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

Problem: Ninja parallelizes the build, which can cause 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= make

R Package: The Build Only Uses a Single Thread

Problem: By default, R compiles packages using a single thread, which causes the build to be slow.

Solution: To parallelize the compilation, create or edit the ~/.R/Makevars file, and add a line like the following:

MAKEFLAGS = -j8

The above will parallelize the compilation using 8 threads. On Linux/macOS, you can add the following to use all of the machine's threads:

MAKEFLAGS = -j$(nproc)

However, note that, the more threads that are used, the higher the RAM consumption. If the system runs out of RAM while compiling, then the R session will crash.

Python Package: No module named 'duckdb.duckdb' Build Error

Problem: Building the Python package succeeds but the package cannot be imported:

cd tools/pythonpkg/
python3 -m pip install .
python3 -c "import duckdb"

This returns the following error message:

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/duckdb/tools/pythonpkg/duckdb/__init__.py", line 4, in <module>
    import duckdb.functional as functional
  File "/duckdb/tools/pythonpkg/duckdb/functional/__init__.py", line 1, in <module>
    from duckdb.duckdb.functional import (
ModuleNotFoundError: No module named 'duckdb.duckdb'

Solution: The problem is caused by Python trying to import from the current working directory. To work around this, navigate to a different directory (e.g., cd ..) and try running Python import again.