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serializing closures is slow on master #16508
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cc: @shashi could also explain the slowdown you are seeing in ComputeFramework. |
This is important for 0.5. |
#16695 helps but is kind of a workaround? |
Not completely sure it's related to this, but deserializing large objects (in this case DataFrames) from disk seems to take significantly longer on 0.5 (took me 9 seconds for a 38 MB dataframe). I'm afraid I can't give my 0.4 number because I replaced the 0.4 build, but I'm quite sure it was much faster (maybe 1 s at most?). Serialization, on the other hand, seems fine. I did some further testing and it seems that this depends strongly on what the stored datatypes are. I had a 300MB dataframe of floats load in 1s, but 38MB of mixed strings, DateTime and Float takes forever (9s). |
Do we still care about this? It seems not to have significantly improved between 0.5 and master, but maybe we should close as wont-fix since no one has complained in 4 years? |
Serializing closures is pretty cruicial for our distributed processing, so yes? |
Julia 0.5 is when fast closures got added, so maybe it's just inevitable? |
Just tried the benchmark again, and still as slow as reported. |
Yes, but we recommend not sending closures (rather load packages on all nodes), so this isn't really an issue |
If that is the case then it would be helpful with hints to how we can avoid closures when communicating between processes in e.g. DistributedArrays as mention above. |
On 0.4
On master
@andreasnoack, your hunch was correct, this looks like the cause of the slowdown in distributed arrays - https://travis-ci.org/JuliaParallel/DistributedArrays.jl/builds/131800408
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