Why is java so slow

JIT compilation took time to become efficient major improvements with each version Classloading has become a lot more efficient over the years. It used to be quite inefficient and slow during startup. Swing and UI code did not use native graphics hardware very well.

Swing is just awful. Heavy use of synchronization in library classes; unsynchronized versions are now available Applets take forever to load, because of transmitting a full JAR over the network and loading the VM to boot. Synchronization used to carry a heavy performance penalty this has been optimized with each Java version. Reflection is still costly, though. Peter Mortensen 29k 21 21 gold badges 97 97 silver badges bronze badges.

You can do much better still if you write your own memory handlers with things like free lists, memory pools, and so on or use a library that implements such. Rex Kerr - Why use memory handlers if you can use e. You are confusing heap memory allocation with object instantiation. Sjoerd - Where did I say that everything in Java is faster? Just read what I said. I said what I meant, and have already addressed everything you said in your last comment.

Show 14 more comments. From the people I've talked to the impression of Java being slow comes from two things: Slow VM startup time. Given the above points, it's no wonder people got the 'Java is slow' impression. Java apps on OSX What evidence for quick startup times? Decompression is absolutely not a performance problem.

My computer in decompressed executables when starting programs which improved performance over loading a longer file from the hard drive. The disparity between CPU and hard drive has grown enormously over the intervening years. However, there is a problem with using the zip archive format for rt.

Sun has invested quite some time to make startup times faster on the platforms they support Windows, Linux and Solaris , but they couldn't do it for Mac OS x since they don't maintain that port. I don't consider java to be slow i know of a game maker who makes games in them ; just bad for UI reasons.

Not a single "regular" java app i've seen has a decent, completely working UI. Show 15 more comments. Sami Sami 3, 3 3 gold badges 27 27 silver badges 37 37 bronze badges. Add a comment. Jerry Coffin Jerry Coffin k 74 74 gold badges silver badges bronze badges. Dan Dyer Dan Dyer Thomas Pornin Thomas Pornin I thought most C libraries were dynamically linked nowadays too.

Or are you speaking of something different? Sean: dynamic linking for C occurs for "external symbols": the functions which are used in one DLL and defined in another. A typical C application will use a dozen DLL. For Java dynamic linking occurs for all methods in all classes: there are thousands of those in a typical Java application including the standard library. In the C world, most of the linking all links which do not cross a DLL boundary are resolved at compile time, only a small proportion still remains to do at runtime.

Java is definitely slow, especially for quantitative work. Hamaad Shah Hamaad Shah 1 1 silver badge 2 2 bronze badges. Following on from my aforementioned comment, I performed the same matrix multiplication operation using JAMA and it took around 50 seconds. Still too slow compared to other languages. How long did Java take when you performed the multiplication in the libraires called via JNI. I am guessing your R and Python matrix multiplication wasn't written in R or Python, just called from those languages.

Spike Williams Spike Williams Rex Kerr Rex Kerr k 26 26 gold badges silver badges bronze badges. Kaleb Brasee Kaleb Brasee This is because Sun has dragged its feet in the worst way in releasing Java 7, so we're stuck with incremental patches to the 4 year old Java 6. Wow, Java 6 is 4 years old??? Yep I guess so if you count the beta. Still feels new to me -- I just stopped using 1. Java 1. Bounds-check and System. So were a lot of synchronization improvements. I think it's fair to say 1.

LOL, I know -- every time I have to iterate manually or use an array instead of a generic List, I want to break my laptop in half There are double-digit percent performance improvements from 1.

Stefano: I have been with Java since the beginning, so from my point of view the fame of being slow was created by non-responsive and slow GUI frontends AWT, and then Swing and in Applets probably because of the additional slow startup times of the VM's. Colt is one of the best examples: The latest stable Colt release breaks the 1. Dieter Dieter 1, 8 8 silver badges 7 7 bronze badges. Ok, so another bad reputation came from the GUI toolkit. Stefano: Swing is actually based on the idea of non-native universal rendering of widgets, so your assumption is kind of wrong.

If you are looking for something like that, you may want to check out SWT eclipse. Java2D used for Swing is very quick these days, and using native widgets SWT provides no performance benefit. Eva 3, 4 4 gold badges 36 36 silver badges 62 62 bronze badges. Greg Fenton Greg Fenton 6 6 silver badges 13 13 bronze badges. Pascal Cuoq Pascal Cuoq Probably not true with HotSpot. Only if you mark the method as synchronized. The compiler doesn't optimise the code, but the JVM is smart enough to dynamically determine only one or two virtual methods are typically called and can call them staticly or even inline them.

Every Java Object has a lock. It has a small overhead about a byte on each object but has little impact if not used. In Java you can allocate at once all the Objects you need. This can give you can application which does not GC all day.

Ken Liu Ken Liu I know they have some strategies like generational layers for objects to be more efficient in the GC phase. What was the strategy at that time?

Wojciech Kaczmarek Wojciech Kaczmarek 1, 4 4 gold badges 21 21 silver badges 35 35 bronze badges. In the case of Eclipse - from the Eclipse infrastructure itself.

I have a gut feeling that it's because lots of boilerplate objects are needed to use a plugin architecture like Eclipse in a statically typed language. Emacs has plugins as well and its memory consumption is x less than Eclipse when doing typical coding.

Emacs Lisp code is compiled to bytecode and loaded into emacs instance, then run - similar to Java classloader. I guess in Java there are tons of intermediate objects instantiated to allow some plugability. Or perhaps "people are idiots" is a better answer. Boy Mr. Boy Interpretation will always be slower than running compiled code. This is why JIT compilers are used. The catch: there is little difference between an ahead of time compiler and a JIT compiler in terms of output, except that a JIT compiler must compile more quickly, and can use runtime info to hint its optimizations.

Platform-specific AoT compilers with platform-specific optimizations will almost always beat JIT because there is no limit how much time they spend on optimization. Thanks for the answer, never thought about the little time JIT compilers have at their disposal. BobMcGee: Very right. A JIT that did this would make the users leave.

JIT compile time is negligible for long running apps like servers. First, most performance difference is achieved by lightweight optimisations. Compare gcc -O2 to gcc -O3. Guess wrong, and you're far behind the JIT. And the actual profile can be extremely config-dependent. Show 1 more comment. The Overflow Blog. Does ES6 make JavaScript frameworks obsolete? Podcast Do polyglots have an edge when it comes to mastering programming Featured on Meta.

Now live: A fully responsive profile. Linked See more linked questions. An application rollback is typically the result of pre-designed business logic. But a non-application rollback is a serious issue and needs to be addressed immediately. The application would throw an exception and the transaction would roll back in return, not allowing the end-user using the application to process their request.

There are three types of non-application rollbacks:. All applications and supporting middleware and back end are run on enterprise servers. This could be a server operating system on a physical box, a virtual machine, or even in the cloud.

A problem in the server hardware or resources will affect the performance of the application running on it. Insufficient CPU, memory, and disk, operating system errors, server hardware faults, high-CPU processes, zombie processes, corrupt services, etc. Especially when the server is virtualized, it is even more difficult to pinpoint problems. A resource contention issue at the virtualized host server can impact all the guest virtual machines and applications running on them.

The same with containers and cloud-based application workloads. Bandwidth congestion in the network, high latency and packet loss, misconfiguration in a router, DNS failure, etc.

Usually there is a lot of finger-pointing between the application team and network team as to where the root cause of an application problem is and who needs to resolve it. When it is actually a network issue, the application team could be chasing a red herring on the server side. It is important for developers to code efficiently and testers to catch and report issues — no doubt!

The IT teams should also act proactively have the necessary performance management measures in place. Monitoring should not be an afterthought for organizations developing, hosting, implementing and using Java-based applications. Constant monitoring of user experience, application transactions, application code, and the supporting infrastructure is vital to detect and resolve problems before they become business-impacting. Save my name, email, and website in this browser for the next time I comment.

Privacy Policy Terms of Use. Make sure you have set this setting to be sufficiently high so that your application can handle the expected workload. The limit for the individual memory spaces also must be tuned correctly. Monitor JVM memory spaces and growth patterns continuously to proactively detect situations when there is a memory shortfall.

When excessive memory usage is detected, take a heap dump from the JVM, analyze the dump using a tool like the Eclipse Memory Analyzer and identify objects that are taking up an unusual amount of memory. Use this to fix code-level issues that may be causing memory leaks.

Fix code-level issues that cause unused objects to use up heap memory. Look for times when full GC happens. This can cause application slowness. A memory issue can manifest as high CPU usage, making performance diagnosis difficult.

Helpful Troubleshooting Tips: Monitor cache size continuously and get alerted when it falls below or exceeds your accepted threshold Monitor cache hit and miss ratios to track the success of the caching process Ensure proper synchronization of distributed caching happens in multiple servers.

Helpful Troubleshooting Tips: Monitor the status of threads in the JVM and determine the count of threads in running, blocked and deadlocked state. Use Java performance monitoring tools to help automatically detect blocked threads and deadlocks. Identify the exact module and the line of code at which the locking is happening.

Helpful Troubleshooting Tips: Continuously monitor connections to the database: total connections, active connections, etc. Track connection pool metrics, such as allocated, freed, created, closed and managed connections.

Correlate application access patterns with database connection pool usage to identify the cause of connection leaks. Get visibility into waiting requests and connection delays, analyze these metrics along with health indicators of the database servers and determine times when database server bottlenecks are affecting application performance.

Helpful Troubleshooting Tips: Analyze database queries issued by the application and identify web pages and corresponding queries that are taking time. Plan database sizing and configuration properly to ensure the consistent performance. Use database monitoring tools to identify and fix missing indexes, optimize the database layout by re-indexing, etc. Helpful Troubleshooting Tips: Incorporate best practices during the entire software development lifecycle — from design, development, testing, to rollout.

Development teams must be skilled to avoid code-level mistakes, and QA teams should be adept to catch issues proactively. Incorporate code optimization practices to ensure the application code meets expected standards. Use transaction profiling tools to isolate code-level problems automatically. He thinks array out of bounds errors are difficult to debug. The chances of him understanding how important memory access patterns are for performance is nil. Also, if the app perform any DB access to query data to help your decision, it may be take another bunch of ms!

High-frequency trading and high-performance computing uses networks like Solarflare or Mellanox, which have about 1 us of overhead. And same-node interprocess communication uses shared memory, which is half that. Whatever the network latency the app can not start processing the data until it has arrived and so the app latency will be an additional overhead on top of any network overhead.

So to say, anything that really needs to crunch numbers as fast as possible and requires a lot of memory manipulation, custom memory management systems, etc.

Also, for example, games make a big use of SIMD compiler intrinsics to utilise the CPU cores as much as possible where the GPU is already filled with tons of graphics work at this time. You can grab a chunk of memory and make any change you want in it.

My experience using Java for low latency inference services for advertising click prediction has yielded me a ton of frustration managing off heap memory and wrestling with the garbage collector. A managed language will never compete in low latency with an unmanaged language. The fact alone that Java has a garbage collector by default would slow it down. Post some benchmarks. NET release.

Who told you that C is faster than Java? C faster than Java? Stats to back that claim? C is absolutely faster than Java. It has more thorough support for value semantics.

You are only allocating when necessary. Also, not that this conversation is about this, it is much easier to write and read. Namely, it is easier and faster to develop in C than Java. It is after all more elegant than Java, being essentially a refinement of Java.

The traditional claim that you spend hours debugging is simply not true. Stop spreading lies! I would say that the title is misleading. All the effort is made to express that Java code is written quicker and with higher maintainability. If you need faster execution time, or faster development, depends on the domain. If I were to write a mathematical number-crunching library, where the latency would be the only reason to choose one library over another, it would probably be a fatal mistake to write it in Java.

Easier to write, maintain and therefore getting people up to speed are valid Business needs. Same goes for transcoded approaches. To be fair there might be Business cases for the middle ground focused in this article but they are never evaluated, explained or put into numbers.

This is accurate. Scala is better for general purpose app development. Python is good for scientific programming due to its excellent numpy library and the large ecosystem of statistical libraries built around it. Java is a not a bad legacy language running on a very good jvm platform. It is not the best of any breed but is often a convenient compromise. Did they use every corner of the library in their unit tests?

I agree with you there. WAY worse. This could mean skips for audio, triggering an airbag late, or failing to process an item on an assembly line. It does odd things when you are memory unsafe. The problem with Java is that performance is hard to predict.

If I avoid allocations in a loop, the JVM is still allowed to trigger garbage collection in the middle of it. This makes tracking down slowness hard.

Non-deterministic execution time is a failure. No-one wants horrific software virtual machines in critical applications. Please study your field a bit more before rambling stuff like this.

I also taught. I found backpropagation code in C and in Python for ideas. The Python code was undoubtedly faster because it was more efficient. The cryptic C code had a major inefficiency. But HFT! HFT is a market maker and ideally at the end of the day you up with no position at all. Jitter is not. That way all the branches etc are taken as if we really were sending an order, just the hardware drops the result.

But here we are talking microseconds and up to milliseconds rather than nanoseconds — many factors above the requirements for HFT. Disclaimer — I am not a HFT developer but work closely on projects with a number of developers who are. A textbook definition of a hard real-time system. No java application can handle such a requirement.

I am also not a HTF developer, but I am quite familiar with real-time systems for various use cases. And this looks like one of them to me. This is the most on-target comment so far. The jitter consideration alone tanks java with its VM as a consideration.

Java is getting better but it is not afaik a candidate for HFT or other hard real-time apps. The only way that could change is by using a hard-realtime jvm. My understanding is that such a jvm has not existed for many years. Thanks, exactly what I was going to reply. Sometimes a screwdriver sometimes a saw. For some cases devs want to decide on the memory layout of objects in memory and not worry about the VM or cache misses etc… Same reason as why webassembly became a thing in browsers.

Also did you notice there are languages like RUST that are quite popular on Stackoverflow these days? JS does not do HFT. They do some form of algo trading. Firms do algo trading in a lot of languages: Python, Java, OCaml etc. This has to be one of the most baffling articles I have read in a while. The one point I really agree with is that it all depends on your definition of low-latency. First and foremost, an article that talks about latency should give some hard numbers.

The only number quoted here is 1ms for 5G latency. These spikes are not just due to the unspeakable things GC has to do to work but also to the increased memory consumption due to GC. The higher mem pressure in turn opens your app to things like TLB shootdowns. Can't mlock some portion of your memory in Java right?

What "large" or "Tier 1" banks do or do not is largely irrelevant. Most of them are not players in the "high speed trading" usually because they have terrible software stacks. Furthermore, exchanges compete on a lot more than latency like commissions and execution rules.

So their choice of tech is also not terribly relevant. Are there any sizable HFT shop still alive mainly using Java these days don't know one but that certainly does not mean that does not exist?

I certainly believe it's better than java. The code is probably very similar with, you know, just terrible tails. Now there is the whole usual set of tired arguments about tools.

It's only been available for 15 years in GCC. You're welcome. All the references here seem to come ads from Java people trying to sell Java software or consultancy. So yeah they'll tell you how LL on Java is so great — mind officially blown.

Experts in the area are well employed in the industry and don't go around trying to sell consultancy to sleepy era banks…. The whole argument is based on opinion and present them as fact. One, debugging is in much better shape than a lot might think. You have address sanitizer available on all popular platforms. You get stack traces when using it, with almost everything you need to identify the problem.

Then you have tools such as valgrind, which will identify bad access, memory leaks and others. If you stay away from macros and define things correctly, the chances are extremely low. As for the massive development costs, without measurements your point is basically useless. When using a system level programming languages, you gain more control and in turn will lower costs of other things around it. When agreeing on a structure, developpement is usually pretty smooth. I might as well say your java application will be slow to develop because it took years to make Minecraft playable and they made the bedrock edition in less time and is more performant.

But of course, such argument is a sophist. This is wrong. This is only a very small fraction of the gain in performance you get. The largest gain I would say is A control over memory. Which object get on the stack, which gets on the heap, contiguous memory etc.

B probably the largest gain and other system languages like rust is that they are optimisable. You get code inlining, constant folding, devirtualization, vectorization. All of which can help reduce the binary size and the make the program faster. Also, being able to control memory to your needs. Dynamic allocations has an impredictable latency. Virtual fonctions may be disallowed since you want to know the cost of every statement in a low latency system. In java, you are forced to do dynamic allocation.

You cannot have a non virtual member function. You cannot have contiguous memory of objects. Data oriented design is almost impossible to do in a efficient manner. The very design of the java language makes it unsuitable for the task.

Ever heard of profile guided optimization? And the simple tools that exists to get hardware info at build time? Of course not. For all the reasons I wrote above, no, there is much more latency than you think here. But you have the tools to write fast code in those. Maybe I should stop.

The committee is the largest it has ever been, the number of conference has more than quadruple over the last 5 years.