Code Monkey home page Code Monkey logo

fast-uuid's Introduction

Maven Central

fast-uuid

fast-uuid is a Java library for quickly and efficiently parsing and writing UUIDs. It yields the most dramatic performance gains when compared to Java 8 and older; in benchmarks, it's a little more than fourteen times faster at parsing UUIDs and six times faster at writing UUIDs than the stock JDK implementation. Compared to Java 9 and newer, it's about six times faster when it comes to parsing UUIDs and offers no benefits for writing UUIDs.

This library is intended for applications that work with large quantities of UUIDs or that work with UUIDs in performance-sensitive code, and probably won't be helpful in applications that work with UUIDs infrequently.

Usage

Using fast-uuid is simple. To parse UUIDs:

UUID uuid = FastUUID.parseUUID(uuidStringOrCharacterSequence);

To convert UUIDs to strings:

String uuidString = FastUUID.toString(uuid);

Getting fast-uuid

For users of Maven (or Maven-compaitble build tools like Gradle), fast-uuid is available via Maven Central. You can add it to your project with the following Maven dependency declaration:

<dependency>
    <groupId>com.eatthepath</groupId>
    <artifactId>fast-uuid</artifactId>
    <version>0.2.0</version>
</dependency>

For users managing their own dependencies, you can add fast-uuid to your project by adding the fast-uuid jar file from the latest release to your classpath. fast-uuid has no additional dependencies.

How it works

Parsing UUIDs

Let's take a look at the OpenJDK implementation of UUID#fromString(String) for Java 8 and older:

public static UUID fromString(String name) {
    String[] components = name.split("-");
    if (components.length != 5)
        throw new IllegalArgumentException("Invalid UUID string: "+name);
    for (int i=0; i<5; i++)
        components[i] = "0x"+components[i];

    long mostSigBits = Long.decode(components[0]).longValue();
    mostSigBits <<= 16;
    mostSigBits |= Long.decode(components[1]).longValue();
    mostSigBits <<= 16;
    mostSigBits |= Long.decode(components[2]).longValue();

    long leastSigBits = Long.decode(components[3]).longValue();
    leastSigBits <<= 48;
    leastSigBits |= Long.decode(components[4]).longValue();

    return new UUID(mostSigBits, leastSigBits);
}

If you're just dealing with UUIDs every now and then, this is just fine. If you're doing a lot of UUID parsing, though, there are a few things we might be concerned about here:

  1. This implementation starts off by creating an array of (presumably) five sub-strings. This can be a bit slow in its own right, but beyond that, it also creates five new strings that will need to be garbage-collected eventually.
  2. For each of those substrings, this implementation performs a string concatenation, which requires still more string allocation and eventual garbage collection.
  3. Eventually, this implementation needs to convert hexadecimal strings into numbers. It does so with Long#decode(String) rather than using Long#parseLong(String, int), which means somebody else needs to do the work of figuring out which radix to use when parsing the strings. This seems unnecessary since we know for sure that we're dealing with hexadecimal strings.

It turns out a lot of these issues are interrelated, and we can untangle them to get a significant performance boost. By recognizing that we're always dealing with hexadecimal strings, for example, we can immediately resolve the third issue. Once we've done that, we don't need to concatenate strings to prepend "0x" to the beginning of each of our substrings. That alone speeds things up by about 50% and cuts the number of string allocations (and presumably garbage collection pressure) in half.

That leaves the first problem: can we find a way to parse a UUID without breaking it into substrings first? It turns out we can! Here we have to move away from the handy parsing tools that the JDK provides us, though, and write some of our own. We can even go further and, because we know for sure that we're dealing with hexadecimal strings of a fixed length, we can write a parser that drops a lot of error-checking and flexibility and picks up a lot of speed in return. That's exactly what FastUUID provides, and the result is that it can parse UUIDs a little more than four times faster than the default JDK implementation and, aside from the finished UUID, doesn't create anything on the heap that will need to get garbage-collected later.

Here are some benchmark results under Java 8:

Benchmark Throughput Margin of error
UUID#fromString(String) 1,402,810 UUIDs/second ± 47,330 UUIDs/second
FastUUID#parseUUID(String) 19,736,169 UUIDs/second ± 247,028 UUIDs/second

The Java 9 implementation (some comments have been removed in the interest of brevity) improves the situation significantly:

public static UUID fromString(String name) {
    int len = name.length();
    if (len > 36) {
        throw new IllegalArgumentException("UUID string too large");
    }

    int dash1 = name.indexOf('-', 0);
    int dash2 = name.indexOf('-', dash1 + 1);
    int dash3 = name.indexOf('-', dash2 + 1);
    int dash4 = name.indexOf('-', dash3 + 1);
    int dash5 = name.indexOf('-', dash4 + 1);

    if (dash4 < 0 || dash5 >= 0) {
        throw new IllegalArgumentException("Invalid UUID string: " + name);
    }

    long mostSigBits = Long.parseLong(name, 0, dash1, 16) & 0xffffffffL;
    mostSigBits <<= 16;
    mostSigBits |= Long.parseLong(name, dash1 + 1, dash2, 16) & 0xffffL;
    mostSigBits <<= 16;
    mostSigBits |= Long.parseLong(name, dash2 + 1, dash3, 16) & 0xffffL;
    long leastSigBits = Long.parseLong(name, dash3 + 1, dash4, 16) & 0xffffL;
    leastSigBits <<= 48;
    leastSigBits |= Long.parseLong(name, dash4 + 1, len, 16) & 0xffffffffffffL;

    return new UUID(mostSigBits, leastSigBits);
}

This implementation does away with the string concatenation (and resulting string allocation) entirely. The obvious gains are gone, but we might still be able to improve the situation by using a more application-specific parser than Long#parseLong(String, int, int, int). As it turns out, using an application-specific parser makes a surprisingly significant difference. In benchmarks, a specialized parser is about six times faster than the Java 9 implementation of UUID#fromString(String).

Benchmark Throughput Margin of error
UUID#fromString(String) 2,613,730 UUIDs/second ± 25,278 UUIDs/second
FastUUID#parseUUID(String) 16,796,302 UUIDs/second ± 191,695 UUIDs/second

UUIDs to strings

We've shown that we can significantly improve upon the stock UUID#fromString(String) implementation. Can we achieve similar gains in going from a UUID to a String? Let's take a look at the stock implementation of UUID#toString() from Java 8:

public String toString() {
    return (digits(mostSigBits >> 32, 8) + "-" +
            digits(mostSigBits >> 16, 4) + "-" +
            digits(mostSigBits, 4) + "-" +
            digits(leastSigBits >> 48, 4) + "-" +
            digits(leastSigBits, 12));
}

private static String digits(long val, int digits) {
    long hi = 1L << (digits * 4);
    return Long.toHexString(hi | (val & (hi - 1))).substring(1);
}

As before, we might notice a few areas of concern:

  1. We're performing a lot of string concatenations. Each of those requires allocating space for a new string and ultimately garbage-collecting the intermediate strings. If we can find a way to do less concatenation, we might see some performance gains.
  2. Furthermore, every call to digits produces two new strings (via the calls to toHexString and substring) that ultimately get discarded.

As before, we know some things about UUIDs that help us avoid some general-case error checking and trade some flexibility for performance. For example, we know that the string representation of a UUID will always be exactly 36 characters long (32 hexadecimal digits and four dashes). That means we can pre-allocate space by way of (for example) a StringBuilder. That alone will save us quite a few string allocations and yield significant performance improvements.

As with UUID parsing, we can go further and write our own "to hexadecimal" method that uses our knowledge about the size and structure of UUID strings to place digits in exactly the right place in the finished string, reducing the need to get substrings and perform concatenations. In the end, this lets us convert UUIDs to strings more than six times faster (and, again, with much less garbage-collection pressure) than the stock implementation.

Some benchmark results under Java 8:

Benchmark Throughput Margin of error
UUID#toString() 2,620,932 UUIDs/second ± 21,128 UUIDs/second
FastUUID#toString(UUID) 17,449,401 UUIDs/second ± 221,382 UUIDs/second

Java 9 uses a native method to convert UUIDs to strings, and our optimized implementation is actually a bit slower than the native approach. As a result, we just pass calls to FastUUID#toString(UUID) through to UUID#toString() under Java 9 and newer.

Benchmarking

Because fast-uuid is a performance-oriented project, it includes jmh benchmarks to compare its performance against the stock JDK implementation. To run the the benchmarks:

cd fast-uuid
mvn clean install

cd benchmark
mvn clean install -U

java -jar target/benchmarks.jar

License

fast-uuid is published under the MIT license.

fast-uuid's People

Contributors

agrison avatar dependabot[bot] avatar jchambers avatar mushymiddle avatar pissedcapslock avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

fast-uuid's Issues

Publish to Maven Central

I'm opening this issue in the interest of transparency. I fully intend to publish this to Maven Central, but am traveling this week. I'll get it published as soon as I'm back home this weekend and can get my hands on my signing keys.

Create `toStringBytes` method that returns a `byte[]` instead of a String

For even better performance, it could even take an existing byte[] array, fill it with values and not create any garbage.
This would be great especially on Java 9+, where char[] aren't the internal representations of UUID Strings anymore.
It would be cool if it would a get a byte array for source as input (see #9), maybe even with an offset as length, like System.arraycopy or Arrays.equals does.

`toString` without the dashes

I realize a proper UUID has dash-delimiters. For my project specifically, we want those gone (to make UUID copyable from the commandline easily).

Any chance you'd accept a PR for toStringWithoutDashes?

Add method to create hash String from byte[] and long/long

Hey, thanks for sharing this little library!

Since UUIDs are sometimes the result of hashing calculations (e.g. MessageDigest.getInstance("md5")#digest), it may make sense to extend the lib with FastUUID.toString(byte[] uuid) and FastUUID.toString(long mostSignificantBits, long leastSignificantBits).

I would gladly contribute this change, if you think it makes sense.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.