使用STREAMS实现Java透视表
我已经在这个问题上挣扎了几天了。我正在尝试使用Java Streams创建透视功能。我只需要执行 总和、计数、最大值、最小值和平均值。对于输入,我得到一个透视表列索引、一个透视表行索引数组和要计算的值。
问题是数据在列表中,其中对象可以是字符串、整数或双精度。但我要到运行时才能知道。我必须以List<;List<;Object>的形式返回我的结果。
我遇到了MAX/MIN问题(我假设平均值将类似于MAX和MIN)
为了透视多个表值,我创建了一个类来使用我的第二个GroupingBy
这将不会编译,我不确定要与什么进行比较,不确定在哪里将对象转换为int,或者我是否需要这样做。我想用一个流来完成这一切,但我不确定这是否可能。我做错了什么,或者我可以用不同的方式来做。提前谢谢。
package pivot.test;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.stream.Collectors;
public class PivotTest {
List<List<Object>> rows = new ArrayList<List<Object>>();
public PivotTest() throws Exception {
rows.add(Arrays.asList(new Object[]{ "East", "Boy", "Tee", 10, 12.00}));
rows.add(Arrays.asList(new Object[]{ "East", "Boy", "Golf", 15, 20.00}));
rows.add(Arrays.asList(new Object[]{ "East", "Girl", "Tee", 8, 14.00}));
rows.add(Arrays.asList(new Object[]{ "East", "Girl", "Golf", 20, 24.00}));
rows.add(Arrays.asList(new Object[]{ "West", "Boy", "Tee", 5, 12.00}));
rows.add(Arrays.asList(new Object[]{ "West", "Boy", "Golf", 12, 20.00}));
rows.add(Arrays.asList(new Object[]{ "West", "Girl", "Tee", 15, 14.00}));
rows.add(Arrays.asList(new Object[]{ "West", "Girl", "Golf", 10, 24.00}));
}
// Dynamic Max based upon Column, Value to sum, and an array of pivot rows
public void MaxTable(int colIdx, int valueIdx, int... rowIdx) {
Map<Object, Map<Object, Integer>> myList = newRows.stream().collect(
Collectors.groupingBy(r -> ((List<Object>) r).get(colIdx),
Collectors.groupingBy( r -> new PivotColumns(r, rowIdx),
Collectors.collectingAndThen( Collectors.maxBy(Comparator.comparingInt(???)),
r -> ((List<Object>) r).get(valueIdx)))));
System.out.println("Dynamic MAX PIVOT"); System.out.println(myList);
}
public static void main(String[] args) {
try {
PivotTest p = new PivotTest();
System.out.println("
Streams PIVOT with index values inside a List
");
p.MaxTable(0, 3, new int[] { 2 });
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
}
class PivotColumns {
ArrayList<Object> columns;
public PivotColumns(
List<Object> objs, int... pRows) {
columns = new ArrayList<Object>();
for (int i = 0; i < pRows.length; i++) {
columns.add(objs.get(pRows[i]));
}
}
public void addObject(Object obj) {
columns.add(obj);
}
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + ((columns == null) ? 0 : columns.hashCode());
return result;
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
PivotColumns other = (PivotColumns) obj;
if (columns == null) {
if (other.columns != null)
return false;
} else if (!columns.equals(other.columns))
return false;
return true;
}
public String toString() {
String s = "";
for (Object obj : columns) {
s += obj + ",";
}
return s.substring(0, s.lastIndexOf(','));
}
}
解决方案
由于已知所有可能的值(String
、Integer
、Double
)都是Comparable
,因此您可以对Comparable
接口执行未经检查的强制转换。此外,不要忘记打开可选的包装。最后,如果我理解正确的话,结果应该是Map<Object, Map<Object, Object>> myList
,而不是Map<Object, Map<Object, Integer>> myList
,因为您的列可能有非整数值:
public void MaxTable(int colIdx, int valueIdx, int... rowIdx) {
Map<Object, Map<Object, Object>> myList = newRows.stream().collect(
Collectors.groupingBy(r -> r.get(colIdx),
Collectors.groupingBy( r -> new PivotColumns(r, rowIdx),
Collectors.collectingAndThen( Collectors.maxBy(
Comparator.comparing(r -> (Comparable<Object>)(((List<Object>) r).get(valueIdx)))),
r -> r.get().get(valueIdx)))));
System.out.println("Dynamic MAX PIVOT"); System.out.println(myList);
}
结果:
> p.MaxTable(0, 3, new int[] { 1 });
{West={Girl=15, Boy=12}, East={Girl=20, Boy=15}}
> p.MaxTable(0, 4, new int[] { 1 });
{West={Girl=24.0, Boy=20.0}, East={Girl=24.0, Boy=20.0}}
如您所见,您可以同时处理Integer
和Double
列。甚至可以处理String
(将按词典顺序选择最大值)。
对于平均值,您可以假设列值是数字(Number
类,Integer
或Double
),并收集到Double
(整数的平均值也可以是非整数):
public void AverageTable(int colIdx, int valueIdx, int... rowIdx) {
Map<Object, Map<Object, Double>> myList = newRows.stream().collect(
Collectors.groupingBy(r -> r.get(colIdx), Collectors
.groupingBy(r -> new PivotColumns(r, rowIdx),
Collectors.averagingDouble(r -> ((Number) (r
.get(valueIdx))).doubleValue()))));
System.out.println("Dynamic AVG PIVOT"); System.out.println(myList);
}
输出:
> p.AverageTable(0, 3, new int[] { 1 });
{West={Girl=12.5, Boy=8.5}, East={Girl=14.0, Boy=12.5}}
> p.AverageTable(0, 4, new int[] { 1 });
{West={Girl=19.0, Boy=16.0}, East={Girl=19.0, Boy=16.0}}
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