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The Iceberg catalog is checked against Spark, Trino, ClickHouse, Doris,
Dremio and RisingWave. The Lance one had only its own reference client,
which is the same thing as checking it against ourselves.
LanceDB connects with connect_namespace("rest", ...), which speaks the
routes this catalog implements, so the suite exercises the protocol rather
than our idea of it: list the catalog, open a table through it, read the
schema, run a vector search and a filtered scan, create a table, and read
the same dataset straight off its URI with no catalog at all.
table_names -> ['lancedb-p0guidmm$ml$embeddings']
open_table -> 64 rows
search -> [1, 0, 2]
create_table -> 4 rows, listed by the catalog
direct read without the catalog -> 64 rows
Seeding is pylance, because the namespace records where a table lives and
does not carry its data. That split is the design rather than a limit of
the test.
One interop note the test encodes: a gateway without STS vends
storage_options carrying an endpoint and a region but no credentials, and
LanceDB uses what the namespace vends on some paths. The container gets
credentials in its environment as well, which is what a deployment without
STS would do.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
210 lines
8.2 KiB
Python
210 lines
8.2 KiB
Python
#!/usr/bin/env python3
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"""Drive the SeaweedFS Lance Namespace with LanceDB.
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The existing client test uses `lance_namespace` and `pylance` directly, which is
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the protocol's reference client. LanceDB is what people actually point at a
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catalog: it connects with `connect_namespace("rest", ...)`, lists what is there,
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opens a table and searches it. This checks the catalog against that path, the
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way the Spark, Trino and ClickHouse suites check the Iceberg one.
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Everything it prints is either "PASS" or a line starting with FAIL, so the Go
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harness can report the first real failure rather than a stack trace.
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"""
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import argparse
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import sys
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import warnings
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warnings.filterwarnings("ignore")
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import lance
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import lance_namespace as ln
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import lancedb
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import pyarrow as pa
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DIM = 8
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def sample_rows(count):
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"""A vector table, which is the only kind worth putting in Lance."""
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return pa.table(
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{
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"id": pa.array(list(range(count)), type=pa.int64()),
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"title": pa.array([f"row-{i}" for i in range(count)]),
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"vector": pa.array(
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[[float(i) + d for d in range(DIM)] for i in range(count)],
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type=pa.list_(pa.float32(), DIM),
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),
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}
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)
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def seed_table(namespace_url, storage, bucket, namespace, table, rows):
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"""Declares a table through the namespace and writes a dataset into it.
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LanceDB reads through the catalog; the writing half is pylance, because the
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namespace records where a table lives and does not carry its data.
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"""
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ns = ln.connect("rest", {"uri": namespace_url})
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ns.create_namespace(
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ln.CreateNamespaceRequest(id=[bucket], mode="EXIST_OK")
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)
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ns.create_namespace(
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ln.CreateNamespaceRequest(id=[bucket, namespace], mode="EXIST_OK")
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)
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table_id = [bucket, namespace, table]
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declared = ns.declare_table(ln.DeclareTableRequest(id=table_id))
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lance.write_dataset(
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sample_rows(rows), declared.location, storage_options=storage, mode="overwrite"
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)
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print(f"seeded {rows} rows at {declared.location}")
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return declared.location
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def check(condition, message):
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if not condition:
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print(f"FAIL: {message}", file=sys.stderr)
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raise SystemExit(1)
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def main():
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--namespace-url", required=True)
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parser.add_argument("--s3-endpoint", required=True)
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parser.add_argument("--bucket", required=True)
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parser.add_argument("--namespace", default="ml")
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parser.add_argument("--table", default="embeddings")
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parser.add_argument("--rows", type=int, default=64)
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parser.add_argument("--access-key", default="any")
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parser.add_argument("--secret-key", default="any")
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args = parser.parse_args()
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# The namespace vends an endpoint correct for its own host; a container
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# reaches the same gateway by another name, so the endpoint is overridden
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# here and the credentials filled in for a deployment without STS.
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storage = {
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"aws_endpoint": args.s3_endpoint,
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"allow_http": "true",
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"aws_access_key_id": args.access_key,
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"aws_secret_access_key": args.secret_key,
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"aws_region": "us-east-1",
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}
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location = seed_table(
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args.namespace_url, storage, args.bucket, args.namespace, args.table, args.rows
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)
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print(f"lancedb {lancedb.__version__} connecting to {args.namespace_url}")
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db = lancedb.connect_namespace(
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"rest", {"uri": args.namespace_url}, storage_options=storage
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)
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# 1. The catalog is browsable: the bucket is a namespace, and the table is
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# in it under the name the namespace gave it.
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tables = list(db.table_names(namespace_path=[args.bucket, args.namespace], limit=100))
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print(f"table_names -> {tables}")
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check(
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any(args.table in name for name in tables),
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f"{args.table} is not listed in {tables}",
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)
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# 2. Opening it goes through the catalog: LanceDB asks the namespace where
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# the table is and reads it from there.
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# storage_options is passed per call as well as on the connection: what the
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# namespace vends for a table is merged in, and a deployment without STS
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# vends no credentials, which is what the client would otherwise be left with.
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table = db.open_table(
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args.table,
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namespace_path=[args.bucket, args.namespace],
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storage_options=storage,
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)
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count = table.count_rows()
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print(f"open_table -> {count} rows")
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check(count == args.rows, f"read {count} rows, want {args.rows}")
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# 3. The schema survived the round trip, vector column included. This is the
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# part a catalog that only records a location cannot fake.
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names = table.schema.names
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print(f"schema -> {names}")
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check("vector" in names and "title" in names, f"schema lost columns: {names}")
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# 4. A vector search, which is what the format exists for.
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query = [float(1) + d for d in range(DIM)]
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hits = table.search(query).limit(3).to_list()
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print(f"search -> {[hit['id'] for hit in hits]}")
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check(len(hits) == 3, f"search returned {len(hits)} hits, want 3")
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check(hits[0]["id"] == 1, f"nearest neighbour was id={hits[0]['id']}, want 1")
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# 5. A filtered scan, so it is not only the ANN path that works.
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filtered = table.search().where("id < 5").limit(10).to_list()
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print(f"filtered scan -> {len(filtered)} rows")
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check(len(filtered) == 5, f"filter returned {len(filtered)} rows, want 5")
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# 6. Creating a table. By default LanceDB declares it through the namespace
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# and writes the data itself, which is exactly the split this catalog
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# serves, so this has to work.
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created = db.create_table(
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"created_by_lancedb",
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data=sample_rows(4),
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namespace_path=[args.bucket, args.namespace],
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storage_options=storage,
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)
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check(created.count_rows() == 4, "create_table wrote the wrong number of rows")
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listed = list(db.table_names(namespace_path=[args.bucket, args.namespace], limit=100))
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check(
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any("created_by_lancedb" in name for name in listed),
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f"a table created through LanceDB is not listed: {listed}",
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)
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print(f"create_table -> {created.count_rows()} rows, listed by the catalog")
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# 7. The same creation with server-side pushdown, which asks the namespace
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# to run CreateTable itself. That operation carries Arrow data and this
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# catalog answers the spec's Unsupported for it. What matters is that the
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# client is left with something coherent either way - it falls back to
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# declare-and-write - rather than a hang, a 404, or a half-made table.
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pushdown = lancedb.connect_namespace(
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"rest",
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{"uri": args.namespace_url},
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storage_options=storage,
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namespace_client_pushdown_operations=["CreateTable"],
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)
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pushed_ok = True
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try:
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pushdown.create_table(
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"pushed_by_lancedb",
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data=sample_rows(2),
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namespace_path=[args.bucket, args.namespace],
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storage_options=storage,
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)
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except Exception as err: # noqa: BLE001 - the point is what the client sees
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pushed_ok = False
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print(f"create_table with pushdown: refused with {type(err).__name__}: {err}")
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after = list(db.table_names(namespace_path=[args.bucket, args.namespace], limit=100))
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landed = any("pushed_by_lancedb" in name for name in after)
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print(f"create_table with pushdown: client ok={pushed_ok}, catalog has it={landed}")
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check(
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pushed_ok == landed,
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f"the client and the catalog disagree: client ok={pushed_ok}, listed={landed}",
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)
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if landed:
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rows = db.open_table(
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"pushed_by_lancedb",
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namespace_path=[args.bucket, args.namespace],
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storage_options=storage,
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).count_rows()
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check(rows == 2, f"the pushed table holds {rows} rows, want 2")
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# 8. And the dataset is still readable straight off its URI, which is what
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# keeps the catalog optional.
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direct = lance.dataset(location, storage_options=storage).count_rows()
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check(direct == args.rows, f"direct read got {direct} rows, want {args.rows}")
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print(f"direct read without the catalog -> {direct} rows")
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print("PASS")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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