Introduction

The TestUC4001 – Table Not Found error in Databricks Unity Catalog indicates that the specified table is not available in the current catalog, schema, or workspace. This can result from incorrect catalog or schema selection, missing table registration, permission issues, or table deletion. If not resolved, it can disrupt queries, jobs, and data pipelines.

🚨 Common symptoms of TestUC4001:

• Error: “TestUC4001 – Table Not Found: my_table.”
• Queries referencing a table fail to execute.
• SHOW TABLES returns an empty list, even though the table should exist.
• Cannot switch catalogs or schemas to access the table.

Common Causes and Fixes for TestUC4001

1. Incorrect Catalog or Schema Selection

Symptoms:

• Error: “Table my_table not found in schema my_schema.”
• Running SHOW TABLES returns an empty list.
• Cannot query the table even though it was previously accessible.

Causes:

• The table resides in a different catalog or schema than the one currently in use.
• USE command was not executed, resulting in a different default schema.

Fix:
✅ Verify the catalog and schema:

SHOW CATALOGS;
USE CATALOG my_catalog;
SHOW SCHEMAS;
USE SCHEMA my_schema;
SHOW TABLES;

✅ Explicitly specify the catalog and schema when querying:

SELECT * FROM my_catalog.my_schema.my_table;

✅ Ensure the table exists in the correct catalog and schema:

DESCRIBE TABLE my_catalog.my_schema.my_table;

2. Table Not Registered in Unity Catalog

Symptoms:

• Error: “Table not found.”
• Cannot query a Delta table after migrating from Hive Metastore.
• Delta table exists in storage but is not available in Unity Catalog.

Causes:

• The table was not registered in Unity Catalog during migration.
• The table was deleted from the metastore but still exists in storage.

Fix:
✅ Register the Delta table in Unity Catalog:

CREATE TABLE my_catalog.my_schema.my_table USING DELTA LOCATION 's3://my-bucket/my-table-path';

✅ Check for external Delta tables and register them:

spark.sql("CREATE TABLE my_catalog.my_schema.my_table USING DELTA LOCATION 'dbfs:/mnt/delta/my_table';")

✅ Verify that the table is registered and available:

SHOW TABLES IN my_catalog.my_schema;

3. Permissions Issues on the Table

Symptoms:

• Error: “Permission denied: Cannot access table my_table.”
• Users cannot query or view tables even though the table exists.
• Only admins can access the table.

Causes:

• Lack of necessary permissions to access the table.
• The table is restricted to specific roles or users.

Fix:
✅ Check table permissions:

SHOW GRANTS ON TABLE my_catalog.my_schema.my_table;

✅ Grant access to the required user or group:

GRANT SELECT ON TABLE my_catalog.my_schema.my_table TO `user@example.com`;

✅ Ensure users have access to the catalog and schema:

GRANT USAGE ON CATALOG my_catalog TO `user@example.com`;
GRANT USAGE ON SCHEMA my_catalog.my_schema TO `user@example.com`;

4. Table Has Been Deleted or Renamed

Symptoms:

• Error: “Table not found.”
• Previously working queries now fail.
• No records returned from SHOW TABLES.

Causes:

• The table was accidentally dropped or renamed.
• A new table version replaced the old one, causing inconsistencies.

Fix:
✅ Check the history of table operations:

DESCRIBE HISTORY my_catalog.my_schema.my_table;

✅ Restore the table if it was dropped:

RESTORE TABLE my_catalog.my_schema.my_table TO VERSION AS OF <version>;

✅ If renamed, find the new table name:

SHOW TABLES IN my_catalog.my_schema;

5. External Table Storage Issues (Cloud Storage)

Symptoms:

• Error: “Table not found.”
• Delta table exists in cloud storage (S3, ADLS, GCS) but cannot be queried.

Causes:

• Cloud storage permissions prevent Databricks from accessing the table.
• Delta table files are corrupted or missing.

Fix:
✅ Verify cloud storage access:

aws s3 ls s3://my-bucket/my-table-path/
az storage blob list --container-name my-container --account-name my-storage

✅ Ensure the Delta table is healthy:

DESCRIBE DETAIL my_catalog.my_schema.my_table;

✅ Check for missing or corrupted files and repair if necessary:

spark.sql("FSCK REPAIR TABLE my_catalog.my_schema.my_table");

Step-by-Step Troubleshooting Guide

1. Verify Current Catalog and Schema

USE CATALOG my_catalog;
USE SCHEMA my_schema;
SHOW TABLES;

2. Check If the Table Exists and Is Registered

DESCRIBE TABLE my_catalog.my_schema.my_table;

3. Check User Permissions on the Table

SHOW GRANTS ON TABLE my_catalog.my_schema.my_table;

4. Inspect Table History and Restore if Necessary

DESCRIBE HISTORY my_catalog.my_schema.my_table;
RESTORE TABLE my_catalog.my_schema.my_table TO VERSION AS OF <version>;

5. Test Cloud Storage Access for External Tables

aws s3 ls s3://my-bucket/my-table-path/

Best Practices to Avoid TestUC4001 – Table Not Found

✅ Always Specify the Full Table Name (Catalog.Schema.Table)

• Prevents confusion when switching between catalogs and schemas.

✅ Use Unity Catalog for Centralized Table Management

• Avoids conflicts with external Delta tables and legacy Hive Metastore.

✅ Regularly Audit and Backup Tables

• Use DESCRIBE HISTORY and backups to track changes.

✅ Ensure Proper Permissions Are Granted to Users

• Avoid accidental permission restrictions by reviewing grants and roles.

Conclusion

The TestUC4001 – Table Not Found error in Databricks Unity Catalog typically arises from incorrect catalog/schema selection, missing table registration, permissions issues, or external storage problems. By following the troubleshooting steps—verifying the catalog, checking table registration, reviewing permissions, and testing storage access—you can resolve this error and ensure seamless data operations.