How much data do you plan to store in each table?
I’ll be honest, this doesn’t sound like a Cassandra use case at first glance.
1 table per report x 1000 is going to be a bad time. Odds are with different
queries, you’ll need multiple views, so lets call that a handful of tables per
report.
Thanks Jeff & Hannu,
Yeah, that's my guess too, I walk around this by set
-Dcassandra.commitlog.ignorereplayerrors=true.
Before upgrade, we did run `nodetool drain`, but seems the 2.1 commit log
were not cleared, and still got replayed by 2.2.
Thanks
Dikang.
On Tue, Apr 18, 2017 at 11:09 PM,
On 2017-04-19 08:10 (-0700), Sylvain Lebresne wrote:
> This is https://issues.apache.org/jira/browse/CASSANDRA-9328 and I'd rather
> not repeat myself here so I'll let you read the details. Let's maybe not
> open another JIRA ticket though since we have this one.
>
Thanks for the context, Syl
This is https://issues.apache.org/jira/browse/CASSANDRA-9328 and I'd rather
not repeat myself here so I'll let you read the details. Let's maybe not
open another JIRA ticket though since we have this one.
On Wed, Apr 19, 2017 at 4:29 PM, benjamin roth wrote:
> Thanks, Jeff!
>
> As soon as I have
Thanks, Jeff!
As soon as I have some spare time I will try to reproduce and open a Jira
for it.
2017-04-19 16:27 GMT+02:00 Jeff Jirsa :
>
>
> On 2017-04-13 05:13 (-0700), benjamin roth wrote:
> > I found out that if the WTEs occur, there was already another process
> > inserting the same primar
On 2017-04-13 05:13 (-0700), benjamin roth wrote:
> I found out that if the WTEs occur, there was already another process
> inserting the same primary key because I found duplicates in some places
> that perfectly match the WTE logs.
>
> Does anybody know, why this throws a WTE instead of retu
Ah, by the way - we are using Cassandra 3.10 and the spark connector version
2.0.0
We are using Spark to do aggregations of our Cassandra data. We recognized even
quite simple jobs to be way to slow and narrowed it down to the data fetching
from C*. It would not be surprising that the most of the time is spend on
fetching the data. But actually for a query (using the
sparkCon
