大数据拆分处理方式

思路：
1：参考分页方式将数据拆成指定大小线程数

2：在每个独立的线程中去读取数据并处理数据

步骤一实现

public class IndexIntiTools {
	
	public static AtomicInteger runflag=new AtomicInteger();

	//用于测试
	public static List<Object>  syncList=new CopyOnWriteArrayList<Object>();
	private static int idxThreadCount = 10;

	private static Executor ex = Executors.newFixedThreadPool(idxThreadCount);

	/**
	 * 构建索引
	 * @param hql
	 * @param size
	 */
	public static void build(String hql, int size) {
		int pagecount = idxThreadCount;
		int count = size / pagecount;
		int mod = size % pagecount;
		List<Runnable> runList = new ArrayList<Runnable>(pagecount);
		IndexExecutor idxExecutor;
		for (int i = 0; i < pagecount; i++) {
			if (i == (pagecount - 1)) {
				idxExecutor = new IndexExecutor(hql, i * count, count + mod);
			} else {
				idxExecutor = new IndexExecutor(hql, i * count, count);
			}
			runList.add(idxExecutor);
		}
		for (Runnable runnable : runList) {
			runflag.incrementAndGet();
			ex.execute(runnable);
		}
	}

}

步骤二实现

public class IndexExecutor implements Runnable{
	
	private static final Log log = LogFactory.getLog(IndexExecutor.class);
	private int start;
	private int limit;
	private String hql;
	public IndexExecutor(String hql,int start, int limit) {
		this.hql=hql;
		this.start = start;
		this.limit = limit;
	}

	@Override
	public void run() {
		log.info("hql:"+hql+",start:"+start+",limit"+limit);
		//查询数据库(hql,start,limit);
		log.info(list);
		IndexIntiTools.syncList.addAll(list);
		IndexIntiTools.runflag.decrementAndGet();
	}


}