ARIES Redo Phase: Reconstructing Consistency

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class RedoPhaseProcessor:
    """
    Complete implementation of the ARIES redo phase processing loop.
    This demonstrates the exact algorithm used in production databases.
    """
    
    def __init__(self, log_manager, buffer_manager, dirty_page_table):
        self.log = log_manager
        self.buffer = buffer_manager
        self.dirty_page_table = dirty_page_table  # From analysis phase
        self.redo_lsn = self._calculate_redo_lsn()
        self.pages_redone = 0
        self.pages_skipped = 0
    
    def _calculate_redo_lsn(self):
        """Calculate starting point from Dirty Page Table"""
        if not self.dirty_page_table:
            return float('inf')  # Nothing to redo
        return min(entry.rec_lsn for entry in self.dirty_page_table.values())
    
    def execute_redo_phase(self):
        """
        Main redo phase execution.
        Scans log from RedoLSN forward, applying operations as needed.
        """
        print(f"Starting redo phase from LSN {self.redo_lsn}")
        
        # Open log scan at RedoLSN
        log_scan = self.log.open_forward_scan(start_lsn=self.redo_lsn)
        
        for record in log_scan:
            self._process_log_record(record)
        
        print(f"Redo phase complete:")
        print(f"  - Records processed: {self.pages_redone + self.pages_skipped}")
        print(f"  - Pages redone: {self.pages_redone}")
        print(f"  - Pages skipped: {self.pages_skipped}")
    
    def _process_log_record(self, record):
        """
        Process a single log record during redo.
        This is the heart of the redo algorithm.
        """
        # Step 1: Filter non-redoable records
        if not self._is_redoable(record):
            return
        
        page_id = record.page_id
        
        # Step 2: Check if page is in Dirty Page Table
        # If page is not in DPT, it was flushed after all its modifications
        # and doesn't need redo
        if page_id not in self.dirty_page_table:
            self.pages_skipped += 1
            return
        
        # Step 3: Check recLSN - if record LSN < recLSN, the modification
        # was flushed before this page became dirty again
        rec_lsn = self.dirty_page_table[page_id].rec_lsn
        if record.lsn < rec_lsn:
            self.pages_skipped += 1
            return
        
        # Step 4: Read page from disk and check pageLSN
        page = self.buffer.fetch_page(page_id)
        page_lsn = page.get_page_lsn()
        
        # Step 5: The critical comparison
        # If pageLSN >= record.lsn, this operation is already on disk
        if page_lsn >= record.lsn:
            self.pages_skipped += 1
            self._log_skip_reason(record, page_lsn, "pageLSN >= record LSN")
            return
        
        # Step 6: Apply the redo
        self._apply_redo(page, record)
        self.pages_redone += 1
    
    def _is_redoable(self, record):
        """Determine if a log record requires redo action"""
        redoable_types = {'UPDATE', 'CLR', 'NESTED_TOP_ACTION'}
        return record.type in redoable_types
    
    def _apply_redo(self, page, record):
        """
        Apply the redo information from the log record to the page.
        This is where the actual modification happens.
        """
        # Extract redo information from log record
        redo_info = record.redo_info
        
        # Apply the operation based on its type
        if record.type == 'UPDATE':
            # Physiological redo: apply operation to specific location
            self._apply_physiological_redo(page, redo_info)
        
        elif record.type == 'CLR':
            # CLR redo is the same as UPDATE redo - just apply the change
            self._apply_physiological_redo(page, redo_info)
        
        # Update the page's LSN to reflect this redo
        page.set_page_lsn(record.lsn)
        
        # Mark page as dirty (it will eventually be flushed)
        self.buffer.mark_dirty(page)
    
    def _apply_physiological_redo(self, page, redo_info):
        """
        Apply physiological redo operation.
        
        Physiological logging means:
        - Physical: identifies the specific page
        - Logical: describes the operation within the page
        
        This allows the operation to work correctly even if
        the page's internal structure has changed.
        """
        operation_type = redo_info['operation']
        
        if operation_type == 'INSERT_RECORD':
            slot = redo_info['slot']
            data = redo_info['data']
            page.insert_at_slot(slot, data)
        
        elif operation_type == 'DELETE_RECORD':
            slot = redo_info['slot']
            page.delete_at_slot(slot)
        
        elif operation_type == 'UPDATE_FIELD':
            slot = redo_info['slot']
            offset = redo_info['offset']
            new_value = redo_info['new_value']
            page.update_field(slot, offset, new_value)
        
        elif operation_type == 'PAGE_SPLIT':
            # B-tree page splits are logged and redone
            new_page_id = redo_info['new_page_id']
            split_key = redo_info['split_key']
            page.apply_split(new_page_id, split_key)
        
        # ... other operation types as needed
    
    def _log_skip_reason(self, record, page_lsn, reason):
        """Log why a redo was skipped (for debugging/monitoring)"""
        # In production, this might update metrics or detailed logs
        pass

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class UpdateLogRecord:
    """
    Structure of an UPDATE log record in ARIES.
    This record contains all information needed for both redo and undo.
    """
    
    def __init__(self):
        # Header fields (present in all log records)
        self.lsn = None           # Log Sequence Number - unique identifier
        self.type = 'UPDATE'      # Record type
        self.txn_id = None        # Transaction that made this change
        self.prev_lsn = None      # Previous LSN for this transaction
        
        # Page identification
        self.page_id = None       # Which page was modified
        
        # Redo information - enough to re-apply the change
        self.redo_info = {
            'operation': None,    # Type of operation (INSERT, DELETE, UPDATE)
            'offset': None,       # Position within page (for byte-level ops)
            'length': None,       # Length of modification
            'new_value': None,    # The value to write (after-image)
        }
        
        # Undo information - enough to reverse the change
        self.undo_info = {
            'operation': None,    # Inverse operation
            'offset': None,       # Same position
            'length': None,       # Same length
            'old_value': None,    # The value to restore (before-image)
        }
 
# Example: A row update operation
def example_row_update():
    """
    Scenario: Update employee salary from 50000 to 55000
    in row at slot 5 of page 1234
    """
    record = UpdateLogRecord()
    record.lsn = 1000
    record.txn_id = 'T1'
    record.prev_lsn = 995
    record.page_id = 1234
    
    # For redo: we need to know what to write
    record.redo_info = {
        'operation': 'UPDATE_FIELD',
        'slot': 5,              # Row position in page
        'field_offset': 32,     # Salary field offset within row
        'length': 4,            # 4 bytes for integer
        'new_value': 55000      # New salary
    }
    
    # For undo: we need to know the original value
    record.undo_info = {
        'operation': 'UPDATE_FIELD',
        'slot': 5,
        'field_offset': 32,
        'length': 4,
        'old_value': 50000      # Original salary
    }
    
    return record

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class CLRLogRecord:
    """
    Compensation Log Record (CLR) - records an undo operation.
    
    Key insight: A CLR is redo-only! It records what was done to 
    undo a previous operation. If we redo a CLR, we're re-applying
    the undo operation, which is exactly what we want.
    """
    
    def __init__(self):
        # Standard header
        self.lsn = None
        self.type = 'CLR'
        self.txn_id = None
        self.prev_lsn = None
        
        # Page being modified by the undo
        self.page_id = None
        
        # The undo operation (which we need to redo during recovery)
        self.redo_info = None   # Same structure as UPDATE redo_info
        
        # The critical CLR field: points to the NEXT record to undo
        self.undo_next_lsn = None
        
        # NOTE: CLRs have NO undo_info field!
        # This is crucial: CLRs themselves are never undone
 
def create_clr_for_undo(original_record, undo_result):
    """
    Create a CLR when undoing an UPDATE record.
    
    The CLR captures what we did (the undo) and where to continue
    if we need to keep undoing (undo_next_lsn).
    """
    clr = CLRLogRecord()
    clr.txn_id = original_record.txn_id
    clr.page_id = original_record.page_id
    
    # The redo_info for a CLR is the UNDO of the original
    # So during redo, we re-apply the undo operation
    clr.redo_info = {
        'operation': original_record.undo_info['operation'],
        'slot': original_record.undo_info.get('slot'),
        'offset': original_record.undo_info.get('offset'),
        'new_value': original_record.undo_info['old_value']  # Restore old!
    }
    
    # Point to the record we should undo next
    clr.undo_next_lsn = original_record.prev_lsn
    
    return clr
 
# Example scenario demonstrating CLR creation and redo
def clr_redo_scenario():
    """
    Scenario:
    1. T1 updates salary 50000 -> 55000 (LSN 100)
    2. T1 is rolled back, salary restored 55000 -> 50000 (CLR at LSN 150)
    3. System crashes
    4. During redo, we redo the CLR (restoring salary to 50000)
    """
    
    # Original update
    original = UpdateLogRecord()
    original.lsn = 100
    original.txn_id = 'T1'
    original.prev_lsn = 90  # Previous operation by T1
    original.page_id = 1234
    original.redo_info = {'operation': 'UPDATE_FIELD', 'new_value': 55000}
    original.undo_info = {'operation': 'UPDATE_FIELD', 'old_value': 50000}
    
    # CLR created when undoing the above
    clr = CLRLogRecord()
    clr.lsn = 150
    clr.txn_id = 'T1'
    clr.prev_lsn = 100
    clr.page_id = 1234
    clr.redo_info = {'operation': 'UPDATE_FIELD', 'new_value': 50000}  # Restoring!
    clr.undo_next_lsn = 90  # Skip LSN 100, go to 90 next
    
    print("During redo phase:")
    print(f"  LSN 100 UPDATE: Would set salary to 55000")
    print(f"  LSN 150 CLR: Would set salary back to 50000")
    print(f"")
    print("After redo, salary = 50000 (the undo was 'redone')")
    print("During undo phase, T1 is seen as still needing undo,")
    print("but undo_next_lsn=90 tells us to skip LSN 100!")
 
clr_redo_scenario()

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import threading
from collections import defaultdict
from queue import Queue
 
class ParallelRedoProcessor:
    """
    Optimized redo processor that parallelizes where safe.
    
    Strategy: 
    - Single thread scans log and dispatches to page-specific queues
    - Multiple worker threads process page queues in parallel
    - Operations on the same page remain ordered within their queue
    """
    
    def __init__(self, num_workers=4):
        self.num_workers = num_workers
        self.page_queues = defaultdict(Queue)  # page_id -> operation queue
        self.workers = []
        self.stop_event = threading.Event()
    
    def execute_parallel_redo(self, log_records, redo_lsn):
        """
        Execute redo phase with page-level parallelism.
        """
        # Start worker threads
        for i in range(self.num_workers):
            worker = threading.Thread(
                target=self._page_worker,
                args=(i,)
            )
            worker.start()
            self.workers.append(worker)
        
        # Main thread: scan log and dispatch to page queues
        pages_seen = set()
        for record in log_records:
            if record.lsn < redo_lsn:
                continue
            
            if not self._is_redoable(record):
                continue
            
            page_id = record.page_id
            pages_seen.add(page_id)
            
            # Add to page-specific queue (maintains order per page)
            self.page_queues[page_id].put(record)
        
        # Signal completion and wait
        for page_id in pages_seen:
            self.page_queues[page_id].put(None)  # Sentinel
        
        self.stop_event.set()
        for worker in self.workers:
            worker.join()
    
    def _page_worker(self, worker_id):
        """
        Worker thread that processes operations for assigned pages.
        Each page's operations are processed in order, but different
        pages can be processed concurrently.
        """
        while not self.stop_event.is_set():
            # Find a page with pending work
            for page_id, queue in self.page_queues.items():
                if not queue.empty():
                    record = queue.get()
                    if record is None:
                        continue  # Sentinel, this page is done
                    
                    # Process this redo operation (same logic as serial)
                    self._process_redo(record)
    
    def _process_redo(self, record):
        """Apply redo - same as sequential version"""
        # ... LSN checks, page fetch, apply redo ...
        pass
    
    def _is_redoable(self, record):
        return record.type in {'UPDATE', 'CLR'}

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def nested_top_action_redo():
    """
    Nested top actions are mini-transactions that commit independently.
    
    Example: Allocating a new page for a B-tree split
    - The allocation itself must persist even if the insert fails
    - Otherwise, we'd leak pages or corrupt free space management
    """
    
    # Log record structure for nested top action
    nested_action_log = {
        'type': 'NESTED_TOP_ACTION',
        'lsn': 200,
        'txn_id': 'T1',
        'page_id': 'free_space_map',
        
        # Only redo info - NO undo info!
        'redo_info': {
            'operation': 'ALLOCATE_PAGE',
            'allocated_page_id': 5678
        },
        
        # Links that make this a "nested" action
        'dummy_clr_lsn': 199,  # Points before the nested action start
        
        # This ensures undo skips over this action
    }
    
    print("During redo: Apply ALLOCATE_PAGE normally")
    print("During undo: The dummy CLR linkage causes this to be skipped")
    print("Result: Page allocation persists even if T1 is rolled back")

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def multi_page_operation_redo():
    """
    B-tree split logged as multiple records with dependencies.
    """
    
    # Step 1: Allocate new sibling page
    log_record_1 = {
        'lsn': 300,
        'type': 'NESTED_TOP_ACTION',  # Page allocation never undone
        'page_id': 'free_space_map',
        'redo_info': {'operation': 'ALLOCATE_PAGE', 'new_page_id': 999}
    }
    
    # Step 2: Initialize new page with half the keys
    log_record_2 = {
        'lsn': 301,
        'type': 'UPDATE',
        'page_id': 999,  # The newly allocated page
        'redo_info': {'operation': 'INIT_BTREE_LEAF', 'keys': [50,51,52]}
    }
    
    # Step 3: Update original page to remove moved keys
    log_record_3 = {
        'lsn': 302,
        'type': 'UPDATE',
        'page_id': 888,  # The original page being split
        'redo_info': {'operation': 'REMOVE_KEYS', 'keys': [50,51,52]}
    }
    
    # Step 4: Update parent with new separator key
    log_record_4 = {
        'lsn': 303,
        'type': 'UPDATE',
        'page_id': 777,  # Parent page
        'redo_info': {'operation': 'INSERT_SEPARATOR', 'key': 50, 'child_ptr': 999}
    }
    
    print("Redo processes these in LSN order (300, 301, 302, 303)")
    print("Even if some pages were flushed, the sequential redo")
    print("ensures the B-tree ends up in a consistent state.")

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class RedoWithPrefetch:
    """
    Redo processor with page prefetching for improved I/O.
    """
    
    def __init__(self, buffer_manager, prefetch_distance=100):
        self.buffer = buffer_manager
        self.prefetch_distance = prefetch_distance
        self.pending_prefetch = set()
    
    def execute_redo_with_prefetch(self, log_records, redo_lsn):
        """
        Process redo while prefetching upcoming pages.
        """
        # Build lookahead buffer
        lookahead = []
        
        for record in log_records:
            if record.lsn < redo_lsn:
                continue
            if not self._is_redoable(record):
                continue
            
            lookahead.append(record)
            
            # When we have enough lookahead, start prefetching
            if len(lookahead) >= self.prefetch_distance:
                self._issue_prefetch(lookahead[-1].page_id)
            
            # Process the oldest record in lookahead
            if len(lookahead) > self.prefetch_distance:
                oldest = lookahead.pop(0)
                self._process_redo(oldest)
        
        # Drain remaining records
        for record in lookahead:
            self._process_redo(record)
    
    def _issue_prefetch(self, page_id):
        """Request async page read"""
        if page_id not in self.pending_prefetch:
            self.buffer.async_prefetch(page_id)
            self.pending_prefetch.add(page_id)