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- ANALYZE Statement 12285
- The ANALYZE statement recomputes the statistics on DuckDB's tables. Usage The statistics recomputed by the ANALYZE statement are only used for join order optimization . It is therefore recommended to recompute these statistics for improved
...join orders, especially after performing large updates (inserts and/or deletes). To recompute the statistics, run: ANALYZE;... - https://man.mtool.work/duckdb/2.0/sql/statements/analyze.html
- Troubleshooting 11471
- This page contains solutions to common problems reported by users. If you have platform-specific issues, make sure you also consult the troubleshooting guide for your platform such as the one for Linux builds . The Build Runs Out of Memory
...use out-of-memory issues on systems with limited resources. These issues have also been reported to occur on Alpine Linux, especially on machines with limited resources. Solution: Avoid using Ninja by setting the Makefile generator to empty via GEN= : GEN=... - https://man.mtool.work/duckdb/2.0/dev/building/troubleshooting.html
- Benchmarks 10241
- For several of the recommendations in our performance guide, we use microbenchmarks to back up our claims. For these benchmarks, we use datasets from the TPC-H benchmark and the LDBC Social Network Benchmark's BI workload . Datasets We use
...n the benchmark are generated with the DuckDB tpch extension . A Note on Benchmarks Running fair benchmarks is difficult , especially when performing system-to-system comparison. When running benchmarks on DuckDB, please make sure you are using the latest... - https://man.mtool.work/duckdb/2.0/guides/performance/benchmarks.html
- File Formats 10241
- Handling Parquet Files DuckDB has advanced support for Parquet files, which includes directly querying Parquet files . When deciding on whether to query these files directly or to first load them to the database, you need to consider severa
...as the hyperloglog statistics that Parquet files do not have. These improve the accuracy of cardinality estimates, and are especially important if the queries contain a large number of join operators. Tip. If you find that DuckDB produces a suboptimal join...ed in the filter condition. DuckDB will only need to read the folders and files that meet the filter criteria. This can be especially helpful when querying remote files. More Tips on Reading and Writing Parquet Files For tips on reading and writing Parquet... - https://man.mtool.work/duckdb/2.0/guides/performance/file_formats.html
- My Workload Is Slow 9825
- If you find that your workload in DuckDB is slow, we recommend performing the following checks. More detailed instructions are linked for each point. Do you have enough memory? DuckDB works best if you have 1-4 GB memory per thread . Is you
...tal RAM using SET memory_limit = '...'; . While this sounds counter-intuitive, it can sometimes improve query performance, especially in memory-constrained environments where other processes are likely using more than 20% of the total system memory. Are yo... - https://man.mtool.work/duckdb/2.0/guides/performance/my_workload_is_slow.html
- jemalloc 9825
- On supported platforms, DuckDB replaces the system's memory allocator with jemalloc . jemalloc is statically linked into DuckDB and cannot be installed or loaded during runtime. For technical reasons, we used to distribute jemalloc as an ex
...y by the foreground threads. This improves allocation performance, and should be noticeable in allocation-heavy workloads, especially on many-core CPUs.... - https://man.mtool.work/duckdb/2.0/internals/jemalloc.html
- JSON Format Settings 8612
- The JSON extension can attempt to determine the format of a JSON file when setting format to auto . Here are some example JSON files and the corresponding format settings that should be used. In each of the below cases, the format setting w
...= false); json {'key1': value1, 'key2': value1} {'key1': value2, 'key2': value2} {'key1': value3, 'key2': value3} This is especially useful if we have non-object JSON, for example, arrays.json : [1, 2, 3] [4, 5, 6] [7, 8, 9] SELECT * FROM read_json('array... - https://man.mtool.work/duckdb/2.0/data/json/format_settings.html
- JSON Overview 8612
- DuckDB supports SQL functions that are useful for reading values from existing JSON and creating new JSON data. JSON is supported with the json extension which is shipped with most DuckDB distributions and is auto-loaded on first use. If yo
...arrays (or other serializable values). While it is not a very efficient format for tabular data, it is very commonly used, especially as a data interchange format. JSONPath and JSON Pointer Syntax DuckDB implements multiple interfaces for JSON extraction:... - https://man.mtool.work/duckdb/2.0/data/json/overview.html
- Environment 7780
- The environment where DuckDB is run has an obvious impact on performance. This page focuses on the effects of the hardware configuration and the operating system used. Hardware Configuration CPU DuckDB's officially supported architectures a
...ased mode is designed to work best with SSD and NVMe disks. While HDDs are supported, they will result in low performance, especially for write operations. Disk-based vs. in-memory storage. Counter-intuitively, using a disk-based DuckDB instance can be fas... - https://man.mtool.work/duckdb/2.0/guides/performance/environment.html
- Schema 7780
- Types It is important to use the correct type for encoding columns (e.g., BIGINT , DATE , DATETIME ). While it is always possible to use string types ( VARCHAR , etc.) to encode more specific values, this is not recommended. Strings use mor
...GINT 70368755640078 1.2 s BIGINT VARCHAR '70368755640078' 2.1 s Bestpractice Avoid representing numeric values as strings, especially if you intend to perform e.g., join operations on them. Encoding Repeated Strings as a Dimension Table When a wide string... - https://man.mtool.work/duckdb/2.0/guides/performance/schema.html
DuckDB 2.0 Documentation / man.mtool.work