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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:    ValueError
Message:      Expected object or value
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/checkpoints/[]/checkpoint) changed from string to number in row 0
              
              During handling of the above exception, another exception occurred:
              
              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 304, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value

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deep-100m-batch-update-eval

Batch-update evaluation workload package generated from deep-100m-static-search-eval.

Dataset

Source static dataset: deep-100m-static-search-eval
Vector count: 100,000,000
Dimension: 96
Dtype: float32
Metric: l2
Initial update index: 80,000,000 vectors with external labels equal to A = P[0:80M]
Update order: update_order.u32, a seed-42 permutation of source IDs [0, 100M)
Insert vector source: base_permuted.fbin, where row j equals base.fbin[P[j]]

Traces

insert-20: starts from A, then inserts P[80M:100M] in twenty 1,000,000-vector batches.
delete-20: starts from the static 100M state, then deletes P[80M:100M] in twenty 1,000,000-vector batches.
mixed-replace-100: keeps 80M live vectors for 100 rounds; each round deletes a cyclic 1,000,000 source-ID slice and inserts base_permuted.fbin row ranges: batches 1-20 use rows 80M:100M, then batches 21-100 use rows 0:80M. Insert external IDs use existing P[80M:100M] labels for the first 20 rounds, then new labels in [100,000,000, 180,000,000).

Batch JSON files use compact descriptors (range, u32_slice, and u32_cyclic_slice) instead of inline million-ID arrays. Insert external_ids continue to express user-visible source IDs. Insert vector_refs are row ranges in the reordered insert source and must be read from base_permuted.fbin.

Ground Truth

Checkpoint ground truth is produced by filtering the static source ground truth in source-distance order through the checkpoint owner map. Files are exact top-10 only when every query retains at least 10 active candidates from the static source GT depth. If a checkpoint cannot provide top-10 for every query, the package writes a matching .invalid.json marker instead of padding.

Files

workload.json: workload contract.
static-workload-reference.json: immutable static-search-eval references.
source_manifest.json: generation manifest.
update_order.u32: seed-42 source-ID permutation.
initial/index_80m_m32_efc500: HNSW index built from base[A] with labels A.
groundtruth/active_80m.bin: initial 80M checkpoint GT, or active_80m.invalid.json.
initial/layout-sidecar/index_80m_m32_efc500.*: optional runtime layout sidecar for the initial HNSW index.
initial/pq/pq_m<M>.*: initial 80M PQ artifacts reordered for initial/index_80m_m32_efc500 internal IDs.
initial_pq_manifest.json: source static PQ files and validation samples for the reordered initial PQ artifacts.
base_permuted.fbin: reordered insert vector source, present when insert vector_refs are row ranges.
reordered_insert_manifest.json: source, formula, size, and sample-check manifest for base_permuted.fbin.
traces/*/trace.json: trace metadata.
traces/*/batches/*.json: compact batch descriptors.
traces/*/groundtruth/*: checkpoint GT or invalid markers.
checksums.sha256: checksums for generated package files.

Static PQ codebooks and metadata are reused. initial/pq/pq_m<M>.pqcodes contains only 80,000,000 rows and is ordered by the initial HNSW internal ID, so it can be used directly with initial/index_80m_m32_efc500.

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