[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-08-18。"],[[["\u003cp\u003eBigtable supports SQL queries through multiple methods, including GoogleSQL for low-latency applications, Spark SQL for batch processing and ETL, and BigQuery for analyzing data from multiple sources.\u003c/p\u003e\n"],["\u003cp\u003eGoogleSQL for Bigtable, which is similar to Cassandra Query Language (CQL), can be used within the Google Cloud console via Bigtable Studio, or programmatically through the Bigtable client library for Java.\u003c/p\u003e\n"],["\u003cp\u003eThe Bigtable Spark connector enables reading and writing Bigtable data with Spark SQL, beneficial for data science and batch processing needs.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery can query and analyze data from Bigtable alongside other sources using external tables, facilitating batch and ad hoc analytics.\u003c/p\u003e\n"]]],[],null,[]]