Java World Interview on Scalability and Other Java Scalability Secrets. OK, this interview is with me on Java scalability issues. I sound like a bigger idiot than I would like, but I suppose it could have been worse. The Java World folks were very nice and did a good job, so theres no blame on them The interview went an interesting direction, but theres more Id like add and I will do so here. Two major rules regarding Java and scalability have popped out at me Java Its the platform stupid. Java the language isnt the big win. What is the big win is the ecosystem building up around the JVM, libraries, and toolsets. Note When a WebLogic domain is setup to use policies based on the OPSS security store, JACC policies and the Java Security Manager become unavailable on all managed. Here you will learn some basics stuff related to Java e. Java and setting enviornment variable. Java Its the community stupid. A lot of creativity is being expended on leveraging the Java platform to meet scalability challenges. Portable Hdd Scan. The amazing community that has built up around Java is pushing Java to the next level in almost every direction imaginable. The fecundity of the Java ecosystem can most readily be seen with the efforts to tame our multi core future. Theres a multi core crisis going in case you havent heard. Its all youll hear mentioned in the halls of the Pentagon. The CPU wizards have maxed out on clock speed and the only way we can scale is by adding more cores. And we dont know how to do that. At 1. 00 cores common ways of doing things break down. Locks dont scale. Cache contention for shared memory slows us down. Bandwidth on the bus is limited. TLB for managing more memory is in short supply. And we need more high speed network cards to handle faster CPUs. And thats just at the hardware level. Its worse for programmers. Difference Between Core Java And Advanced Java Pdf' title='Difference Between Core Java And Advanced Java Pdf' />Locking is just a nightmare. I didnt believe that at first. Early in my career I worked on several multi core systems. I thought everything was cool. Be careful and it will all work out. But work with a group and it all goes to hell. People add functions, locks, take too much time. Problems like deadlock, priority inversion, and high latency all kill a system. What can we do As well see, Java and more importantly the JVM have become a platform for many interesting technologies and scalability patterns. Lets take a look at few. How Java affects both Performance and Scalability. Peter Williams in this very informative blog post discusses how Java affects both performance and scalability. The main points are Java does not scale any better, or worse, than any other general purpose language. How easily can you increase the number of requestssec the system can handle derives from the architecture of the system sharding, caching, avoid database etc. Javas culture encourages practices that scale only to medium size system because it encourages techniques that do not scale well favors multi threadingshared statevertical scalinglarge monolithic componentsmultiple tiers, lots of layers. Java is for performance and is the reason to use Java even though the good performance means it scales pretty well out of the box. Keygen Draw Plus X6. Scaling with Java requires going your own way and bucking the culture to implement more scalable practices. Alain Penders makes some good points in the comments Java scalable not because its better suitable for building scalable systems, but because how to build scalable systems with it is well understood and the components you need to do so are widely available. Not only are those components widely available, they are available from multiple vendors some free, some commercial so youre never locked in, an aspect thats extremely valuable when producing commercial software. Ruby Rails applications can be built to scale well, but the techniques are not as well understood as for Java. Ron takes an apposing view and says Java is less scalable During garbage collection all threads are blocked and the garbage collection time can expand to minutes. These huge latencies effectively limit memory which limits scalability. Increased garbage collection latencies make Java less useful for application that use heart beats, make real time trades, etc. Real Time Java API extensions were developed as a way of addressing garbage collection problems. Greg Frank weighs in with some excellent points Java language itself has nothing to do with scalability. Rons comments about garbage collection dont apply to post 1. JVMS. Old school J2. EE is dead. The monolithic server is being replaced with advanced patterns based on new technologies like jgroups, ehcache and terracotta. The true force pushing scalability is the java community itself. Java is merely a convenient and commonly spoken language that allows for the formation of a global community. We should stop debating language internals and start debating sophisticated design patterns that promote scalability. The Top 1. 0 Ways to Botch Enterprise Java Application Scalability and Reliability. This is a wonderful presentation by Oracles Cameron Purdy. Heres a PDF. Cameron was CEO of Tangosol before Oracle bought them out. Tangosol made Coherence, a distributed cache. Cameron is a long time prolific contributor to the Java community. His presentation is a must see. Hes both entertaining and technically excellent. The main points he makes in the presentation are 1. Avoid proprietary featuresBelieve product claims. Assume the network works. Use big JVM machine heaps. Use a one size fits all architecture. Assume disaster recovery can be added when it becomes necessary. Abuse AbstractionsAvoid abstractions. Introduce a single point of bottleneckIntroduce a single point of failure. Abuse the databaseAvoid the database. Assume you are smarter than the infrastructureFollow the rules blindly. Optimize performance assuming that it will translate to scalabilityIgnore the potential impact of performance on scalability and vice versa. Remember, iff these seem backwards remember these are botching strategies. Youll want to see the presentation to see each point fleshed out in more detail. Azul. Azul is a Java Compute Appliance and is the ultimate scale up play for Java. It kind of does what Google App Engine does at the framework level but does it to the JVM at the hardware level. Current standard practice is to deploy Java application across a cluster of commodity servers. Azul does the opposite. It goes big. The most recent release can contain up to 8. GB of memory. Thats big. Azul transparently runs unmodified Java applications on their specialized hardware platform which allows even the most mild mannered of Java apps to scale. Their hardware assisted garbage collector dramatically reduces application pauses and gives access to hundred of gigabytes of RAM. Some very impressive performance improvements are possible. In one case study Breakthrough Scalability of an Application Constrained to an x. Server, an application was given access to 3. GB of memory on an Azul compute appliance. The result was a 4. Scalability was increased along a number of dimensions quoted from their article Thread count Initially the application was artificially limiting the number of threads that were allowed to execute. With few threads, the application started at 2,2. OPS on Azul below the 1. OPS. Memory locks When many threads access the same piece of memory, traditional systems force developers to serialize the threads to make sure two threads do not simultaneously change the same memory location similar to how airlines make sure the same seat is not assigned to two different people. Azul appliances can detect such collisions in real time and assure correct execution.