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Dataproc versi 1.5 dan Dataproc versi 2.0 menawarkan versi Beta HBase tanpa dukungan. Namun, karena sifat cluster Dataproc yang sementara, penggunaan HBase tidak direkomendasikan.
Penginstalan komponen HBase opsional terbatas pada cluster Dataproc yang dibuat dengan versi image 1.5 atau 2.0.
Meskipun Google Cloud menyediakan banyak layanan yang memungkinkan Anda men-deploy Apache HBase yang dikelola sendiri, Bigtable sering kali menjadi opsi terbaik karena menyediakan API terbuka dengan portabilitas beban kerja dan HBase.
Tabel database HBase dapat dimigrasikan ke Bigtable untuk pengelolaan data pokok, sementara aplikasi yang sebelumnya beroperasi dengan HBase, seperti Spark, dapat tetap berada di Dataproc dan terhubung dengan aman ke Bigtable.
Dalam panduan ini, kami memberikan langkah-langkah tingkat tinggi untuk mulai menggunakan Bigtable dan memberikan referensi untuk memigrasikan data ke Bigtable dari deployment Dataproc HBase.
Mulai menggunakan Bigtable
Cloud Bigtable adalah platform NoSQL berperforma tinggi dan sangat skalabel yang menyediakan
kompatibilitas dan portabilitas klien API Apache HBase
untuk beban kerja HBase. Klien ini kompatibel dengan HBase API versi 1.x dan 2.x serta dapat disertakan dengan aplikasi yang ada untuk membaca dan menulis ke Bigtable. Aplikasi HBase yang ada dapat menambahkan library klien HBase Bigtable untuk membaca dan menulis data yang disimpan di Bigtable.
Lihat
Bigtable dan HBase API
untuk mengetahui informasi selengkapnya tentang cara mengonfigurasi aplikasi HBase dengan Bigtable.
Membuat cluster Bigtable
Anda dapat mulai menggunakan Bigtable dengan membuat cluster dan tabel untuk menyimpan data yang sebelumnya disimpan di HBase. Ikuti langkah-langkah dalam dokumentasi Bigtable untuk membuat instance, cluster, dan tabel dengan skema yang sama seperti tabel HBase. Untuk pembuatan tabel otomatis dari DDL tabel HBase, lihat alat penerjemah skema.
Buka instance Bigtable di konsol untuk melihat tabel dan diagram pemantauan sisi server, termasuk baris per detik, latensi, dan throughput, untuk mengelola tabel yang baru disediakan. Google Cloud Untuk mengetahui informasi tambahan, lihat
Pemantauan.
Memigrasikan data dari Dataproc ke Bigtable
Setelah membuat tabel di Bigtable, Anda dapat mengimpor dan memvalidasi
data dengan mengikuti panduan di
Memigrasikan HBase di Google Cloud ke Bigtable.
Setelah memigrasikan data, Anda dapat memperbarui aplikasi untuk mengirim operasi baca dan tulis ke Bigtable.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 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."]]
