在具有大型数据集的Firebase数据库上查询非常慢 [英] Querying on Firebase Database with large data set is very very slow
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
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