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- Environment 13848
- 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
...uire 3-4 GB memory per thread. Larger-than-Memory Workloads DuckDB can process larger-than-memory workloads by spilling to disk. This is possible thanks to out-of-core support for grouping, joining, sorting and windowing operators. Note that larger-t...han-memory workloads can be processed both in persistent mode and in in-memory mode as DuckDB still spills to disk in both modes. Local Disk Disk type. DuckDB's disk-based 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 faster than an in-memory insta... - https://man.mtool.work/duckdb/2.0/guides/performance/environment.html
- Copying an In-Memory Database to a File 11909
- Imagine the following situation – you started DuckDB in in-memory mode but would like to persist the state of your database to disk. To achieve this, attach to a new disk-based database and use the COPY FROM DATABASE ... TO command : ATTACH
...'my_database.db'; COPY FROM DATABASE memory TO my_database; DETACH my_database; Ensure that the disk-based database file does not exist before attaching to it.... - https://man.mtool.work/duckdb/2.0/guides/snippets/copy_in-memory_database_to_fil...
- Tuning Workloads 10074
- DuckDB aims to perform well out of the box, so most workloads do not require any tuning. When tuning is worthwhile, there is no single configuration or magic number that is optimal for every workload: the right settings depend on what you a
...ble cores Row group sizing and the threads setting Parallelism Processing data larger than memory Configuring the spill-to-disk directory Larger-than-memory workloads Diagnosing a slow query Inspecting the query plan Profiling Running the same query...s section explains the prerequisites, scope, and known limitations of larger-than-memory processing in DuckDB. Spilling to Disk Larger-than-memory workloads are supported by spilling to disk. With the default configuration, DuckDB creates the ⟨databa...o the complex interplay of these operators. Some aggregate functions , such as string_agg() , do not support offloading to disk. Aggregate functions that use sorting are holistic, i.e., they need all inputs before the aggregation can start. As DuckDB... - https://man.mtool.work/duckdb/2.0/guides/performance/how_to_tune_workloads.html
- Connect 9589
- Connect or Create a Database To use DuckDB, you must first create a connection to a database. The exact syntax varies between the client APIs but it typically involves passing an argument to configure persistence. Since DuckDB 1.5.3, you ca
...h directs queries to a remote instance. Persistence DuckDB can operate in both persistent mode, where the data is saved to disk, and in in-memory mode, where the entire dataset is stored in the main memory. Tip Both persistent and in-memory databases...use spilling to disk to facilitate larger-than-memory workloads (i.e., out-of-core-processing). Persistent Database To create or open a persist...ial value :memory: as the database file or omitting the database file argument. In in-memory mode, no data is persisted to disk, therefore, all data is lost when the process finishes.... - https://man.mtool.work/duckdb/2.0/connect/overview.html
- Files Created by DuckDB 9589
- DuckDB creates several files and directories on disk. This page lists both the global and the local ones. Global Files and Directories DuckDB creates the following global files and directories in the user's home directory (denoted with ~ ):
...database file (for persistent connections): Name Description Example ⟨database_filename⟩ Database file. Only created in on-disk mode. The file can have any extension with typical extensions being .duckdb , .db and .ddb . weather.duckdb .tmp/ Temporar...y directory. Only created in in-memory mode. .tmp/ ⟨database_filename⟩.tmp/ Temporary directory. Only created in on-disk mode. weather.duckdb.tmp/ ⟨database_filename⟩.wal Write-ahead log file. If DuckDB exits normally, the WAL file is deleted... - https://man.mtool.work/duckdb/2.0/operations_manual/footprint_of_duckdb/files_cr...
- Limits 9222
- This page contains DuckDB's built-in limit values. To check the value of a setting on your system, use the current_setting function. Limit Values Limit Default value Configuration option Comment Array size 100000 - BLOB size 4 GB - Expressi
...ry_limit Note: This limit only applies to the buffer manager. String size 4 GB - Temporary directory size 90% of available disk space max_temp_directory_size Size of Database Files DuckDB doesn't have a practical limit for the size of a single DuckDB...database file. We have database files using 15 TB+ of disk space and they work fine. However, connecting to such a huge database may take a few seconds and checkpointing can be slow... - https://man.mtool.work/duckdb/2.0/operations_manual/limits.html
- DROP Statement 9222
- The DROP statement removes a catalog entry added previously with the CREATE command. Examples Delete the table with the name tbl : DROP TABLE tbl; Drop the view with the name view1 ; do not throw an error if the view does not exist: DROP VI
...w1; This returns the following error message: Catalog Error: Table with name tbl does not exist! Limitations on Reclaiming Disk Space Running DROP TABLE should free the memory used by the table, but not always disk space. Even if disk space does not... - https://man.mtool.work/duckdb/2.0/sql/statements/drop.html
- CREATE TABLE Statement 9104
- The CREATE TABLE statement creates a table in the catalog. Examples Create a table with two integer columns ( i and j ): CREATE TABLE t1 (i INTEGER, j INTEGER); Create a table with a primary key: CREATE TABLE t1 (id INTEGER PRIMARY KEY, j V
...lification is required to refer to a regular table e.g., memory.main.t1 . Temporary tables reside in memory rather than on disk even when connecting to a persistent DuckDB, but if the temp_directory configuration is set, data will be spilled to disk...pes): CREATE TEMP TABLE t1 AS SELECT * FROM read_csv('path/file.csv'); Allow temporary tables to off-load excess memory to disk: SET temp_directory = '/path/to/directory/'; CREATE OR REPLACE The CREATE OR REPLACE syntax allows a new table to be creat...lumn. Generated columns come in two varieties: VIRTUAL and STORED . The data of virtual generated columns is not stored on disk, instead it is computed from the expression every time the column is referenced (through a select statement). The data of... - https://man.mtool.work/duckdb/2.0/sql/statements/create_table.html
- Python API 8855
- Installation To use the DuckDB Python client, visit the Python installation page . The latest stable version of the DuckDB Python client is 2.0.0. Installation The DuckDB Python API can be installed using pip : pip install duckdb . Please s
...duckdb.sql("SELECT i * 2 AS k FROM r1").show() Data Input DuckDB can ingest data from a wide variety of formats – both on-disk and in-memory. See the data ingestion page for more information. import duckdb duckdb.read_csv("example.csv") # read a CSV...ELECT 42").to_arrow_reader() # Arrow RecordBatchReader duckdb.sql("SELECT 42").fetchnumpy() # NumPy Arrays Writing Data to Disk DuckDB supports writing Relation objects directly to disk in a variety of formats. The COPY statement can be used to write...data to disk using SQL as an alternative. import duckdb duckdb.sql("SELECT 42").write_parquet("out.parquet") # Write to a Parquet file... - https://man.mtool.work/duckdb/2.0/clients/python/overview.html
- Out-of-Memory Issues 8370
- Configuration Options If you are experiencing out-of-memory issues with DuckDB, try tweaking the following configuration options: Reduce the number of threads using the SET threads = ... command. Setting the memory limit lower than the defa
...you run in a memory-constrained environment, using smaller data types (e.g., TINYINT ) can reduce the amount of memory and disk space required to complete a query. DuckDB's bitpacking compression means small values stored in larger data types will no...t take up larger sizes on disk, but they will take up more memory during processing – hence, using the most restrictive types possible when creating colu... - https://man.mtool.work/duckdb/2.0/guides/performance/oom.html
DuckDB 2.0 Documentation / man.mtool.work