如何在Google Cloud Datastore中完成结果集查询规模
[英]How is Result-Set Query Scale done in Google Cloud Datastore
问题描述
It is mentioned that making queries in Google Cloud Datastore is as expensive, with regards to time, as the number of results, which means that, for example, the time it takes to run any query would be proportional only to the number of matching results. 
要提到的是，就时间而言，在Google Cloud Datastore中进行查询与结果数量一样昂贵，这意味着，例如，运行任何查询所花费的时间只会与匹配结果的数量成比例。
Can anyone give some explanation about how is it done in GCD or NoSQL Documented database? 谁能给出一些关于如何在GCD或NoSQL文档数据库中完成操作的解释？
I know there is a possible that you can implement the distributed system and run queries in parallel. 我知道您有可能实现分布式系统并并行运行查询。 But it is mentioned that the Datastore uses indexing to accomplish this, how would the indexing be in this way? 但有人提到数据存储区使用索引来完成此操作，索引将如何以这种方式进行？
1 个解决方案
解决方案1
1 2019-04-30 15:21:13
Queries in Cloud Datastore must use an index. Cloud Datastore中的查询必须使用索引。 There are no queries that scan the entire database. 没有查询会扫描整个数据库。
On how indexes work in general, the indexes in Cloud Datastore all ordered indexes, and for each indexed property there is a write to a separate index table which is used to answer a query. 关于索引的一般工作方式，Cloud Datastore中的索引是所有排序的索引，对于每个索引属性，都有一个单独的索引表的写操作，该表用于回答查询。 You can find details at https://cloud.google.com/datastore/docs/concepts/indexes . 您可以在https://cloud.google.com/datastore/docs/concepts/indexes上找到详细信息。
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