Timwi wrote: Why not use a daemon to scan the logs on each squid, and then only increment the database read count for (say) one in a hundred, or one in a thousand of these hits, chosen as (pseudo) random, with the increment being 100 if only 1 in 100 hits is logged, and so on. Over time, the law of large numbers will arrange for it to average out to reasonably representative hit counts. Something as simple as the following run at intervals from a cron job should do it, combined with logrotate. Since it's mostly CPU-intensive, the analysis job can be niced down to avoid interfering with the main task of squid processing. If this would not be practical, please let me know why. # Note: pythonesque pseudocode, not a real program import random. time, re # and SQL stuff... N = 1000 # or some other suitable value... conn = make_sql_connection() def log_article_hits(url, count): time.sleep(5) # to avoid hitting the DB too hard... # stub: should parse URL using regexp for project/language/article title, # then call SQL code that increments the article read counter by "count" return for line in open("/var/log/squid/access.log"): # or whatever... fields = string.split(line) if len(fields) < 7: continue url = fields[6] if random.randint(1,N) == 1: log_article_hits(url, N) -- Neil