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package net.spy.memcached.util;

import java.util.Iterator;
import java.util.Map;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;

import net.spy.memcached.MemcachedClientIF;
import net.spy.memcached.compat.SpyObject;
import net.spy.memcached.internal.ImmediateFuture;

/**
 * CacheLoader provides efficient mechanisms for storing lots of data.
 */
public class CacheLoader extends SpyObject {

	private final ExecutorService executorService;
	private final StorageListener storageListener;
	private final MemcachedClientIF client;
	private final int expiration;

	/**
	 * Simple CacheLoader constructor that doesn't provide any feedback and
	 * caches forever.
	 *
	 * @param c a client
	 */
	public CacheLoader(MemcachedClientIF c) {
		this(c, null, null, 0);
	}

	/**
	 * Get a CacheLoader with all the options.
	 *
	 * @param c a client
	 * @param es an ExecutorService (e.g. thread pool) to dispatch results
	 *           (may be null, in which case no listener may be provided)
	 * @param sl a storage listener (may be null)
	 * @param exp expiration to use while loading
	 */
	public CacheLoader(MemcachedClientIF c, ExecutorService es,
			StorageListener sl, int exp) {
		super();
		client = c;
		executorService = es;
		storageListener = sl;
		expiration = exp;
	}

	/**
	 * Load data from the given iterator.
	 *
	 * @param  type of data being loaded
	 * @param i the iterator of data to load
	 */
	public  Future loadData(Iterator> i) {
		Future mostRecent = null;
		while(i.hasNext()) {
			Map.Entry e = i.next();
			mostRecent = push(e.getKey(), e.getValue());
			watch(e.getKey(), mostRecent);
		}

		return mostRecent == null ? new ImmediateFuture(true) : mostRecent;
	}

	/**
	 * Load data from the given map.
	 *
	 * @param  type of data being loaded
	 * @param map the map of keys to values that needs to be loaded
	 */
	public  Future loadData(Map map) {
		return loadData(map.entrySet().iterator());
	}

	/**
	 * Push a value into the cache.
	 *
	 * This is a wrapper around set that throttles and retries on full queues.
	 *
	 * @param  the type being stored
	 * @param k the key
	 * @param value the value
	 * @return the future representing the stored data
	 */
	public  Future push(String k, T value) {
		Future rv = null;
		while(rv == null) {
			try {
				rv = client.set(k, expiration, value);
			} catch(IllegalStateException ex) {
				// Need to slow down a bit when we start getting rejections.
				try {
					if(rv != null) {
						rv.get(250, TimeUnit.MILLISECONDS);
					} else {
						Thread.sleep(250);
					}
				} catch(InterruptedException ie) {
					Thread.currentThread().interrupt();
				} catch(Exception e2) {
					// Ignore exceptions here.  We're just trying to slow
					// down input.
				}
			}

		}
		return rv;
	}

	private void watch(final String key, final Future f) {
		if(executorService != null && storageListener != null) {
			executorService.execute(new Runnable() {
				public void run() {
					try {
						storageListener.storeResult(key, f.get());
					} catch(Exception e) {
						storageListener.errorStoring(key, e);
					}
				}
			});
		}
	}

	/**
	 * If you are interested in the results of your data load, this interface
	 * will receive them.
	 */
	public interface StorageListener {

		/**
		 * Normal path response for a set.
		 *
		 * @param k the key that was being set
		 * @param result true if the set changed the DB value
		 */
		void storeResult(String k, boolean result);

		/**
		 * @param k the key that was attempting to be stored
		 * @param e the error received while storing that key
		 */
		void errorStoring(String k, Exception e);
	}
}




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