This page shows you how to resolve common issues with the Google Cloud Lakehouse and its associated resources.
Cannot create views over Lakehouse Apache Iceberg REST catalog endpoint tables
This issue occurs when you try to create a view in BigQuery over a Lakehouse Iceberg REST catalog table managed by the Iceberg REST catalog endpoint.
Creating views over these tables is not supported.
Cannot query metadata tables
This issue occurs when you query metadata tables, such as .snapshots or
.files, for your Lakehouse Iceberg REST catalog tables in
BigQuery using a five-part name identifier.
To resolve this issue, query these tables using Apache Spark.
metadata.json file size limit
The Apache Iceberg metadata.json file size is limited to 1MB. This limit
applies to the metadata file that tracks table snapshots, schemas, and partition
specs. If your metadata file exceeds this size, you might encounter errors when
performing table operations through the Apache Iceberg REST catalog endpoint.
To resolve this issue, request a limit increase by contacting your Google account team.
NOT_FOUND errors when querying multi-region catalogs
This issue occurs when you create a catalog in the Lakehouse runtime catalog
using a multi-region Cloud Storage bucket without specifying a primary
location, and then attempt to query the catalog by specifying a
BigQuery virtual region (such as US or EU).
When a catalog is created with a multi-region bucket, its metadata is stored in
specific regional locations within the geographic scope of the multi-region
rather than in the corresponding BigQuery virtual region. If you
force a query to run in a virtual region where the metadata is not present, the
query fails with a NOT_FOUND error.
To resolve this issue, specify the primary location (for example, US or EU)
when you create the catalog. For more information, see Specify primary regions
for US and EU multi-regions.