Possible memory leak

[Yixiao-Zhang]

Describe the bug

The total memory usage keeps increasing when repeatedly calling a function that opens an NC file, does some allocation, and closes that NC file.

To Reproduce

using Printf
using NCDatasets

function create_dummpy_netcdf()
    dset = NCDataset("output.nc", "c")
    close(dset)
end

function output_dummy_netcdf()
    dset = NCDataset("output.nc", "a")
    zeros(1000, 1000)
    close(dset)
end

create_dummpy_netcdf()

for i in 1:1000
    output_dummy_netcdf()

    @info Printf.@sprintf "Max. RSS:  %9.3f MiB\n" Sys.maxrss()/2^20
end

The total memory usage keeps increasing at a rate of 7.5 MiB per iteration. The size of the allocated array in output_dummy_netcdf is 7.6 MiB.

Besides, when we force garbage collection during the iteration, the total memory usage still keeps increasing, although the rate is lower than the case without manual garbage collection.

for i in 1:1000
    output_dummy_netcdf()

    # force garbage collection
    if i % 50 == 0
        GC.gc()
    end

    @info Printf.@sprintf "Max. RSS:  %9.3f MiB\n" Sys.maxrss()/2^20
end

Expected behavior

I expect the total memory usage stays roughly a constant after several iterations. Actually, this is true when I use the "c" mode in output_dummy_netcdf instead of the "a" mode.

Environment

• operating system: Ubuntu 20.04.6 LTS
• Julia version: 1.10.4
• NCDatasets version: 0.14.5

Output of the julia command `versioninfo()`

Julia Version 1.10.4 Commit 48d4fd48430 (2024-06-04 10:41 UTC) Build Info: Official https://julialang.org/ release Platform Info: OS: Linux (x86_64-linux-gnu) CPU: 16 × 11th Gen Intel(R) Core(TM) i7-11700 @ 2.50GHz WORD_SIZE: 64 LIBM: libopenlibm LLVM: libLLVM-15.0.7 (ORCJIT, rocketlake) Threads: 1 default, 0 interactive, 1 GC (on 16 virtual cores)

Output of `using Pkg; Pkg.status(mode=PKGMODE_MANIFEST)`

Project TestNCDatasets v0.1.0 Status `~/Documents/IdealizedOceanWorlds.jl/TestNCDatasets.jl/Manifest.toml` [179af706] CFTime v0.1.3 [1fbeeb36] CommonDataModel v0.3.6 [34da2185] Compat v4.16.0 [864edb3b] DataStructures v0.18.20 ⌅ [3c3547ce] DiskArrays v0.3.23 [692b3bcd] JLLWrappers v1.6.0 [8ac3fa9e] LRUCache v1.6.1 [3da0fdf6] MPIPreferences v0.1.11 [85f8d34a] NCDatasets v0.14.5 [6fe1bfb0] OffsetArrays v1.14.1 [bac558e1] OrderedCollections v1.6.3 [21216c6a] Preferences v1.4.3 [0b7ba130] Blosc_jll v1.21.5+0 [6e34b625] Bzip2_jll v1.0.8+1 [0951126a] GnuTLS_jll v3.8.4+0 ⌃ [0234f1f7] HDF5_jll v1.14.2+1 [e33a78d0] Hwloc_jll v2.11.1+0 [1d63c593] LLVMOpenMP_jll v17.0.6+0 [94ce4f54] Libiconv_jll v1.17.0+0 [5ced341a] Lz4_jll v1.10.0+0 [7cb0a576] MPICH_jll v4.2.2+0 [f1f71cc9] MPItrampoline_jll v5.4.0+0 [9237b28f] MicrosoftMPI_jll v10.1.4+2 ⌃ [7243133f] NetCDF_jll v400.902.209+0 ⌅ [4c82536e] Nettle_jll v3.7.2+0 [fe0851c0] OpenMPI_jll v5.0.5+0 [458c3c95] OpenSSL_jll v3.0.15+0 [c2071276] P11Kit_jll v0.24.1+0 [02c8fc9c] XML2_jll v2.13.3+0 [ffd25f8a] XZ_jll v5.4.6+0 [3161d3a3] Zstd_jll v1.5.6+0 [477f73a3] libaec_jll v1.1.2+0 [337d8026] libzip_jll v1.10.1+0 [0dad84c5] ArgTools v1.1.1 [56f22d72] Artifacts [2a0f44e3] Base64 [ade2ca70] Dates [f43a241f] Downloads v1.6.0 [7b1f6079] FileWatching [b77e0a4c] InteractiveUtils [4af54fe1] LazyArtifacts [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 [8f399da3] Libdl [37e2e46d] LinearAlgebra [56ddb016] Logging [d6f4376e] Markdown [ca575930] NetworkOptions v1.2.0 [44cfe95a] Pkg v1.10.0 [de0858da] Printf [3fa0cd96] REPL [9a3f8284] Random [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization [6462fe0b] Sockets [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [cf7118a7] UUIDs [4ec0a83e] Unicode [e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [781609d7] GMP_jll v6.2.1+6 [deac9b47] LibCURL_jll v8.4.0+0 [e37daf67] LibGit2_jll v1.6.4+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.2+1 [14a3606d] MozillaCACerts_jll v2023.1.10 [4536629a] OpenBLAS_jll v0.3.23+4 [bea87d4a] SuiteSparse_jll v7.2.1+1 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.8.0+1 [8e850ede] nghttp2_jll v1.52.0+1 [3f19e933] p7zip_jll v17.4.0+2

Full output

Full Output without Manual GC

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In case of an error, please paste the full error message and stack trace.

[Yixiao-Zhang]

I suspect this originates from a bug in the netcdf-C library (or even libhdf5); possibly related to #Unidata/netcdf-c#2626). When I use the :netcdf3_classic format, there is no memory leak; using a lower version of libnetcdf (v4.8.1) also solves the issue.

[Alexander-Barth]

Thank you for preparing this well-done reproducer!

Indeed, here is an example where I can make Max. RSS increase by just using NetCDF_jll (independently from NCDatasets.jl):

using Printf
using NetCDF_jll: libnetcdf

function create_dummpy_netcdf()
    ncidp = Ref(Cint(0))
    path = "output.nc"
    mode = 0x1000 # NC_NETCDF4
    ccall((:nc_create,libnetcdf),Cint,(Cstring,Cint,Ptr{Cint}),path,mode,ncidp)

    ccall((:nc_close,libnetcdf),Cint,(Cint,),ncidp[])
end

function output_dummy_netcdf()
    ncidp = Ref(Cint(0))
    path = "output.nc"
    mode = 1
    ccall((:nc_open,libnetcdf),Cint,(Cstring,Cint,Ptr{Cint}),path,mode,ncidp)

    zeros(1000, 1000)

    ccall((:nc_close,libnetcdf),Cint,(Cint,),ncidp[])
end

create_dummpy_netcdf()

for i in 1:1000
    output_dummy_netcdf()

    # force garbage collection
    if i % 50 == 0
        GC.gc()
    end

    @info Printf.@sprintf "Max. RSS:  %9.3f MiB\n" Sys.maxrss()/2^20
end

This indeed confirms that the issues is probably in netCDF-C.

[Yixiao-Zhang]

Thank you for response! Your example clearly demonstrates that the bug is upstream (either netcdf-C or Julia).

I am still surprised that the memory leak is amplified by allocations between ccalls. The actual memory leak due to C function calls seems tiny (several MiBs in the example) and should not do much damage to the program. But when combined with allocations in Julia, Max. RSS may increase to tens of GiBs. What if what happens in libnetcdf was not memory leak but it needed to keep the allocated memory? It seems the memory management by ccall is potentially flawed.

[Alexander-Barth]

Sorry, for cross-posting, but it is maybe better to put my reply here:

| I am still surprised that the memory leak is amplified by allocations between

Yes, I think that this is probably due to memory fragmentation (generated by the memory leak in netcdf-c). Julia needs a contiguous block of memory for its arrays. Even if netcdf-c leaks just a couple of bytes, such contiguous large blocks will be more and more difficult to find if they happen to spoil a a previously large contiguous block of memory (the memory allocated by zeros(Float64,1000, 1000)). Consider if this block of floats is surrounded by data structures of NetCDF and the leading structure is increased by a call to realloc after the block of floats is deallocated. The remaining block is no longer large enough for a new call to zeros(Float64,1000, 1000).

Of course, this is just a hypothesis :-)

[Yixiao-Zhang]

Thank you for your response! The hypothesis of memory fragmentation makes sense to me. I still think that the memory management of Julia amplifies the memory leak.

For example, we can try replacing

zeros(Float64, 1000, 1000)

with

p = Libc.malloc(1000 * 1000 * sizeof(Float64))
Libc.free(p)

The two do very similar things. However, only zeros(Float64, 1000, 1000) triggers the spurious memory leak.

As mentioned in Unidata/netcdf-c#2626, the memory leak in the Python code is also tiny compared to the Julia version that I posted. This should also be the case for pure C code.

I regard this as an issue of Julia rather than NCDatasets. I am thinking of bringing this discussion of Julia discourse, because it is beyond my understanding right now.

[ezaron]

Hi Yixiao and Alexander:

I am curious what your recommended workaround is? I've not looked inside the packages (NCDatasets.jl or NetCDF.jl) to see how the library version is controlled.

-Ed

[Alexander-Barth]

I think it is preferable to not open/close repeatedly the same file, but rather open/close it once for a program and possibly use sync (even independently of this issue).

If you are using 1000s of different files, then I do not know a workaround.

In any case, I think it is better to ask for work-arounds in the upstream issue Unidata/netcdf-c#2626 . The fine folks at unidata have a better understanding of the C side (as the memory leak can be reproduced in pure C, indentently of julia).

To control the library version, have a look here:
https://alexander-barth.github.io/NCDatasets.jl/stable/issues/#Using-a-custom-NetCDF-library

For example:

# install these packages if necessary
using Preferences, NetCDF_jll

set_preferences!(NetCDF_jll, "libnetcdf_path" => "/path/to/libnetcdf.so.xyz")

This works for any BinaryBuilder JLL (including HDF5...).

If you find a combination of NetCDF/HDF5 which is not affected, please let us know :-)

[Alexander-Barth]

Maybe updating HDF5_jll solves the issue?

HDFGroup/hdf5#3396 (comment)

https://github.com/JuliaPackaging/Yggdrasil/blob/b028f2de66a1b360511d0e0b8e32b26b991c5277/H/HDF5/build_tarballs.jl#L9

[ezaron]

-- thank you. Yes, I have about 16k files to process. Simplest workaround was just to run a single executable 16 times to process 1K files per run, and separately merge the results afterwards.

[Yixiao-Zhang]

I use NetCDF3, which does not depend on HDF5, as a workaround.

I remember downgrading netcdf-c to 4.8 worked for me. However, I have multiple machines with several different platforms, and thus using NetCDF3 would be a much simpler workaround for me.