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- EXPLAIN: Inspect Query Plans 13239
- EXPLAIN SELECT * FROM tbl; The EXPLAIN statement displays the physical plan, i.e., the query plan that will get executed, and is enabled by prepending the query with EXPLAIN . The physical plan is a tree of operators that are executed in a
...ngs are available: The default setting. Only shows the physical plan. SET explain_output = 'physical_only'; Shows only the optimized plan. SET explain_output = 'optimized_only'; Shows both the physical and optimized plans. SET explain_output = 'all'; See... - https://man.mtool.work/duckdb/2.0/guides/meta/explain.html
- Profiling Queries 12147
- DuckDB supports profiling queries via the EXPLAIN and EXPLAIN ANALYZE statements. EXPLAIN To see the query plan of a query without executing it, run: EXPLAIN ⟨query⟩; The output of EXPLAIN contains the estimated cardinalities for each opera
...tor. EXPLAIN (SQL) New As of DuckDB 2.0, EXPLAIN (SQL) renders the optimized logical plan back as an executable DuckDB SQL string instead of as a plan tree: sql EXPLAIN (SQL) SELECT 1 + 2 AS answer;...explain_key explain_value sql SELECT CAST(3 AS INTEGER) AS answer Because the output is the optimized plan, it can differ substantially from the input query (for example through join reordering, constant folding, or subquery... - https://man.mtool.work/duckdb/2.0/sql/statements/profiling.html
- Integration with Polars 10830
- Polars is a DataFrames library built in Rust with bindings for Python and Node.js. It uses Apache Arrow's columnar format as its memory model. DuckDB can read Polars DataFrames and convert query results to Polars DataFrames. It does this in
...it UNION ALL SELECT 2, 'apple' UNION ALL SELECT 3, 'mango'""" ).pl(lazy=True) print(df) naive plan: (run LazyFrame.explain(optimized=True) to see the optimized plan) PYTHON SCAN [] PROJECT */2 COLUMNS A relation also implements the Arrow PyCapsule interfa... - https://man.mtool.work/duckdb/2.0/guides/python/polars.html
- Regular Expressions 8629
- DuckDB offers pattern matching operators ( LIKE , SIMILAR TO , GLOB ), as well as support for regular expressions via functions. Regular Expression Syntax DuckDB uses the RE2 library as its regular expression engine. For the regular express
...LECT regexp_matches(E'hello\nworld', 'hello.world', 's'); -- true Using regexp_matches The regexp_matches operator will be optimized to the LIKE operator when possible. To achieve best performance, the 'c' option (case-sensitive matching) should be passed...if applicable. Note that by default the RE2 library doesn't match the . character to newline. Original Optimized equivalent regexp_matches('hello world', '^hello', 'c') prefix('hello world', 'hello') regexp_matches('hello world', 'worl... - https://man.mtool.work/duckdb/2.0/sql/functions/regular_expressions.html
- Overview of DuckDB Internals 8404
- Tip For a detailed explanation of DuckDB internals, see the Design and Implementation of DuckDB Internals ("DiDi") library entry. On this page is a brief description of the internals of the DuckDB engine. Parser The parser converts a query
...zer After the logical planner has created the logical query tree, the optimizers are run over that query tree to create an optimized query plan. The following query optimizers are run: Expression Rewriter : Simplifies expressions, performs constant foldin... - https://man.mtool.work/duckdb/2.0/internals/overview.html
- Pragmas 8196
- The PRAGMA statement is a SQL extension adopted by DuckDB from SQLite. PRAGMA statements can be issued in a similar manner to regular SQL statements. PRAGMA commands may alter the internal state of the database engine, and can influence the
...show only the physical plan. The default configuration of EXPLAIN : SET explain_output = 'physical_only'; To only show the optimized query plan: SET explain_output = 'optimized_only'; To show all query plans: SET explain_output = 'all'; Profiling Enable P... - https://man.mtool.work/duckdb/2.0/configuration/pragmas.html
- Lance Extension 7971
- 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
... - https://man.mtool.work/duckdb/2.0/core_extensions/lance.html
- Building Configuration 7971
- Build Types DuckDB can be built in many different settings, most of these correspond directly to CMake but not all of them. release This build has been stripped of all the assertions and debug symbols and code, optimized for performance. de
... - https://man.mtool.work/duckdb/2.0/dev/building/build_configuration.html
- sqllogictest Introduction 7971
- For testing plain SQL, we use an extended version of the SQL logic test suite, adopted from SQLite . Every test is a single self-contained file located in the test/sql directory. To run tests located outside of the default test directory, s
...portant part of that is that it verifies that optimizers do not cause bugs in the query. It does this by running both an unoptimized and optimized version of the query, and verifying that the results of these queries are identical. Query verification is v...because it not only discovers bugs in optimizers, but also finds bugs in e.g., join implementations. This is because the unoptimized version will typically run using cross products instead. Because of this, query verification can be very slow to do when w... - https://man.mtool.work/duckdb/2.0/dev/sqllogictest/intro.html
- Execution Format 7971
- 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 defa... - https://man.mtool.work/duckdb/2.0/internals/vector.html
DuckDB 2.0 Documentation / man.mtool.work