[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-07-11 (世界標準時間)。"],[[["The Apache Beam Bigtable I/O connector facilitates writing data from Dataflow to Bigtable, and pre-built Google Dataflow templates can also be used depending on the use case."],["Bigtable cluster nodes dictate parallelism, with each node managing key ranges that can shift during load balancing, and node count directly affects Bigtable costs."],["Performance metrics for Bigtable I/O write operations were measured at 65 MBps or 60,000 elements per second using a specific setup, though real-world pipeline performance can vary greatly."],["Avoid using transactions when writing to Bigtable with Dataflow due to potential issues with idempotency and retries, and use `GroupByKey` for improved write efficiency."],["Utilizing `withFlowControl` is advised when writing substantial datasets to Bigtable to automatically manage traffic and prevent Bigtable server overload."]]],[]]
