Skip to main content

Optimized code for text de-duplication, written in Rust

Project description

dupekit

Raison d'être: Home for the Rust code used for text deduplication.

Install

  • Locally: This code is auto-magically built by uv via Cargo and Maturin. You might need to install them (e.g., brew install maturin rust on macOS).
  • Cluster: This code is compiled as part of the Docker build (uv pip install -e ... step): Maturin builds the Rust code and places it in the system site-packages (e.g., /home/ray/anaconda3/lib/python3.11/site-packages/dupekit/dupekit.abi3.so).

[!NOTE] What about making dupekit a hybrid Python/Rust Maturin workspace? We tried and experienced issues getting the Docker build to work while keeping it simple—a simple Rust workspace helps keep the setup clean.

[!NOTE] Building from source requires a Rust toolchain (Cargo). Pre-built wheels are available from GitHub Releases for users who don't want to compile locally.

Benchmarking

The goal of these benchmarks is to test different ways of marshaling large text content between Python and Rust "foreign function interface" (wiki:FFI). These tests are designed to isolate the overhead of marshaling from the actual Rust computation (by doing minimal processing in Rust).

Dataset: 1 shard of HuggingFaceFW/fineweb-edu/sample/10BT (2.15 GB Parquet file, benchmarked on 250k out of 726k documents)

Install:

uv sync --all-packages --extra=benchmark --group dev

Benchmark (Takes a few minutes):

uv run pytest rust/dupekit/tests/bench/test_dedupe.py --run-benchmark --benchmark-min-rounds=20
uv run pytest rust/dupekit/tests/bench/test_marshaling.py --run-benchmark
uv run pytest rust/dupekit/tests/bench/test_batch_tuning.py --run-benchmark
uv run pytest rust/dupekit/tests/bench/test_io.py --run-benchmark
uv run pytest rust/dupekit/tests/bench/test_hashing.py --run-benchmark
uv run pytest rust/dupekit/tests/bench/test_minhash.py --run-benchmark

Note: Run separated by type of benchmark (otherwise results are mixed within one table)

Footprint (Note: sampling the stack might taint the mem measurements, so we disable benchmarking):

uv run pytest rust/dupekit/tests/bench/test_marshaling.py \
  --run-benchmark \
  --benchmark-disable \
  --memray \
  --native \
  --most-allocations=0

Results

Dedup: Rust vs. Python

---------------------------------------------------------------------------- benchmark 'Documents: Exact Deduplication': 2 tests ----------------------------------------------------------------------------
Name (time in ms)                             Min                 Max                Mean            StdDev              Median               IQR            Outliers       OPS            Rounds  Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_deduplication[rust-documents]         3.9872 (1.0)        5.2516 (1.0)        4.2341 (1.0)      0.1949 (1.0)        4.2247 (1.0)      0.2845 (1.0)          52;2  236.1805 (1.0)         188           1
test_deduplication[python-documents]     133.8747 (33.58)    157.3844 (29.97)    139.6233 (32.98)    7.7842 (39.94)    135.3300 (32.03)    9.6717 (34.00)         5;0    7.1621 (0.03)         20           1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

--------------------------------------------------------------------------- benchmark 'Documents: Hash Generation': 2 tests ---------------------------------------------------------------------------
Name (time in ms)                       Min                 Max                Mean            StdDev              Median               IQR            Outliers       OPS            Rounds  Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_hashing[rust-documents]         2.2755 (1.0)        2.4842 (1.0)        2.3041 (1.0)      0.0301 (1.0)        2.2938 (1.0)      0.0381 (1.0)          50;9  434.0169 (1.0)         375           1
test_hashing[python-documents]     130.0445 (57.15)    132.3783 (53.29)    130.7795 (56.76)    0.6663 (22.13)    130.5910 (56.93)    0.6259 (16.44)         5;3    7.6465 (0.02)         20           1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

----------------------------------------------------------------------------- benchmark 'Paragraphs: Exact Deduplication': 2 tests ----------------------------------------------------------------------------
Name (time in ms)                              Min                 Max                Mean             StdDev              Median                IQR            Outliers      OPS            Rounds  Iterations
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_deduplication[rust-paragraphs]        85.4666 (1.0)      109.3652 (1.0)       90.2916 (1.0)       6.8294 (1.0)       87.3405 (1.0)       2.0275 (1.0)           4;4  11.0752 (1.0)          20           1
test_deduplication[python-paragraphs]     303.0885 (3.55)     342.9836 (3.14)     321.3022 (3.56)     13.8377 (2.03)     329.4886 (3.77)     25.1111 (12.39)         9;0   3.1123 (0.28)         20           1
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

--------------------------------------------------------------------------- benchmark 'Paragraphs: Hash Generation': 2 tests ---------------------------------------------------------------------------
Name (time in ms)                        Min                 Max                Mean             StdDev              Median               IQR            Outliers      OPS            Rounds  Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_hashing[rust-paragraphs]        23.9739 (1.0)       26.9860 (1.0)       25.3823 (1.0)       0.4419 (1.0)       25.3160 (1.0)      0.2099 (1.0)           5;5  39.3975 (1.0)          38           1
test_hashing[python-paragraphs]     247.5415 (10.33)    321.4654 (11.91)    255.3421 (10.06)    19.0653 (43.15)    249.1948 (9.84)     1.7899 (8.53)          2;2   3.9163 (0.10)         20           1
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Marshaling

-------------------------------------------------------------------------------------------- benchmark: 7 tests -------------------------------------------------------------------------------------------
Name (time in ms)                    Min                   Max                  Mean             StdDev                Median                IQR            Outliers      OPS            Rounds  Iterations
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_arrow_giant                 86.4414 (1.0)         96.0537 (1.01)        90.0259 (1.0)       2.8582 (31.54)       90.4363 (1.0)       4.1787 (27.96)         3;0  11.1079 (1.0)          11           1
test_arrow_small                 94.4010 (1.09)        94.6679 (1.0)         94.5616 (1.05)      0.0906 (1.0)         94.5570 (1.05)      0.1494 (1.0)           5;0  10.5751 (0.95)         11           1
test_dicts_batched_stream     3,975.1581 (45.99)    3,979.7102 (42.04)    3,977.7639 (44.18)     1.8357 (20.26)    3,978.3399 (43.99)     2.8370 (18.98)         2;0   0.2514 (0.02)          5           1
test_dicts_batch              4,398.7191 (50.89)    4,421.9632 (46.71)    4,410.0489 (48.99)     8.7694 (96.78)    4,411.2232 (48.78)    12.0295 (80.50)         2;0   0.2268 (0.02)          5           1
test_dicts_loop               4,411.8727 (51.04)    4,457.0985 (47.08)    4,431.9081 (49.23)    19.8323 (218.86)   4,430.5465 (48.99)    35.6846 (238.78)        2;0   0.2256 (0.02)          5           1
test_rust_structs             4,449.5728 (51.47)    4,479.8173 (47.32)    4,465.2999 (49.60)    14.1041 (155.65)   4,472.5336 (49.46)    24.8971 (166.60)        3;0   0.2239 (0.02)          5           1
test_arrow_tiny               7,023.5789 (81.25)    7,064.2094 (74.62)    7,044.9691 (78.25)    19.4414 (214.55)   7,047.1538 (77.92)    37.8036 (252.96)        1;0   0.1419 (0.01)          5           1
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

PyArrow Batch Size

--------------------------------------------------------------------------------------------- benchmark: 11 tests ----------------------------------------------------------------------------------------------
Name (time in ms)                         Min                   Max                  Mean             StdDev                Median                IQR            Outliers      OPS            Rounds  Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_arrow_batch_sizes[8192]          28.6030 (1.0)         32.0178 (1.07)        29.2802 (1.0)       0.8846 (4.75)        28.9333 (1.0)       0.7970 (3.52)          5;3  34.1528 (1.0)          34           1
test_arrow_batch_sizes[16384]         28.7303 (1.00)        30.8987 (1.03)        29.3111 (1.00)      0.5447 (2.92)        29.1404 (1.01)      0.5907 (2.61)          9;2  34.1168 (1.00)         33           1
test_arrow_batch_sizes[4096]          28.8488 (1.01)        30.1474 (1.01)        29.2876 (1.00)      0.3776 (2.03)        29.2212 (1.01)      0.6339 (2.80)         12;0  34.1441 (1.00)         34           1
test_arrow_batch_sizes[2048]          29.1493 (1.02)        30.4442 (1.02)        29.5710 (1.01)      0.3013 (1.62)        29.5505 (1.02)      0.3483 (1.54)         10;1  33.8169 (0.99)         32           1
test_arrow_batch_sizes[32768]         29.2200 (1.02)        29.9410 (1.0)         29.5896 (1.01)      0.1863 (1.0)         29.5706 (1.02)      0.2423 (1.07)         11;0  33.7956 (0.99)         34           1
test_arrow_batch_sizes[65536]         30.3973 (1.06)        31.3805 (1.05)        30.9409 (1.06)      0.2453 (1.32)        30.9829 (1.07)      0.2263 (1.0)           9;3  32.3197 (0.95)         33           1
test_arrow_batch_sizes[131072]        30.7074 (1.07)        33.1845 (1.11)        31.4322 (1.07)      0.6799 (3.65)        31.1102 (1.08)      0.8739 (3.86)          6;1  31.8145 (0.93)         32           1
test_arrow_batch_sizes[1024]          30.7724 (1.08)        32.6049 (1.09)        31.6173 (1.08)      0.5506 (2.96)        31.6311 (1.09)      0.9233 (4.08)         13;0  31.6283 (0.93)         30           1
test_arrow_batch_sizes[512]           33.8866 (1.18)        36.2981 (1.21)        34.5224 (1.18)      0.6189 (3.32)        34.2960 (1.19)      0.5087 (2.25)          6;3  28.9667 (0.85)         29           1
test_arrow_batch_sizes[128]           51.0530 (1.78)        56.3190 (1.88)        53.5492 (1.83)      1.6124 (8.65)        53.7474 (1.86)      2.3557 (10.41)         7;0  18.6744 (0.55)         18           1
test_arrow_batch_sizes[1]          2,781.2088 (97.23)    2,812.2547 (93.93)    2,797.8572 (95.55)    11.6892 (62.74)    2,801.0024 (96.81)    15.3956 (68.03)         2;0   0.3574 (0.01)          5           1
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

I/O

------------------------------------------------------------------------------- benchmark: 4 tests ------------------------------------------------------------------------------
Name (time in s)          Min               Max              Mean            StdDev            Median               IQR            Outliers     OPS            Rounds  Iterations
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_rust_native       1.6757 (1.0)      1.6848 (1.0)      1.6794 (1.0)      0.0035 (1.26)     1.6783 (1.0)      0.0047 (1.73)          2;0  0.5955 (1.0)           5           1
test_arrow_giant       2.9501 (1.76)     2.9570 (1.76)     2.9521 (1.76)     0.0028 (1.0)      2.9511 (1.76)     0.0027 (1.0)           1;0  0.3387 (0.57)          5           1
test_arrow_small       3.3476 (2.00)     3.6588 (2.17)     3.5583 (2.12)     0.1241 (44.48)    3.5726 (2.13)     0.1289 (47.18)         1;0  0.2810 (0.47)          5           1
test_dicts_loop_io     7.3664 (4.40)     7.3913 (4.39)     7.3837 (4.40)     0.0101 (3.63)     7.3871 (4.40)     0.0113 (4.14)          1;0  0.1354 (0.23)          5           1
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Hashing

--------------------------------------------------------------------------------------- benchmark: 6 tests ---------------------------------------------------------------------------------------
Name (time in ms)                     Min                Max               Mean            StdDev             Median               IQR            Outliers       OPS            Rounds  Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_hash_rust_xxh3_64_batch       4.4886 (1.0)       4.9466 (1.0)       4.5860 (1.0)      0.0616 (1.57)      4.5939 (1.0)      0.0957 (2.52)         74;1  218.0558 (1.0)         210           1
test_hash_rust_xxh3_64_scalar      5.0276 (1.12)      5.3367 (1.08)      5.1276 (1.12)     0.0393 (1.0)       5.1307 (1.12)     0.0379 (1.0)         41;12  195.0244 (0.89)        190           1
test_hash_rust_xxh3_128            6.1686 (1.37)      6.5772 (1.33)      6.2901 (1.37)     0.1098 (2.79)      6.2334 (1.36)     0.1731 (4.56)         37;0  158.9811 (0.73)        160           1
test_hash_rust_blake3             28.7743 (6.41)     29.0392 (5.87)     28.8919 (6.30)     0.0593 (1.51)     28.8799 (6.29)     0.0709 (1.87)         10;1   34.6118 (0.16)         35           1
test_hash_rust_blake2             54.1043 (12.05)    55.0271 (11.12)    54.4180 (11.87)    0.3711 (9.43)     54.1916 (11.80)    0.7337 (19.34)         5;0   18.3763 (0.08)         19           1
test_hash_python_blake2b          84.0109 (18.72)    84.1698 (17.02)    84.0611 (18.33)    0.0465 (1.18)     84.0469 (18.30)    0.0595 (1.57)          3;0   11.8961 (0.05)         12           1
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Mem Footprin (sorted from high to low):

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_rust_structs at the high watermark

	 📦 Total memory allocated: 4.3GiB
	 📏 Total allocations: 21
	 📊 Histogram of allocation sizes: | ▃█▁▃|

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_dicts_batch at the high watermark

	 📦 Total memory allocated: 3.3GiB
	 📏 Total allocations: 20
	 📊 Histogram of allocation sizes: |  ▁█▂|

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_dicts_loop at the high watermark

	 📦 Total memory allocated: 3.3GiB
	 📏 Total allocations: 19
	 📊 Histogram of allocation sizes: |  ▁█▂|

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_arrow_giant at the high watermark

	 📦 Total memory allocated: 64.9MiB
	 📏 Total allocations: 36
	 📊 Histogram of allocation sizes: |▅█   |

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_dicts_batched_stream at the high watermark

	 📦 Total memory allocated: 28.1MiB
	 📏 Total allocations: 7
	 📊 Histogram of allocation sizes: |█▄▄▄▄|

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_arrow_tiny at the high watermark

	 📦 Total memory allocated: 22.0MiB
	 📏 Total allocations: 37
	 📊 Histogram of allocation sizes: |█▇   |

Allocation results for rust/dupekit/tests/bench/test_marshaling.py::test_arrow_small at the high watermark

	 📦 Total memory allocated: 551.7KiB
	 📏 Total allocations: 42
	 📊 Histogram of allocation sizes: |▂█▁  |

Statement of attribution:

  • This code was seeded from nelson-liu/rbloom-gcs.
  • Bloom filters were originally proposed in (Bloom, 1970). Furthermore, this implementation makes use of a constant recommended by (L'Ecuyer, 1999) for redistributing the entropy of a single hash over multiple integers using a linear congruential generator.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

marin_dupekit-0.1.2.dev202606060824.tar.gz (94.0 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.28+ x86-64

marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_aarch64.whl (4.4 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.28+ ARM64

marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_11_0_arm64.whl (4.2 MB view details)

Uploaded CPython 3.11+macOS 11.0+ ARM64

marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_10_12_x86_64.whl (4.6 MB view details)

Uploaded CPython 3.11+macOS 10.12+ x86-64

File details

Details for the file marin_dupekit-0.1.2.dev202606060824.tar.gz.

File metadata

File hashes

Hashes for marin_dupekit-0.1.2.dev202606060824.tar.gz
Algorithm Hash digest
SHA256 1699752b40a810667d4cdd3912ea188a34c72776123eafa50cd8529d5aadd58e
MD5 2002cb271b6a6f0341beb236b8a83f13
BLAKE2b-256 490d535c570511513a46515892104a1b3113fadb234cc06707b85f0d7a9ea244

See more details on using hashes here.

Provenance

The following attestation bundles were made for marin_dupekit-0.1.2.dev202606060824.tar.gz:

Publisher: dupekit-release-wheels.yaml on marin-community/marin

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5dc5ece35cfb7e9a9db1a2284c018997a3e5a785a959a017b05ecd4369b5763f
MD5 d71b442a894151682710f53160011c1b
BLAKE2b-256 937ad75c42a05d0eb5ac8ea09aaec14f5a68405b3b1b284a24c763d78434f7eb

See more details on using hashes here.

Provenance

The following attestation bundles were made for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_x86_64.whl:

Publisher: dupekit-release-wheels.yaml on marin-community/marin

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 a008a324586e8b41929ff0ac09006c035305a5d18f43932877a218f8cf9732b5
MD5 553babb35468831bf5fe3d8c01dd26d1
BLAKE2b-256 58ff7682a63f148b5891ec56d452a40ba10684ae0fcfe680928c73b59d9833ed

See more details on using hashes here.

Provenance

The following attestation bundles were made for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-manylinux_2_28_aarch64.whl:

Publisher: dupekit-release-wheels.yaml on marin-community/marin

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 41e834662b5e9e5ade9408694a43b688a5b40d011e834ed9877177a03de030e8
MD5 e900b809114d1ee063e8e731369a42bf
BLAKE2b-256 867cc2e4d275a520ec3c29547627f7e45f856359a93758dfd805dab346c4a721

See more details on using hashes here.

Provenance

The following attestation bundles were made for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_11_0_arm64.whl:

Publisher: dupekit-release-wheels.yaml on marin-community/marin

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 77f3371df309acbfbcda2c8a0a171d633925f8109a04b871da2a90b3470e7c06
MD5 6c299d6f3436987d61ebc72584342144
BLAKE2b-256 e4b84a5489243993059357207c5d0151e4cd298396da55f7158873bf02a03aa8

See more details on using hashes here.

Provenance

The following attestation bundles were made for marin_dupekit-0.1.2.dev202606060824-cp311-abi3-macosx_10_12_x86_64.whl:

Publisher: dupekit-release-wheels.yaml on marin-community/marin

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page