我想根据谓词筛选java.util.Collection。


当前回答

JFilter http://code.google.com/p/jfilter/最适合您的需求。

JFilter是一个简单、高性能的开源库,用于查询Java bean集合。

关键特性

Support of collection (java.util.Collection, java.util.Map and Array) properties. Support of collection inside collection of any depth. Support of inner queries. Support of parameterized queries. Can filter 1 million records in few 100 ms. Filter ( query) is given in simple json format, it is like Mangodb queries. Following are some examples. { "id":{"$le":"10"} where object id property is less than equals to 10. { "id": {"$in":["0", "100"]}} where object id property is 0 or 100. {"lineItems":{"lineAmount":"1"}} where lineItems collection property of parameterized type has lineAmount equals to 1. { "$and":[{"id": "0"}, {"billingAddress":{"city":"DEL"}}]} where id property is 0 and billingAddress.city property is DEL. {"lineItems":{"taxes":{ "key":{"code":"GST"}, "value":{"$gt": "1.01"}}}} where lineItems collection property of parameterized type which has taxes map type property of parameteriszed type has code equals to GST value greater than 1.01. {'$or':[{'code':'10'},{'skus': {'$and':[{'price':{'$in':['20', '40']}}, {'code':'RedApple'}]}}]} Select all products where product code is 10 or sku price in 20 and 40 and sku code is "RedApple".

其他回答

JFilter http://code.google.com/p/jfilter/最适合您的需求。

JFilter是一个简单、高性能的开源库,用于查询Java bean集合。

关键特性

Support of collection (java.util.Collection, java.util.Map and Array) properties. Support of collection inside collection of any depth. Support of inner queries. Support of parameterized queries. Can filter 1 million records in few 100 ms. Filter ( query) is given in simple json format, it is like Mangodb queries. Following are some examples. { "id":{"$le":"10"} where object id property is less than equals to 10. { "id": {"$in":["0", "100"]}} where object id property is 0 or 100. {"lineItems":{"lineAmount":"1"}} where lineItems collection property of parameterized type has lineAmount equals to 1. { "$and":[{"id": "0"}, {"billingAddress":{"city":"DEL"}}]} where id property is 0 and billingAddress.city property is DEL. {"lineItems":{"taxes":{ "key":{"code":"GST"}, "value":{"$gt": "1.01"}}}} where lineItems collection property of parameterized type which has taxes map type property of parameteriszed type has code equals to GST value greater than 1.01. {'$or':[{'code':'10'},{'skus': {'$and':[{'price':{'$in':['20', '40']}}, {'code':'RedApple'}]}}]} Select all products where product code is 10 or sku price in 20 and 40 and sku code is "RedApple".

考虑使用支持泛型的更新的Collections框架谷歌Collections。

更新:谷歌集合库现在已弃用。你应该使用最新发布的番石榴。它仍然具有对集合框架的所有相同扩展,包括基于谓词进行筛选的机制。

我的回答建立在Kevin Wong的基础上,这里是一个使用spring中的CollectionUtils和Java 8 lambda表达式的一行程序。

CollectionUtils.filter(list, p -> ((Person) p).getAge() > 16);

这是我见过的最简洁易读的方法(不使用基于方面的库)。

Spring CollectionUtils可从Spring版本4.0.2获得。请记住,您需要JDK 1.8和语言级别8+。

Java集合流的一个替代(更轻量级的)选择是Ocl.java库,它使用vanilla集合和lambdas: https://github.com/eclipse/agileuml/blob/master/Ocl.java

例如,对数组列表中的单词进行简单的筛选和求和 可能是:

ArrayList<Word> sel = Ocl.selectSequence(words, 
                             w -> w.pos.equals("NN")); 
int total = Ocl.sumint(Ocl.collectSequence(sel,
                             w -> w.text.length())); 

Where Word有字符串pos;字符串文本;属性。效率似乎与流选项相似,例如,在两个版本中,10000个单词在大约50毫秒内处理。

Python、Swift等都有等效的OCL库。基本上,Java集合流重新发明了OCL操作——>select, ->collect等,这些操作自1998年以来就存在于OCL中。

这里有一些非常棒的答案。对我来说,我想让事情尽可能简单易懂:

public abstract class AbstractFilter<T> {

    /**
     * Method that returns whether an item is to be included or not.
     * @param item an item from the given collection.
     * @return true if this item is to be included in the collection, false in case it has to be removed.
     */
    protected abstract boolean excludeItem(T item);

    public void filter(Collection<T> collection) {
        if (CollectionUtils.isNotEmpty(collection)) {
            Iterator<T> iterator = collection.iterator();
            while (iterator.hasNext()) {
                if (excludeItem(iterator.next())) {
                    iterator.remove();
                }
            }
        }
    }
}