Information schema

Applies to: Databricks SQL Databricks Runtime 10.4 LTS and above Unity Catalog only

In the SYSTEM catalog, the INFORMATION_SCHEMA is a SQL standard schema that provides metadata about objects across all catalogs in the metastore. It does not contain metadata about hive_metastore objects.

Separately, each catalog created in Unity Catalog also automatically includes an information_schema that describes metadata about objects in that catalog only.

Both types of information schemas automatically filter results to include only the objects you have Unity Catalog privileges to access. This behavior differs from other Azure Databricks system tables. See How information schema system tables handle permissions.

The purpose of the information schema is to provide a SQL-based, privilege-aware, and self-describing API for accessing catalog metadata.

How information schema system tables handle permissions

system.information_schema differs from other system tables in that it implements automatic filtering. This means you see only the objects (catalogs, schemas, tables, columns, etc.) that you have privileges to access in Unity Catalog. If your privileges change, what you see in the information schema changes accordingly. For example, when you query information_schema.tables, only rows for tables you have permission to see are returned.

Like all other system tables, you need explicit USE and SELECT permissions to access and query from the information schema.

Entity relationship diagram of the information schema

The following entity relationship (ER) diagram provides an overview of a subset of information schema views and how they relate to each other.

Information schema views

Notes

• The information schema implements privilege-aware filtering. You automatically see only the objects you have Unity Catalog permissions to access. See How information schema system tables handle permissions.
• A manual sync using REPAIR TABLE may be required for some catalog metadata changes to be reflected in the information schema. For more information, see REPAIR TABLE.
• All identifiers except column and tag names are stored in the information schema as lowercase STRING. For query performance, avoid using functions like LOWER() or UPPER() on the identifier column. Instead, compare identifiers directly using lowercase values.
• To prevent query timeouts, apply selective filters when querying the information schema (e.g. WHERE table_catalog = 'main' AND table_schema = 'default'). Refer to the documentation above for a full list of columns that can be used as filters for each Information Schema table.
  • Note that LIMIT pushdown is not currently supported, so although it can truncate the results it will not improve performance.

Examples

> SELECT table_name, column_name
    FROM information_schema.columns
    WHERE data_type = 'DOUBLE'
      AND table_schema = 'information_schema';

The following are examples of workflows that use the system level information schema tables.

If you want to view all tables that have been created in the last 24 hours, your query could look like the following.

> SELECT table_name, table_owner, created_by, last_altered, last_altered_by, table_catalog
    FROM system.information_schema.tables
    WHERE  datediff(now(), last_altered) < 1;

If you want to view how many tables you have in each schema, consider the following example.

> SELECT table_schema, count(table_name)
    FROM system.information_schema.tables
    WHERE table_schema = 'tpch'
    GROUP BY table_schema
    ORDER BY 2 DESC

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