Java中高效处理时空事件重叠：基于空间索引的实践指南

import java.time.Instant;
import java.util.Collection;
import java.util.List;
import java.util.stream.Collectors;

// 假设我们有一个事件类
class SpatioTemporalEvent {
    String id;
    double kilometerInitial;
    double kilometerFinal;
    Instant instantDateInitial;
    Instant instantDateFinal;

    public SpatioTemporalEvent(String id, double ki, double kf, Instant ti, Instant tf) {
        this.id = id;
        this.kilometerInitial = ki;
        this.kilometerFinal = kf;
        this.instantDateInitial = ti;
        this.instantDateFinal = tf;
    }

    // 获取事件的最小/最大坐标，用于构建索引
    public double[] getMinCoords() {
        return new double[]{kilometerInitial, instantDateInitial.toEpochMilli()};
    }

    public double[] getMaxCoords() {
        return new double[]{kilometerFinal, instantDateFinal.toEpochMilli()};
    }

    @Override
    public String toString() {
        return "Event{" + "id='" + id + '\'' +
               ", k=[" + kilometerInitial + ", " + kilometerFinal +
               "], t=[" + instantDateInitial + ", " + instantDateFinal + "]}";
    }
}

// 假设有一个通用的空间索引接口
// 实际使用时会是具体的库实现，如 Tinspin 的 RTree
interface SpatialIndex<T> {
    void insert(double[] minCoords, double[] maxCoords, T data);
    Collection<T> queryOverlapping(double[] queryMinCoords, double[] queryMaxCoords);
    // 其他方法如 delete, update 等
}

// 模拟一个简单的R树实现（仅用于演示接口，非真实R树逻辑）
class SimpleRTreeIndex<T extends SpatioTemporalEvent> implements SpatialIndex<T> {
    private List<T> storedEvents = new java.util.ArrayList<>();

    @Override
    public void insert(double[] minCoords, double[] maxCoords, T data) {
        // 在实际R树中，这里会执行复杂的树结构插入逻辑
        storedEvents.add(data); // 简化处理，仅添加
    }

    @Override
    public Collection<T> queryOverlapping(double[] queryMinCoords, double[] queryMaxCoords) {
        // 实际R树会高效地遍历树结构
        // 这里为了演示，进行简单的线性扫描，实际性能远低于R树
        return storedEvents.stream()
                .filter(event -> {
                    // 检查当前事件与查询矩形是否重叠
                    boolean xOverlap = Math.max(queryMinCoords[0], event.kilometerInitial) <= Math.min(queryMaxCoords[0], event.kilometerFinal);
                    boolean yOverlap = Math.max(queryMinCoords[1], event.instantDateInitial.toEpochMilli()) <= Math.min(queryMaxCoords[1], event.instantDateFinal.toEpochMilli());
                    return xOverlap && yOverlap;
                })
                .collect(Collectors.toList());
    }
}

public class SpatioTemporalOverlapFinder {

    public static void main(String[] args) {
        // 初始化空间索引
        // 实际应用中，会使用如 Tinspin.RTree.create(2, 64, 0.5) 等具体实现
        SpatialIndex<SpatioTemporalEvent> eventIndex = new SimpleRTreeIndex<>();

        // 插入一些时空事件
        eventIndex.insert(new double[]{0, Instant.parse("2023-01-01T00:00:00Z").toEpochMilli()},
                          new double[]{10, Instant.parse("2023-01-01T01:00:00Z").toEpochMilli()},
                          new SpatioTemporalEvent("E1", 0, 10, Instant.parse("2023-01-01T00:00:00Z"), Instant.parse("2023-01-01T01:00:00Z")));

        eventIndex.insert(new double[]{5, Instant.parse("2023-01-01T00:30:00Z").toEpochMilli()},
                          new double[]{15, Instant.parse("2023-01-01T01:30:00Z").toEpochMilli()},
                          new SpatioTemporalEvent("E2", 5, 15, Instant.parse("2023-01-01T00:30:00Z"), Instant.parse("2023-01-01T01:30:00Z")));

        eventIndex.insert(new double[]{20, Instant.parse("2023-01-02T00:00:00Z").toEpochMilli()},
                          new double[]{30, Instant.parse("2023-01-02T01:00:00Z").toEpochMilli()},
                          new SpatioTemporalEvent("E3", 20, 30, Instant.parse("2023-01-02T00:00:00Z"), Instant.parse("2023-01-02T01:00:00Z")));

        // 定义一个查询事件
        SpatioTemporalEvent queryEvent = new SpatioTemporalEvent(
            "Q1", 3, 12, Instant.parse("2023-01-01T00:45:00Z"), Instant.parse("2023-01-01T01:15:00Z")
        );

        // 执行重叠查询
        Collection<SpatioTemporalEvent> overlappingEvents = eventIndex.queryOverlapping(
            queryEvent.getMinCoords(), queryEvent.getMaxCoords()
        );

        System.out.println("查询事件: " + queryEvent);
        System.out.println("重叠事件: ");
        overlappingEvents.forEach(System.out::println);
        // 预期输出应包含 E1 和 E2
    }
}