21–30 of 373 posts
Not just heavy but I really don't like all our processes named "java" with stupid -D cmd line parameters. A Nice native binary app will let you can name it what you want with config as you like it.
I agree with many points in this article. That being said, there are dimensions of heaviness not captured in the article as far as I can see: 1. The startup times, not so much of the JVM itself, that just takes 1,5 secs, but the startup time of your application gets higher if you have a lot of classes on the classpath. I guess it's the classpath scanning that takes a lot of time (?). 2. Memory usage of Java objects i…
Not just heavy but I really don't like all our processes named "java" with stupid -D cmd line parameters. A Nice native binary app will let you can name it what you want with config as you like it.
I used to think this too, until I came across http://www.scylladb.com/ It is a fork of cassandra written in the Seastar c++ framework and is drop-in compatible with cassandra. Claims 10x increase in performance. I always thought there was a few percentage points difference - never a 10x performance difference between java and c++. And that too for a project with as many man hours and facebook-scale tuning as cassandr…
Naive translations from Java to C++ will normally result in only a small % difference.
But clever rewrites where control of memory locality is leveraged, and SIMD intrinsics are leveraged (either via pragmas to induce it automatically, or by hand), good understanding of compiler settings for given architectures, etc, the differences can get quite large, depending on the problem domain.
Then again, there are ways around some of the performance limitations in the JVM, but it often involves writing very painful coding styles. But you could narrow the gap a bit with that effort. (but if you are going to add effort, maybe just do it is in C++?)
A couple of years ago I wrote a simple tool (https://github.com/aerofs/openjdk-trim) that allows you to filter out what you don't need. We were able to get the size of OpenJDK from 100MB down to around 10MB.
Note that the work of determining which classes you need is entirely manual. In our case I used strace to check what classes where being loaded.
Also worth noting that the JVM itself only weighs a couple of megabytes. The bulk of the size comes from the Java runtime (ie: the "standard libraries"), and there are lots of things that your app may not need there (XML parsing, serialization, etc...) A couple of years ago I wrote a simple tool ( https://github.com/aerofs/openjdk-trim ) that allows you to filter out what you don't need. We were able to get the size…
Also worth noting that the JVM itself only weighs a couple of megabytes. The bulk of the size comes from the Java runtime (ie: the "standard libraries"), and there are lots of things that your app may not need there (XML parsing, serialization, etc...) A couple of years ago I wrote a simple tool ( https://github.com/aerofs/openjdk-trim ) that allows you to filter out what you don't need. We were able to get the size…
Already today you can build a custom JDK in the early access release.
I agree with many points in this article. That being said, there are dimensions of heaviness not captured in the article as far as I can see: 1. The startup times, not so much of the JVM itself, that just takes 1,5 secs, but the startup time of your application gets higher if you have a lot of classes on the classpath. I guess it's the classpath scanning that takes a lot of time (?). 2. Memory usage of Java objects i…
I used to think this too, until I came across http://www.scylladb.com/ It is a fork of cassandra written in the Seastar c++ framework and is drop-in compatible with cassandra. Claims 10x increase in performance. I always thought there was a few percentage points difference - never a 10x performance difference between java and c++. And that too for a project with as many man hours and facebook-scale tuning as cassandr…
This might seem like a good thing (ScyllaDB gives you extra performance when you have the memory for it), but it does mean that if your dataset grows, performance falls off a cliff. Something to keep in mind.