在具有大型数据集的Firebase数据库上查询非常慢

本文介绍了在具有大型数据集的Firebase数据库上查询非常慢的处理方法，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

我在Android应用上使用Firebase数据库。通常，它工作正常。但是，当数据库变大时，查询性能会变差。我在数据库（在 elk和 su节点下）上添加了约5k记录，然后在数据库（在 cut和 user节点上）上查询，但是所有查询都非常慢。我在数据库规则上定义了数据索引，但是它没有用。我该如何解决这个问题？

I use Firebase database on my Android app. Normally, it works fine. But when the database is getting larger, the query performance is getting worse. I added about 5k record on database (under "elk" and "su" nodes), then I queried on database (on "cut" and "user" nodes) but all the queries are very very slow. I defined data index on database rules but it did not work. How can I solve that problem?

这是我的查询：

// query to get the zones followed by user FirebaseDatabase.getInstance() .getReference() .child("user") .child(userID) .child("zones"); // query to get cuts on a zone FirebaseDatabase.getInstance() .getReference() .child("cut") .child(cutType) .orderByChild("zoneID") .equalTo(zoneID);

推荐答案

如果要继续扩展，最好的方法是是要在区域引用中复制您的数据，在该区域引用中您知道哪个麋鹿/苏。像这样的东西：

If you want to continue expanding the best thing to do would be to duplicate your data in a zone reference where it knows which elk/su are a part of it. Something like this:

{ zones: { elk: { "istan-besik": { "-KSp)bL5....": true, ...: true } } } }

这样，当您要搜索所有内容时，只需做以下操作即可：

That way when you want to search for all you would just do:

...child('zones').child(zoneId).child(cutType)

然后循环遍历，直接获得每个麋鹿/ su

And then loop through those to go get each elk/su directly