Read from Apache Iceberg to Dataflow

To read from Apache Iceberg to Dataflow, use the managed I/O connector.

Managed I/O supports the following capabilities for Apache Iceberg:

Catalogs	Hadoop Hive REST-based catalogs BigQuery metastore (requires Apache Beam SDK 2.62.0 or later if not using Runner v2)
Read capabilities	Batch read
Write capabilities	Batch write Streaming write Dynamic destinations Dynamic table creation

For BigQuery tables for Apache Iceberg, use the BigQueryIO connector with BigQuery Storage API. The table must already exist; dynamic table creation is not supported.

Dependencies

Add the following dependencies to your project:

Java

<dependency>
  <groupId>org.apache.beam</groupId>
  <artifactId>beam-sdks-java-managed</artifactId>
  <version>${beam.version}</version>
</dependency>

<dependency>
  <groupId>org.apache.beam</groupId>
  <artifactId>beam-sdks-java-io-iceberg</artifactId>
  <version>${beam.version}</version>
</dependency>

Example

The following example reads from an Apache Iceberg table and writes the data to text files.

Java

To authenticate to Dataflow, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

import com.google.common.collect.ImmutableMap;
import java.util.Map;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.managed.Managed;
import org.apache.beam.sdk.options.Description;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.transforms.MapElements;
import org.apache.beam.sdk.values.PCollectionRowTuple;
import org.apache.beam.sdk.values.TypeDescriptors;

public class ApacheIcebergRead {

  static final String CATALOG_TYPE = "hadoop";

  public interface Options extends PipelineOptions {
    @Description("The URI of the Apache Iceberg warehouse location")
    String getWarehouseLocation();

    void setWarehouseLocation(String value);

    @Description("Path to write the output file")
    String getOutputPath();

    void setOutputPath(String value);

    @Description("The name of the Apache Iceberg catalog")
    String getCatalogName();

    void setCatalogName(String value);

    @Description("The name of the table to write to")
    String getTableName();

    void setTableName(String value);
  }

  public static void main(String[] args) {

    // Parse the pipeline options passed into the application. Example:
    //   --runner=DirectRunner --warehouseLocation=$LOCATION --catalogName=$CATALOG \
    //   --tableName= $TABLE_NAME --outputPath=$OUTPUT_FILE
    // For more information, see https://beam.apache.org/documentation/programming-guide/#configuring-pipeline-options
    Options options = PipelineOptionsFactory.fromArgs(args).withValidation().as(Options.class);
    Pipeline pipeline = Pipeline.create(options);

    // Configure the Iceberg source I/O
    Map catalogConfig = ImmutableMap.<String, Object>builder()
        .put("warehouse", options.getWarehouseLocation())
        .put("type", CATALOG_TYPE)
        .build();

    ImmutableMap<String, Object> config = ImmutableMap.<String, Object>builder()
        .put("table", options.getTableName())
        .put("catalog_name", options.getCatalogName())
        .put("catalog_properties", catalogConfig)
        .build();

    // Build the pipeline.
    pipeline.apply(Managed.read(Managed.ICEBERG).withConfig(config))
        .getSinglePCollection()
        // Format each record as a string with the format 'id:name'.
        .apply(MapElements
            .into(TypeDescriptors.strings())
            .via((row -> {
              return String.format("%d:%s",
                  row.getInt64("id"),
                  row.getString("name"));
            })))
        // Write to a text file.
        .apply(
            TextIO.write()
                .to(options.getOutputPath())
                .withNumShards(1)
                .withSuffix(".txt"));

    pipeline.run().waitUntilFinish();
  }
}

What's next

• Write to Apache Iceberg.
• Learn more about Managed I/O.