build instructions and other comments
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tree: 1f50ffcbcd3013c923f91ba053bddbfd5b1d5b20
  1. .gitignore
  2. .gitmodules
  3. CMakeLists.txt
  4. DISCLAIMER-WIP
  5. LICENSE
  6. MANIFEST.in
  7. Makefile
  8. NOTICE
  9. README.md
  10. cmake/
  11. common/
  12. config.mk
  13. cpc/
  14. fi/
  15. hll/
  16. kll/
  17. pyproject.toml
  18. python/
  19. setup.py
  20. theta/
README.md

This is a C++ version of the DataSketches core library. See Apache DataSketches home

Apache DataSketches is an open source, high-performance library of stochastic streaming algorithms commonly called “sketches” in the data sciences. Sketches are small, stateful programs that process massive data as a stream and can provide approximate answers, with mathematical guarantees, to computationally difficult queries orders-of-magnitude faster than traditional, exact methods.

This code requires C++11. It was tested with GCC 4.8.5 (standard in RedHat at the time of this writing), GCC 8.2.0 and Apple LLVM version 10.0.1 (clang-1001.0.46.4)

This includes Python bindings. For the Python interface, see the README notes in the python subdirectory.

This library was intended to be header-only, but this goal was not fully achieved yet with CPC sketch code. This work is in progress.

Building and running unit tests requires CppUnit.

Installing CppUnit on OSX: brew install cppunit

Installing CppUnit on RHEL: yum install cppunit-devel

There are currently two ways of building: using existing make files and generating make files using cmake. Exsisting make files might not work on all platforms or with all C++ compilers. Generating make files using cmake should solve this problem, but it currently requires cmake version 3.12.0 or later that might not be readily available as a package on all platforms. Installing latest cmake on OSX: brew install cmake

Building and running unit tests using existing make files:

$ make
$ make test

Building and running unit tests using cmake:

$ mkdir build
$ cd build
$ cmake ..
$ make
$ make test