We are running AWS Aurora(Serverless RDS) in our production environment. It has to scale between 2 capacity units(4GB RAM) and 8 capacity units(16GB RAM).
For the last 2 months, our database has never auto-scaled, it was running in the minimum capacity unit. In the past week, due to an increase in system usage, auto-scaling started triggering every few mins. It was scaling between 4 and 8 capacity units during the day time.
And since last week, we were getting an …
mysql amazon-web-services amazon-rds autoscaling amazon-aurora
我有一个抽象类BaseTemplate和多个扩展它的类.在其中一个具体的class(SmsTemplate extends BaseTemplate)中,我们有一个私有变量Gson.我们Gson在抽象类中也有相同的私有变量().
在测试具体类的单元时,抽象类中的方法是从具体类调用的.在我的单元测试中,我Whitebox.setInternalState(smsTemplateObj, gsonObj);用来将Gson对象注入到私有成员中SmsTemplate,BaseTemplate但是Gson只是在子类中注入.在抽象类中,它的NULL意思是不注入.以下是实施.
请问有人可以告诉如何在抽象类中注入Gson对象吗?
abstract class BaseTemplate{
private Gson gson;//Here its not getting injected
protected String getContent(Content content){
return gson.toJson(content); // ERROR - gson here throws NPE as its not injected
}
}
class SmsTemplate extends BaseTemplate{
private Gson gson;//Here its getting injected
public String processTemplate(Content content){
String strContent = getContent(content);
...
...
gson.fromJson(strContent, Template.class);
}
}
Run Code Online (Sandbox Code Playgroud) 我们配置<time-to-live-seconds>为1200(20分钟)但缓存在缓存创建时间一分钟后自动逐出.
有人可以告诉如何在指定的时间段内使缓存生效吗?
我们在一个表中有超过2000万条记录,并且我们尝试更新3K记录,但是这花费了7分钟以上的时间,并且没有完成,因此终止了查询。
示例查询
UPDATE TABLE_A
SET STATUS = 'PENDING'
WHERE ID IN (
SELECT ID
FROM TMP_TABLE_A_STATUS_FIX
); /*took more than 7 mins and didn't complete even after that*/
Run Code Online (Sandbox Code Playgroud)
我们在临时表TMP_TABLE_A_STATUS_FIX(只有3K记录)中收集了所有需要更新的ID。
由于上述查询花费的时间太长,我们分别进行了如下更新:
UPDATE TABLE_A SET STATUS = 'PENDING' WHERE ID = 1;
UPDATE TABLE_A SET STATUS = 'PENDING' WHERE ID = 2;
UPDATE TABLE_A SET STATUS = 'PENDING' WHERE ID = 3;
.
.
.
UPDATE TABLE_A SET STATUS = 'PENDING' WHERE ID = 2999;
UPDATE TABLE_A SET STATUS = 'PENDING' WHERE …Run Code Online (Sandbox Code Playgroud) mysql ×2
amazon-rds ×1
autoscaling ×1
caching ×1
database ×1
hazelcast ×1
java ×1
junit ×1
mockito ×1
spring ×1
spring-cache ×1
sql ×1
unit-testing ×1