DESCRIBE TABLE

Applies to: check marked yes Databricks SQL check marked yes Databricks Runtime

Returns the basic metadata information of a table. The metadata information includes column name, column type and column comment. Optionally, you can specify a partition spec or column name to return the metadata pertaining to a partition or column respectively. With Delta tables, not all fields are returned.

The metadata is either returned in report form or as a JSON document.

Important

The non-JSON output of DESCRIBE TABLE can change, and new columns might be appended over time. Avoid relying on the output meeting a specific size or schema. For programmatic consumption, use DESCRIBE TABLE ... AS JSON.

Syntax

{ DESC | DESCRIBE } [ TABLE ] [ EXTENDED ] table_name { [ PARTITION clause ] | [ column_name ] } [ AS JSON ]

For compatibility FORMATTED can be specified as a synonym for EXTENDED.

Parameters

  • EXTENDED

    If specified display detailed information about the specified columns, including the column statistics collected by the command, and additional metadata information (such as schema qualifier, owner, and access time).

    In Databricks SQL and Databricks Runtime 19 and above, the extended metadata for a view includes SQL Path, the PATH captured when the view was created. With AS JSON, that value is the sql_path field.

  • table_name

    Identifies the table to be described. The name may not use a temporal specification or options specification. If the table cannot be found Azure Databricks raises a TABLE_OR_VIEW_NOT_FOUND error.

  • PARTITION clause

    An optional parameter directing Databricks SQL to return addition metadata for the named partitions.

  • column_name

    An optional parameter with the column name that needs to be described. Currently nested columns are not allowed to be specified.

    JSON format is supported for individual columns.

  • AS JSON

    Applies to: check marked yes Databricks SQL check marked yes Databricks Runtime 16.2 and above

    Optionally returns the table metadata as a JSON string instead of a human-readable report. Use this format when parsing the result using a program.

    Only supported when EXTENDED format is specified.

Parameters partition_spec and column_name are mutually exclusive and cannot be specified together.

Note

For a parameterized metric view, DESCRIBE TABLE lists the view parameters after the column metadata under a # Parameters heading, reusing the col_name, data_type, and comment fields. Parameter default values are not shown. With AS JSON, parameters are returned in a parameters field that includes each parameter's name, type, and default. Parameters require Databricks Runtime 18.2 and above.

For a Unity Catalog metric view that has relationships (Beta), DESCRIBE TABLE EXTENDED lists them under a # Constraints heading, with one row for each relationship. With AS JSON, relationships are returned in the table_constraints field. Relationships require Databricks Runtime 19 and above.

JSON formatted output

When AS JSON is specified, the output is returned as a JSON string. The following schema is supported:

{
  "table_name": "<table_name>",
  "catalog_name": "<catalog_name>",
  "schema_name": "<schema_name>",
  "namespace": ["<schema_name>"],
  "type": "<table_type>",
  "provider": "<provider>",
  "columns": [
    {
      "name": "<name>",
      "type": <type_json>,
      "comment": "<comment>",
      "nullable": <boolean>,
      "default": "<default_val>",
      "is_measure": <boolean>, // Included only for measure columns of metric views
    }
  ],
  "parameters": [ // Included only for parameterized metric views; requires Databricks Runtime 18.2 and above
    {
      "name": "<name>",
      "type": <type_json>,
      "default": "<default_val>"
    }
  ],
  "partition_values": {
    "<col_name>": "<val>"
  },
  "partition_columns": ["col1", "col2"],
  "location": "<path>",
  "view_text": "<view_text>",
  "view_original_text": "<view_original_text>",
  "view_schema_mode": "<view_schema_mode>",
  "view_catalog_and_namespace": "<view_catalog_and_namespace>",
  "view_query_output_columns": ["<col_name>"],
  "sql_path": [ // Available in Databricks Runtime 19 and above, included only for views, one object per path element
    { "catalog_name": "<catalog_name>", "namespace": ["<schema_name>"] }
  ],
  "comment": "<comment>",
  "table_properties": {
    "property1": "<property1>",
    "property2": "<property2>"
  },
  "statistics": {
    "num_rows": <count>,
    "size_in_bytes": <bytes>,
    "table_change_stats": {
      "inserted": <count>,
      "deleted": <count>,
      "updated": <count>,
      "change_percent": <percent_changed_float>
    }
  },
  "storage_properties": {
    "property1": "<property1>",
    "property2": "<property2>"
  },
  "serde_library": "<serde_library>",
  "input_format": "<input_format>",
  "output_format": "<output_format>",
  "num_buckets": <num_buckets>,
  "bucket_columns": ["<col_name>"],
  "sort_columns": ["<col_name>"],
  "created_time": "<timestamp_ISO-8601>",
  "created_by": "<created_by>",
  "last_access": "<timestamp_ISO-8601>",
  "partition_provider": "<partition_provider>",
  "collation": "<default_collation>", // Available in Databricks Runtime 16.4 and above
  "language": "<language>", // Language such as YAML, included only for metric views
  "row_filter": { // Available in Databricks Runtime 17.0 and above
     "filter_function": {
        "catalog_name": "<catalog_name>",
        "schema_name": "<schema_name>",
        "function_name: "<function_name>",
        "specific_name": "<specific_name>"
     },
     "arguments": ["<arg1>", "<arg2>"]
     },
  "column_masks": [ // Available in Databricks Runtime 17.0 and above
    {"column_name": "<column_name>",
     "mask_function": {
        "catalog_name": "<catalog_name>",
        "schema_name": "<schema_name>",
        "function_name: "<function_name>",
        "specific_name": "<specific_name>"
     },
     "arguments": ["<arg1>", "<arg2>"]
    }
  ]
  "refresh_information": { // Available in Databricks Runtime 17.3 and above, included only for materialized views and streaming tables
    "last_refreshed_at": "<timestamp_ISO-8601>",
    "last_refresh_type": "<refresh_type>",
    "latest_refresh_status": "<refresh_status>",
    "latest_refresh_link": "<refresh_url>",
    "refresh_schedule": "<schedule>"
  },
  "predictive_optimization_evaluations": { // Available in Databricks Runtime 18 and above, included only for managed tables with predictive optimization enabled
    "<operation_type>": {
      "last_run_status": "<last_run_status>",
      "last_run_time": "<timestamp_ISO-8601>",
      "latest_evaluation_time": "<timestamp_ISO-8601>",
      "latest_evaluation": "<latest_evaluation>"
    }
  }
}

Below are the schema definitions for <type_json>:

SQL Type JSON Representation
TINYINT { "name" : "tinyint" }
SMALLINT { "name" : "smallint" }
INT { "name" : "int" }
BIGINT { "name" : "bigint" }
FLOAT { "name" : "float" }
DOUBLE { "name" : "double" }
DECIMAL(p, s) { "name" : "decimal", "precision": p, "scale": s }
STRING { "name" : "string", "collation": "<collation>" }
VARCHAR(n) { "name" : "varchar", "length": n }
CHAR(n) { "name" : "char", "length": n }
BINARY { "name" : "binary" }
BOOLEAN { "name" : "boolean" }
DATE { "name" : "date" }
TIMESTAMP { "name" : "timestamp_ltz" }
TIMESTAMP_NTZ { "name" : "timestamp_ntz" }
INTERVAL start_unit TO end_unit { "name" : "interval", "start_unit": "<start_unit>", "end_unit": "<end_unit>" }
ARRAY<element_type> { "name" : "array", "element_type": <type_json>, "element_nullable": <boolean_val> }
MAP<key_type, value_type> { "name" : "map", "key_type": <type_json>, "value_type": <type_json>, "element_nullable": <boolean_val> }
STRUCT<field_name …, …> { "name" : "struct", "fields": [ {"name" : "<field_name>", "type" : <type_json>, “nullable”: <boolean_val>, "comment": “<field_comment>”, "default": “<default_val>”}] }
VARIANT { "name" : "variant" }

Examples

-- Creates a table `customer`. Assumes current schema is `salesdb`.
> CREATE TABLE customer(
        cust_id INT,
        state VARCHAR(20),
        name STRING COMMENT 'Short name'
    )
    USING parquet
    PARTITIONED BY (state);

> INSERT INTO customer PARTITION (state = 'AR') VALUES (100, 'Mike');

-- Returns basic metadata information for unqualified table `customer`
> DESCRIBE TABLE customer;
                col_name data_type    comment
 ----------------------- --------- ----------
                 cust_id       int       null
                    name    string Short name
                   state    string       null
 # Partition Information
              # col_name data_type    comment
                   state    string       null

-- Returns basic metadata information for qualified table `customer`
> DESCRIBE TABLE salesdb.customer;
                col_name data_type    comment
 ----------------------- --------- ----------
                 cust_id       int       null
                    name    string Short name
                   state    string       null
 # Partition Information
              # col_name data_type    comment
                   state    string       null

-- Returns additional metadata such as parent schema, owner, access time etc.
> DESCRIBE TABLE EXTENDED customer;
                     col_name                      data_type    comment
 ---------------------------- ------------------------------ ----------
                      cust_id                            int       null
                         name                         string Short name
                        state                         string       null
      # Partition Information
                   # col_name                      data_type    comment
                        state                         string       null

 # Detailed Table Information
                     Database                        default
                        Table                       customer
                        Owner                  <TABLE OWNER>
                 Created Time   Tue Apr 07 22:56:34 JST 2020
                  Last Access                        UNKNOWN
                   Created By                <SPARK VERSION>
                         Type                        MANAGED
                     Provider                        parquet
                     Location file:/tmp/salesdb.db/custom...
                Serde Library org.apache.hadoop.hive.ql.i...
                  InputFormat org.apache.hadoop.hive.ql.i...
                 OutputFormat org.apache.hadoop.hive.ql.i...
           Partition Provider                        Catalog

-- Returns partition metadata such as partitioning column name, column type and comment.
> DESCRIBE TABLE EXTENDED customer PARTITION (state = 'AR');
                       col_name                      data_type    comment
 ------------------------------ ------------------------------ ----------
                         cust_id                            int       null
                           name                         string Short name
                          state                         string       null
        # Partition Information
                     # col_name                      data_type    comment
                          state                         string       null

 # Detailed Partition Inform...
                       Database                        default
                          Table                       customer
               Partition Values                     [state=AR]
                       Location file:/tmp/salesdb.db/custom...
                  Serde Library org.apache.hadoop.hive.ql.i...
                    InputFormat org.apache.hadoop.hive.ql.i...
                   OutputFormat org.apache.hadoop.hive.ql.i...
             Storage Properties [serialization.format=1, pa...
           Partition Parameters {transient_lastDdlTime=1586...
                   Created Time   Tue Apr 07 23:05:43 JST 2020
                    Last Access                        UNKNOWN
           Partition Statistics                      659 bytes

          # Storage Information
                       Location file:/tmp/salesdb.db/custom...
                  Serde Library org.apache.hadoop.hive.ql.i...
                    InputFormat org.apache.hadoop.hive.ql.i...
                   OutputFormat org.apache.hadoop.hive.ql.i...
 ------------------------------ ------------------------------ ----------

-- Returns the metadata for `name` column.
-- Optional `TABLE` clause is omitted and column is fully qualified.
> DESCRIBE customer salesdb.customer.name;
 info_name info_value
 --------- ----------
  col_name       name
 data_type     string
   comment Short name

- Returns the table metadata in JSON format.
> DESCRIBE EXTENDED customer AS JSON;
{
  "table_name":"customer",
  "catalog_name":"spark_catalog",
  "schema_name":"default",
  "namespace":["default"],
  "columns":[
    {"name":"cust_id","type":{"name":"integer"},"nullable":true},
    {"name":"name","type":{"name":"string"},"comment":"Short name","nullable":true},
    {"name":"state","type":{"name":"varchar","length":20},"nullable":true}],
  "location": "file:/tmp/salesdb.db/custom...",
  "created_time":"2020-04-07T14:05:43Z",
  "last_access":"UNKNOWN",
  "created_by":"None",
  "type":"MANAGED",
  "provider":"parquet",
  "partition_provider":"Catalog",
  "partition_columns":["state"]}

-- The JSON describe of a metric view
> DESCRIBE EXTENDED region_sales_metrics AS JSON;
{
  "table_name":"region_sales_metrics",
  "catalog_name":"main",
  "namespace":["default"],
  "schema_name":"default",
  "columns":[
    {"name":"month","type":{"name":"timestamp_ltz"},"nullable":true},
    {"name":"status","type":{"name":"string","collation":"UTF8_BINARY"},"nullable":true},
    {"name":"prder_priority","type":{"name":"string","collation":"UTF8_BINARY"},"nullable":true},
    {"name":"count_orders","type":{"name":"bigint"},"nullable":false,"is_measure":true},
    {"name":"total_revenue","type":{"name":"decimal","precision":28,"scale":2},"nullable":true,"is_measure":true},
    {"name":"total_revenue_per_customer","type":{"name":"decimal","precision":38,"scale":12},"nullable":true,"is_measure":true}],
  "owner":"alf@melmak.et",
  "created_time":"2025-05-18T23:45:25Z",
  "last_access":"UNKNOWN",
  "created_by":"Spark ",
  "type":"METRIC_VIEW",
  "comment":"A metric view for regional sales metrics.",
  "view_text":"\n version: 0.1\n source: samples.tpch.orders\n filter: o_orderdate > '1990-01-01'\n dimensions:\n - name: month\n expr: date_trunc('MONTH', o_orderdate)\n - name: status\n expr: case\n when o_orderstatus = 'O' then 'Open'\n when o_orderstatus = 'P' then 'Processing'\n when o_orderstatus = 'F' then 'Fulfilled'\n end\n - name: prder_priority\n expr: split(o_orderpriority, '-')[1]\n measures:\n - name: count_orders\n expr: count(1)\n - name: total_revenue\n expr: SUM(o_totalprice)\n - name: total_revenue_per_customer\n expr: SUM(o_totalprice) / count(distinct o_custkey)\n ","language":"YAML","table_properties":{"metric_view.from.name":"samples.tpch.orders","metric_view.from.type":"ASSET","metric_view.where":"o_orderdate > '1990-01-01'"},
  "view_creation_spark_configuration":{ ... },
  "collation":"UTF8_BINARY"}

DESCRIBE DETAIL

DESCRIBE DETAIL [schema_name.]table_name

Return information about schema, partitioning, table size, and so on. For example, for Delta tables, you can see the current reader and writer versions of a table. See Review table details with describe detail for the detail schema.