Fre*_*Goo 11 java java-8 java-stream
我只需要针对特定条件执行转换.我做这个转变:
// filter 1: less date - group by max date by groupId
List<Info> listResult = new ArrayList<>(listInfo.stream()
.filter(info -> info.getDate().getTime() < date.getTime())
.collect(Collectors.groupingBy(Info::getGroupId, Collectors.collectingAndThen(
Collectors.reducing((Info i1, Info i2) -> i1.getDate().getTime() > i2.getDate().getTime() ? i1 : i2),
Optional::get))).values());
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但是对于超过指定日期的情况,我不需要转换任何东西,我只需要返回这些数据:
// filter 2: more date - nothing change in list
List<Info> listMoreByDate = listInfo.stream()
.filter(info -> info.getDate().getTime() >= date.getTime())
.collect(Collectors.toList());
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接下来,要结合这两个过滤器 - 我将两个列表组合在一起:
listResult.addAll(listMoreByDate);
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我的问题是,这可以在一个流中完成吗?因为过滤器2绝对没用,它只返回这个条件的列表.
是否可以通过一个连续表达式执行这些转换?
我的完整代码:
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.*;
import java.util.stream.Collectors;
public class App {
public static void main(String[] args) throws ParseException {
Info info1 = new Info(1L, getDateFromStr("2018-02-02T10:00:00"), 3L);
Info info2 = new Info(2L, getDateFromStr("2018-02-02T12:00:00"), 3L);
Info info3 = new Info(3L, getDateFromStr("2018-02-05T12:00:00"), 6L);
Info info4 = new Info(4L, getDateFromStr("2018-02-05T10:00:00"), 6L);
Date date = getDateFromStr("2018-02-03T10:10:10");
List<Info> listInfo = new ArrayList<>();
listInfo.add(info1);
listInfo.add(info2);
listInfo.add(info3);
listInfo.add(info4);
// filter 1: less date - group by max date by groupId
List<Info> listResult = new ArrayList<>(listInfo.stream()
.filter(info -> info.getDate().getTime() < date.getTime())
.collect(Collectors.groupingBy(Info::getGroupId, Collectors.collectingAndThen(
Collectors.reducing((Info i1, Info i2) -> i1.getDate().getTime() > i2.getDate().getTime() ? i1 : i2),
Optional::get))).values());
// filter 2: more date - nothing change in list
List<Info> listMoreByDate = listInfo.stream()
.filter(info -> info.getDate().getTime() >= date.getTime())
.collect(Collectors.toList());
listResult.addAll(listMoreByDate);
System.out.println("result: " + listResult);
}
private static Date getDateFromStr(String dateStr) throws ParseException {
return new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss").parse(dateStr);
}
}
class Info {
private Long id;
private Date date;
private Long groupId;
public Info(Long id, Date date, Long groupId) {
this.id = id;
this.date = date;
this.groupId = groupId;
}
public Long getId() {
return id;
}
public void setId(Long id) {
this.id = id;
}
public Date getDate() {
return date;
}
public void setDate(Date date) {
this.date = date;
}
public Long getGroupId() {
return groupId;
}
public void setGroupId(Long groupId) {
this.groupId = groupId;
}
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
Info info = (Info) o;
return Objects.equals(id, info.id) &&
Objects.equals(date, info.date) &&
Objects.equals(groupId, info.groupId);
}
@Override
public int hashCode() {
return Objects.hash(id, date, groupId);
}
@Override
public String toString() {
final StringBuilder sb = new StringBuilder("Info{");
sb.append("id=").append(id);
sb.append(", date=").append(date);
sb.append(", groupId=").append(groupId);
sb.append('}');
return sb.toString();
}
}
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Hol*_*ger 10
我看不到任何简单的东西
List<Info> listResult = Stream.concat(
listInfo.stream()
.filter(info -> info.getDate().getTime() < date.getTime())
.collect(Collectors.toMap(Info::getGroupId, Function.identity(),
BinaryOperator.maxBy(Comparator.comparing(Info::getDate))))
.values().stream(),
listInfo.stream()
.filter(info -> info.getDate().getTime() >= date.getTime())
)
.collect(Collectors.toList());
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因为这两个操作根本不同.Map在第一步中构建a 是不可避免的,因为它将用于识别具有相同getGroupId属性的项目.
也就是说,您应该考虑从使用切换Date到java.timeAPI.
是的,您可以使用partitioningBy收集器合并这两个条件,如下所示:
List<Info> resultSet =
listInfo.stream()
.collect(collectingAndThen(partitioningBy(info -> info.getDate().getTime() < date.getTime()),
map -> Stream.concat(map.get(true)
.stream()
.collect(toMap(Info::getGroupId,
Function.identity(),
(Info i1, Info i2) -> i1.getDate().getTime() > i2.getDate().getTime() ? i1 : i2))
.values().stream(), map.get(false).stream())
.collect(Collectors.toCollection(ArrayList::new))));
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这基本上使用partitioningBy收集器来组织元素,使得所有元素都传递标准info.getDate().getTime() < date.getTime()以及它的错误,即哪里info -> info.getDate().getTime() >= date.getTime()是真的Map<Boolean, List<T>>.
此外,我们利用collectingAndThen集电极在所述施加精加工函数Map<Boolean, List<T>>由返回partitioningBy集热器,在这种情况下我们串接的应用逻辑的结果:
.collect(Collectors.groupingBy(Info::getGroupId,
Collectors.collectingAndThen(Collectors.reducing((Info i1, Info i2) -> i1.getDate().getTime() > i2.getDate().getTime() ? i1 : i2),
Optional::get))))
.values();
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我简化为:
.collect(toMap(Info::getGroupId, Function.identity(), (Info i1, Info i2) -> i1.getDate().getTime() > i2.getDate().getTime() ? i1 : i2)))
.values();
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返回的元素返回info.getDate().getTime() < date.getTime()false(map.get(false).stream()).
最后,我们将结果收集到收集器的ArrayList实现中toCollection.