Skip to main content
Version: 2.3.5

Vertica

JDBC Vertica Sink Connector

Support Those Engines​

Spark
Flink
SeaTunnel Zeta

Description​

Write data through jdbc. Support Batch mode and Streaming mode, support concurrent writing, support exactly-once semantics (using XA transaction guarantee).

Using Dependency​

  1. You need to ensure that the jdbc driver jar package has been placed in directory ${SEATUNNEL_HOME}/plugins/.

For SeaTunnel Zeta Engine​

  1. You need to ensure that the jdbc driver jar package has been placed in directory ${SEATUNNEL_HOME}/lib/.

Key Features​

Use Xa transactions to ensure exactly-once. So only support exactly-once for the database which is support Xa transactions. You can set is_exactly_once=true to enable it.

Supported DataSource Info​

DatasourceSupported VersionsDriverUrlMaven
VerticaDifferent dependency version has different driver class.com.vertica.jdbc.Driverjdbc:vertica://localhost:5433/verticaDownload

Database Dependency​

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 Mapping​

Vertica Data TypeSeaTunnel 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 UNSIGNEDDECIMAL(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 UNSIGNEDDECIMAL((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
DATEDATE
TIMETIME
DATETIME
TIMESTAMP
TIMESTAMP
TINYBLOB
MEDIUMBLOB
BLOB
LONGBLOB
BINARY
VARBINAR
BIT(n)
BYTES
GEOMETRY
UNKNOWN
Not supported yet

Sink Options​

NameTypeRequiredDefaultDescription
urlStringYes-The URL of the JDBC connection. Refer to a case: jdbc:vertica://localhost:5433/vertica
driverStringYes-The jdbc class name used to connect to the remote data source,
if you use Vertical the value is com.vertica.jdbc.Driver.
userStringNo-Connection instance user name
passwordStringNo-Connection instance password
queryStringNo-Use this sql write upstream input datas to database. e.g INSERT ...,query have the higher priority
databaseStringNo-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.
tableStringNo-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_keysArrayNo-This option is used to support operations such as insert, delete, and update when automatically generate sql.
support_upsert_by_query_primary_key_existBooleanNofalseChoose 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_secIntNo30The time in seconds to wait for the database operation used to validate the connection to complete.
max_retriesIntNo0The number of retries to submit failed (executeBatch)
batch_sizeIntNo1000For 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_onceBooleanNofalseWhether to enable exactly-once semantics, which will use Xa transactions. If on, you need to
set xa_data_source_class_name.
generate_sink_sqlBooleanNofalseGenerate sql statements based on the database table you want to write to
xa_data_source_class_nameStringNo-The xa data source class name of the database Driver, for example, vertical is com.vertical.cj.jdbc.VerticalXADataSource, and
please refer to appendix for other data sources
max_commit_attemptsIntNo3The number of retries for transaction commit failures
transaction_timeout_secIntNo-1The timeout after the transaction is opened, the default is -1 (never timeout). Note that setting the timeout may affect
exactly-once semantics
auto_commitBooleanNotrueAutomatic transaction commit is enabled by default
propertiesMapNo-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-optionsno-Sink plugin common parameters, please refer to Sink Common Options for details
enable_upsertBooleanNotrueEnable upsert by primary_keys exist, If the task has no key duplicate data, setting this parameter to false can speed up data import

Tips​

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 Example​

Simple:​

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 SQL​

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 :​

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"
}
}