Hi Ali,Please find my answers 1) The table holds customer history data, where we receive the transaction data everyday for multiple vendors and batch job is executed which updates the data if the customer do any transactions that day, and insert will happen if he is new customer. Reads will
For what its worth, I highly recommend you remove that option in all
cassandra clusters first thing. A possibly non existent improvement (ie
/tmp on different low throughput drive) vs being able to diagnose issues is
a no brainer. You can measure or monitor gc logs for your safepoint pauses
to see
Dinesh this is my understanding of streamng options in C* 3.0
1) nodetool rebuild - is a default option to stream data to a new node,
when adding new regions
pros: simply run rebuild to stream data to a new node: nodetool rebuild -dc
&
cons: If internode compression enabled or per table
Thank you Yuki, this explains it.
I am used to working on C* 2.1 in production where this JVM flag is not
enabled.
On Wed, 19 Sep 2018 at 00:29, Yuki Morishita wrote:
> This is because Cassandra sets -XX:+PerfDisableSharedMem JVM option by
> default.
> This prevents tools such as jps to list
In other words, your write amplification would increase from 30-50 for
normal LCS to 200-300 when fan-out changes to 100.
On 18/09/2018 14.54, Marcus Eriksson wrote:
problem would be that for every file you flush, you would recompact
all of L1 - files are flushed to L0, then compacted together
I guess also OS-level page cache also will help out implicitly to make sure
your common pages aren't touching disk.
On Fri, Sep 14, 2018 at 2:46 AM Alaa Zubaidi (PDF)
wrote:
> Hi,
>
> We are using Apache Cassandra 3.11.2 on RedHat 7
> The data can grow to +100TB however the hot data will be in
Hello Rajasekhar,
It's not really clear to me what your workload is. As I understand it, you
do heavy writes, but what about reads?
So, could you:
1) execute
nodetool tablestats
nodetool tablehistograms
nodetool compactionstats
we should be able to see the latency, workload type, and the #
