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Apache Iceberg

Apache Iceberg sink connector

Support Iceberg Version

  • 1.4.2

Support Those Engines

Spark
Flink
SeaTunnel Zeta

Description

Sink connector for Apache Iceberg. It can support cdc mode 、auto create table and table schema evolution.

Key features

Supported DataSource Info

DatasourceDependentMaven
Iceberghive-execDownload
Iceberglibfb303Download

Database Dependency

In order to be compatible with different versions of Hadoop and Hive, the scope of hive-exec in the project pom file are provided, so if you use the Flink engine, first you may need to add the following Jar packages to <FLINK_HOME>/lib directory, if you are using the Spark engine and integrated with Hadoop, then you do not need to add the following Jar packages.

hive-exec-xxx.jar
libfb303-xxx.jar

Some versions of the hive-exec package do not have libfb303-xxx.jar, so you also need to manually import the Jar package.

Data Type Mapping

SeaTunnel Data typeIceberg Data type
BOOLEANBOOLEAN
INTINTEGER
BIGINTLONG
FLOATFLOAT
DOUBLEDOUBLE
DATEDATE
TIMETIME
TIMESTAMPTIMESTAMP
STRINGSTRING
BYTESFIXED
BINARY
DECIMALDECIMAL
ROWSTRUCT
ARRAYLIST
MAPMAP

Sink Options

NameTypeRequiredDefaultDescription
catalog_namestringyesdefaultUser-specified catalog name. default is default
namespacestringyesdefaultThe iceberg database name in the backend catalog. default is default
tablestringyes-The iceberg table name in the backend catalog.
iceberg.catalog.configmapyes-Specify the properties for initializing the Iceberg catalog, which can be referenced in this file:"https://github.com/apache/iceberg/blob/main/core/src/main/java/org/apache/iceberg/CatalogProperties.java"
hadoop.configmapno-Properties passed through to the Hadoop configuration
iceberg.hadoop-conf-pathstringno-The specified loading paths for the 'core-site.xml', 'hdfs-site.xml', 'hive-site.xml' files.
case_sensitivebooleannofalseIf data columns where selected via schema [config], controls whether the match to the schema will be done with case sensitivity.
iceberg.table.write-propsmapno-Properties passed through to Iceberg writer initialization, these take precedence, such as 'write.format.default', 'write.target-file-size-bytes', and other settings, can be found with specific parameters at 'https://github.com/apache/iceberg/blob/main/core/src/main/java/org/apache/iceberg/TableProperties.java'.
iceberg.table.auto-create-propsmapno-Configuration specified by Iceberg during automatic table creation.
iceberg.table.schema-evolution-enabledbooleannofalseSetting to true enables Iceberg tables to support schema evolution during the synchronization process
iceberg.table.primary-keysstringno-Default comma-separated list of columns that identify a row in tables (primary key)
iceberg.table.partition-keysstringno-Default comma-separated list of partition fields to use when creating tables
iceberg.table.upsert-mode-enabledbooleannofalseSet to true to enable upsert mode, default is false
schema_save_modeEnumnoCREATE_SCHEMA_WHEN_NOT_EXISTthe schema save mode, please refer to schema_save_mode below
data_save_modeEnumnoAPPEND_DATAthe data save mode, please refer to data_save_mode below
iceberg.table.commit-branchstringno-Default branch for commits

Task Example

Simple:

env {
parallelism = 1
job.mode = "STREAMING"
checkpoint.interval = 5000
}

source {
MySQL-CDC {
result_table_name = "customers_mysql_cdc_iceberg"
server-id = 5652
username = "st_user"
password = "seatunnel"
table-names = ["mysql_cdc.mysql_cdc_e2e_source_table"]
base-url = "jdbc:mysql://mysql_cdc_e2e:3306/mysql_cdc"
}
}

transform {
}

sink {
Iceberg {
catalog_name="seatunnel_test"
iceberg.catalog.config={
"type"="hadoop"
"warehouse"="file:///tmp/seatunnel/iceberg/hadoop-sink/"
}
namespace="seatunnel_namespace"
table="iceberg_sink_table"
iceberg.table.write-props={
write.format.default="parquet"
write.target-file-size-bytes=536870912
}
iceberg.table.primary-keys="id"
iceberg.table.partition-keys="f_datetime"
iceberg.table.upsert-mode-enabled=true
iceberg.table.schema-evolution-enabled=true
case_sensitive=true
}
}

Hive Catalog:

sink {
Iceberg {
catalog_name="seatunnel_test"
iceberg.catalog.config={
type = "hive"
uri = "thrift://localhost:9083"
warehouse = "hdfs://your_cluster//tmp/seatunnel/iceberg/"
}
namespace="seatunnel_namespace"
table="iceberg_sink_table"
iceberg.table.write-props={
write.format.default="parquet"
write.target-file-size-bytes=536870912
}
iceberg.table.primary-keys="id"
iceberg.table.partition-keys="f_datetime"
iceberg.table.upsert-mode-enabled=true
iceberg.table.schema-evolution-enabled=true
case_sensitive=true
}
}

Hadoop catalog:

sink {
Iceberg {
catalog_name="seatunnel_test"
iceberg.catalog.config={
type = "hadoop"
warehouse = "hdfs://your_cluster/tmp/seatunnel/iceberg/"
}
namespace="seatunnel_namespace"
table="iceberg_sink_table"
iceberg.table.write-props={
write.format.default="parquet"
write.target-file-size-bytes=536870912
}
iceberg.table.primary-keys="id"
iceberg.table.partition-keys="f_datetime"
iceberg.table.upsert-mode-enabled=true
iceberg.table.schema-evolution-enabled=true
case_sensitive=true
}
}

Multiple table

example1

env {
parallelism = 1
job.mode = "STREAMING"
checkpoint.interval = 5000
}

source {
Mysql-CDC {
base-url = "jdbc:mysql://127.0.0.1:3306/seatunnel"
username = "root"
password = "******"

table-names = ["seatunnel.role","seatunnel.user","galileo.Bucket"]
}
}

transform {
}

sink {
Iceberg {
...
namespace = "${database_name}_test"
table = "${table_name}_test"
}
}

example2

env {
parallelism = 1
job.mode = "BATCH"
}

source {
Jdbc {
driver = oracle.jdbc.driver.OracleDriver
url = "jdbc:oracle:thin:@localhost:1521/XE"
user = testUser
password = testPassword

table_list = [
{
table_path = "TESTSCHEMA.TABLE_1"
},
{
table_path = "TESTSCHEMA.TABLE_2"
}
]
}
}

transform {
}

sink {
Iceberg {
...
namespace = "${schema_name}_test"
table = "${table_name}_test"
}
}

Changelog

2.3.4-SNAPSHOT 2024-01-18

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