• Most edi files are just a few kilobyes. An edi file of 5Mb is very large (edifact, x12). If you encounter larger ones: please let me know.
  • AFAIK there are no issues with performance. If you run into this: please inform me eg via mailing list.

Get More Performance

  • (Bots >= 2.2.0) Cdecimals (Extern library) speeds up bots. This library will be included in python 3.3, but can be installed in earlier python versions.
  • (bots >= 3.1) Do not use get_checklevel=2 in config/bots.ini. This does extended checking of mpath’s, use this during development only.
  • (bots >= 3.0) Schedule bots-engine via the job queue server.
  • For xml: check if the c-version of python’s elementtree is installed and used.
  • Enough memory is important for performance: disk-memory swapping is slow. Actual memory usage depends on size of edi-files.
  • Check mappings for slow/inefficient algorithms.
  • Bots works with pypy, see below on this page.
  • Use SSD for faster reading/writing. In config/bots.ini the botssys-directory can be set, in config/ the place of the SQLite-database.

Strategy for bigger edi volumes

  • Best strategy is to schedule bots-engine more often.
  • (bots >= 3.0) Schedule bots-engine via the jobqueue server.
  • Routes can be scheduled independently.
  • Set-up good scheduling, keeping volumes in mind.
  • EDI in the real world has often large peaks.
  • Dome edi transactions are time critical (eg orders), others not so much (eg invoices)
  • Check where the large volumes are (size and number of edi-transactions)
  • Look at the sending pattern of your customers. Often edi is send in night jobs, so you might receive lot of volume early in the morning.
  • Check where you send large volumes. Send this at a time that does not interfere with other flows.
  • Incoming volumes can be limited per run. This way the time bots-engine runs is predictable.
    • The max time a channel fetches incoming files is a parameter for each channel.
    • This is dependent upon the communication type used; eg file system I/O is much faster than SFTP.
    • Files “left behind” will be fetched on subsequent runs.
  • (Bots >= 3.0) Limit for max file-size (set in bots.ini). If an incoming file is larger, bots will give error. This is to prevent accidents.

Performance/throughput testing

  1. Tests are done using file system I/O (no testing of communication performance).
  2. Tests done in one run of bots-engine.
  3. Test system: Intel Q9400 2.66GHz; 4Gb memory; ubuntu 10.04(lucid); python 2.7; default SQLite database.
  4. Please note that these tests are artificial: if you have such high volumes and big files look at good scheduling.
  5. Tests are with edifact; x12 performance is the same.
Description File Count Total Size Message Count Time(bots2.0) Speed(bots2.0) Time(bots2.2) Speed(bots2.2) Time(bots3.2) Speed(bots3.2)
01 edifact2fixed 32 305Mb 32 1:01:39 82 kb/s 0:50:57 100 kb/s 0:44:01 115 kb/s
02 edifact2fixed 116 300Mb 116 1:14:18 68 kb/s 0:36:20 137 kb/s 0:37:25 133 kb/s
03 edifact2fixed 94048 295Mb 141072 0:47:21 104 kb/s 0:39:54 125 kb/s 0:42:30 115 kb/s
04 fixed2edifact 14244 300Mb 78342 1:04:11 78 kb/s 0:33:21 150 kb/s 0:32:40 153 kb/s
05 xml2edifact 17424 300Mb 17424 0:41:24 121 kb/s 0:35:48 139 kb/s 0:35:20 141 kb/s
06 edifact2xml(1to1) 14609 300Mb 74919 1:23:03 60 kb/s 0:58:19 85 kb/s 0:44:38 112 kb/s

Conclusions of performance measurements:

  1. Memory usage is stable (no leakage).
  2. Memory usage is directly related to the size of the edi-files. In test 01 (edifact files of 9.5Mb) bots-engine uses 1.5Gb memory.
  3. Tested with edifact files of 120Mb; memory usage is stable at 4.5Gb.
  4. Performance is reasonably independent from the size of edi-files/messages.
  5. An edifact file of 9.5Mb takes about 85sec to be processed.
  6. For outgoing edi files: writing to one file or multiple file does not significantly affect performance.

Testing with pypy

pypy s a python implementation that is faster by using a JIT. Results of the first tests with pypy (beta-versions of pypy 2.0):

  • Bots works with pypy.
  • Comparing some stress tests: much faster, 2-3 times faster.
  • Did not run all test-sets. Probably I will do that with definitive version of pypy 2.0 and/or release of bots 3.1.
  • Problem might be that not all libraries/dependencies work with pypy.
    • SQLite3 database connector: OK
    • MySQL database connector: version 1.2.5 does. Note that bots 3.1.0 gave am error with this version, a patch was easy.
    • paramiko (for SFTP/SSH): no, dependency pycrypto is not supported.

This looks like a very interesting development.