Hello Kazi, There is no need to be a root when running this benchmark. Could you let me know the exact Memcached version you are using?
I guess you wanted to say "-S 30" in your command, rather than -S 3. I see that you are using two servers at the same time. I suggest you create two files: server1.txt and server2.txt each containing the corresponding server details. Then run the following command to scale the dataset and warm up one server: ./loader -a ../twitter_dataset/twitter_dataset_unscaled -o ../twitter_dataset/twitter_dataset_30x -s servers1.txt -S 30 -D 4096 -j -T 1 Once it finishes, you can just warm up the other server: ./loader -a ../twitter_dataset/twitter_dataset_30x -s servers2.txt -S 1 -D 4096 -j -T 1 Let me know what happens. Regards, Djordje ________________________________________ From: Kazi Sudipto Arif [[email protected]] Sent: Tuesday, August 27, 2013 9:30 AM To: [email protected] Subject: running data-caching magic number error Hello, I am attempting to get the data-caching benchmark up and running on Ubuntu 10.04 OS (x86). I receive a magic number error when attempting to scale the dataset. The output file is not produced and I cannot start the benchmark. I cannot understand why this is happening and any help in tracking the cause would be much appreciated. Scaling the dataset: root@server:/opt/memcached/memcached_client# sudo ./loader -a ../twitter_dataset/twitter_dataset_unscaled -o ../twitter_dataset_30x -s servers.txt -w 2 -S 3 -D 4096 -j -T 1 stats_time = 1 Configuration: nProcessors on system: 8 nWorkers: 2 runtime: -1 Get fraction: 0.900000 Naggle's algorithm: False host: 10.0.5.2 address: 10.0.5.2 host: 192.168.10.116 address: 192.168.10.116 Loading key value file...Average Size = 1057.34758 Keys to Preload = 802302 created uniform distribution 1000 rps -1 cpus 2 Overridge n_connections_total because < n_workers num_worker_connections 1 num_worker_connections 1 Creating worker on tid 1340749568 starting receive base loop On read Incorrect magic number: 48 should be: ffffff81 Thank you, Kazi
