从Firebase以外的其他来源同时将数据保存在bigquery中 [英] Saving data in bigquery simultaneously from a source other than firebase

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本文介绍了从Firebase以外的其他来源同时将数据保存在bigquery中的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我们正在尝试根据应用程序记录一些事件.事件有两种类型,

We are trying to log some events based on our application. There are two types of events,

  1. 客户端事件:由Android应用程序使用firebase SDK记录,并由firebase保存到bigquery
  2. 服务器端事件:我们使用bigquery的go客户端对其进行记录

现在,firebase将当天的事件存储到events_intraday_ $ date表中,然后将该表刷新到分区表events_ $ date中.

Now, firebase stores current day's events into events_intraday_$date table and then flushes that table into partitioned table events_$date.

因此,我也将当天的事件记录到events_intraday_ $ date表中.

So, I also logged current day's events into events_intraday_$date table.

事件已成功登录到表中,但是第二天在将events_intraday_ $ date表刷新到events_ $ date表中时被删除了.

The events got logged successfully into the table but got deleted the next day when the events_intraday_$date table is flushed into events_$date table.

我不知道那是怎么回事.

I'm not able to understand how is that happening.

推荐答案

类似这样的是

在每个数据集中,每天导出的表格都会被导入.每日表格的格式为"ga_sessions_YYYYMMDD".

Within each dataset, a table is imported for each day of export. Daily tables have the format "ga_sessions_YYYYMMDD".

日内数据大约一天导入3次.日内表格的格式为"ga_sessions_intraday_YYYYMMDD".在同一天,每次导入的盘中数据都会覆盖同一表格中的上一次导入.

Intraday data is imported approximately three times a day. Intraday tables have the format "ga_sessions_intraday_YYYYMMDD". During the same day, each import of intraday data overwrites the previous import in the same table.

完成每日导入后,将从前一天开始的日内表格被删除.对于当前日期,直到第一个日内导入之前,都没有日内表.如果日内表写入失败,则将保留前一天的日内表.

When the daily import is complete, the intraday table from the previous day is deleted. For the current day, until the first intraday import, there is no intraday table. If an intraday-table write fails, then the previous day's intraday table is preserved.

直到完成每日导入,当前日期的数据才是最终的.您可能会注意到,根据跨越上次导入日期的时间范围的活动用户会话,日内数据和每日数据之间存在差异.

Data for the current day is not final until the daily import is complete. You may notice differences between intraday and daily data based on active user sessions that cross the time boundary of last intraday import.

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