Hi,
Depending on the use case, you may also consider storage tiering with fresh data on hot-tier (Cassandra) and older data on cold-tier (Spark/Parquet or Presto/Parquet). It would be a lot more complex, but may fit more appropriately the budget and you may reuse some tech already present in your environment.
You may even do subsampling during the transformation offloading data from Cassandra in order to keep one point out of 10 for older data if subsampling makes sense for your data signal.

Regards
Julien

Le lun. 30 sept. 2019 à 22:03, DuyHai Doan <doanduyhai@gmail.com> a écrit :
Thanks all for your reply 

The target deployment is on Azure so with the Nice disk snapshot feature, replacing a dead node is easier, no streaming from Cassandra 

About compaction overhead, using TwCs with a 1 day bucket and removing read repair and subrange repair should be sufficient 

Now the only remaining issue is Quorum read which triggers repair automagically

Before 4.0  there is no flag to turn it off unfortunately 

Le 30 sept. 2019 15:47, "Eric Evans" <john.eric.evans@gmail.com> a écrit :
On Sat, Sep 28, 2019 at 8:50 PM Jeff Jirsa <jjirsa@gmail.com> wrote:

[ ... ]

> 2) The 2TB guidance is old and irrelevant for most people, what you really care about is how fast you can replace the failed machine
>
> You’d likely be ok going significantly larger than that if you use a few vnodes, since that’ll help rebuild faster (you’ll stream from more sources on rebuild)
>
> If you don’t want to use vnodes, buy big machines and run multiple Cassandra instances in it - it’s not hard to run 3-4TB per instance and 12-16T of SSD per machine

We do this too.  It's worth keeping in mind though that you'll still
have a 12-16T blast radius in the event of a host failure.  As the
host density goes up, consider steps to make the host more robust
(RAID, redundant power supplies, etc).

--
Eric Evans
john.eric.evans@gmail.com

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