The Apache Gravitino Spark connector leverages the Spark DataSourceV2 interface to facilitate the management of diverse catalogs under Gravitino. This capability allows users to perform federation queries, accessing data from various catalogs through a unified interface and consistent access control.
| Property | Type | Default Value | Description | Required | Since Version |
|---|---|---|---|---|---|
| spark.plugins | string | (none) | Gravitino spark plugin name, org.apache.gravitino.spark.connector.plugin.GravitinoSparkPlugin | Yes | 0.5.0 |
| spark.sql.gravitino.metalake | string | (none) | The metalake name that spark connector used to request to Gravitino. | Yes | 0.5.0 |
| spark.sql.gravitino.uri | string | (none) | The uri of Gravitino server address. | Yes | 0.5.0 |
| spark.sql.gravitino.enableIcebergSupport | string | false | Set to true to use Iceberg catalog. | No | 0.5.1 |
| spark.sql.gravitino.enablePaimonSupport | string | false | Set to true to use Paimon catalog. | No | 1.0.0 |
| spark.sql.gravitino.client. | string | (none) | The configuration key prefix for the Gravitino client config. | No | 1.0.0 |
To configure the Gravitino client, use properties prefixed with spark.sql.gravitino.client.. These properties will be passed to the Gravitino client after removing the spark.sql. prefix.
Example: Setting spark.sql.gravitino.client.socketTimeoutMs is equivalent to setting gravitino.client.socketTimeoutMs for the Gravitino client.
Note: Invalid configuration properties will result in exceptions. Please see Gravitino Java client configurations for more support client configuration.
./bin/spark-sql -v \ --conf spark.plugins="org.apache.gravitino.spark.connector.plugin.GravitinoSparkPlugin" \ --conf spark.sql.gravitino.uri=http://127.0.0.1:8090 \ --conf spark.sql.gravitino.metalake=test \ --conf spark.sql.gravitino.enableIcebergSupport=true \ --conf spark.sql.gravitino.client.socketTimeoutMs=60000 \ --conf spark.sql.gravitino.client.connectionTimeoutMs=60000 \ --conf spark.sql.warehouse.dir=hdfs://127.0.0.1:9000/user/hive/warehouse-hive
Download corresponding runtime jars and place it to the classpath of Spark if using Iceberg catalog.
Execute the Spark SQL query.
Suppose there are two catalogs in the metalake test, hive for Hive catalog and iceberg for Iceberg catalog.
// use hive catalog USE hive; CREATE DATABASE db; USE db; CREATE TABLE hive_students (id INT, name STRING); INSERT INTO hive_students VALUES (1, 'Alice'), (2, 'Bob'); // use Iceberg catalog USE iceberg; USE db; CREATE TABLE IF NOT EXISTS iceberg_scores (id INT, score INT) USING iceberg; INSERT INTO iceberg_scores VALUES (1, 95), (2, 88); // execute federation query between hive table and iceberg table SELECT hs.name, is.score FROM hive.db.hive_students hs JOIN iceberg_scores is ON hs.id = is.id;
:::info The command SHOW CATALOGS will only display the Spark default catalog, named spark_catalog, due to limitations within the Spark catalog manager. It does not list the catalogs present in the metalake. However, after explicitly using the USE command with a specific catalog name, that catalog name then becomes visible in the output of SHOW CATALOGS. :::
Gravitino spark connector support the following datatype mapping between Spark and Gravitino.
| Spark Data Type | Gravitino Data Type | Since Version |
|---|---|---|
BooleanType | boolean | 0.5.0 |
ByteType | byte | 0.5.0 |
ShortType | short | 0.5.0 |
IntegerType | integer | 0.5.0 |
LongType | long | 0.5.0 |
FloatType | float | 0.5.0 |
DoubleType | double | 0.5.0 |
DecimalType | decimal | 0.5.0 |
StringType | string | 0.5.0 |
CharType | char | 0.5.0 |
VarcharType | varchar | 0.5.0 |
TimestampType | timestamp with time zone | 0.5.0 |
TimestampNTZType | timestamp without time zone | 0.5.0 |
DateType | date | 0.5.0 |
BinaryType | binary | 0.5.0 |
ArrayType | array | 0.5.0 |
MapType | map | 0.5.0 |
StructType | struct | 0.5.0 |