Menulis dari Dataflow ke Apache Iceberg

Untuk menulis dari Dataflow ke Apache Iceberg, gunakan konektor I/O terkelola.

Dependensi

Tambahkan dependensi berikut ke project Anda:

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>2.56.0</version>
</dependency>

Configuration

Konektor Apache Iceberg menggunakan parameter konfigurasi berikut:

• table (string). Nama Apache Iceberg. Contoh: "db.table1".
• catalog_config (peta). Konfigurasi katalog. Berisi kolom berikut:
  • catalog_name (string). Nama katalog. Contoh: "local".
  • catalog_type (string). Jenis katalog. Nilai yang didukung: "hadoop", "hive", "rest".
  • warehouse_location (string). Lokasi gudang. Contoh: file://path/to/warehouse.

Contoh

Contoh berikut menulis data JSON dalam memori ke tabel Apache Iceberg.

Java

Untuk mengautentikasi ke Dataflow, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import com.google.common.collect.ImmutableMap;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import org.apache.beam.sdk.Pipeline;
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.schemas.Schema;
import org.apache.beam.sdk.transforms.Create;
import org.apache.beam.sdk.transforms.JsonToRow;
import org.apache.beam.sdk.values.PCollectionRowTuple;

public class ApacheIcebergWrite {
  static final List<String> TABLE_ROWS = Arrays.asList(
      "{\"id\":0, \"name\":\"Alice\"}",
      "{\"id\":1, \"name\":\"Bob\"}",
      "{\"id\":2, \"name\":\"Charles\"}"
  );

  static final String CATALOG_TYPE = "hadoop";

  // The schema for the table rows.
  public static final Schema SCHEMA = new Schema.Builder()
      .addStringField("name")
      .addInt64Field("id")
      .build();

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

    void setWarehouseLocation(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
    // 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("catalog_name", options.getCatalogName())
        .put("warehouse_location", options.getWarehouseLocation())
        .put("catalog_type", CATALOG_TYPE)
        .build();

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

    // Build the pipeline.
    var input = pipeline
        .apply(Create.of(TABLE_ROWS))
        .apply(JsonToRow.withSchema(SCHEMA));

    PCollectionRowTuple.of("input", input).apply(
        Managed.write(Managed.ICEBERG)
            .withConfig(config)
    );

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