Reflection on not using Reflection

SLF4J has done a good job by allowing users to continue using whatever logging framework they are currently using and then in time move on to LogBack. I like the way they require the adapter jar (e.g. slf4j-jcl.jar or slf4j-log4j12.jar) to have the org.slf4j.impl.StaticLoggerBinder and a few other classes for static binding. And those classes are supposed to implement interfaces from the aptly named org.slf4j.spi package

I thought they would load that class via reflection (=dynamically bind) but looking at the code in org.slf4j.LoggerFactory, it is not the case:

StaticLoggerBinder.getSingleton().getLoggerFactory();

So that might suggest that when they packaged the slf4j-api.jar, they had either slf4j-simple.jar or slf4j-nop.jar in the classpath, however that would result in a circular dependency as ILoggerFactory interface that the above method returns is defined in slf4j-api.jar. So, I think when they packaged slf4j-api.jar, they have a stub implementation of StaicLoggerBinder (and other similar classes) but then remove the .class files from the jar. Sounds a bit unkosher, doesn't it?


I was comparing this approach to how JDBC registers drivers:

java.sql.DriverManager.registerDriver(java.sql.Driver driver);

But this would be called from a static intialization block in the driver implementaion, e.g.

package com.usta.MyDatabase;
public class MyDriver implements Driver {
  static {
    Driver SINGLETON = new MyDriver(...);
    DriverManager.registerDriver(SINGLETON);
  }
...

And that is why we have to do the following:

Class.forName("com.usta.MyDatabase.MyDriver");
Connection con = DriverManager.getConnection("jdbc:mydatabase:dbname","guest","");

And getConnection() will ask the registered drivers if they can handle the url provided.

As we see with JDBC the Driver(the service provider) has to register itself, whereas, with SLF4J ILoggerFactory (the service provider), the registration (actually binding) is done automatically. This makes sense because with JDBC, we might want to use multiple databases at the same time.

String.intern() and concurrency

Have there been times when you needed some form of locking but could not find an easy way to granularize it? For example lets say you have

Map<Person, Double> salariesMap = Collections.synchronizedMap(new HashMap<Person, Double>());//BigDecimal might be a better value type

void giveRaise(final Person person, double raisePercentage){
    synchronized(salariesMap){
        oldSalary = salariesMap.get(person);
        Double newSalary = (1 + raisePercentage/100.0) * oldSalary;
        salariesMap.put(person, newSalary);
    }
}

Our first attempt at making the locking granular could be:

void giveRaise(final Person person, double raisePercentage){
    synchronized(person){
        Double oldSalary = salariesMap.get(person);
        Double newSalary = (1 + raisePercentage/100.0) * oldSalary;
        salariesMap.put(person, newSalary);
    }
}

Unless there is a guarantee that for any two Person instances p1 and p2, p1.equals(p2) implies p1 == p2, our locking on the Person object (the map key) would be wrong.

Such a guarantee can be obtained if all Person instances are looked up from a pool of unique Persons.

But then again what if an instance was obtained from the pool and a reference to it held long after it was removed from the pool? To avoid such a stale reference, would one now lock the pool itself too?

Map<String, Person> persons = Collections.synchronizedMap(new HashMap<String, Person>());

void giveRaise(String pName, double raisePercentage){
    synchronized(persons){
        final Person p = persons.get(pName);
        synchronized(p) {
            Double oldSalary = salariesMap.get(p);
            Double newSalary = (1 + raisePercentage/100.0) * oldSalary;
            salariesMap.put(person, newSalary);
        }
    }
}

But this beats the whole purpose of locking only on one Person key for granularity!

Luckily such a unique pool is maintained by the JVM itself for strings and the unique instances in the pool can be accessed via String.intern()

Thus we can obtain a granular locking as follows:

void giveRaise(final Person p, double raisePercentage){
    synchronized(p.getName().intern()){
        Double oldSalary = salariesMap.get(p);
        Double newSalary = (1 + raisePercentage/100.0) * oldSalary;
        salariesMap.put(p, newSalary);
    }
}

Note that the use of a ConcurrentMap instead of Collections.synchronizedMap in the above might lead to better parallelism in the calls to put above. Also, we could probably use replace() instead of simple put():

ConcurrentMap<Person, Double> salariesMap = new ConcurrentHashMap<Person, Double>();

void giveRaise(final Person person, double raisePercentage){
    synchronized(person.getName().intern()){
        oldSalary = salariesMap.get(person);
        Double newSalary = (1 + raisePercentage/100.0) * oldSalary;
        if(!salariesMap.replace(person, oldSalary, newSalary)) {
            logger.error("Salary was modified concurrently");
        }
    }
}

Also see comments on http://stackoverflow.com/questions/348985/deadlock-on-synchronized-string-intern

If the "key" is likely to collide with the key of another class of objects then synchronize(key.intern()) will introduce an unnecessary mutual exclusion among completely unrelated code. In such a case one might instead use a WeakHashMap<String, WeakReference<Object>> as a mapping from a string to a lock object. Then by having one such map for each class of objects, the accidental mutual exclusion because of shared keys can be avoided.