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L'installazione del componente HBase facoltativo è limitata ai cluster Dataproc creati con la versione immagine 1.5 o 2.0.
Sebbene Google Cloud fornisca molti servizi che consentono di eseguire il deployment di Apache HBase autogestito, Bigtable è spesso l'opzione migliore, in quanto fornisce un'API aperta con HBase e la portabilità del workload.
Le tabelle del database HBase possono essere migrate a Bigtable per la gestione dei dati sottostanti, mentre le applicazioni che in precedenza interagivano con HBase, come Spark, possono rimanere su Dataproc e connettersi in modo sicuro a Bigtable.
In questa guida, forniamo i passaggi di alto livello per iniziare a utilizzare Bigtable
e forniamo riferimenti per la migrazione dei dati a Bigtable dalle implementazioni
Dataproc HBase.
Inizia a utilizzare Bigtable
Cloud Bigtable è una piattaforma NoSQL altamente scalabile e performante che offre
compatibilità e portabilità del client API Apache HBase
per i carichi di lavoro HBase. Il client è compatibile con le versioni 1.x e 2.x dell'API HBase e può essere incluso nell'applicazione esistente per leggere e scrivere su Bigtable. Le applicazioni HBase esistenti possono aggiungere la libreria client Bigtable HBase
per leggere e scrivere i dati archiviati in Bigtable.
Per saperne di più sulla configurazione dell'applicazione HBase con Bigtable, consulta
Bigtable e l'API HBase.
Crea un cluster Bigtable
Per iniziare a utilizzare Bigtable, crea un cluster e tabelle per archiviare i dati precedentemente archiviati in HBase. Segui i passaggi descritti nella documentazione di Bigtable per
creare un'istanza,
un cluster e
tabelle con
lo stesso schema delle tabelle HBase. Per la creazione automatica di tabelle da DDL di tabelle HBase, consulta lo
strumento di conversione dello schema.
Apri l'istanza Bigtable nella console Google Cloud per visualizzare la tabella e
i grafici di monitoraggio lato server, tra cui righe al secondo, latenza e velocità effettiva, per gestire
la tabella appena sottoposta a provisioning. Per ulteriori informazioni, vedi
Monitoraggio.
Migrazione dei dati da Dataproc a Bigtable
Dopo aver creato le tabelle in Bigtable, puoi importare e convalidare
i dati seguendo le indicazioni riportate in
Migrazione di HBase su Google Cloud a Bigtable.
Dopo aver eseguito la migrazione dei dati, puoi aggiornare le applicazioni per inviare letture e scritture
a Bigtable.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-04 UTC."],[[["\u003cp\u003eThe HBase component is deprecated in Dataproc version 2.1 and later, and while a Beta version was available in versions 1.5 and 2.0, its use is not recommended due to the ephemeral nature of Dataproc clusters.\u003c/p\u003e\n"],["\u003cp\u003eBigtable is recommended as an alternative to HBase, offering an open API with HBase compatibility and workload portability, making it suitable for applications that previously used HBase.\u003c/p\u003e\n"],["\u003cp\u003eYou can migrate existing HBase applications and their data to Bigtable by using the Bigtable HBase client library and following the provided migration steps.\u003c/p\u003e\n"],["\u003cp\u003eGetting started with Bigtable involves creating a cluster and tables, which can be done manually or through automated tools like the schema translator for HBase DDLs.\u003c/p\u003e\n"],["\u003cp\u003eAfter migrating, you can use tools like server-side monitoring charts to manage the Bigtable tables and review examples of using Spark with Bigtable for continued application functionality.\u003c/p\u003e\n"]]],[],null,["| **Deprecated:** Starting with Dataproc [version 2.1](/dataproc/docs/concepts/versioning/dataproc-release-2.1), you can no longer use the optional HBase component. Dataproc [version 1.5](/dataproc/docs/concepts/versioning/dataproc-release-1.5) and Dataproc [version 2.0](/dataproc/docs/concepts/versioning/dataproc-release-2.0) offer a Beta version of HBase with no support. However, due to the ephemeral nature of Dataproc clusters, using HBase is not recommended.\n\nInstallation of the optional HBase component is limited to\nDataproc clusters created with image version\n[1.5](/dataproc/docs/concepts/versioning/dataproc-release-1.5) or\n[2.0](/dataproc/docs/concepts/versioning/dataproc-release-2.0).\n\nWhile Google Cloud provides many services that let you deploy self-managed Apache\nHBase, [Bigtable](/bigtable/docs/overview) is\noften the best option as it provides an open API with HBase and workload portability.\nHBase database tables can be migrated to Bigtable for management of the\nunderlying data, while applications that previously interoperated with HBase,\nsuch as Spark, may remain on Dataproc and securely connect with Bigtable.\nIn this guide, we provide the high-level steps for getting started with Bigtable\nand provide references for migrating data to Bigtable from Dataproc HBase\ndeployments.\n\nGet started with Bigtable\n\nCloud Bigtable is a highly scalable and performant NoSQL platform that provides\n[Apache HBase API client compatibility](https://cloud.google.com/bigtable/docs/hbase-bigtable)\nand portability for HBase workloads. The client is compatible with HBase API\nversions 1.x and 2.x and may be included with the existing application to read\nand write to Bigtable. Existing HBase applications may add the Bigtable HBase\nclient library to read and write data stored in Bigtable.\n\nSee\n[Bigtable and the HBase API](https://cloud.google.com/bigtable/docs/hbase-bigtable)\nfor more information on configuring your HBase application with Bigtable.\n\nCreate a Bigtable cluster\n\nYou can get started using Bigtable by creating a cluster and tables for\nstoring data that was previously stored in HBase. Follow the steps in the Bigtable documentation for\n[creating an instance](/bigtable/docs/creating-instance#creating-instance),\na cluster, and\n[tables](/bigtable/docs/managing-tables) with\nthe same schema as the HBase tables. For automated creation of tables from HBase\ntable DDLs, refer to the\n[schema translator tool](/bigtable/docs/migrate-hbase-on-google-cloud-to-bigtable#create-destination-table).\n\nOpen the Bigtable instance in Google Cloud console to view the table and\nserver-side monitoring charts, including rows per second, latency, and throughput, to manage\nthe newly provisioned table. For additional information, see\n[Monitoring](/bigtable/docs/monitoring-instance).\n\nMigrate data from Dataproc to Bigtable\n\nAfter you create the tables in Bigtable, you can import and validate\nyour data by following the guidance at\n[Migrate HBase on Google Cloud to Bigtable](/bigtable/docs/migrate-hbase-on-google-cloud-to-bigtable).\nAfter you migrate the data, you can update applications to send reads and writes\nto Bigtable.\n\nWhat's next\n\n- See [Wordcount Spark examples](https://github.com/GoogleCloudPlatform/java-docs-samples/tree/main/bigtable/spark) for running Spark with the Bigtable.\n- Review online migration options with [live replication from HBase to Bigtable](/bigtable/docs/hbase-replication).\n- Watch [How Box modernized their NoSQL databases](https://www.youtube.com/watch?v=DteQ09WFhaU) to understand other benefits."]]
