When Java's cup runs over

据首席投资副总裁David Campbell表示，第一季度报告纪录于第一季度纪录的24.8亿利润，这是一季度的历史上，这是一季度，这是一项由其良好的财富带来的问题，即储存交易职位的能力耗尽容量。该公司。服务器已经吸收了12千兆字节的新信息，服务器面临着每日数据负载，这些数据负载是从现在开始的一年水平的两倍。添加更多硬件是显而易见的答案，但涉及的Java重新编程将采取“几个月来完成数十万美元或更多”，坎贝尔估计。

高盛的情况并非独特。据估计，在编程语言中编写的80％的新墙街应用程序，Java开始揭示其限制。

"Raw Java, off the shelf, lacks certain things that can be useful when building applications that require several servers to work together," says Michael Gilpin, a research director at Cambridge, Massachusettsbased consulting firm Forrester Research. He adds that clustering is becoming more common on Wall Street.

Goldman Sachs hasn't yet decided how it will program its new servers, but Campbell is betting that other firms share its clustering problem. For that reason, his group led a $13.5 million second round of financing in February for San Franciscobased Terracotta, a technology company that specializes in solutions for Java scalability.

"Financial services companies need the ability to add capacity on the fly," says Ari Zilka, Terracotta's CEO, who believes that traditional ways of clustering or scaling up Java applications are error-prone owing to one of its most popular features: the automation of processes that underlie complex applications. These automated elements, which free developers to focus on the code needed for a particular business problem, sometimes get in the way.

"Memory management is one of the things people typically run up against when they're scaling applications in Java," says Charles Doerr, chief architect at New Yorkbased derivatives trading platform Creditex. At Bank of New York, chief systems architect Sateesh Prabakaran says some applications are slowed by Java's automated release of idle memory for use by other applications. This "garbage collection" feature disposes of an application's outdated content and reallocates the dedicated memory to more pertinent tasks. By contrast, C++, an older programming language that dominated Wall Street applications until recently, requires a developer to decide how that additional memory should be used.

"Garbage collection adds a step that can't be controlled by programmers," says Prabakaran. "It has been a problem in terms of achieving the highly optimized performance we're looking to gain from high-end computation."

Although some users say they like garbage collection, others work around it by employing different programs. For example, when Creditex had to expand its primary trading application from one server to four because of an increase in volume, Doerr used open-source software to supplement the customized Java programming done by his developers. For its analytics applications, J.P. Morgan Chase & Co. programs in C++.

Ray Valdes, research director for Internet platforms at Gartner Research, a Stamford, Connecticutbased consulting firm, says Java is less efficient in its use of computational power than C++ because Java runs on a virtual machine layer that sits above the hardware. Although this allows Java to mask the underlying hardware, enabling applications to run on anything from a cellular phone to a mainframe, it takes up valuable space.

“Java添加开销,”他说。”一个certai c++做n task runs 30 to 50 percent faster than a Java program."

None of this means that Java is headed out the door anytime soon. Wall Street technologists say it's still their favorite language, because it is quick, easy to use and hardware-neutral, permitting the linkage of platforms that otherwise wouldn't be able to communicate. It is employed for solutions ranging from risk calculators to Web sites, and because it's not owned by a single vendor, Java offers access to a vast and growing network of programmers and open-source libraries.

“到目前为止，它比我们使用的任何其他事情都更好，”J.P. Morgan的首席信息官Michael Ashworth Sums Up up Michael Ashworth。