- 1 WAL 原則
- 2 WAL 記錄格式
- 3 WAL 管理員實作
- 4 檢查點：限制恢復時間
- 5 ARIES：恢復演算法
- 6 恢復範例：逐步說明
- 7 WAL 歸檔和時間點恢復
- 8 用 Rust 建構的挑戰
- 9 AI 如何加速這項工作
- 總結：WAL 和 ARIES 一張圖
在 第三部分 中，我們建構了用於併發交易的 MVCC。但有一個可怕的問題我們還沒有回答。
停電時會發生什麼？
Transaction: UPDATE accounts SET balance = 1000 WHERE id = 1
1. Read page into buffer pool
2. Modify page in memory (balance = 1000)
3. Mark page as dirty
4. ACK to client: "Done!"
5. ⚡ POWER FAILURE ⚡
6. Dirty page never written to disk
7. Client's money: GONE 💸這就是資料庫使用 WAL：預寫日誌 的原因。
今天：在 Rust 中實作 WAL 和 ARIES 恢復演算法。這就是確保你的資料在崩潰、停電和核心恐慌中存活的程式碼。
1 WAL 原則
基本規則
預寫日誌： 在修改任何資料頁面前，你必須將變更寫入 WAL。
// ❌ WRONG - data modification before WAL
pub fn update(&self, row_id: RowId, new_data: &[u8]) -> Result<(), Error> {
let mut page = self.buffer_pool.get_page(row_id.page_id)?;
page.write(row_id.offset, new_data); // Modified in memory!
page.mark_dirty();
// WAL comes too late
self.wal.log_update(row_id, new_data)?; // Too late!
Ok(())
}
// ✅ CORRECT - WAL first
pub fn update(&self, row_id: RowId, new_data: &[u8]) -> Result<(), Error> {
// 1. Generate LSN (Log Sequence Number)
let lsn = self.wal.log_update(row_id, new_data)?;
// 2. Flush WAL to disk (fsync)
self.wal.flush(lsn)?;
// 3. NOW safe to modify page
let mut page = self.buffer_pool.get_page(row_id.page_id)?;
page.write(row_id.offset, new_data);
page.set_lsn(lsn); // Track which LSN modified this page
page.mark_dirty();
Ok(())
}為什麼這樣有效：
Crash at different points:
After WAL write, before page modify:
→ Recovery replays WAL, data is restored ✓
After page modify, before flush:
→ WAL on disk, recovery ensures durability ✓
After flush to disk:
→ Data is durable ✓日誌序列號 (LSN)
每個 WAL 記錄獲得一個獨特的、單調遞增的識別符：
// src/wal/lsn.rs
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
pub struct Lsn(u64);
impl Lsn {
pub const INVALID: Lsn = Lsn(0);
pub const fn new(value: u64) -> Self {
Self(value)
}
pub const fn invalid(&self) -> bool {
self.0 == 0
}
// LSN encoding: segment_id (high 32) + offset (low 32)
pub const fn from_segment_offset(segment: u32, offset: u32) -> Self {
Self(((segment as u64) << 32) | (offset as u64))
}
pub const fn segment(&self) -> u32 {
(self.0 >> 32) as u32
}
pub const fn offset(&self) -> u32 {
(self.0 & 0xFFFFFFFF) as u32
}
}LSN 順序保證：
LSN 100: BEGIN txn 1
LSN 101: INSERT row A (txn 1)
LSN 102: INSERT row B (txn 1)
LSN 103: COMMIT txn 1
LSN 104: BEGIN txn 2
LSN 105: UPDATE row A (txn 2)
...
LSN 100 < LSN 101 < LSN 102 < ... (strictly increasing)2 WAL 記錄格式
記錄結構
// src/wal/record.rs
use crate::storage::PageId;
use crate::transaction::TransactionId;
#[derive(Debug, Clone)]
pub struct WalRecord {
pub lsn: Lsn,
pub prev_lsn: Lsn, // Link to previous record from same transaction
pub transaction_id: TransactionId,
pub record_type: WalRecordType,
pub page_id: PageId,
pub offset: u16,
pub data: WalData,
pub checksum: u32,
}
#[derive(Debug, Clone)]
pub enum WalRecordType {
Begin,
Insert,
Update { before_image: Vec<u8>, after_image: Vec<u8> },
Delete { before_image: Vec<u8> },
Commit,
Abort,
CheckpointBegin,
CheckpointEnd,
Compensation { undo_next_lsn: Lsn }, // For aborts
}
#[derive(Debug, Clone)]
pub enum WalData {
PageImage(Vec<u8>), // Full page image (for checkpoints)
RowData(Vec<u8>), // Row-level change
IndexEntry { key: Vec<u8>, value: Vec<u8> },
}磁碟上的實體佈局：
┌─────────────────────────────────────────────────────────────┐
│ WAL Segment File (e.g., 000000010000000000000001) │
├─────────────────────────────────────────────────────────────┤
│ PageHeader (16 bytes) │
├─────────────────────────────────────────────────────────────┤
│ Record 1: │
│ ├─ Length (4 bytes) │
│ ├─ LSN (8 bytes) │
│ ├─ Prev LSN (8 bytes) │
│ ├─ Transaction ID (4 bytes) │
│ ├─ Record Type (1 byte) │
│ ├─ Page ID (8 bytes) │
│ ├─ Offset (2 bytes) │
│ ├─ Data Length (4 bytes) │
│ ├─ Data (variable) │
│ └─ Checksum (4 bytes) │
├─────────────────────────────────────────────────────────────┤
│ Record 2: │
│ ... │
└─────────────────────────────────────────────────────────────┘實體 vs. 邏輯 WAL
PostgreSQL 使用實體 WAL（頁面級別變更）：
| 類型 | 記錄內容 | 優點 | 缺點 |
|---|---|---|---|
| 實體 | 頁面上的位元組範圍 | 簡單的 replay，精確的變更 | 較大的日誌，依賴頁面格式 |
| 邏輯 | SQL 操作 (INSERT/UPDATE) | 較小的日誌，格式獨立 | 複雜的 replay，必須重新執行 |
Vaultgres 方法： 實體 WAL 以簡單化（匹配 PostgreSQL）：
pub struct PhysicalWalRecord {
pub page_id: PageId,
pub offset: u16,
pub length: u16,
pub before_image: Option<Vec<u8>>, // For undo
pub after_image: Vec<u8>, // For redo
}3 WAL 管理員實作
寫入 WAL 記錄
// src/wal/manager.rs
use std::fs::{File, OpenOptions};
use std::io::{Write, Seek, SeekFrom};
use std::path::PathBuf;
use parking_lot::Mutex;
pub struct WalManager {
wal_dir: PathBuf,
current_segment: u32,
current_file: Mutex<File>,
current_offset: Mutex<u32>,
flush_lsn: Mutex<Lsn>,
last_lsn: AtomicU64,
}
impl WalManager {
pub fn new(wal_dir: &str) -> Result<Self, WalError> {
std::fs::create_dir_all(wal_dir)?;
let mut manager = Self {
wal_dir: PathBuf::from(wal_dir),
current_segment: 0,
current_file: Mutex::new(File::create("")?), // Placeholder
current_offset: Mutex::new(0),
flush_lsn: Mutex::new(Lsn::INVALID),
last_lsn: AtomicU64::new(0),
};
manager.open_or_create_segment(0)?;
Ok(manager)
}
fn open_or_create_segment(&mut self, segment: u32) -> Result<(), WalError> {
let path = self.wal_dir.join(format!("{:024X}", segment));
let file = OpenOptions::new()
.read(true)
.write(true)
.create(true)
.open(&path)?;
*self.current_file.lock() = file;
self.current_segment = segment;
*self.current_offset.lock() = 0;
Ok(())
}
pub fn append(&self, record: WalRecord) -> Result<Lsn, WalError> {
// Assign new LSN
let lsn = Lsn::new(self.last_lsn.fetch_add(1, Ordering::SeqCst) + 1);
// Serialize record
let mut buffer = Vec::new();
self.serialize_record(&record, lsn, &mut buffer)?;
// Check if we need a new segment
let mut offset = self.current_offset.lock();
if *offset + buffer.len() as u32 > SEGMENT_SIZE {
drop(offset);
self.rotate_segment()?;
offset = self.current_offset.lock();
}
// Write to file
let mut file = self.current_file.lock();
file.seek(SeekFrom::Start(*offset as u64))?;
file.write_all(&buffer)?;
*offset += buffer.len() as u32;
Ok(lsn)
}
pub fn flush(&self, target_lsn: Lsn) -> Result<(), WalError> {
let mut flush_lsn = self.flush_lsn.lock();
// Already flushed?
if *flush_lsn >= target_lsn {
return Ok(());
}
// Sync to disk
self.current_file.lock().sync_all()?;
*flush_lsn = target_lsn;
Ok(())
}
}讀取 WAL 記錄
impl WalManager {
pub fn read_from(&self, start_lsn: Lsn) -> Result<WalIterator, WalError> {
let segment = start_lsn.segment();
let offset = start_lsn.offset();
let path = self.wal_dir.join(format!("{:024X}", segment));
let file = File::open(&path)?;
Ok(WalIterator {
current_file: file,
current_segment: segment,
current_offset: offset,
wal_dir: self.wal_dir.clone(),
})
}
}
pub struct WalIterator {
current_file: File,
current_segment: u32,
current_offset: u32,
wal_dir: PathBuf,
}
impl Iterator for WalIterator {
type Item = Result<WalRecord, WalError>;
fn next(&mut self) -> Option<Self::Item> {
// Try to read record at current position
match self.read_record() {
Ok(Some(record)) => Some(Ok(record)),
Ok(None) => {
// End of segment, try next segment
self.current_segment += 1;
self.current_offset = 0;
let path = self.wal_dir.join(format!("{:024X}", self.current_segment));
self.current_file = File::open(&path).ok()?;
self.read_record().map(|r| r.ok()).flatten()
}
Err(e) => Some(Err(e)),
}
}
}4 檢查點：限制恢復時間
問題：無邊界的 replay
沒有檢查點：
Day 1: Database created
Day 30: Crash!
Recovery: Replay 30 days of WAL records 😱解決方案： 定期檢查點。
檢查點流程
sequenceDiagram
participant DB as Database
participant WAL as WAL Manager
participant BP as Buffer Pool
participant CKPT as Checkpoint File
DB->>DB: 1. Write CHECKPOINT_BEGIN record
DB->>BP: 2. Flush all dirty pages
BP-->>DB: Pages written to disk
DB->>DB: 3. Write CHECKPOINT_END record
DB->>WAL: 4. Flush WAL to disk
DB->>CKPT: 5. Save checkpoint LSN
CKPT-->>DB: Checkpoint complete
// src/wal/checkpoint.rs
pub struct Checkpoint {
pub checkpoint_lsn: Lsn,
pub active_transactions: Vec<TransactionId>,
pub dirty_pages: Vec<(PageId, Lsn)>, // page_id → page_lsn
}
impl WalManager {
pub fn create_checkpoint(&self, buffer_pool: &BufferPool) -> Result<Checkpoint, WalError> {
// 1. Log checkpoint begin
let begin_lsn = self.append(WalRecord::checkpoint_begin())?;
// 2. Flush all dirty pages (this is the expensive part!)
buffer_pool.flush_all()?;
// 3. Get current state
let checkpoint = Checkpoint {
checkpoint_lsn: begin_lsn,
active_transactions: self.get_active_transactions(),
dirty_pages: buffer_pool.get_dirty_pages(),
};
// 4. Log checkpoint end
let end_lsn = self.append(WalRecord::checkpoint_end(&checkpoint))?;
// 5. Flush WAL
self.flush(end_lsn)?;
// 6. Save checkpoint to known location
self.save_checkpoint_record(&checkpoint)?;
Ok(checkpoint)
}
}Fuzzy 檢查點 (PostgreSQL 風格)
Sharp 檢查點： 檢查點期間阻塞所有寫入。簡單但會造成停頓。
Fuzzy 檢查點： 檢查點期間允許寫入。複雜但無停頓。
// Fuzzy checkpoint approach
pub fn create_fuzzy_checkpoint(&self, buffer_pool: &BufferPool) -> Result<Checkpoint, WalError> {
// 1. Record checkpoint start LSN
let start_lsn = self.current_lsn();
// 2. Write CHECKPOINT_BEGIN (don't block)
self.append(WalRecord::checkpoint_begin())?;
// 3. Get list of dirty pages (snapshot)
let dirty_pages = buffer_pool.get_dirty_pages_snapshot();
// 4. Flush dirty pages in background (don't block new writes)
let checkpoint_lsn = self.current_lsn();
for (page_id, page_lsn) in dirty_pages {
if page_lsn < checkpoint_lsn {
buffer_pool.flush_page(page_id)?;
}
}
// 5. Write CHECKPOINT_END with final LSN
let end_lsn = self.current_lsn();
self.append(WalRecord::checkpoint_end_at(end_lsn))?;
self.flush(end_lsn)?;
Ok(Checkpoint {
checkpoint_lsn: end_lsn,
// ...
})
}5 ARIES：恢復演算法
三個階段
ARIES = Algorithm for Recovery and Isolation Exploiting Semantics
┌─────────────────────────────────────────────────────────────┐
│ ARIES Recovery │
├─────────────────────────────────────────────────────────────┤
│ Phase 1: ANALYSIS │
│ - Scan WAL from last checkpoint │
│ - Determine which transactions were active at crash │
│ - Build dirty page table │
├─────────────────────────────────────────────────────────────┤
│ Phase 2: REDO │
│ - Replay ALL logged changes from analysis end │
│ - Bring database to exact crash state │
│ - Skip pages already on disk (using page LSN) │
├─────────────────────────────────────────────────────────────┤
│ Phase 3: UNDO │
│ - Roll back all uncommitted transactions │
│ - Write Compensation Log Records (CLRs) │
│ - Database is now consistent │
└─────────────────────────────────────────────────────────────┘第一階段：Analysis
// src/recovery/analysis.rs
pub struct AnalysisResult {
pub transactions_at_crash: HashMap<TransactionId, TxnStatus>,
pub dirty_page_table: HashMap<PageId, Lsn>, // page → first LSN that dirtied it
pub redo_start_lsn: Lsn,
}
pub fn analyze(wal: &WalManager, checkpoint: &Checkpoint) -> Result<AnalysisResult, RecoveryError> {
let mut txn_status: HashMap<TransactionId, TxnStatus> = HashMap::new();
let mut dirty_page_table: HashMap<PageId, Lsn> = HashMap::new();
// Initialize from checkpoint
for txn in &checkpoint.active_transactions {
txn_status.insert(*txn, TxnStatus::Active);
}
for (page_id, page_lsn) in &checkpoint.dirty_pages {
dirty_page_table.insert(*page_id, *page_lsn);
}
// Scan WAL from checkpoint
let mut iterator = wal.read_from(checkpoint.checkpoint_lsn)?;
for record_result in iterator {
let record = record_result?;
match record.record_type {
WalRecordType::Begin => {
txn_status.insert(record.transaction_id, TxnStatus::Active);
}
WalRecordType::Commit => {
txn_status.insert(record.transaction_id, TxnStatus::Committed);
}
WalRecordType::Abort => {
txn_status.insert(record.transaction_id, TxnStatus::Aborted);
}
WalRecordType::Insert | WalRecordType::Update | WalRecordType::Delete => {
// Track first LSN that dirtied each page
dirty_page_table.entry(record.page_id)
.or_insert(record.lsn);
}
_ => {}
}
}
// Find minimum redo LSN
let redo_start_lsn = dirty_page_table.values()
.min()
.copied()
.unwrap_or(checkpoint.checkpoint_lsn);
Ok(AnalysisResult {
transactions_at_crash: txn_status,
dirty_page_table,
redo_start_lsn,
})
}第二階段：Redo
// src/recovery/redo.rs
pub fn redo(
wal: &WalManager,
buffer_pool: &BufferPool,
analysis: &AnalysisResult,
) -> Result<(), RecoveryError> {
let mut iterator = wal.read_from(analysis.redo_start_lsn)?;
for record_result in iterator {
let record = record_result?;
// Only redo committed transactions' changes
// (We redo ALL changes first, undo uncommitted later)
match &record.record_type {
WalRecordType::Insert | WalRecordType::Update | WalRecordType::Delete => {
// Check if page needs redo
let page = buffer_pool.get_page(record.page_id)?;
let page_lsn = page.get_lsn();
// Only apply if page is older than this LSN
if page_lsn < record.lsn {
apply_redo(&record, &page)?;
page.set_lsn(record.lsn);
}
// Else: page already has this change (written before crash)
}
_ => {}
}
}
Ok(())
}
fn apply_redo(record: &WalRecord, page: &Page) -> Result<(), RecoveryError> {
match &record.data {
WalData::PageImage(image) => {
// Full page image (from checkpoint)
page.copy_from_slice(image);
}
WalData::RowData(data) => {
// Partial page update
page.write(record.offset, data);
}
_ => {}
}
Ok(())
}關鍵洞察： Redo 是冪等的。多次執行產生相同的結果。
第三階段：Undo
// src/recovery/undo.rs
pub fn undo(
wal: &mut WalManager,
buffer_pool: &BufferPool,
analysis: &AnalysisResult,
) -> Result<(), RecoveryError> {
// Find transactions to undo (active at crash, not committed)
let losers: Vec<TransactionId> = analysis.transactions_at_crash
.iter()
.filter(|(_, status)| **status == TxnStatus::Active)
.map(|(txn, _)| *txn)
.collect();
// Undo in reverse order (LIFO - Last Committed, First Undone)
for txn_id in losers.into_iter().rev() {
undo_transaction(wal, buffer_pool, txn_id)?;
}
Ok(())
}
fn undo_transaction(
wal: &mut WalManager,
buffer_pool: &BufferPool,
txn_id: TransactionId,
) -> Result<(), RecoveryError> {
// Find all records for this transaction (in reverse)
let records = wal.get_transaction_records(txn_id)?;
for record in records.iter().rev() {
// Write Compensation Log Record (CLR)
let clr = WalRecord {
lsn: wal.next_lsn(),
prev_lsn: record.lsn,
transaction_id: txn_id,
record_type: WalRecordType::Compensation {
undo_next_lsn: record.prev_lsn,
},
page_id: record.page_id,
offset: record.offset,
data: WalData::RowData(record.before_image.clone().unwrap_or_default()),
checksum: 0, // Calculate checksum
};
let clr_lsn = wal.append(clr)?;
// Apply undo (restore before_image)
if let Some(before_image) = &record.before_image {
let page = buffer_pool.get_page(record.page_id)?;
page.write(record.offset, before_image);
page.set_lsn(clr_lsn);
}
}
// Log transaction abort
wal.append(WalRecord::abort(txn_id))?;
wal.flush_all()?;
Ok(())
}完整的恢復流程
// src/recovery/mod.rs
pub fn recover(
wal: &mut WalManager,
buffer_pool: &BufferPool,
data_dir: &str,
) -> Result<RecoveryStats, RecoveryError> {
// 1. Find last checkpoint
let checkpoint = find_last_checkpoint(wal, data_dir)?;
println!("Starting recovery from checkpoint LSN {}", checkpoint.checkpoint_lsn);
// 2. Phase 1: Analysis
println!("Phase 1: Analysis...");
let analysis = analyze(wal, &checkpoint)?;
println!(" Found {} active transactions at crash",
analysis.transactions_at_crash.len());
println!(" Redo will start from LSN {}", analysis.redo_start_lsn);
// 3. Phase 2: Redo
println!("Phase 2: Redo...");
redo(wal, buffer_pool, &analysis)?;
println!(" Redo complete");
// 4. Phase 3: Undo
println!("Phase 3: Undo...");
undo(wal, buffer_pool, &analysis)?;
println!(" Undo complete");
// 5. Truncate old WAL (optional)
truncate_wal_before(wal, checkpoint.checkpoint_lsn)?;
Ok(RecoveryStats {
checkpoint_lsn: checkpoint.checkpoint_lsn,
redo_start_lsn: analysis.redo_start_lsn,
transactions_aborted: analysis.transactions_at_crash
.iter()
.filter(|(_, s)| **s == TxnStatus::Active)
.count(),
})
}6 恢復範例：逐步說明
崩潰情境
Time LSN Transaction Action
─────────────────────────────────────────────────────
10:00 100 CKPT Checkpoint created
10:01 101 T1 (xid=1) BEGIN
10:02 102 T1 INSERT row A (balance=100)
10:03 103 T2 (xid=2) BEGIN
10:04 104 T2 INSERT row B (balance=200)
10:05 105 T1 COMMIT
10:06 106 T2 UPDATE row B (balance=250)
10:07 ───── ⚡ CRASH ⚡崩潰時的狀態：
- T1: Committed (LSN 105)
- T2: Active (not committed)
- Dirty pages: A (LSN 102), B (LSN 106)
恢復執行
┌─────────────────────────────────────────────────────────────┐
│ Phase 1: ANALYSIS │
├─────────────────────────────────────────────────────────────┤
│ Start from checkpoint LSN 100 │
│ Scan records 100-106 │
│ │
│ Result: │
│ - T1: Committed (LSN 105) │
│ - T2: Active (loser!) │
│ - Dirty pages: A→102, B→106 │
│ - Redo start: LSN 102 │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ Phase 2: REDO │
├─────────────────────────────────────────────────────────────┤
│ Replay from LSN 102: │
│ │
│ LSN 102: INSERT row A │
│ → Check page A LSN │
│ → If page LSN < 102: apply insert │
│ → Else: skip (already on disk) │
│ │
│ LSN 104: INSERT row B │
│ → Apply if needed │
│ │
│ LSN 106: UPDATE row B │
│ → Apply if needed │
│ │
│ Result: Database at exact crash state │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ Phase 3: UNDO │
├─────────────────────────────────────────────────────────────┤
│ Loser transactions: T2 │
│ │
│ Undo T2 (in reverse order): │
│ 1. Undo LSN 106 (UPDATE B: 200→250) │
│ → Write CLR: undo_next_lsn = 104 │
│ → Restore B to balance=200 │
│ │
│ 2. Undo LSN 104 (INSERT B) │
│ → Write CLR: undo_next_lsn = 103 │
│ → Delete row B │
│ │
│ 3. Log T2 ABORT │
│ │
│ Result: T2's changes rolled back, T1's changes preserved │
└─────────────────────────────────────────────────────────────┘7 WAL 歸檔和時間點恢復
WAL 歸檔
連續歸檔： 在重用前將 WAL 區段複製到安全儲存。
// src/wal/archiver.rs
pub struct WalArchiver {
wal_dir: PathBuf,
archive_dir: PathBuf,
archive_timeout: Duration,
last_archived_segment: u32,
}
impl WalArchiver {
pub fn archive_ready_segments(&mut self) -> Result<(), WalError> {
// Find completed segments (can't be overwritten)
for segment in self.get_ready_segments() {
let src = self.wal_dir.join(format!("{:024X}", segment));
let dst = self.archive_dir.join(format!("{:024X}.backup", segment));
// Copy to archive (could be remote storage like S3)
std::fs::copy(&src, &dst)?;
self.last_archived_segment = segment;
}
Ok(())
}
}時間點恢復 (PITR)
Goal: Restore database to state at 2026-03-22 14:30:00
1. Restore base backup from 2026-03-22 00:00:00
2. Replay WAL segments from archive
3. Stop replay at target time (14:30:00)
4. Database restored to exact point in time// src/recovery/pitr.rs
pub fn recover_to_point_in_time(
base_backup: &str,
archive_dir: &str,
target_time: chrono::DateTime<chrono::Utc>,
) -> Result<(), RecoveryError> {
// 1. Restore base backup
restore_base_backup(base_backup)?;
// 2. Find WAL segments to replay
let segments = find_wal_segments_for_time_range(archive_dir, target_time)?;
// 3. Replay WAL up to target time
for segment in segments {
let records = read_wal_segment(&segment)?;
for record in records {
// Check if we've passed target time
if record.timestamp > target_time {
println!("Reached target time, stopping recovery");
return Ok(());
}
apply_redo_record(&record)?;
}
}
Ok(())
}8 用 Rust 建構的挑戰
挑戰 1：fsync 和持久性
問題： Rust 的 File::sync_all() 是正確的，但容易忘記。
// ❌ Missing fsync - data NOT durable!
pub fn commit(&self, txn_id: TransactionId) -> Result<(), Error> {
let record = WalRecord::commit(txn_id);
self.wal.append(record)?;
// Forgot to flush!
Ok(())
}
// ✅ Correct
pub fn commit(&self, txn_id: TransactionId) -> Result<(), Error> {
let record = WalRecord::commit(txn_id);
let lsn = self.wal.append(record)?;
self.wal.flush(lsn)?; // fsync!
Ok(())
}教訓： 將 WAL 操作包裝在強制刷新的安全抽象中。
挑戰 2：LSN 順序和併發
問題： 多個執行緒附加 WAL 記錄必須獲得單調遞增的 LSN。
// ❌ Race condition - LSNs not ordered!
pub fn append(&self, record: WalRecord) -> Lsn {
let lsn = self.current_lsn + 1; // Not atomic!
self.current_lsn = lsn;
// ...
}
// ✅ Correct - atomic LSN allocation
pub fn append(&self, record: WalRecord) -> Result<Lsn, WalError> {
let lsn = Lsn::new(self.last_lsn.fetch_add(1, Ordering::SeqCst) + 1);
// ...
}挑戰 3：部分寫入和校驗和
問題： WAL 寫入期間崩潰 = 磁碟上的部分記錄。
// Solution: Checksums + length prefix
pub fn serialize_record(record: &WalRecord, buffer: &mut Vec<u8>) {
let data_start = buffer.len();
// Write placeholder for length (fill in later)
buffer.extend_from_slice(&[0u8; 4]);
// Write record fields
buffer.extend_from_slice(&record.lsn.to_le_bytes());
// ... more fields ...
buffer.extend_from_slice(&record.data);
// Calculate checksum over everything except checksum field
let checksum = crc32::calculate(&buffer[data_start + 4..]);
buffer.extend_from_slice(&checksum.to_le_bytes());
// Fill in length
let total_len = buffer.len() - data_start;
buffer[data_start..data_start + 4]
.copy_from_slice(&(total_len as u32).to_le_bytes());
}
pub fn deserialize_record(buffer: &[u8]) -> Result<WalRecord, WalError> {
// Read length
let length = u32::from_le_bytes(buffer[0..4].try_into()?) as usize;
// Verify we have enough data
if buffer.len() < length {
return Err(WalError::PartialWrite);
}
// Verify checksum
let stored_checksum = u32::from_le_bytes(
buffer[length - 4..length].try_into()?
);
let calculated = crc32::calculate(&buffer[4..length - 4]);
if stored_checksum != calculated {
return Err(WalError::ChecksumMismatch);
}
// ... parse record ...
}9 AI 如何加速這項工作
AI 做對了什麼
| 任務 | AI 貢獻 |
|---|---|
| ARIES 階段 | 清楚解釋 analysis/redo/undo |
| LSN 結構 | 建議區段/偏移編碼 |
| 檢查點設計 | 概述 fuzzy vs. sharp 權衡 |
| CLR 記錄 | 解釋補償日誌記錄目的 |
AI 做錯了什麼
| 問題 | 發生什麼事 |
|---|---|
| Redo 邏輯 | 初稿只 redo 已提交交易（錯誤！Redo ALL，然後 undo） |
| Undo 順序 | 建議正向順序而不是反向（LIFO） |
| Page LSN | 忽略了 page LSN 用於跳過冗餘 redo |
模式： ARIES 很微妙。「redo all, undo some」的洞察是反直覺的。
範例：理解 Redo 哲學
我問 AI 的問題：
“為什麼 ARIES redo 未提交的交易？我們不應該只 redo 已提交的嗎？”
我學到的：
- Redo 階段： 將資料庫帶到精確的崩潰狀態（包括未提交的變更）
- Undo 階段： 回滾未提交交易
- 為什麼？ 比在 redo 期間追蹤依賴關係更簡單
- 關鍵洞察： Redo 是冪等的，undo 必須記錄（CLRs）
結果： 正確的 redo 實作：
// Redo ALL records, not just committed
if page_lsn < record.lsn {
apply_redo(&record, &page)?; // Apply regardless of txn status
}
// Undo phase will handle uncommitted transactions總結：WAL 和 ARIES 一張圖
flowchart TD
subgraph "Normal Operation"
A[Transaction] --> B[Write WAL Record]
B --> C[Flush WAL fsync]
C --> D[Modify Page]
D --> E[Mark Dirty]
E --> F[ACK to Client]
F --> G[Checkpoint Later]
end
subgraph "Crash Recovery"
H[⚡ CRASH ⚡] --> I[Restart Database]
I --> J[Phase 1: Analysis]
J --> K[Find Active Transactions]
K --> L[Phase 2: Redo]
L --> M[Replay All WAL from Checkpoint]
M --> N[Phase 3: Undo]
N --> O[Rollback Loser Transactions]
O --> P[Database Consistent]
end
subgraph "WAL Structure"
Q[WAL Segment 1] --> R[WAL Segment 2]
R --> S[WAL Segment 3]
T[Checkpoint Record] -.-> Q
end
style C fill:#fff3e0,stroke:#f57c00
style J fill:#e3f2fd,stroke:#1976d2
style L fill:#e3f2fd,stroke:#1976d2
style N fill:#e3f2fd,stroke:#1976d2
style P fill:#e8f5e9,stroke:#388e3c
關鍵要點：
| 概念 | 為什麼重要 |
|---|---|
| WAL | 不犧牲效能的持久性 |
| LSN | 所有變更的總順序 |
| 檢查點 | 限制恢復時間 |
| ARIES Analysis | 確定需要恢復的內容 |
| ARIES Redo | replay 到精確崩潰狀態 |
| ARIES Undo | 回滾未提交的工作 |
| CLRs | 冪等的 undo，防止重複 undo |
進一步閱讀：
- “ARIES: A Transaction Recovery Method Supporting Fine Granularity Locking” by Mohan et al. (1992)
- PostgreSQL Source:
src/backend/access/transam/xlog.c - PostgreSQL Source:
src/backend/access/transam/xlogfuncs.c - “Database Management Systems” by Ramakrishnan (Ch. 17: Recovery)
- “Readings in Database Systems” (Red Book) - ARIES chapter
- Vaultgres Repository: github.com/neoalienson/Vaultgres