Recover accidentally deleted Databricks managed tables using the UNDROP command. Learn permissions requirements, how to list dropped tables, and step-by-step recovery with real SQL examples.
Source: official Databricks documentation · Databricks announcement
Key takeaways
- UNDROP recovers accidentally deleted managed tables; requires Unity Catalog and DBR 11.1 or above.
- Four permission models enable table recovery: metastore owner, catalog owner, schema owner plus create table, or table owner.
- SHOW TABLES DROPPED lists dropped tables with name, ID, catalog, schema, and managed/external status.
- UNDROP accepts table name or table ID for recovery; deleted tables remain recoverable within retention window.
- Catalog browser allows schema navigation without leaving notebooks; copy full table paths easily.
- Table recovery requires appropriate ownership or grant permissions from permissions holders.
Chapters
- 0:00 — UNDROP Feature & Requirements
- 0:32 — Catalog Browser: Schema Navigation
- 1:03 — Permissions Model for Table Recovery
- 1:34 — SHOW TABLES DROPPED: List Deleted Tables
- 2:07 — UNDROP Command: Recovery Execution
Frequently asked questions
What permissions are required to undrop a table?
One of: metastore owner, catalog owner, schema owner with create table permissions, or table owner. Users without required permissions can request grants.
How do you find and recover a deleted table?
Run SHOW TABLES DROPPED IN <schema> to list deleted tables with IDs. Then UNDROP TABLE <name> or UNDROP TABLE WITH ID <id> to restore.
What information does SHOW TABLES DROPPED provide?
The command shows table name, ID, catalog, schema, and whether the table was managed or external. This helps identify the correct table if multiple deletions occurred.
Full transcript
Auto-generated from the video and lightly edited for readability. Timestamps link to the moment in the video.
Show full transcript (7 segments)
0:00hello my name is Yousef and today I will show you how to undrop a table this is the new feature that just has been released and it's required of course to have a Unity catalog and to use a dbr 11.1 or above let's just go to uh
0:22the notebook and of course we have also a new feature that you can benefit which will help you to browse your catalogs and schemas without leaving the notebook and here as you can see I'm filtering using the name of my catalog and then I can browse the catalog the schema and of course the table I can also copy the
0:45path and so on so for my case I'm gonna use the demo UC underscore usap I'm gonna use the schema both and of course I will query my table called Titanic and now I will drop this table and to and drop the table in order to bring it back you need to have one of
1:09the following permissions so either the user is the owner of the meta store or the user is the owner of the catalog or the user course has the used catalog on the catalog and is the owner of the schema or the user has the use catalog and the use schema create table and a
1:31user is the owner of the table of course you can ask uh someone to Grant you the permission so for my case I'm granting myself to use catalog and a u schema then we create table on the specific schema and of course you can list quickly all the tables that has been dropped in a specific schema with the
1:55command show tables dropped in the schema it shows you the name of the catalog the schema name the table name the table ID whether the table is managed or external and you can bring back this table using uh or you will have two options it's either and drop table with the name of the table or Android table with ID and
2:19you need to add this table ID so I'm Android paying the table and now you can see I can query disable back again thank you for watching this video
Official Databricks resources
- Unity Catalog documentation — docs
- Databricks Free Edition — product
- What is a Data and AI Platform? (Databricks blog) — blog
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Databricks Answers
Looking for a quick, source-backed answer? Browse Databricks Answers on Delta Lake & storage optimization — direct, documentation-validated answers to common Databricks questions, curated by Youssef Mrini, Senior Developer Advocate at Databricks.