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Version: 2.3.7

Apache Iceberg

Apache Iceberg source connector

Support Iceberg Versionโ€‹

  • 1.4.2

Support Those Enginesโ€‹

Spark
Flink
SeaTunnel Zeta

Key featuresโ€‹

Descriptionโ€‹

Source connector for Apache Iceberg. It can support batch and stream mode.

Supported DataSource Infoโ€‹

DatasourceDependentMaven
Iceberghive-execDownload
Iceberglibfb303Download

Database Dependencyโ€‹

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. If you are using the hadoop s3 catalog, you need to add the hadoop-aws,aws-java-sdk jars for your Flink and Spark engine versions. (Additional locations: <FLINK_HOME>/lib, <SPARK_HOME>/jars)

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 Mappingโ€‹

Iceberg Data typeSeaTunnel Data type
BOOLEANBOOLEAN
INTEGERINT
LONGBIGINT
FLOATFLOAT
DOUBLEDOUBLE
DATEDATE
TIMETIME
TIMESTAMPTIMESTAMP
STRINGSTRING
FIXED
BINARY
BYTES
DECIMALDECIMAL
STRUCTROW
LISTARRAY
MAPMAP

Source Optionsโ€‹

NameTypeRequiredDefaultDescription
catalog_namestringyes-User-specified catalog name.
namespacestringyes-The iceberg database name in the backend catalog.
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.
schemaconfigno-Use projection to select data columns and columns order.
case_sensitivebooleannofalseIf data columns where selected via schema [config], controls whether the match to the schema will be done with case sensitivity.
start_snapshot_timestamplongno-Instructs this scan to look for changes starting from the most recent snapshot for the table as of the timestamp.
timestamp โ€“ the timestamp in millis since the Unix epoch
start_snapshot_idlongno-Instructs this scan to look for changes starting from a particular snapshot (exclusive).
end_snapshot_idlongno-Instructs this scan to look for changes up to a particular snapshot (inclusive).
use_snapshot_idlongno-Instructs this scan to look for use the given snapshot ID.
use_snapshot_timestamplongno-Instructs this scan to look for use the most recent snapshot as of the given time in milliseconds. timestamp โ€“ the timestamp in millis since the Unix epoch
stream_scan_strategyenumnoFROM_LATEST_SNAPSHOTStarting strategy for stream mode execution, Default to use FROM_LATEST_SNAPSHOT if donโ€™t specify any value,The optional values are:
TABLE_SCAN_THEN_INCREMENTAL: Do a regular table scan then switch to the incremental mode.
FROM_LATEST_SNAPSHOT: Start incremental mode from the latest snapshot inclusive.
FROM_EARLIEST_SNAPSHOT: Start incremental mode from the earliest snapshot inclusive.
FROM_SNAPSHOT_ID: Start incremental mode from a snapshot with a specific id inclusive.
FROM_SNAPSHOT_TIMESTAMP: Start incremental mode from a snapshot with a specific timestamp inclusive.
common-optionsno-Source plugin common parameters, please refer to Source Common Options for details.

Task Exampleโ€‹

Simple:โ€‹

env {
parallelism = 2
job.mode = "BATCH"
}

source {
Iceberg {
schema {
fields {
f2 = "boolean"
f1 = "bigint"
f3 = "int"
f4 = "bigint"
f5 = "float"
f6 = "double"
f7 = "date"
f9 = "timestamp"
f10 = "timestamp"
f11 = "string"
f12 = "bytes"
f13 = "bytes"
f14 = "decimal(19,9)"
f15 = "array<int>"
f16 = "map<string, int>"
}
}
catalog_name = "seatunnel"
iceberg.catalog.config={
type = "hadoop"
warehouse = "file:///tmp/seatunnel/iceberg/hadoop/"
}
namespace = "database1"
table = "source"
result_table_name = "iceberg"
}
}

transform {
}

sink {
Console {
source_table_name = "iceberg"
}
}

Hadoop S3 Catalog:โ€‹

source {
iceberg {
catalog_name = "seatunnel"
iceberg.catalog.config={
"type"="hadoop"
"warehouse"="s3a://your_bucket/spark/warehouse/"
}
hadoop.config={
"fs.s3a.aws.credentials.provider" = "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
"fs.s3a.endpoint" = "s3.cn-north-1.amazonaws.com.cn"
"fs.s3a.access.key" = "xxxxxxxxxxxxxxxxx"
"fs.s3a.secret.key" = "xxxxxxxxxxxxxxxxx"
"fs.defaultFS" = "s3a://your_bucket"
}
namespace = "your_iceberg_database"
table = "your_iceberg_table"
result_table_name = "iceberg_test"
}
}

Hive Catalog:โ€‹

source {
Iceberg {
catalog_name = "seatunnel"
iceberg.catalog.config={
type = "hive"
uri = "thrift://localhost:9083"
warehouse = "hdfs://your_cluster//tmp/seatunnel/iceberg/"
}
catalog_type = "hive"

namespace = "your_iceberg_database"
table = "your_iceberg_table"
}
}

Column Projection:โ€‹

source {
Iceberg {
catalog_name = "seatunnel"
iceberg.catalog.config={
type = "hadoop"
warehouse = "hdfs://your_cluster/tmp/seatunnel/iceberg/"
}
namespace = "your_iceberg_database"
table = "your_iceberg_table"

schema {
fields {
f2 = "boolean"
f1 = "bigint"
f3 = "int"
f4 = "bigint"
}
}
}
}

Changelogโ€‹

2.2.0-beta 2022-09-26โ€‹

  • Add Iceberg Source Connector

next versionโ€‹

  • [Feature] Support Hadoop3.x (3046)
  • [improve][api] Refactoring schema parse (4157)