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[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis content demonstrates how to write data from Dataflow to an existing BigQuery table using Java.\u003c/p\u003e\n"],["\u003cp\u003eThe code sample utilizes the \u003ccode\u003eBigQueryIO.write()\u003c/code\u003e transform to send data to BigQuery, including specifying the table destination, data format, and write dispositions.\u003c/p\u003e\n"],["\u003cp\u003eThe process involves creating a Dataflow pipeline, generating an in-memory collection of custom data objects, and applying a transformation to convert it into the needed format.\u003c/p\u003e\n"],["\u003cp\u003eAuthentication with Dataflow is achieved through the setup of Application Default Credentials (ADC).\u003c/p\u003e\n"],["\u003cp\u003ePipeline options such as project ID, dataset name, and table name are configured for dynamic table targeting.\u003c/p\u003e\n"]]],[],null,["# Write to BigQuery\n\nWrite from Dataflow to an existing BigQuery table\n\nExplore further\n---------------\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [Write from Dataflow to BigQuery](/dataflow/docs/guides/write-to-bigquery)\n\nCode sample\n-----------\n\n### Java\n\n\nTo authenticate to Dataflow, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n import com.google.api.services.bigquery.model.TableRow;\n import java.util.Arrays;\n import java.util.List;\n import org.apache.beam.sdk.Pipeline;\n import org.apache.beam.sdk.coders.DefaultCoder;\n import org.apache.beam.sdk.extensions.avro.coders.AvroCoder;\n import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO;\n import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write;\n import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write.CreateDisposition;\n import org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write.WriteDisposition;\n import org.apache.beam.sdk.options.PipelineOptionsFactory;\n import org.apache.beam.sdk.transforms.Create;\n\n public class BigQueryWrite {\n // A custom datatype for the source data.\n @DefaultCoder(AvroCoder.class)\n public static class MyData {\n public String name;\n public Long age;\n\n public MyData() {}\n\n public MyData(String name, Long age) {\n this.name = name;\n this.age = age;\n }\n }\n\n public static void main(String[] args) {\n // Example source data.\n final List\u003cMyData\u003e data = Arrays.asList(\n new MyData(\"Alice\", 40L),\n new MyData(\"Bob\", 30L),\n new MyData(\"Charlie\", 20L)\n );\n\n // Parse the pipeline options passed into the application. Example:\n // --projectId=$PROJECT_ID --datasetName=$DATASET_NAME --tableName=$TABLE_NAME\n // For more information, see https://beam.apache.org/documentation/programming-guide/#configuring-pipeline-options\n PipelineOptionsFactory.register(ExamplePipelineOptions.class);\n ExamplePipelineOptions options = PipelineOptionsFactory.fromArgs(args)\n .withValidation()\n .as(ExamplePipelineOptions.class);\n\n // Create a pipeline and apply transforms.\n Pipeline pipeline = Pipeline.create(options);\n pipeline\n // Create an in-memory PCollection of MyData objects.\n .apply(Create.of(data))\n // Write the data to an exiting BigQuery table.\n .apply(BigQueryIO.\u003cMyData\u003ewrite()\n .to(String.format(\"%s:%s.%s\",\n options.getProjectId(),\n options.getDatasetName(),\n options.getTableName()))\n .withFormatFunction(\n (MyData x) -\u003e new TableRow().set(\"user_name\", x.name).set(\"age\", x.age))\n .withCreateDisposition(CreateDisposition.CREATE_NEVER)\n .withWriteDisposition(WriteDisposition.WRITE_APPEND)\n .withMethod(Write.Method.STORAGE_WRITE_API));\n pipeline.run().waitUntilFinish();\n }\n }\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=dataflow)."]]