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Environment 14681
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 ... e dataset size and the queries to execute. Maybe surprisingly, the queries have a larger effect on the memory requirement. Workloads containing large joins over many-to-many tables yield large intermediate datasets and thus require more memory for their e ... valuation to fully fit into the memory. As an approximation, aggregation-heavy workloads require 1-2 GB memory per thread and join-heavy workloads require 3-4 GB memory per thread. Larger-than-Memory Workloads D ... uckDB 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 ...
https://man.mtool.work/duckdb/2.0/guides/performance/environment.html
Tuning Workloads 10292
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 ... 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 many times with different parameters Pr ... o slowdowns. In these cases, it's worth manually limiting the number of threads using SET threads = X . Larger-than-Memory Workloads (Out-of-Core Processing) A key strength of DuckDB is support for larger-than-memory workloads, i.e., it is able to process ... rerequisites, 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 ⟨database_file_name⟩.tmp temporary d ...
https://man.mtool.work/duckdb/2.0/guides/performance/how_to_tune_workloads.html
My Workload Is Slow 9230
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 ... e you using a fast disk? Network-attached disks (such as cloud block storage) cause write-intensive and larger than memory workloads to slow down. For running such workloads in cloud environments, it is recommended to use instance-attached storage (NVMe S ...
https://man.mtool.work/duckdb/2.0/guides/performance/my_workload_is_slow.html
Performance Guide 8742
DuckDB aims to automatically achieve high performance by using well-chosen default configurations and having a forgiving architecture. Of course, there are still opportunities for tuning the system for specific workloads. The Performance Gu ...
https://man.mtool.work/duckdb/2.0/guides/performance/overview.html
Linux 8499
Prerequisites On Linux, install the required packages with the package manager of your distribution. Ubuntu and Debian CLI Client On Ubuntu and Debian (and also MX Linux, Linux Mint, etc.), the requirements for building the DuckDB CLI clien ... s C standard library. DuckDB binaries built with musl libc have lower performance compared to the glibc variants: for some workloads, the slowdown can be more than 5×. Therefore, it's recommended to use glibc for performance-oriented workloads. Distributi ...
https://man.mtool.work/duckdb/2.0/dev/building/linux.html
Benchmarks 8324
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 ... e the datasets of and some queries provided by the TPC-H and the LDBC BI benchmark frameworks, and omit other parts of the workloads such as updates. ...
https://man.mtool.work/duckdb/2.0/guides/performance/benchmarks.html
jemalloc 8255
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 ... ynchronously 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
Connect 8168
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 ... ored 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 persistent database, set the path of the database ...
https://man.mtool.work/duckdb/2.0/connect/overview.html
Guides 7924
The guides section contains compact how-to guides that are focused on achieving a single goal. For API references and examples, see the rest of the documentation. Note that there are many tools using DuckDB, which are not covered in the off ... make join operations efficient What performance implications do Parquet files and (compressed) CSV files have How to tune workloads How to avoid out-of-memory issues How to work with huge databases Benchmarks Meta Queries How to list all tables How to vi ...
https://man.mtool.work/duckdb/2.0/guides/overview.html
Lance Extension 7837
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
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