Google Cloud Search API - 每秒文档投放数量是否有限制？ [英] Google Cloud Search API - is there a limit to number of document puts per second?

问题描述

使用Google Cloud 搜索API 是否有限制或限制每秒可以向搜索索引添加多少个文档？

我知道Search API非常适合以这种方式进行查询和扩展，但每秒多少个单独文档呢？对每个文档使用唯一索引会提高性能吗？

我之所以问这个问题，是因为我将构建一个应用程序，它将包含许多Datastore投入和一个相应的搜索Datastore实体放置后立即放置文档。我很想知道，如果Search API与数据存储一样强大，那么每秒提交很多提交内容时都会如此。我希望随着应用程序的增长而线性扩展，而不是使用任务队列稍后将搜索文档与数据存储实体同步。

我的应用程序的性质要求同时放置实体和文档。

解决方案

在文档：

Search API强制使用这些限制来确保
服务的可靠性。这些适用于免费和付费应用程序：

最大查询使用情况：每个
分钟的查询执行时间总计100分钟

增加或删除的最大文件数量：每分钟15,000美元

因此，看起来存在安全限制每秒大约250次写/删除。如果应用持续增长并且不断增长，那将无法跟上数据存储。

如果有人有关于此的更多信息，请评论/回答。谢谢：）

With the Google Cloud Search API is there a limit or restriction to how many documents you can add to a search index per second?

I know the Search API is great for querying and scales well that way, but what about many individual document puts per second? Would using a unique index for each document put improve performance?

The reason I ask is because of an application I will be building that will have many Datastore puts with one respective Search document put right after the Datastore entity gets put. I am wondering if the Search API is as robust as the Datastore when it comes to many puts per second. I'd like to scale both linearly as the application grows rather than use a Task Queue to sync the Search document with the Datastore entity later.

The nature of my application calls for both the entity and document to be put at the same time.

解决方案

Found this at the bottom of the docs:

The Search API imposes these limits to ensure the reliability of the service. These apply to both free and paid apps:

Maximum query usage: 100 aggregated minutes of query execution time per minute

Maximum documents added or deleted: 15,000 per minute

So it looks like there is a safety limit that works out to be about 250 writes/deletes per second. That would not be able to keep up with the Datastore if the app kept growing and growing.

If anyone has any more information on this please comment/answer. Thank you :)

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