Help Understanding Memory Management in ROOT for Large Dataset Analysis

ROOT
1

Hi everyone… :wave:

I am relatively new to ROOT and currently using it for a project involving the analysis of large datasets (~200 GB). I’ve been encountering memory issues, and I suspect it has something to do with my lack of understanding regarding ROOT’s memory management, particularly when handling TTrees and histograms.

Here’s my workflow:

  1. I load a large TTree from a ROOT file and apply some selection criteria.
  2. I loop over the selected entries to fill histograms for further analysis.
  3. As I process more data files in the same session, the memory usage keeps increasing until my system becomes unresponsive.

I’ve tried using TTree::SetCacheSize() and splitting the analysis into smaller chunks, but the problem persists. I’ve also experimented with deleting objects using delete and calling gDirectory->Clear(), but I might not be using them correctly.

Could someone clarify the best practices for managing memory in ROOT? Specifically:

  1. What’s the proper way to clean up memory when working with large datasets in a single ROOT session?
  2. Are there common pitfalls when dealing with TTrees or histograms that might cause memory leaks?
  3. Is there a more efficient way to structure the analysis to avoid these issues altogether?

I have not found any solution. Any advice, examples, or documentation references would be greatly appreciated. Thanks in advance for your help!

2

Hi,

Thanks for the interesting post!

I think TTree can be excluded from the potential list of culprits of the memory hoarding: we know of applications running in multithreaded mode over tens of TB of data without encountering issues.

What you describe might look like a memory leak, i.e. memory you allocate in your program and never release. Typical signs could be objects, like histograms, allocated on the heap (e.g. new TH1D(...)).

My suggestion would be to make a copy of your current analysis code and then artificially remove pieces to understand where the leak is coming from. Alternatively, you might use tools such as valgrind to identify immediately the symbols leaking memory.

Dealing with resource leaks is very common, it happens to everybody, don’t feel too discouraged…

Cheers,
Danilo