdb::StringVector::AddStringOrBlob(
list_entry_vec, reinterpret_cast<const char*>(value.data()), value.size());
}
} else {
// String array
auto* list_data = duckdb::FlatVector::GetData<duckdb::string_t>(list_entry_vec);
for (int64_t i = 0; i < array_len; ++i) {
auto elem = sample[i];
auto elem_view = base::string_view_cast<const unsigned char>(elem.data());
list_data[offset + i] = add_string(list_entry_vec, elem_view.data(), elem_view.size());
}
}
});
// Set list entry metadata
auto& list_data = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector)[row_in_batch];
list_data.offset = offset;
list_data.length = array_len;
}
// General N-dimensional array output (for 3D+ arrays)
// Uses a simplified approach: for 3D arrays, just call set_2d_array_output for each "page"
void set_nd_array_output(duckdb::Vector& output_vector,
duckdb::idx_t row_in_batch,
nd::array&& sample,
const icm::shape& array_shape)
{
auto ndim = array_shape.size();
if (ndim == 3) {
// 3D array: treat as array of 2D arrays
auto num_pages = array_shape[0];
auto nrows = array_shape[1];
auto ncols = array_shape[2];
// Get the child vector (type: LIST(LIST(LIST(T))))
auto& child_vec = duckdb::ListVector::GetEntry(output_vector);
auto child_offset = duckdb::ListVector::GetListSize(output_vector);
// Reserve space for num_pages elements in the top-level list
duckdb::ListVector::Reserve(output_vector, child_offset + num_pages);
duckdb::ListVector::SetListSize(output_vector, child_offset + num_pages);
// Process each page (2D slice)
auto* child_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector);
for (int64_t page = 0; page < num_pages; ++page) {
auto page_array = sample[page];
auto page_offset = duckdb::ListVector::GetListSize(child_vec);
set_2d_array_output(child_vec, child_offset + page, std::move(page_array), nrows, ncols);
}
// Set up the top-level list entry
auto* output_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector);
output_entries[row_in_batch].offset = child_offset;
output_entries[row_in_batch].length = num_pages;
} else {
// For 4D+ arrays, use recursive decomposition
// Treat as array of (N-1)D arrays
auto first_dim_size = array_shape[0];
auto& child_vec = duckdb::ListVector::GetEntry(output_vector);
auto child_offset = duckdb::ListVector::GetListSize(output_vector);
duckdb::ListVector::Reserve(output_vector, child_offset + first_dim_size);
duckdb::ListVector::SetListSize(output_vector, child_offset + first_dim_size);
// Build sub-shape (remove first dimension)
icm::shape sub_shape(array_shape.data() + 1, array_shape.data() + array_shape.size());
for (int64_t i = 0; i < first_dim_size; ++i) {
auto sub_array = sample[i];
set_nd_array_output(child_vec, child_offset + i, std::move(sub_array), sub_shape);
}
auto* output_entries = duckdb::FlatVector::GetData<duckdb::list_entry_t>(output_vector);
output_entries[row_in_batch].offset = child_offset;
output_entries[row_in_batch].length = first_dim_size;
}
}
void set_array_column_output(unsigned output_column_id, nd::array&& samples)
{
auto& output_vector = output_.data[output_column_id];
for (duckdb::idx_t row_in_batch = 0; row_in_batch < output_.size(); ++row_in_batch) {
auto sample = samples[row_in_batch];
if (sample.is_none()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
continue;
}
auto array_shape = sample.shape();
if (array_shape.size() == 0 || array_shape[0] == 0) {
set_empty_array_output(output_vector, row_in_batch);
} else if (array_shape.size() == 1) {
int64_t array_len = array_shape[0];
set_1d_array_output(output_vector, row_in_batch, std::move(sample), array_len);
} else if (array_shape.size() == 2) {
int64_t nrows = array_shape[0];
int64_t ncols = array_shape[1];
set_2d_array_output(output_vector, row_in_batch, std::move(sample), nrows, ncols);
} else {
// 3D+ arrays: use the general N-dimensional handler
set_nd_array_output(output_vector, row_in_batch, std::move(sample), array_shape);
}
}
}
void set_column_output(unsigned output_column_id, nd::array&& samples)
{
const auto col_idx = global_state_.column_ids[output_column_id];
const bool is_array = is_array_type(col_idx);
const bool is_uuid = is_uuid_type(col_idx);
if (!is_array && !is_uuid && samples.dtype() == nd::dtype::string) {
set_string_column_output(output_column_id, std::move(samples));
} else if (!is_array && is_uuid) {
set_uuid_column_output(output_column_id, std::move(samples));
} else if (!is_array) {
set_non_array_column_output(output_column_id, std::move(samples));
} else {
set_array_column_output(output_column_id, std::move(samples));
}
}
void set_streaming_column_output(unsigned output_column_id, int64_t current_row)
{
const auto col_idx = global_state_.column_ids[output_column_id];
if (is_array_type(col_idx)) {
throw duckdb::InternalException("Array columns should not have streamers");
}
const bool is_uuid = is_uuid_type(col_idx);
const auto batch_size = output_.size();
auto& td = bind_data_.table_data;
auto& output_vector = output_.data[output_column_id];
auto col_view = td.get_column_view(col_idx);
nd::switch_dtype(col_view->dtype(), [&]<typename T>() {
if constexpr (std::is_arithmetic_v<T>) {
auto att_type = td.get_atttypid(col_idx);
auto* value_ptr = td.get_streamers().value_ptr<T>(col_idx, current_row);
if (att_type == VARCHAROID || att_type == CHAROID || att_type == BPCHAROID) {
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
for (duckdb::idx_t row_in_batch = 0; row_in_batch < batch_size; ++row_in_batch) {
duckdb_data[row_in_batch] =
add_string(output_vector, reinterpret_cast<const char*>(value_ptr + row_in_batch), 1);
}
return;
}
std::memcpy(duckdb::FlatVector::GetData<T>(output_vector),
value_ptr,
static_cast<size_t>(batch_size) * sizeof(T));
} else if constexpr (std::is_same_v<T, nd::dict>) {
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
for (duckdb::idx_t row_in_batch = 0; row_in_batch < batch_size; ++row_in_batch) {
const int64_t row_idx = current_row + row_in_batch;
auto sample = td.get_streamers().get_sample(col_idx, row_idx);
if (sample.is_none()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
} else {
auto json_str = sample.dict_value(0).serialize();
duckdb_data[row_in_batch] = add_string(output_vector, json_str.data(), json_str.size());
}
}
} else {
for (duckdb::idx_t row_in_batch = 0; row_in_batch < batch_size; ++row_in_batch) {
const int64_t row_idx = current_row + row_in_batch;
auto value = td.get_streamers().value<std::string_view>(col_idx, row_idx);
// workaround. value is not always remain valid. Trying to make a copy as soon as possible.
// Most likely due to nd::array temporary object destruction.
std::string str_value(value);
if (is_uuid) {
// Treat empty string as NULL for UUID columns
if (str_value.empty()) {
duckdb::FlatVector::SetNull(output_vector, row_in_batch, true);
} else {
duckdb::hugeint_t uuid_value;
if (!duckdb::UUID::FromString(str_value, uuid_value)) {
elog(ERROR, "Failed to parse UUID string: %s", str_value.c_str());
}
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::hugeint_t>(output_vector);
duckdb_data[row_in_batch] = uuid_value;
}
} else {
auto* duckdb_data = duckdb::FlatVector::GetData<duckdb::string_t>(output_vector);
duckdb_data[row_in_batch] = add_string(output_vector, str_value.data(), str_value.size());
}
}
}
});
}
void do_index_search()
{
if (!has_index_search()) {
return;
}
std::lock_guard lock(global_state_.index_search_mutex);
if (is_index_search_done()) {
return;
}
icm::vector<async::promise<icm::roaring>> promises;
for (auto& is : global_state_.index_searchers) {
promises.push_back(is().then_any([](icm::vector<icm::roaring>&& results) {
ASSERT(results.size() == 1);
return std::move(results.front());
}));
}
auto combined_promise = async::combine(std::move(promises)).then_any([](icm::vector<icm::roaring>&& results) {
ASSERT(!results.empty());
icm::roaring& combined = results[0];
for (size_t i = 1; i < results.size(); ++i) {
combined &= results[i];
}
return std::move(combined);
});
auto indices = combined_promise.get_future().get();
icm::vector<int64_t> indices_vec;
indices_vec.reserve(indices.cardinality());
for (auto x : indices) {
indices_vec.push_back(x);
}
global_state_.index_search_result = heimdall_common::create_filtered_dataset(
bind_data_.table_data.get_read_only_dataset(), icm::index_mapping_t<int64_t>::list(std::move(indices_vec)));
}
int64_t next_chunk()
{
int64_t num_rows = -1;
if (has_index_search()) {
ASSERT(is_index_search_done());
num_rows = global_state_.index_search_result->num_rows();
} else {
num_rows = bind_data_.table_data.num_rows();
}
// Determine batch size (DuckDB's standard vector size is 2048)
constexpr duckdb::idx_t DUCKDB_VECTOR_SIZE = 2048;
auto current_row = global_state_.current_row.fetch_add(DUCKDB_VECTOR_SIZE);
if (current_row >= num_rows) {
output_.SetCardinality(0);
current_row = -1;
} else {
const duckdb::idx_t chunk_size = std::min<duckdb::idx_t>(DUCKDB_VECTOR_SIZE, num_rows - current_row);
output_.SetCardinality(chunk_size);
}
return current_row;
}
auto request_range_and_set_column_output(heimdall::column_view_ptr cv, unsigned column_id, int64_t start_row)
{
const auto end_row = start_row + output_.size();
return async::run_on_main([cv, start_row, end_row]() {
return cv->request_range(start_row, end_row, {});
})
.then([this, column_id](nd::array&& samples) {
set_column_output(column_id, std::move(samples));
});
}
void do_scan()
{
do_index_search();
const auto current_row = next_chunk();
if (current_row < 0) {
return;
}
ASSERT(output_.ColumnCount() == global_state_.column_ids.size());
// Pre-trigger parallel batch initialization for all streaming columns.
// Without this, each column's batch download would block sequentially,
// serializing I/O waits. This overlaps all column batch downloads.
if (!has_index_search() && pg::eager_batch_prefetch) {
std::vector<int32_t> streaming_cols;
for (unsigned i = 0; i < global_state_.column_ids.size(); ++i) {
const auto col_idx = global_state_.column_ids[i];
if (bind_data_.table_data.is_column_requested(col_idx) &&
bind_data_.table_data.column_has_streamer(col_idx)) {
streaming_cols.push_back(col_idx);
}
}
bind_data_.table_data.get_streamers().prefetch_batches_for_row(streaming_cols, current_row);
}
icm::vector<async::promise<void>> column_promises;
// Fill output vectors column by column using table_data streamers
for (unsigned i = 0; i < global_state_.column_ids.size(); ++i) {
const auto col_idx = global_state_.column_ids[i];
ASSERT(col_idx >= 0 && col_idx < bind_data_.table_data.num_columns());
// Example query, when column is not referenced but requested by duckdb:
// SELECT COUNT(*) FROM table_name;
if (!bind_data_.table_data.is_column_requested(col_idx)) {
continue;
}
auto& output_vector = output_.data[i];
output_vector.SetVectorType(duckdb::VectorType::FLAT_VECTOR);
auto& mask = duckdb::FlatVector::Validity(output_vector);
if (has_index_search()) {
auto cv = ((*global_state_.index_search_result)[col_idx]).shared_from_this();
column_promises.emplace_back(request_range_and_set_column_output(cv, i, current_row));
} else if (bind_data_.table_data.column_has_streamer(col_idx)) {
set_streaming_column_output(i, current_row);
} else {
auto cv = bind_data_.table_data.get_column_view(col_idx);
column_promises.emplace_back(request_range_and_set_column_output(cv, i, current_row));
}
}
async::combine(std::move(column_promises)).get_future().get();
}
};