Results of 1 - 10 of about 34 for Vector (0.004 sec.)
- Vectors 13501
- Vectors represent a horizontal slice of a column. They hold a number of values of a specific type, similar to an array. Vectors are the core data representation used in DuckDB. Vectors are typically stored within data chunks . The vector an
...ing for the highest performance. However, the interfaces are also difficult to use and care must be taken when using them. Vector Format Vectors are arrays of a specific data type. The logical type of a vector can be obtained using duckdb_vector_get_co...lumn_type . The type id of the logical type can then be obtained using duckdb_get_type_id . Vectors themselves do not have sizes. Instead, the parent data chunk has a size (that can be obtained through duckdb_data_chunk_g...et_size ). All vectors that belong to a data chunk have the same size. Primitive Types For primitive types, the underlying array can be obtained... - https://man.mtool.work/duckdb/2.0/clients/c/vector.html
- Complete API 12302
- This page contains the reference for DuckDB's C API. The reference contains several deprecation notices. These concern methods whose long-term availability is not guaranteed as they may be removed in the future. That said, DuckDB's develope
...ult , idx_t col , idx_t row ); Helpers void * duckdb_malloc ( size_t size ); void duckdb_free ( void * ptr ); idx_t duckdb_vector_size (); bool duckdb_string_is_inlined ( duckdb_string_t string ); uint32_t duckdb_string_t_length ( duckdb_string_t strin...data_chunk_reset ( duckdb_data_chunk chunk ); idx_t duckdb_data_chunk_get_column_count ( duckdb_data_chunk chunk ); duckdb_vector duckdb_data_chunk_get_vector ( duckdb_data_chunk chunk , idx_t col_idx ); idx_t duckdb_data_chunk_get_size ( duckdb_data_c...hunk chunk ); void duckdb_data_chunk_set_size ( duckdb_data_chunk chunk , idx_t size ); Vector Interface duckdb_vector duckdb_create_vector ( duckdb_logical_type type , idx_t capacity ); void duckdb_destroy_vector ( d... - https://man.mtool.work/duckdb/2.0/clients/c/api.html
- Execution Format 11296
- Vector is the container format used to store in-memory data during execution. DataChunk is a collection of Vectors, used for instance to represent a column list in a PhysicalProjection operator. Data Flow DuckDB uses a vectorized query exec
...ution model. All operators in DuckDB are optimized to work on Vectors of a fixed size. This fixed size is commonly referred to in the code as STANDARD_VECTOR_SIZE . The default STANDARD_VECTO...R_SIZE is 2048 tuples. Vector Format Vectors logically represent arrays that contain data of a single type. DuckDB supports different vector formats , w...pressed representation, and potentially allows for compressed execution throughout the system. Below the list of supported vector formats is shown. Flat Vectors Flat vectors are physically stored as a contiguous array, this is the standard uncompressed... - https://man.mtool.work/duckdb/2.0/internals/vector.html
- Data Chunks 10529
- Data chunks represent a horizontal slice of a table. They hold a number of vectors , that can each hold up to the VECTOR_SIZE rows. The vector size can be obtained through the duckdb_vector_size function and is configurable, but is usually
...set to 2048 . Data chunks and vectors are what DuckDB uses natively to store and represent data. For this reason, the data chunk interface is the most efficien...ware, however, that correctly interfacing with DuckDB using the data chunk API does require knowledge of DuckDB's internal vector format. Data chunks can be used in two manners: Reading Data : Data chunks can be obtained from query results using the du...ckdb_fetch_chunk method, or as input to a user-defined function. In this case, the vector methods can be used to read individual values. Writing Data : Data chunks can be created using duckdb_create_data_chunk .... - https://man.mtool.work/duckdb/2.0/clients/c/data_chunk.html
- Writing Tests 9155
- Development and Testing It is crucial that any new features that get added have correct tests that not only test the “happy path”, but also test edge cases and incorrect usage of the feature. In this section, we describe how DuckDB tests ar
...────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ test_vector_types Function The test_vector_types table function takes n arguments col1 , ..., coln and an optional BOOLEAN argument al...l_flat . The function generates a table with n columns test_vector , test_vector2 , ..., test_vectorn . In each row, each field contains values conforming to the type of their respective co...lumn. FROM test_vector_types(NULL::BIGINT); ┌──────────────────────┐ │ test_vector │ │ int64 │ ├──────────────────────┤ │ -9223372036854775808 │... - https://man.mtool.work/duckdb/2.0/dev/sqllogictest/writing_tests.html
- Vector Similarity Search Extension 8771
- The vss extension is an experimental extension for DuckDB that adds indexing support to accelerate vector similarity search queries using DuckDB's new fixed-size ARRAY type. See the announcement blog post and the “What's New in the Vector S
...RRAY column, use the CREATE INDEX statement with the USING HNSW clause. For example: INSTALL AND LOAD vss; CREATE TABLE my_vector_table (vec FLOAT[3]); INSERT INTO my_vector_table SELECT array_value(a, b, c) FROM range(1, 10) ra(a), range(1, 10) rb(b),...range(1, 10) rc(c); CREATE INDEX my_hnsw_index ON my_vector_table USING HNSW (vec); The index will then be used to accelerate queries that use an ORDER BY clause evaluating one of th...e supported distance metric functions against the indexed columns and a constant vector, followed by a LIMIT clause. For example: SELECT * FROM my_vector_table ORDER BY array_distance(vec, [1, 2, 3]::FLOAT[3])... - https://man.mtool.work/duckdb/2.0/core_extensions/vss.html
- Write User Defined Functions 8723
- Overview The JDBC driver can register user-defined functions (UDFs) written in Java, including scalar functions and table functions. This page covers building and registering both, from the simple functional-interface overloads to the vector
...eption . Registration-time problems, such as an undefined return type or an invalid type declaration, throw SQLException . Vectorized Scalar Functions The examples above process one value per call. To process a whole batch of rows at once, register a D...uckDBScalarFunction with withVectorizedFunction() . The callback receives the input as a DuckDBDataChunkReader (up to 2,048 rows) and writes results into a Du...ckDBWritableVector . Read each input column with input.vector(columnIndex) , iterate the row indices with input.stream() , and write each res... - https://man.mtool.work/duckdb/2.0/clients/java/functions.html
- Handle Results 8516
- Overview Beyond the standard JDBC ResultSet , the DuckDB driver can hand results to Apache Arrow , stream large results instead of materializing them, and expose raw columnar data chunks. This page covers each of these result-handling optio
...s an Arrow stream from a query result and consumes it using the Java Arrow bindings. Each batch is loaded in turn, and its vectors are read from the VectorSchemaRoot . import org.apache.arrow.memory.RootAllocator; import org.apache.arrow.vector.ipc.Arr...(ArrowReader) resultset.arrowExportStream(allocator, 256)) { while (reader.loadNextBatch()) { System.out.println(reader.getVectorSchemaRoot().getVector("generate_series")); } } } Arrow Import The following example consumes an Arrow stream produced by t....c.ArrowArrayStream; import org.apache.arrow.c.Data; import org.apache.arrow.memory.RootAllocator; import org.apache.arrow.vector.ipc.ArrowStreamReader; import org.duckdb.DuckDBConnection; import org.duckdb.DuckDBResultSet; // Arrow binding try (var al... - https://man.mtool.work/duckdb/2.0/clients/java/result_handling.html
- Write User Defined Functions 8196
- Overview The Rust client can register user-defined functions written in Rust: scalar functions with the vscalar feature and table functions with the vtab feature. Both operate on DuckDB's columnar data chunks, so a single call processes a b
...the crate's vscalar example . It reads the single BIGINT argument as a slice of i64 and writes each result into the output vector: use duckdb::{ Connection, Result, core::{DataChunkHandle, LogicalTypeHandle, LogicalTypeId}, vscalar::{ScalarFunctionSign...ature, VScalar}, vtab::arrow::WritableVector, }; struct AddOne; impl VScalar for AddOne { // No per-function state is needed. type State = (); fn invoke( _: &Self::Sta...te, input: &mut DataChunkHandle, output: &mut dyn WritableVector, ) -> Result<(), Box<dyn std::error::Error>> { let len = input.len(); let src = input.flat_vector(0); let src = unsafe { s... - https://man.mtool.work/duckdb/2.0/clients/rust/functions.html
- Lance Extension 7940
- The lance extension adds support for reading and writing Lance tables. Lance is a modern lakehouse format optimized for ML/AI workloads, with native cloud storage support. Installing and Loading You can install the lance extension from Duck
...id, 'a'::VARCHAR AS s UNION ALL SELECT 2::BIGINT AS id, 'b'::VARCHAR AS s; SELECT count(*) FROM lance_ns.main.my_dataset; Vector Search -- Search a vector column, returning distances in `_distance` (smaller is closer) SELECT id, label, _distance FROM...lance_vector_search( '⟨path/to/dataset.lance⟩', 'vec', [0.1, 0.2, 0.3, 0.4]::FLOAT[4], k = 5, prefilter = true ) ORDER BY _distance ASC..., k = 10, prefilter = true ) ORDER BY _score DESC; See the SQL reference for full parameter documentation . Hybrid Search (Vector + FTS) -- Combine vector and text scores, returning `_hybrid_score` in addition to `_distance` / `_score` SELECT id, _hybr... - https://man.mtool.work/duckdb/2.0/core_extensions/lance.html
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