Dataset Viewer

Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
format: string
version: int64
space: string
dtype: string
dim: int64
distance_type: string
payload_bytes_per_vector: int64
index_file: string
index_file_size: int64
max_elements: int64
cur_element_count: int64
size_data_per_element: int64
label_offset: int64
offset_data: int64
max_M: int64
max_M0: int64
M: int64
ef_construction: int64
elapsed_seconds: double
start_time: string
command: list<item: string>
  child 0, item: string
end_time: string
sidecar: string
threads: int64
dataset: string
index_path: string
index_bytes: int64
to
{'M': Value('int64'), 'command': List(Value('string')), 'dataset': Value('string'), 'dtype': Value('string'), 'ef_construction': Value('int64'), 'elapsed_seconds': Value('float64'), 'end_time': Value('string'), 'index_bytes': Value('int64'), 'index_path': Value('string'), 'sidecar': Value('string'), 'space': Value('string'), 'start_time': Value('string'), 'threads': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              format: string
              version: int64
              space: string
              dtype: string
              dim: int64
              distance_type: string
              payload_bytes_per_vector: int64
              index_file: string
              index_file_size: int64
              max_elements: int64
              cur_element_count: int64
              size_data_per_element: int64
              label_offset: int64
              offset_data: int64
              max_M: int64
              max_M0: int64
              M: int64
              ef_construction: int64
              elapsed_seconds: double
              start_time: string
              command: list<item: string>
                child 0, item: string
              end_time: string
              sidecar: string
              threads: int64
              dataset: string
              index_path: string
              index_bytes: int64
              to
              {'M': Value('int64'), 'command': List(Value('string')), 'dataset': Value('string'), 'dtype': Value('string'), 'ef_construction': Value('int64'), 'elapsed_seconds': Value('float64'), 'end_time': Value('string'), 'index_bytes': Value('int64'), 'index_path': Value('string'), 'sidecar': Value('string'), 'space': Value('string'), 'start_time': Value('string'), 'threads': Value('int64')}
              because column names don't match

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bigann-100m-static-search-eval

Static 100M search-evaluation dataset with original vectors, original query/ground-truth files, a rebuilt hnswlib HNSW index, and generated PQ artifacts.

Files

Base: base.u8bin
HNSW index: index_m_32_ef_500
Query: orig_query_10k.u8bin
Ground truth: groundtruth.bin
Checksums: checksums.sha256
Kaggle metadata is provided via dataset-metadata.json during upload and is stored by Kaggle as dataset configuration, not as a listed data file.

Data Sources

base.u8bin -> base.u8bin
unif_query_10k.u8bin -> orig_query_10k.u8bin
unif_groundtruth_10k.bin -> groundtruth.bin

Source license/terms note: Original source terms apply; Kaggle metadata uses license other.

Dataset Properties

Vector count: 100000000
Dimension: 128
Dtype: uint8
Metric: l2
Query count label: 10k
Query count: 10000

Environment

CPU threads used: 96
Python: Python 3.10.12
hnswlib package version: unknown
hnswlib git commit: fe873b1cee484795bd254088c0d4579f567f1979
faiss: 1.14.3
numpy: 2.2.6
kaggle: unknown
kagglehub: 1.0.2
vectordb-cxl commit: 73e82318a4c346b64b8c645d030ac86696351632

HNSW Index

Parameters: M=32, ef_construction=500
Index dtype: uint8
hnswlib space: l2
Thread count: 96
Build start: 2026-07-04 23:38:36 UTC
Build end: 2026-07-05 01:29:06 UTC
Build elapsed seconds: 6630.319
Built from original base vectors: true
Prebuilt Kaggle index reused: false

Primary Search

Parameters: ef_search=150, k=10
Thread count: 96
Recall@10: 0.984250
Batch throughput qps: 5487.035622
Latency mean_ms: 17.166175
Latency p50_ms: 1.833859
Latency p95_ms: 2.784008
Latency p99_ms: 22.797722
Instrumented latency from batch run: True
Search elapsed seconds: 1.822478

Optional ef_search Sweep

Not run unless a search_sweep.json file is included and referenced in the status log.

PQ

Implementation path: cpp

Fallback used: False

Thread count: 96

Elapsed seconds: 1502.026

Final m values: m8, m16, m32

Kaggle upload file names: pq_m8.pqcodes/.pqmeta/.pqcodebook, pq_m16.pqcodes/.pqmeta/.pqcodebook, pq_m32.pqcodes/.pqmeta/.pqcodebook

Downloads last month: -

Total file size:

59.4 GB