Reducing Bloom Filter CPU Overhead in LSM-Trees on Modern Storage Devices
时间: 2023-04-11 14:01:00 浏览: 130
作为一个 AI,我可以回答这个问题。LSM-Tree 是一种常用的键值存储引擎,它使用 Bloom Filter 来加速查询操作。然而,在现代存储设备上,Bloom Filter 的 CPU 开销可能会成为瓶颈。为了减少这种开销,可以使用一些技术,例如使用 SIMD 指令集、压缩 Bloom Filter 等。
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(Collectors.reducing((c1,c2)->c1.getLeadScore()>c2.getLeadScore()?c1:c2), Optional::get)
这是一个 Java 8 中的 Collectors 类的 reducing 方法,用于将一个 Stream 中的元素按照某个规则进行归约操作,这里的规则是比较两个元素的 LeadScore 属性,返回 LeadScore 更高的那个元素。最后通过 Optional 类的 get 方法获取结果。
Exception in thread "main" java.lang.OutOfMemoryError: GC overhead limit exceeded
This error occurs when the Java Virtual Machine (JVM) is spending too much time on garbage collection (GC) and is unable to free up enough memory. When this happens, the JVM throws an OutOfMemoryError with the message "GC overhead limit exceeded".
The GC overhead limit is a threshold that specifies the maximum percentage of time that the JVM can spend on garbage collection before it is considered excessive. By default, this limit is set to 98%, which means that if the JVM spends more than 98% of its time on garbage collection, it will throw an OutOfMemoryError.
To resolve this issue, you can try one or more of the following:
1. Increase the heap size: This error can occur when the JVM is running out of memory. You can increase the heap size using the -Xmx option. For example, you can set the heap size to 2GB by adding the following to your command line: -Xmx2g.
2. Reduce the amount of memory used by your application: If your application is using too much memory, you can try reducing the amount of memory it uses. This can be done by optimizing your code, reducing the amount of data stored in memory, or using more efficient data structures.
3. Tune the garbage collector: You can tune the garbage collector to better suit your application's needs. This can be done by adjusting the GC algorithms, the heap size, and other parameters.
4. Use a profiler: You can use a profiler to identify memory leaks and other performance issues in your application. A profiler can help you identify which parts of your code are causing the JVM to spend too much time on garbage collection.