I have taken a database class this semester and we are studying about maintaining cache consistency between the RDBMS and a cache server such as memcached. The consistency issue
The code below gives some idea of how to use Memcached's operations add
, gets
and cas
to implement optimistic locking to ensure consistency of cache with the database.
Disclaimer: i do not guarantee that it's perfectly correct and handles all race conditions. Also consistency requirements may vary between applications.
def read(k):
loop:
get(k)
if cache_value == 'updating':
handle_too_many_retries()
sleep()
continue
if cache_value == None:
add(k, 'updating')
gets(k)
get_from_db(k)
if cache_value == 'updating':
cas(k, 'value:' + version_index(db_value) + ':' + extract_value(db_value))
return db_value
return extract_value(cache_value)
def write(k, v):
set_to_db(k, v)
loop:
gets(k)
if cache_value != 'updated' and cache_value != None and version_index(cache_value) >= version_index(db_value):
break
if cas(k, v):
break
handle_too_many_retries()
# for deleting we can use some 'tumbstone' as a cache value