‫Partitioning times, so that's what we did, partitioning range as the example I gave IDs, you can
‫partition by a long day.
‫Let's say you you have an Iot devices spitting out measurement or something like that.
‫And there is a log date with every single measurement.
‫And you go on a partition like, oh, 2012 data 2013, the 2020 data on each year by partition of each
‫quarter or each month put it in a given partition.
‫So that's ranged right from this date to this date, throw it in this partition and then the beauty
‫of this like, oh, this, this table, this partition is old and nobody uses it anymore to who's going
‫to query 1995 data anymore.
‫So let's move it into a slower archive like, I don't know, running on tape somewhere.
‫So if it's slow, I don't care.
‫That's range bilis discrete values.
‫States, for example, California, Oros or any customer in California goes on this table.
‫This is not range.
‫This is a value say that partition is for California people that partition for Alabama or zip codes.
‫Right.
‫Or countries the same thing.
‫Right.
‫So that's that's another way of partitioning by hash.
‫Another popular Feinglass Cassandra uses that right where where you use the hash function to to spread
‫the value.
‫So hash function, that gives you a hash.
‫If you got this hash, go to this table.
‫If you got this hash goes to this table.
‫So that's a very, very popular thing.
‫I know in the proxy's we use IAP hash to kind of decide which back into it based on the IP.
‫So that's another idea.