Vertica
JDBC Vertica Sink Connector
Support Those Enginesâ
Spark
Flink
SeaTunnel Zeta
Descriptionâ
Write data through jdbc. Support Batch mode and Streaming mode, support concurrent writing, support exactly-once semantics (using XA transaction guarantee).
Using Dependencyâ
For Spark/Flink Engineâ
- You need to ensure that the jdbc driver jar package has been placed in directory
${SEATUNNEL_HOME}/plugins/
.
For SeaTunnel Zeta Engineâ
- You need to ensure that the jdbc driver jar package has been placed in directory
${SEATUNNEL_HOME}/lib/
.
Key Featuresâ
Use
Xa transactions
to ensureexactly-once
. So only supportexactly-once
for the database which is supportXa transactions
. You can setis_exactly_once=true
to enable it.
Supported DataSource Infoâ
Datasource | Supported Versions | Driver | Url | Maven |
---|---|---|---|---|
Vertica | Different dependency version has different driver class. | com.vertica.jdbc.Driver | jdbc:vertica://localhost:5433/vertica | Download |
Database Dependencyâ
Please download the support list corresponding to 'Maven' and copy it to the '$SEATNUNNEL_HOME/plugins/jdbc/lib/' working directory
For example Vertica datasource: cp vertica-jdbc-xxx.jar $SEATNUNNEL_HOME/plugins/jdbc/lib/
Data Type Mappingâ
Vertica Data Type | SeaTunnel Data Type |
---|---|
BIT(1) INT UNSIGNED | BOOLEAN |
TINYINT TINYINT UNSIGNED SMALLINT SMALLINT UNSIGNED MEDIUMINT MEDIUMINT UNSIGNED INT INTEGER YEAR | INT |
INT UNSIGNED INTEGER UNSIGNED BIGINT | BIGINT |
BIGINT UNSIGNED | DECIMAL(20,0) |
DECIMAL(x,y)(Get the designated column's specified column size.<38) | DECIMAL(x,y) |
DECIMAL(x,y)(Get the designated column's specified column size.>38) | DECIMAL(38,18) |
DECIMAL UNSIGNED | DECIMAL((Get the designated column's specified column size)+1, (Gets the designated column's number of digits to right of the decimal point.))) |
FLOAT FLOAT UNSIGNED | FLOAT |
DOUBLE DOUBLE UNSIGNED | DOUBLE |
CHAR VARCHAR TINYTEXT MEDIUMTEXT TEXT LONGTEXT JSON | STRING |
DATE | DATE |
TIME | TIME |
DATETIME TIMESTAMP | TIMESTAMP |
TINYBLOB MEDIUMBLOB BLOB LONGBLOB BINARY VARBINAR BIT(n) | BYTES |
GEOMETRY UNKNOWN | Not supported yet |
Sink Optionsâ
Name | Type | Required | Default | Description |
---|---|---|---|---|
url | String | Yes | - | The URL of the JDBC connection. Refer to a case: jdbc:vertica://localhost:5433/vertica |
driver | String | Yes | - | The jdbc class name used to connect to the remote data source, if you use Vertical the value is com.vertica.jdbc.Driver . |
user | String | No | - | Connection instance user name |
password | String | No | - | Connection instance password |
query | String | No | - | Use this sql write upstream input datas to database. e.g INSERT ... ,query have the higher priority |
database | String | No | - | Use this database and table-name auto-generate sql and receive upstream input datas write to database.This option is mutually exclusive with query and has a higher priority. |
table | String | No | - | Use database and this table-name auto-generate sql and receive upstream input datas write to database. This option is mutually exclusive with query and has a higher priority. |
primary_keys | Array | No | - | This option is used to support operations such as insert , delete , and update when automatically generate sql. |
support_upsert_by_query_primary_key_exist | Boolean | No | false | Choose to use INSERT sql, UPDATE sql to process update events(INSERT, UPDATE_AFTER) based on query primary key exists. This configuration is only used when database unsupport upsert syntax. Note: that this method has low performance |
connection_check_timeout_sec | Int | No | 30 | The time in seconds to wait for the database operation used to validate the connection to complete. |
max_retries | Int | No | 0 | The number of retries to submit failed (executeBatch) |
batch_size | Int | No | 1000 | For batch writing, when the number of buffered records reaches the number of batch_size or the time reaches checkpoint.interval , the data will be flushed into the database |
is_exactly_once | Boolean | No | false | Whether to enable exactly-once semantics, which will use Xa transactions. If on, you need to set xa_data_source_class_name . |
generate_sink_sql | Boolean | No | false | Generate sql statements based on the database table you want to write to |
xa_data_source_class_name | String | No | - | The xa data source class name of the database Driver, for example, vertical is com.vertical.cj.jdbc.VerticalXADataSource , andplease refer to appendix for other data sources |
max_commit_attempts | Int | No | 3 | The number of retries for transaction commit failures |
transaction_timeout_sec | Int | No | -1 | The timeout after the transaction is opened, the default is -1 (never timeout). Note that setting the timeout may affect exactly-once semantics |
auto_commit | Boolean | No | true | Automatic transaction commit is enabled by default |
properties | Map | No | - | Additional connection configuration parameters,when properties and URL have the same parameters, the priority is determined by the specific implementation of the driver. For example, in MySQL, properties take precedence over the URL. |
common-options | no | - | Sink plugin common parameters, please refer to Sink Common Options for details | |
enable_upsert | Boolean | No | true | Enable upsert by primary_keys exist, If the task has no key duplicate data, setting this parameter to false can speed up data import |
Tipsâ
If partition_column is not set, it will run in single concurrency, and if partition_column is set, it will be executed in parallel according to the concurrency of tasks.
Task Exampleâ
Simple:â
This example defines a SeaTunnel synchronization task that automatically generates data through FakeSource and sends it to JDBC Sink. FakeSource generates a total of 16 rows of data (row.num=16), with each row having two fields, name (string type) and age (int type). The final target table is test_table will also be 16 rows of data in the table. Before run this job, you need create database test and table test_table in your vertical. And if you have not yet installed and deployed SeaTunnel, you need to follow the instructions in Install SeaTunnel to install and deploy SeaTunnel. And then follow the instructions in Quick Start With SeaTunnel Engine to run this job.
# Defining the runtime environment
env {
parallelism = 1
job.mode = "BATCH"
}
source {
# This is a example source plugin **only for test and demonstrate the feature source plugin**
FakeSource {
parallelism = 1
result_table_name = "fake"
row.num = 16
schema = {
fields {
name = "string"
age = "int"
}
}
}
# If you would like to get more information about how to configure seatunnel and see full list of source plugins,
# please go to https://seatunnel.apache.org/docs/category/source-v2
}
transform {
# If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
# please go to https://seatunnel.apache.org/docs/category/transform-v2
}
sink {
jdbc {
url = "jdbc:vertica://localhost:5433/vertica"
driver = "com.vertica.jdbc.Driver"
user = "root"
password = "123456"
query = "insert into test_table(name,age) values(?,?)"
}
# If you would like to get more information about how to configure seatunnel and see full list of sink plugins,
# please go to https://seatunnel.apache.org/docs/category/sink-v2
}
Generate Sink SQLâ
This example not need to write complex sql statements, you can configure the database name table name to automatically generate add statements for you
sink {
jdbc {
url = "jdbc:vertica://localhost:5433/vertica"
driver = "com.vertica.jdbc.Driver"
user = "root"
password = "123456"
# Automatically generate sql statements based on database table names
generate_sink_sql = true
database = test
table = test_table
}
}
Exactly-once :â
For accurate write scene we guarantee accurate once
sink {
jdbc {
url = "jdbc:vertica://localhost:5433/vertica"
driver = "com.vertica.jdbc.Driver"
max_retries = 0
user = "root"
password = "123456"
query = "insert into test_table(name,age) values(?,?)"
is_exactly_once = "true"
xa_data_source_class_name = "com.vertical.cj.jdbc.VerticalXADataSource"
}
}