BigQuery 现在支持 函数调用 GENERATE_UUID.这将返回一个 STRING，其中包含 8-4-4-4-12 形式的连字符分隔的五组中的 32 个十六进制数字.

BigQuery now supports a function called GENERATE_UUID. This returns a STRING with 32 hexadecimal digits in five groups separated by hyphens in the form 8-4-4-4-12.

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权衡的一些讨论:

• UUID 与其他系统中的表示兼容，例如，如果您导出到 CSV，然后想要与其他地方的导出合并.
• UUID 与 BigQuery 的可能是 UUID 实现兼容.您将能够使用函数生成相同形式的 UUID(在实现该功能时).
• 如果您稍后决定将 UUID 表示为 BYTES，则可以使用 UDF 进行转换.
• 缺点:根据运算符，比较可能不如 BYTES 快，因为字符串比较必须考虑 UTF-8 编码.(听起来这对您来说不是问题).
• 缺点:存储成本较高.(听起来这对您来说不是问题).

• UUIDs are compatible with the representation in other systems, such as if you export to CSV and then want to merge with exports from elsewhere.
• UUIDs are compatible with BigQuery's probably UUID implementation. You will be able to generate UUIDs of this same form using a function (when the feature is implemented).
• If you decide to represent the UUIDs as BYTES later, you can potentially convert using a UDF.
• Downside: Comparisons may not be as fast as with BYTES depending on the operator, since string comparisons have to take UTF-8 encoding into account. (It sounds like this isn't an issue for you).
• Downside: Storage costs are higher. (It sounds like this isn't an issue for you).

• UUID 的存储更加紧凑；存储更便宜，比较更快.
• 如果您决定稍后将 UUID 表示为 STRING，则可以使用 UDF 潜在地转换它们.
• 缺点:UUID 导出后与其他系统不兼容，也可能与 BigQuery 的实现不兼容.

• UUIDs are stored more compactly; storage is cheaper and comparisons are faster.
• If you decide to represent the UUIDs as STRINGs later, you can potentially convert them using a UDF.
• Downside: UUIDs are not compatible with other systems after export, and will likely not be compatible with BigQuery's implementation either.