amberjs 1.17.0

// 智能内存分配器 - Stage 90 Phase 5.2
// 基于使用模式预测的智能内存分配器

use serde::{Deserialize, Serialize};
use std::collections::{BTreeMap, HashMap};
use std::sync::{Arc, Mutex, RwLock};
use std::time::Instant;

/// 分配模式
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum AllocationPattern {
    /// 频繁小对象
    FrequentSmall,
    /// 偶尔大对象
    OccasionalLarge,
    /// 持续增长
    Growing,
    /// 周期性分配
    Cyclic,
    /// 随机分配
    Random,
}
/// 分配策略
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum AllocationStrategy {
    /// 快速分配
    Fast,
    /// 节省内存
    MemoryEfficient,
    /// 平衡模式
    Balanced,
    /// AI 驱动自适应
    AIAdaptive,
}
/// 内存池
#[derive(Debug, Clone)]
pub struct MemoryPool {
    pub pool_id: String,
    pub block_size: usize,
    pub max_blocks: usize,
    pub allocated_blocks: usize,
    pub free_blocks: Vec<usize>,
}
/// 内存池配置
#[derive(Debug, Clone)]
pub struct PoolConfig {
    pub small_pool_size: usize,
    pub medium_pool_size: usize,
    pub large_pool_size: usize,
    pub pool_count: usize,
}
/// 分配指标
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AllocationMetrics {
    pub total_allocations: u64,
    pub total_deallocations: u64,
    pub cache_hits: u64,
    pub cache_misses: u64,
    pub average_allocation_time_ns: u64,
}
/// 智能内存分配器
pub struct SmartMemoryAllocator {
    pools: Arc<RwLock<Vec<MemoryPool>>>,
    metrics: Arc<RwLock<AllocationMetrics>>,
    config: PoolConfig,
}
impl SmartMemoryAllocator {
    /// 创建新的智能内存分配器
    pub fn new() -> Self {
        Self::with_config(PoolConfig {
            small_pool_size: 1024,
            medium_pool_size: 1024 * 64,
            large_pool_size: 1024 * 1024,
            pool_count: 4,
        })
    }
    /// 使用配置创建分配器
    pub fn with_config(config: PoolConfig) -> Self {
        let pools: _ = (0..config.pool_count)
            .map(|i| MemoryPool {
                pool_id: format!("pool_{}", i),
                block_size: 64 * (i + 1), // 64, 128, 256, 512 bytes
                max_blocks: 1000,
                allocated_blocks: 0,
                free_blocks: (0..1000).collect(),
            })
            .collect();
        Self {
            pools: Arc::new(Mutex::new(pools)))
            metrics: Arc::new(Mutex::new(AllocationMetrics {)),
                total_allocations: 0,
                total_deallocations: 0,
                cache_hits: 0,
                cache_misses: 0,
                average_allocation_time_ns: 0,
            }))
            config,
        }
    }
    /// 分配内存
    pub async fn allocate(&self, size: usize) -> Option<Vec<u8> {
        let start: _ = std::time::Instant::now();
        // 查找合适的池
        let pools: _ = self.pools.read().await;
        let suitable_pool: _ = pools.iter().find(|p| p.block_size >= size && !p.free_blocks.is_empty());
        let result: _ = if let Some(pool) = suitable_pool {
            // 使用池分配
            let mut pools = self.pools.write().await;
            if let Some(pool_mut) = pools.iter_mut().find(|p| p.pool_id == pool.pool_id) {
                if let Some(block_id) = pool_mut.free_blocks.pop() {
                    pool_mut.allocated_blocks += 1;
                    pool_mut.allocated_blocks = pool_mut.allocated_blocks.min(pool_mut.max_blocks);
                    // 更新指标
                    {
                        let mut metrics = self.metrics.write().await;
                        metrics.total_allocations += 1;
                        metrics.cache_hits += 1;
                        let elapsed: _ = start.elapsed();
                        metrics.average_allocation_time_ns = elapsed.as_nanos() as u64;
                    }
                    Some(vec![0u8; size])
                } else {
                    None
                }
            } else {
                None
            }
        } else {
            // 直接分配
            let mut metrics = self.metrics.write().await;
            metrics.total_allocations += 1;
            metrics.cache_misses += 1;
            Some(vec![0u8; size])
        };
        result
    }
    /// 释放内存
    pub async fn deallocate(&self, data: Vec<u8>) {
        let size: _ = data.len();
        // 更新指标
        {
            let mut metrics = self.metrics.write().await;
            metrics.total_deallocations += 1;
        }
        // 这里可以添加将内存返回池的逻辑
        drop(data);
    }
    /// 获取分配指标
    pub async fn get_metrics(&self) -> AllocationMetrics {
        self.metrics.read().await.clone()
    }
}
#[cfg(test)]
mod tests {
    #[tokio::test]
    async fn test_smart_allocator() {
        let allocator: _ = SmartMemoryAllocator::new();
        let data: _ = allocator.allocate(128).await;
        assert!(data.is_some());
        if let Some(data) = data {
            allocator.deallocate(data).await;
        }
        let metrics: _ = allocator.get_metrics().await;
        assert_eq!(metrics.total_allocations, 1);
        assert_eq!(metrics.total_deallocations, 1);
    }
}