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Accelerate your RMI programming

Speed up performance bottlenecks created by RMI

By Ashok Mathew and Mark Roulo, JavaWorld.com, 09/07/01

RMI lets you write distributed Java programs with minimal extra work. Unfortunately, RMI also introduces new opportunities for performance bottlenecks in addition to those typically present in nonnetworked Java programs. You can reduce or eliminate many of these bottlenecks with careful design or with hand optimizations. This article shows how to safely optimize around a number of those bottlenecks.

Where does the time go?

An RMI call consists of three basic steps: pounding an object or object tree into an array of bytes, sending those bytes across a network, and rebuilding the byte array into an equivalent object or object tree at the far end. We will ignore a fourth activity -- shipping missing classes across the network -- because it only happens during the first RMI call with new classes.

The object-to-bytes and bytes-to-object conversions are paired, and in this article, we treat them as a unit for throughput purposes. The time spent sending bytes over the network tends to be independent of the time spent converting objects to bytes and back again. Instead, that time can be influenced by two factors: by the byte array's length, and by optimizations that reduce the number of bytes sent over the network; those bytes sometimes run faster because fewer bytes are transmitted.

The network

RMI is built on top of network sockets and, thus, network problems can slow RMI calls. For applets running over the Internet, you may not be able to ensure that the network settings provide reasonable throughput. However, you do have control over applets and applications that run only on local networks. At the very least, you should ensure that your part of the network connection is not responsible for any bandwidth limitations.

This cost of suboptimal network settings can be higher than you might assume. On one internal application, we found that some machines, containing small subnets, were running 50 times faster than others. Further investigation revealed that the slow machines had their networks misconfigured and were only getting 100-200 Kbps out of a 100 Mbps network!

The netperf tool

We measured our network performance using a tool called netperf, which lets you measure the network bandwidth between machines under a variety of configurations. It showed us that our fast machines were running at 70 Mbps and the slow machines at 100-200 Kbps. As the hardware was identical, this rapidly led to a comparison of network configurations and the problem was resolved.

The lesson here is that even a fast network can run slowly if misconfigured. Before spending time optimizing your code, ensure that the problem isn't your network.

The TcpWindowSize parameter

TcpWindowSize is one of many TCP/IP tuning parameters, and seems to have the most direct influence over network bandwidth. TcpWindowSize controls the amount of data you can send from one machine to another without receiving an acknowledgment packet from the other side. A detailed discussion of this parameter is beyond this article's scope, but a short summary is that reliable networks, like internal ethernet networks, run faster with large window sizes. Unreliable networks, like the Internet, run faster with smaller window sizes. Usually, the default size is fine, and you don't want to change this parameter without measuring the benefit. We found that for one example, changing TcpWindowSize increased the netperf bandwidth by about 10 percent, but only increased our RMI bandwidth by less than 1 percent. Your application may be different, especially if run over a less reliable network. In any event, if you tune this to speed up netperf, verify that it helps your RMI performance as well.

 

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