Mantenha tudo organizado com as coleções
Salve e categorize o conteúdo com base nas suas preferências.
Conector Bigtable Beam
O conector de Beam do Bigtable (BigtableIO) é um conector de E/S do Apache Beam de código aberto que pode ajudar a realizar operações em lote e de streaming no Bigtable em um pipeline usando o
Dataflow.
Se você estiver migrando do HBase para o Bigtable ou estiver executando um aplicativo que usa a API HBase em vez das APIs do Bigtable, use o conector HBase Beam do Bigtable (CloudBigtableIO) em vez do conector descrito nesta página.
Antes de criar um pipeline do Dataflow, verifique o suporte ao ambiente de execução do Apache Beam para garantir que você esteja usando uma versão do Java compatível com o Dataflow. Use a versão com suporte mais recente do Apache Beam.
O conector Bigtable Beam é usado em conjunto com o cliente do Bigtable para Java, uma biblioteca de cliente que chama as APIs do Bigtable. Você escreve o código para implantar um pipeline que usa o
conector para o Dataflow, que processa o provisionamento e
o gerenciamento de recursos e ajuda na escalonabilidade e na confiabilidade do processamento
de dados.
Para mais informações sobre o modelo de programação do Apache Beam, consulte a documentação do Beam.
Controle de fluxo de gravação em lote
Ao enviar gravações em lote (incluindo solicitações de exclusão) a uma tabela usando o conector Bigtable Beam, é possível ativar o controle de fluxo de gravação em lote. Quando
esse recurso é ativado, o Bigtable faz automaticamente o
seguinte:
Limite o tráfego para evitar sobrecarregar o cluster do Bigtable
Garante que o cluster esteja sob carga suficiente para acionar o escalonamento automático do Bigtable (se ativado), para que mais nós sejam adicionados automaticamente ao cluster quando necessário.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-27 UTC."],[[["\u003cp\u003eThe Bigtable Beam connector (\u003ccode\u003eBigtableIO\u003c/code\u003e) facilitates batch and streaming operations on Bigtable data within Apache Beam pipelines, especially when used in conjunction with Dataflow.\u003c/p\u003e\n"],["\u003cp\u003eFor migrations from HBase or applications using the HBase API, the Bigtable HBase Beam connector (\u003ccode\u003eCloudBigtableIO\u003c/code\u003e) should be used instead of the standard \u003ccode\u003eBigtableIO\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe Bigtable Beam connector is a component of the Apache Beam GitHub repository, and users should refer to the \u003ccode\u003eClass BigtableIO\u003c/code\u003e Javadoc for detailed information.\u003c/p\u003e\n"],["\u003cp\u003eWhen using Dataflow pipelines with the connector, it is important to refer to the Apache Beam runtime support page to ensure you are using a compatible version of Java.\u003c/p\u003e\n"],["\u003cp\u003eBatch write flow control, when enabled, allows Bigtable to automatically rate-limit traffic and ensure the cluster has enough load to trigger autoscaling.\u003c/p\u003e\n"]]],[],null,["# Bigtable Beam connector\n=======================\n\nThe Bigtable Beam connector (`BigtableIO`) is an open source [Apache\nBeam](https://beam.apache.org/) I/O connector that can help you perform batch and streaming\noperations on Bigtable data in a [pipeline](https://beam.apache.org/documentation/programming-guide/#creating-a-pipeline) using\n[Dataflow](/dataflow/docs/overview).\n\nIf you are migrating from HBase to Bigtable or you are running an\napplication uses the HBase API instead of the Bigtable\nAPIs, use the [Bigtable HBase Beam connector](/bigtable/docs/hbase-dataflow-java)\n(`CloudBigtableIO`) instead of the connector described on this page.\n\nConnector details\n-----------------\n\nThe Bigtable Beam connector is a component of the\n[Apache Beam GitHub\nrepository](https://github.com/apache/beam). The Javadoc is available\nat [`Class\nBigtableIO`](https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigtable/BigtableIO.html).\n\nBefore you create a Dataflow pipeline, check [Apache Beam\nruntime support](/dataflow/docs/support/beam-runtime-support) to make sure you\nare using a version of Java that is supported for Dataflow. Use\nthe most recent supported release of Apache Beam.\n\nThe Bigtable Beam connector is used in conjunction with the\nBigtable client for Java, a client library that calls the\nBigtable APIs. You write code to deploy a pipeline that uses the\nconnector to Dataflow, which handles the provisioning and\nmanagement of resources and assists with the scalability and reliability of data\nprocessing.\n\nFor more information on the Apache Beam programming model, see the [Beam\ndocumentation](https://beam.apache.org/get-started/beam-overview/).\n\nBatch write flow control\n------------------------\n\nWhen you send batch writes (including delete requests) to a table using the\nBigtable Beam connector, you can enable *batch write flow control*. When\nthis feature is enabled, Bigtable automatically does the\nfollowing:\n\n- Rate-limits traffic to avoid overloading your Bigtable cluster\n- Ensures the cluster is under enough load to trigger Bigtable autoscaling (if enabled), so that more nodes are automatically added to the cluster when needed\n\nFor more information, see [Batch write flow\ncontrol](/bigtable/docs/writes#flow-control). For a code sample, see [Enable\nbatch write flow control](/bigtable/docs/writing-data#batch-write-flow-control).\n\nWhat's next\n-----------\n\n- [Read an overview of Bigtable write requests.](/bigtable/docs/writes)\n- [Review a list of Dataflow templates that work with\n Bigtable.](/bigtable/docs/dataflow-templates)\n- [Bigtable Kafka Connect sink connector](/bigtable/docs/kafka-sink-connector)"]]
