Wrap-around file & Write-Ahead L

2023-09-08  本文已影响0人  做一只有趣的芦苇

Wrap-around file

The concept of a wrap-around file, like the transaction log in SQL Server, can be likened to the concept of a circular buffer. In a circular buffer, when the end is reached, the pointer wraps around to the start of the buffer, and data begins to overwrite from the beginning. Here's a simple illustration using a Python list to demonstrate the concept:

class CircularBuffer:
    def __init__(self, size):
        self.buffer = [None] * size
        self.size = size
        self.index = 0

    def append(self, value):
        self.buffer[self.index] = value
        self.index = (self.index + 1) % self.size  # This line ensures the wrap-around

    def get(self):
        return self.buffer

# Example Usage:

buf = CircularBuffer(5)
buf.append("A")
buf.append("B")
buf.append("C")
buf.append("D")
buf.append("E")

print(buf.get())  # ['A', 'B', 'C', 'D', 'E']

buf.append("F")  # This will overwrite 'A' due to wrap-around

print(buf.get())  # ['F', 'B', 'C', 'D', 'E']

buf.append("G")
buf.append("H")

print(buf.get())  # ['F', 'G', 'H', 'D', 'E']

Write-Ahead Logging (WAL) is a crucial concept in database systems to ensure data integrity. The basic idea behind WAL is that changes (modifications) to data files (where the actual database data is stored) are always written to a log before they are applied to the data files.

Here's a simplified example of how a WAL system might operate:

  1. A user requests to change a piece of data.
  2. The system writes a log entry about the change. This log entry contains the old value, the new value, and the location of the change.
  3. The system updates the actual data in the database.
  4. Periodically, a process will checkpoint the system. This involves:
  5. Ensuring all changes up to the checkpoint have been written to the data file.
    Writing a special checkpoint entry in the log.

In the event of a system crash:

  1. The system will restart.
  2. It will read the log from the last checkpoint.
  3. Any changes found in the log that weren't written to the data file will be redone.
  4. Any changes after the last checkpoint that were written to the data file but didn't have a corresponding log entry will be undone.

Here's a basic Python representation of the WAL concept:

class WAL:
    def __init__(self):
        self.log = []
        self.data = {}

    def write(self, key, value):
        # Step 2: Write to log first
        old_value = self.data.get(key)
        self.log.append((key, old_value, value))

        # Step 3: Write to the actual data
        self.data[key] = value

    def checkpoint(self):
        # Step 4: Periodic checkpointing (simplified)
        self.log.append("CHECKPOINT")
        # Here you'd typically ensure all logged changes have been written to the data.

    def recover(self):
        # After a system crash, use the log to recover the data
        reached_checkpoint = False
        for entry in reversed(self.log):
            if entry == "CHECKPOINT":
                reached_checkpoint = True
            if reached_checkpoint and isinstance(entry, tuple):
                key, _, value = entry
                self.data[key] = value

# Example Usage:

wal = WAL()

wal.write("username", "john_doe")
wal.write("email", "john@example.com")
wal.checkpoint()
wal.write("username", "john_updated")

print(wal.data)  # {'username': 'john_updated', 'email': 'john@example.com'}

# Simulate crash and recovery
wal.data = {}  # Reset data to simulate crash
wal.recover()

print(wal.data)  # {'username': 'john_doe', 'email': 'john@example.com'}
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