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Version: 0.5.1

Gravitino connector - Iceberg catalog

Apache Iceberg is an open table format for huge analytic datasets. The Iceberg catalog allows Trino querying data stored in files written in Iceberg format, as defined in the Iceberg Table Spec. The catalog supports Apache Iceberg table spec versions 1 and 2.


To use Iceberg, you need:

  • Network access from the Trino coordinator and workers to the distributed object storage.
  • Access to a Hive metastore service (HMS), an AWS Glue catalog, a JDBC catalog, a REST catalog, or a Nessie server.
  • Data files stored in a supported file format. These can be configured using file format configuration properties per catalog:
    • ORC
    • Parquet (default)

Schema operations

Create a schema

Users can create a schema through Gravitino Trino connector as follows:

CREATE SCHEMA "metalake.catalog".schema_name 

Table operations

Create table

The Gravitino connector currently supports basic Iceberg table creation statements, such as defining fields, allowing null values, and adding comments. The Gravitino connector does not support CREATE TABLE AS SELECT.

The following example shows how to create a table in the Iceberg catalog:

CREATE TABLE "metalake.catalog".schema_name.table_name
name varchar,
salary int

Alter table

Support for the following alter table operations:

  • Rename table
  • Add a column
  • Drop a column
  • Rename a column
  • Change a column type
  • Set a table property


The Gravitino connector supports most SELECT statements, allowing the execution of queries successfully. Currently, it doesn't support certain query optimizations, such as pushdown and pruning functionalities.

Table and Schema properties

Create a schema with properties

Iceberg schema does not support properties.

Create a table with properties

Users can use the following example to create a table with properties:

CREATE TABLE "metalake.catalog".dbname.tabname
name varchar,
salary int
) WITH (
format = 'TEXTFILE',

The following tables are the properties supported by the Iceberg table:

PropertyDescriptionDefault ValueRequiredReservedSince Version
partitioningPartition columns for the table(none)NoNo0.4.0
sorted_bySorted columns for the table(none)NoNo0.4.0

Reserved properties: A reserved property is one can't be set by users but can be read by users.

Basic usage examples

You need to do the following steps before you can use the Iceberg catalog in Trino through Gravitino.

  • Create a metalake and catalog in Gravitino. Assuming that the metalake name is test and the catalog name is iceberg_test, then you can use the following code to create them in Gravitino:
curl -X POST -H "Content-Type: application/json" \
-d '{
"name": "test",
"comment": "comment",
"properties": {}
}' http://gravitino-host:8090/api/metalakes

curl -X POST -H "Content-Type: application/json" \
-d '{
"name": "iceberg_test",
"type": "RELATIONAL",
"comment": "comment",
"provider": "lakehouse-iceberg",
"properties": {
"uri": "thrift://hive-host:9083",
"catalog-backend": "hive",
"warehouse": "hdfs://hdfs-host:9000/user/iceberg/warehouse"
}' http://gravitino-host:8090/api/metalakes/test/catalogs

For More information about the Iceberg catalog, please refer to Iceberg catalog.

  • Set the value of configuration gravitino.metalake to the metalake you have created, named 'test', and start the Trino container.

Use the Trino CLI to connect to the Trino container and run a query.

Listing all Gravitino managed catalogs:


The results are similar to:

(4 rows)

Query 20231017_082503_00018_6nt3n, FINISHED, 1 node

The gravitino catalog is a catalog defined By Trino catalog configuration. The test.iceberg_test catalog is the catalog created by you in Gravitino. Other catalogs are regular user-configured Trino catalogs.

Creating tables and schemas

Create a new schema named database_01 in test.iceberg_test catalog.

CREATE SCHEMA iceberg_test.database_01;

Create a new table named table_01 in schema "test.iceberg_test".database_01.

CREATE TABLE iceberg_test.database_01.table_01
name varchar,
salary int
) with (
partitioning = ARRAY['salary'],
sorted_by = ARRAY['name']

Writing data

Insert data into the table table_01:

INSERT INTO iceberg_test.database_01.table_01 (name, salary) VALUES ('ice', 12);

Insert data into the table table_01 from select:

INSERT INTO iceberg_test.database_01.table_01 (name, salary) SELECT * FROM "test.iceberg_test".database_01.table_01;

Querying data

Query the table_01 table:

SELECT * FROM "test.iceberg_test".database_01.table_01;

Modify a table

Add a new column age to the table_01 table:

ALTER TABLE "test.iceberg_test".database_01.table_01 ADD COLUMN age int;

Drop a column age from the table_01 table:

ALTER TABLE "test.iceberg_test".database_01.table_01 DROP COLUMN age;

Rename the table_01 table to table_02:

ALTER TABLE "test.iceberg_test".database_01.table_01 RENAME TO "test.iceberg_test".database_01.table_02;


Drop a schema:

DROP SCHEMA "test.iceberg_test".database_01;

Drop a table:

DROP TABLE "test.iceberg_test".database_01.table_01;

HDFS username and permissions

Before running any Insert statements for Iceberg tables in Trino, you must check that the user Trino is using to access HDFS has access to the warehouse directory. You can override this username by setting the HADOOP_USER_NAME system property in the Trino JVM config, replacing hdfs_user with the appropriate username: