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PostgreSql

JDBC PostgreSql 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
PostgreSQLDifferent dependency version has different driver class.org.postgresql.Driverjdbc:postgresql://localhost:5432/testDownload
PostgreSQLIf you want to manipulate the GEOMETRY type in PostgreSQL.org.postgresql.Driverjdbc:postgresql://localhost:5432/testDownload

Database Dependency

Please download the support list corresponding to 'Maven' and copy it to the '$SEATNUNNEL_HOME/plugins/jdbc/lib/' working directory
For example PostgreSQL datasource: cp postgresql-xxx.jar $SEATNUNNEL_HOME/plugins/jdbc/lib/
If you want to manipulate the GEOMETRY type in PostgreSQL, add postgresql-xxx.jar and postgis-jdbc-xxx.jar to $SEATNUNNEL_HOME/plugins/jdbc/lib/

Data Type Mapping

PostgreSQL Data TypeSeaTunnel Data Type
BOOL
BOOLEAN
_BOOL
ARRAY<BOOLEAN>
BYTEA
BYTES
_BYTEA
ARRAY<TINYINT>
INT2
SMALLSERIAL
INT4
SERIAL
INT
_INT2
_INT4
ARRAY<INT>
INT8
BIGSERIAL
BIGINT
_INT8
ARRAY<BIGINT>
FLOAT4
FLOAT
_FLOAT4
ARRAY<FLOAT>
FLOAT8
DOUBLE
_FLOAT8
ARRAY<DOUBLE>
NUMERIC(Get the designated column's specified column size>0)DECIMAL(Get the designated column's specified column size,Gets the number of digits in the specified column to the right of the decimal point)
NUMERIC(Get the designated column's specified column size<0)DECIMAL(38, 18)
BPCHAR
CHARACTER
VARCHAR
TEXT
GEOMETRY
GEOGRAPHY
JSON
JSONB
UUID
STRING
_BPCHAR
_CHARACTER
_VARCHAR
_TEXT
ARRAY<STRING>
TIMESTAMP
TIMESTAMP
TIME
TIME
DATE
DATE
OTHER DATA TYPESNOT SUPPORTED YET

Options

NameTypeRequiredDefaultDescription
urlStringYes-The URL of the JDBC connection. Refer to a case: jdbc:postgresql://localhost:5432/test
if you would use json or jsonb type insert please add jdbc url stringtype=unspecified option
driverStringYes-The jdbc class name used to connect to the remote data source,
if you use PostgreSQL the value is org.postgresql.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.The table parameter can fill in the name of an unwilling table, which will eventually be used as the table name of the creation table, and supports variables (${table_name}, ${schema_name}). Replacement rules: ${schema_name} will replace the SCHEMA name passed to the target side, and ${table_name} will replace the name of the table passed to the table at the target side.
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, PostgreSQL is org.postgresql.xa.PGXADataSource, 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
field_ideStringNo-Identify whether the field needs to be converted when synchronizing from the source to the sink. ORIGINAL indicates no conversion is needed;UPPERCASE indicates conversion to uppercase;LOWERCASE indicates conversion to lowercase.
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
schema_save_modeEnumnoCREATE_SCHEMA_WHEN_NOT_EXISTBefore the synchronous task is turned on, different treatment schemes are selected for the existing surface structure of the target side.
data_save_modeEnumnoAPPEND_DATABefore the synchronous task is turned on, different processing schemes are selected for data existing data on the target side.
custom_sqlStringno-When data_save_mode selects CUSTOM_PROCESSING, you should fill in the CUSTOM_SQL parameter. This parameter usually fills in a SQL that can be executed. SQL will be executed before synchronization tasks.
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

table [string]

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.

The table parameter can fill in the name of an unwilling table, which will eventually be used as the table name of the creation table, and supports variables (${table_name}, ${schema_name}). Replacement rules: ${schema_name} will replace the SCHEMA name passed to the target side, and ${table_name} will replace the name of the table passed to the table at the target side.

for example:

  1. ${schema_name}.${table_name} _test
  2. dbo.tt_${table_name} _sink
  3. public.sink_table

schema_save_mode[Enum]

Before the synchronous task is turned on, different treatment schemes are selected for the existing surface structure of the target side.
Option introduction:
RECREATE_SCHEMA :Will create when the table does not exist, delete and rebuild when the table is saved
CREATE_SCHEMA_WHEN_NOT_EXIST :Will Created when the table does not exist, skipped when the table is saved
ERROR_WHEN_SCHEMA_NOT_EXIST :Error will be reported when the table does not exist

data_save_mode[Enum]

Before the synchronous task is turned on, different processing schemes are selected for data existing data on the target side.
Option introduction:
DROP_DATA: Preserve database structure and delete data
APPEND_DATA:Preserve database structure, preserve data
CUSTOM_PROCESSING:User defined processing
ERROR_WHEN_DATA_EXISTS:When there is data, an error is reported

custom_sql[String]

When data_save_mode selects CUSTOM_PROCESSING, you should fill in the CUSTOM_SQL parameter. This parameter usually fills in a SQL that can be executed. SQL will be executed before synchronization tasks.

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 PostgreSQL. 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 {
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 {
# if you would use json or jsonb type insert please add jdbc url stringtype=unspecified option
url = "jdbc:postgresql://localhost:5432/test"
driver = "org.postgresql.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 {
# if you would use json or jsonb type insert please add jdbc url stringtype=unspecified option
url = "jdbc:postgresql://localhost:5432/test"
driver = org.postgresql.Driver
user = root
password = 123456

generate_sink_sql = true
database = test
table = "public.test_table"
}
}

Exactly-once :

For accurate write scene we guarantee accurate once

sink {
jdbc {
# if you would use json or jsonb type insert please add jdbc url stringtype=unspecified option
url = "jdbc:postgresql://localhost:5432/test"
driver = "org.postgresql.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 = "org.postgresql.xa.PGXADataSource"
}
}

CDC(Change Data Capture) Event

CDC change data is also supported by us In this case, you need config database, table and primary_keys.

sink {
jdbc {
# if you would use json or jsonb type insert please add jdbc url stringtype=unspecified option
url = "jdbc:postgresql://localhost:5432/test"
driver = "org.postgresql.Driver"
user = root
password = 123456

generate_sink_sql = true
# You need to configure both database and table
database = test
table = sink_table
primary_keys = ["id","name"]
field_ide = UPPERCASE
}
}

Save mode function

sink {
Jdbc {
# if you would use json or jsonb type insert please add jdbc url stringtype=unspecified option
url = "jdbc:postgresql://localhost:5432/test"
driver = org.postgresql.Driver
user = root
password = 123456

generate_sink_sql = true
database = test
table = "public.test_table"
schema_save_mode = "CREATE_SCHEMA_WHEN_NOT_EXIST"
data_save_mode="APPEND_DATA"
}
}