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Chris LuandGitHub
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* test: drive the Lance namespace with Spark
The counterpart of catalog_spark, which does this for the Iceberg REST
catalog. Spark is the engine most likely to be pointed at a lakehouse,
and it reaches the Lance catalog through the connector's DSV2 catalog -
org.lance.spark.LanceNamespaceSparkCatalog with impl=rest - over the same
routes every other client uses.
SHOW NAMESPACES -> ['`sparklance-lcephd80`.ml']
SHOW TABLES -> ['sparklance-lcephd80$ml$embeddings']
count -> 3
filtered -> [(2, 'two'), (3, 'three')]
count after a second commit -> 4
The second insert is there on purpose: a store that cannot order commits
fails on the second one, not the first.
Two things the run settled that were guesses beforehand. CREATE TABLE
works, because the connector declares through the namespace and writes the
data itself rather than pushing Arrow at the server. And SHOW TABLES
returns the namespace's own identifiers - bucket, namespace and name
joined by the delimiter - not bare Spark table names.
Credentials go under the catalog's storage.* prefix, which is handed to
lance as object_store options; a gateway without STS vends none, the same
trap the LanceDB suite documents.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: verify the Lance table bucket was actually created
weed shell prints a command's own failure and still exits 0, so the harness
would go on to blame Spark for a bucket that was never made.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: bound the Docker probe
An unhealthy daemon makes docker version hang, and the probe runs before the
test has a timeout of its own.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: keep the ivy cache under the user's cache directory
It is mounted into a container running as root, so a shared temp path lets
another local user pre-create it and choose what Spark loads.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: assert the vector column's type, not only its name
A column that came back as array<double> or array<string> would still be
called vector and still pass.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: read the dataset off its location for real
The catalog being optional is the property that lets duckdb and pandas read
these tables; it was asserted in a comment and printed, never exercised.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: do not persist credentials in the Spark Lance checkout
The job only uploads a log on failure; nothing in it pushes.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
* test: say the hosts in the README are placeholders
The suite passes dynamically allocated host.docker.internal ports.
Claude-Session: https://claude.ai/code/session_01Rkp1Mw5E89Jp6dzJFYiMrm
Populate data run:
- make -C test/s3tables help
- make -C test/s3tables populate-trino
- make -C test/s3tables populate-spark
Run:
- make -C test/s3tables populate
- If your account id differs, override: make -C test/s3tables populate
TABLE_ACCOUNT_ID=000000000000