Scan resistance and loop resistance are completely different. They are also distinguished in the papers. Note that ARC has scan resistance but no loop resistance.
181 karma · joined February 22, 2021
Note that S3-FIFO has no loop resistance. Nevertheless, the result that this library is functioning in a loop indicates that some important changes have been made. Also, the result that Ristretto, which has loop resistance, is not functioning in a loop is clearly an anomaly and likely not being measured correctly. Ristretto's benchmark results on S3, DS1, and OLTP differ markedly from the official ones (https://github.com/dgraph-io/ristretto). Otter's benchmark results are quite suspicious.
It means BBQ?
BTW, why isn't this on the top page despite the high points? Is this oppressed? I checked HN at least every half day for the last few days and this must never have been ranked on the top page.
> So instead of having to do network operations, serialization, and deserialization, the reads and writes to home timelines in our implementation are literally just in-memory operations on a hash map. This is dramatically simpler and more efficient than operating a separate in-memory database.
> To minimize memory usage and GC pressure, we use a ring buffer and Java primitives to represent each home timeline. The buffer contains pairs of author ID and status ID. The author ID is stored along with the status ID since it is static information that will never change, and materializing it means that information doesn’t need to be looked up at query time. The home timeline stores the most recent 600 statuses, so the buffer size is 1,200 to accommodate each author ID and status ID pair. The size is fixed since storing full timelines would require a prohibitive amount of memory (the number of statuses times the average number of followers).
> Each user utilizes about 10kb of memory to represent their home timeline. For a Twitter-scale deployment of 500M users, that requires about 4.7TB of memory total around the cluster, which is easily achievable.
Isn't this where the most difficult(expensive) part is and Rama has little to do with it? It appears that the other parts also do not have to be Rama.
Too long.
https://github.com/apple/foundationdb/tree/main/fdbserver/wo...
> Someone could probably integrate this functionality into a Kubernetes operator or something so that outside engineers could run large scale simulations reliably. But it is really expensive and CPU/compute intense, no matter how you go about it.
Maybe this.
https://github.com/makenowjust-labs/recheck
I use the checker to basically fix even regular expressions that are not actually vulnerable. This checker can be used as a lint, so there is no excuse to allow regular lint but not regular expression lint. ReDoS hunt is very enjoyable. Enjoy!