Metadata caching

cpp/arcticdb/CMakeLists.txt

@@ -464,7 +464,7 @@ set(arcticdb_srcs
         version/version_utils.cpp
         version/symbol_list.cpp
         version/version_map_batch_methods.cpp
-        version/symbol_metadata.hpp version/metadata_cache.hpp util/frame_adapter.hpp)
+        version/symbol_metadata.hpp version/metadata_cache.hpp util/frame_adapter.hpp version/metadata_cache.cpp version/symbol_metadata.cpp)
 
 if(${ARCTICDB_INCLUDE_ROCKSDB})
     list (APPEND arcticdb_srcs

cpp/arcticdb/async/async_store.hpp

@@ -120,6 +120,7 @@ entity::VariantKey write_sync(
     const StreamId &stream_id,
     IndexValue start_index,
     IndexValue end_index,
+    timestamp creation_ts,
     SegmentInMemory &&segment) override {
 
     util::check(segment.descriptor().id() == stream_id,
@@ -128,12 +129,23 @@ entity::VariantKey write_sync(
                 segment.descriptor().id());
 
     auto encoded = EncodeAtomTask{
-        key_type, version_id, stream_id, start_index, end_index, current_timestamp(),
+        key_type, version_id, stream_id, start_index, end_index, creation_ts,
         std::move(segment), codec_, encoding_version_
     }();
     return WriteSegmentTask{library_}(std::move(encoded));
 }
 
+entity::VariantKey write_sync(
+    stream::KeyType key_type,
+    VersionId version_id,
+    const StreamId &stream_id,
+    IndexValue start_index,
+    IndexValue end_index,
+    SegmentInMemory &&segment) override {
+
+    return write_sync(key_type, version_id, stream_id, start_index, end_index, current_timestamp(), std::move(segment));
+}
+
 entity::VariantKey write_sync(PartialKey pk, SegmentInMemory &&segment) override {
     return write_sync(pk.key_type, pk.version_id, pk.stream_id, pk.start_index, pk.end_index, std::move(segment));
 }
@@ -157,7 +169,7 @@ void write_compressed_sync(storage::KeySegmentPair &&ks) override {
 
 folly::Future<entity::VariantKey> update(const entity::VariantKey &key,
                                          SegmentInMemory &&segment,
-                                         storage::UpdateOpts opts) override {
+                                         storage::StorageUpdateOptions opts) override {
     auto stream_id = variant_key_id(key);
     util::check(segment.descriptor().id() == stream_id,
                 "Descriptor id mismatch in variant key {} != {}",

cpp/arcticdb/async/tasks.hpp

@@ -183,9 +183,9 @@ struct WriteSegmentTask : BaseTask {
 
 struct UpdateSegmentTask : BaseTask {
     std::shared_ptr<storage::Library> lib_;
-    storage::UpdateOpts opts_;
+    storage::StorageUpdateOptions opts_;
 
-    explicit UpdateSegmentTask(std::shared_ptr<storage::Library> lib, storage::UpdateOpts opts) :
+    explicit UpdateSegmentTask(std::shared_ptr<storage::Library> lib, storage::StorageUpdateOptions opts) :
         lib_(std::move(lib)),
         opts_(opts) {
     }

cpp/arcticdb/column_store/column.cpp

@@ -173,6 +173,7 @@ void Column::append_sparse_map(const util::BitMagic& bv, position_t at_row) {
 void Column::append(const Column& other, position_t at_row) {
     if (other.row_count() == 0)
         return;
+
     util::check(type() == other.type(), "Cannot append column type {} to column type {}", type(), other.type());
     const bool was_sparse = is_sparse();
     const bool was_empty = empty();

cpp/arcticdb/entity/native_tensor.hpp

@@ -77,7 +77,8 @@ struct NativeTensor {
     dt_(other.dt_),
     elsize_(other.elsize_),
     ptr(other.ptr),
-    expanded_dim_(other.expanded_dim_){
+    expanded_dim_(other.expanded_dim_),
+    native_type_(other.native_type_){
         for (ssize_t i = 0; i < std::min(MaxDimensions, ndim_); ++i)
             shapes_[i] = other.shapes_[i];
 
@@ -94,6 +95,7 @@ struct NativeTensor {
         swap(left.elsize_, right.elsize_);
         swap(left.ptr, right.ptr);
         swap(left.expanded_dim_, right.expanded_dim_);
+        swap(left.native_type_, right.native_type_);
         for(ssize_t i = 0; i < MaxDimensions; ++i) {
             swap(left.shapes_[i], right.shapes_[i]);
             swap(left.strides_[i], right.strides_[i]);
@@ -134,6 +136,14 @@ struct NativeTensor {
         return (&(reinterpret_cast<const T *>(ptr)[signed_pos]));
     }
 
+    void set_is_native_type() {
+        native_type_ = true;
+    }
+
+    bool is_native_type() const {
+        return native_type_;
+    }
+
     // returns number of elements, not bytesize
     [[nodiscard]] ssize_t size() const {
         return calc_elements(shape(), ndim());
@@ -142,17 +152,18 @@ struct NativeTensor {
     NativeTensor &request() { return *this; }
 
     util::MagicNum<'T','n','s','r'> magic_;
-    int64_t nbytes_;
-    int ndim_;
+    int64_t nbytes_ = 0;
+    int ndim_ = 0;
     StrideContainer strides_ = {};
     StrideContainer shapes_ = {};
     DataType dt_;
-    stride_t elsize_;
-    const void *ptr;
+    stride_t elsize_ = 0;
+    const void *ptr = nullptr;
     /// @note: when iterating strides and shapes we should use the ndim as it is the dimension reported by the
     /// API providing the strides and shapes arrays, expanded_dim is what ArcticDB thinks of the tensor and using it
     /// can lead to out of bounds reads from strides and shapes.
-    int expanded_dim_;
+    int32_t expanded_dim_ = 0;
+    bool native_type_ = false;
 };
 
 template <ssize_t> ssize_t byte_offset_impl(const stride_t* ) { return 0; }

cpp/arcticdb/pipeline/frame_utils.hpp

@@ -95,6 +95,7 @@ RawType* flatten_tensor(
 
 template<typename Aggregator>
 std::optional<convert::StringEncodingError> aggregator_set_data(
+    const pipelines::InputTensorFrame& frame,
     const TypeDescriptor& type_desc,
     const entity::NativeTensor& tensor,
     Aggregator& agg,
@@ -146,28 +147,45 @@ std::optional<convert::StringEncodingError> aggregator_set_data(
                 column.allocate_data(rows_to_write * sizeof(entity::position_t));
                 auto out_ptr = reinterpret_cast<entity::position_t*>(column.buffer().data());
                 auto& string_pool = agg.segment().string_pool();
-                for (size_t s = 0; s < rows_to_write; ++s, ++ptr_data) {
-                    if (*ptr_data == none.ptr()) {
-                        *out_ptr++ = not_a_string();
-                    } else if(is_py_nan(*ptr_data)){
-                        *out_ptr++ = nan_placeholder();
-                    } else {
-                        if constexpr (is_utf_type(slice_value_type(dt))) {
-                            wrapper_or_error = convert::py_unicode_to_buffer(*ptr_data, scoped_gil_lock);
+                if(tensor.is_native_type()) {
+                    auto offset_data = reinterpret_cast<StringPool::offset_t*>(data);
+                    offset_data += row;
+                    auto input_string_pool = frame.string_pool();
+                    util::check(static_cast<bool>(input_string_pool) || frame.empty(), "Expected string pool for native sequence types");
+                    for (size_t s = 0; s < rows_to_write; ++s, ++ptr_data) {
+                        if (*offset_data == not_a_string() || *offset_data == nan_placeholder()) {
+                            *out_ptr++ =*offset_data;
                         } else {
-                            wrapper_or_error = convert::pystring_to_buffer(*ptr_data, false);
-                        }
-                        // Cannot use util::variant_match as only one of the branches would have a return type
-                        if (std::holds_alternative<convert::PyStringWrapper>(wrapper_or_error)) {
-                            convert::PyStringWrapper wrapper(std::move(std::get<convert::PyStringWrapper>(wrapper_or_error)));
-                            const auto offset = string_pool.get(wrapper.buffer_, wrapper.length_);
+                            const auto view = input_string_pool->get_view(reinterpret_cast<StringPool::offset_t>(*offset_data));
+                            const auto offset = string_pool.get(view);
                             *out_ptr++ = offset.offset();
-                        } else if (std::holds_alternative<convert::StringEncodingError>(wrapper_or_error)) {
-                            auto error = std::get<convert::StringEncodingError>(wrapper_or_error);
-                            error.row_index_in_slice_ = s;
-                            return std::optional<convert::StringEncodingError>(error);
+                        }
+                    }
+                } else {
+                    for (size_t s = 0; s < rows_to_write; ++s, ++ptr_data) {
+                        if (*ptr_data == none.ptr()) {
+                            *out_ptr++ = not_a_string();
+                        } else if (is_py_nan(*ptr_data)) {
+                            *out_ptr++ = nan_placeholder();
                         } else {
-                            internal::raise<ErrorCode::E_ASSERTION_FAILURE>("Unexpected variant alternative");
+                            if constexpr (is_utf_type(slice_value_type(dt))) {
+                                wrapper_or_error = convert::py_unicode_to_buffer(*ptr_data, scoped_gil_lock);
+                            } else {
+                                wrapper_or_error = convert::pystring_to_buffer(*ptr_data, false);
+                            }
+                            // Cannot use util::variant_match as only one of the branches would have a return type
+                            if (std::holds_alternative<convert::PyStringWrapper>(wrapper_or_error)) {
+                                convert::PyStringWrapper
+                                    wrapper(std::move(std::get<convert::PyStringWrapper>(wrapper_or_error)));
+                                const auto offset = string_pool.get(wrapper.buffer_, wrapper.length_);
+                                *out_ptr++ = offset.offset();
+                            } else if (std::holds_alternative<convert::StringEncodingError>(wrapper_or_error)) {
+                                auto error = std::get<convert::StringEncodingError>(wrapper_or_error);
+                                error.row_index_in_slice_ = s;
+                                return std::optional<convert::StringEncodingError>(error);
+                            } else {
+                                internal::raise<ErrorCode::E_ASSERTION_FAILURE>("Unexpected variant alternative");
+                            }
                         }
                     }
                 }

cpp/arcticdb/pipeline/index_utils.cpp

@@ -17,8 +17,7 @@ folly::Future<entity::AtomKey> write_index(
     TimeseriesDescriptor &&metadata,
     std::vector<SliceAndKey> &&sk,
     const IndexPartialKey &partial_key,
-    const std::shared_ptr<stream::StreamSink> &sink
-    ) {
+    const std::shared_ptr<stream::StreamSink> &sink) {
     auto slice_and_keys = std::move(sk);
     IndexWriter<IndexType> writer(sink, partial_key, std::move(metadata));
     for (const auto &slice_and_key : slice_and_keys) {

cpp/arcticdb/pipeline/input_tensor_frame.hpp

@@ -14,6 +14,10 @@
 #include <arcticdb/entity/types.hpp>
 #include <arcticdb/util/flatten_utils.hpp>
 
+namespace arcticdb {
+class StringPool;
+}
+
 namespace arcticdb::pipelines {
 
 using namespace arcticdb::entity;
@@ -39,6 +43,15 @@ struct InputTensorFrame {
     ssize_t num_rows = 0;
     mutable ssize_t offset = 0;
     mutable bool bucketize_dynamic = 0;
+    std::shared_ptr<StringPool> string_pool_;
+
+    void set_string_pool(std::shared_ptr<StringPool> string_pool) {
+        string_pool_ = std::move(string_pool);
+    }
+
+    const std::shared_ptr<StringPool>& string_pool() const {
+        return string_pool_;
+    }
 
     void set_offset(ssize_t off) const {
         offset = off;