使用多线程获取大量数据集合中的关键数据

/**
* 将一个list均分成n个list
* @param source
* @return
*/
public  <T> List<List<T>> averageAssign(List<T> source,int n){
List<List<T>> result=new ArrayList<List<T>>();
int remaider=source.size()%n;  //(先计算出余数)
int number=source.size()/n;  //然后是商
int offset=0;//偏移量
for(int i=0;i<n;i++){
List<T> value=null;
if(remaider>0){
value=source.subList(i*number+offset, (i+1)*number+offset+1);
remaider--;
offset++;
}else{
value=source.subList(i*number+offset, (i+1)*number+offset);
}
result.add(value);
}
return result;
}

class MyCallable implements Callable<Object> {
private List<Map<String,Object>> els;
private List<Map<String,Object>> elsend=new ArrayList<>();
private String content;

MyCallable(List<Map<String,Object>> els,String content) {
this.els = els;
this.content = content;
}

public Object call() throws Exception {
for (int i = 0; i < els.size(); i++) {
Map<String, Object> stringObjectMap =  els.get(i);
String el = (String) stringObjectMap.get("el");
if(content.indexOf(el)!=-1){
elsend.add(stringObjectMap);
}
}
return elsend;
}
}

List<List<Map<String,Object>>> elsArr = averageAssign(els,10);

// 创建一个线程池
ExecutorService pool = Executors.newFixedThreadPool(elsArr.size());
// 创建多个有返回值的任务
List<Future<List<Map<String,Object>>>> list = new ArrayList<Future<List<Map<String,Object>>>>();
for (int i = 0; i < elsArr.size(); i++) {
Callable c = new MyCallable(elsArr.get(i),content);
// 执行任务并获取Future对象
Future f = pool.submit(c);
list.add(f);
}
// 关闭线程池
pool.shutdown();

// 获取所有并发任务的运行结果
for (Future<List<Map<String,Object>>> f : list) {
List<Map<String,Object>> l = f.get();
for (int i = 0; i < l.size(); i++) {
Map<String, Object> stringObjectMap =  l.get(i);
elsend.add(stringObjectMap);
}
}
pbdDocument.setEls(elsend);