The compare-and-swap (CAS) feature in Memcached is used when you want to ensure that the value you are setting in the cache has not been overwritten by another process since you last fetched it. This is extremely useful in multi-threaded and distributed systems where multiple entities might be trying to update the same key.
Let's say we have a Memcached instance mc
and a key my_key
. We want to increment its value using CAS operation to prevent potential race conditions:
import pymemcache.client.base as memcache # Connect to memcached client = memcache.Client(('localhost', 11211)) def cas_increment(client, key): while True: result, cas_id = client.gets(key) if result is None: # Handle missing key case break incremented_value = int(result) + 1 if client.cas(key, str(incremented_value), cas_id): break # Assume 'my_key' is already set cas_increment(client, 'my_key')
In this example, we first retrieve the value and the unique CAS ID for the given key using client.gets()
. Then, we attempt to increment the value with client.cas()
. If the value hasn't been modified by someone else, client.cas()
will return True and we break the loop. If not, we retry the whole process until successful.
gets()
and cas()
calls.cas()
. It can indicate whether the operation was successful or not.1. When should I use CAS in Memcached?
2. What happens if a key does not exist when I perform a CAS operation?
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.