Intro

The benchmarks were done using two test files (for mdf version 3 and 4) of around 170MB. The files contain 183 data groups and a total of 36424 channels.

asamdf 2.1.0 was compared against mdfreader 0.2.5. mdfreader seems to be the most used Python package to handle MDF files, and it also supports both version 3 and 4 of the standard.

The three benchmark cathegories are file open, file save and extracting the data for all channels inside the file(36424 calls). For each cathegory two aspect were noted: elapsed time and peak RAM usage.

Dependencies

You will need the following packages to be able to run the benchmark script

  • psutil
  • mdfreader

x64 Python results

The test environment used for 64 bit tests had:

  • Python 3.6.1 (v3.6.1:69c0db5, Mar 21 2017, 18:41:36) [MSC v.1900 64 bit (AMD64)]
  • Windows-7-6.1.7601-SP1
  • Intel64 Family 6 Model 94 Stepping 3, GenuineIntel (i7-6820Q)
  • 16GB installed RAM

The notations used in the results have the following meaning:

  • nodata = MDF object created with load_measured_data=False (raw channel data no loaded into RAM)
  • compression = MDF object created with compression=True (raw channel data loaded into RAM and compressed)
  • noconvert = MDF object created with convertAfterRead=False

Raw data

Open file Time [ms] RAM [MB]
asammdf 2.1.0 mdfv3 801 352
asammdf 2.1.0 compression mdfv3 946 278
asammdf 2.1.0 nodata mdfv3 490 172
mdfreader 0.2.5 mdfv3 2962 525
mdfreader 0.2.5 no convert mdfv3 2740 392
asammdf 2.1.0 mdfv4 1674 440
asammdf 2.1.0 compression mdfv4 1916 343
asammdf 2.1.0 nodata mdfv4 1360 245
mdfreader 0.2.5 mdfv4 31915 737
mdfreader 0.2.5 noconvert mdfv4 31425 607
Save file Time [ms] RAM [MB]
asammdf 2.1.0 mdfv3 575 353
asammdf 2.1.0 compression mdfv3 705 276
mdfreader 0.2.5 mdfv3 21591 1985
asammdf 2.1.0 mdfv4 913 447
asammdf 2.1.0 compression mdfv4 1160 352
mdfreader 0.2.5 mdfv4 18666 2782
Get all channels (36424 calls) Time [ms] RAM [MB]
asammdf 2.1.0 mdfv3 2835 363
asammdf 2.1.0 compression mdfv3 18188 287
asammdf 2.1.0 nodata mdfv3 11926 188
mdfreader 0.2.5 mdfv3 29 525
asammdf 2.1.0 mdfv4 2338 450
asammdf 2.1.0 compression mdfv4 15566 355
asammdf 2.1.0 nodata mdfv4 12598 260
mdfreader 0.2.5 mdfv4 39 737

x86 Python results

The test environment used for 32 bit tests had:

  • Python 3.6.1 (v3.6.1:69c0db5, Mar 21 2017, 17:54:52) [MSC v.1900 32 bit (Intel)]
  • Windows-7-6.1.7601-SP1
  • Intel64 Family 6 Model 94 Stepping 3, GenuineIntel (i7-6820Q)
  • 16GB installed RAM

The notations used in the results have the following meaning:

  • nodata = MDF object created with load_measured_data=False (raw channel data no loaded into RAM)
  • compression = MDF object created with compression=True (raw channel data loaded into RAM and compressed)
  • noconvert = MDF object created with convertAfterRead=False

Raw data

Open file Time [ms] RAM [MB]
asammdf 2.1.0 mdfv3 1031 284
asammdf 2.1.0 compression mdfv3 1259 192
asammdf 2.1.0 nodata mdfv3 584 114
mdfreader 0.2.5 mdfv3 3809 455
mdfreader 0.2.5 no convert mdfv3 3498 321
asammdf 2.1.0 mdfv4 2109 341
asammdf 2.1.0 compression mdfv4 2405 239
asammdf 2.1.0 nodata mdfv4 1686 159
mdfreader 0.2.5 mdfv4 44400 578
mdfreader 0.2.5 noconvert mdfv4 43867 449
Save file Time [ms] RAM [MB]
asammdf 2.1.0 mdfv3 713 286
asammdf 2.1.0 compression mdfv3 926 194
mdfreader 0.2.5 mdfv3 19862 1226
asammdf 2.1.0 mdfv4 1109 347
asammdf 2.1.0 compression mdfv4 1267 246
mdfreader 0.2.5 mdfv4 17518 1656
Get all channels (36424 calls) Time [ms] RAM [MB]
asammdf 2.1.0 mdfv3 3943 295
asammdf 2.1.0 compression mdfv3 29682 203
asammdf 2.1.0 nodata mdfv3 23215 129
mdfreader 0.2.5 mdfv3 38 455
asammdf 2.1.0 mdfv4 3227 351
asammdf 2.1.0 compression mdfv4 26070 250
asammdf 2.1.0 nodata mdfv4 21619 171
mdfreader 0.2.5 mdfv4 51 578