[erlang-patches] Fix for: extremely slow Erlang to/from Java communication via JInterface

Nico Kruber <>
Wed Nov 30 10:32:33 CET 2011


We discovered, that the communication between Erlang and Java is
extremely slow when sending longer lists.

We had two lists, each containing about **700.000** Strings (typically of 
length 20-30). This resulted in a message size of about **40MB** when being 
sent over to Erlang. The transformation of these lists into the (binary) 
message took Java about **10 minutes** in an RPC call.

The reason for this is in the JInterface, which incrementally allocates memory 
for the send-buffer in OtpOutputStream and increases this buffer by a constant 
size of 2KB in each iteration. Each increase involves a complete copying of 
the old buffer to a new one - for this **40MB** message, about 20000 memory 
copies are needed!

We can reduce the send time from 10 minutes to less than 10 seconds (almost
two orders of magnitude) with the patch below. It allocates 50% more
memory in each step, instead of constantly adding only 2k. (This behaviour was 
inspired by the one used by java.util.ArrayList.)

The following table provides some examples of how many memory copies are 
needed in order to reach a certain size:

size         n*2048   (n*3)/2+1 and at least +2048
   1K             1              1
   2K             1              1
   5K             3              3
  10K             5              5
  20K            10              6
 100K            50             10
 500K           250             14
1024K=1M        512             16
     10M       5120             22
     50M      25600             26
    100M      51200             28


git fetch git://github.com/NicoK/otp.git jinterface_better_buffer_alloc

https://github.com/NicoK/otp/compare/jinterface_better_buffer_alloc
https://github.com/NicoK/otp/compare/jinterface_better_buffer_alloc.patch


It would be nice to see this in R15B as it significantly improves performance 
for large messages as shown.


Regards
Nico Kruber

Note: Sending binary data is not affected, as it already allocates as much 
memory as needed to include the bytes.
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