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Re: [EXTERNAL] Availability issues for write/update/read workloads (up to 100s downtime) in case of a Cassandra node failure

Hi Daniel,

it seems like the driver isn't detecting that the node went down, which is probably due to the way the node is being killed. 
If I remember correctly, in some cases Netty transport is still up in the client, which will still allows to send queries without them answering back : https://datastax-oss.atlassian.net/browse/JAVA-1346
Eventually, the node gets discarded when the heartbeat system catches up.
It's also possible that the stuck queries then eat up all the available slots in the driver, preventing any other query to be sent in that JVM.

Which version of the Datastax Driver are you using for your tests?
How is it configured (load balancing policies, etc...) ?
Do you have some debug logs on the client side that could help?


On Fri, Nov 16, 2018 at 1:19 PM Daniel Seybold <daniel.seybold@xxxxxxxxxx> wrote:

Hi Sean,

thanks for your comments, find below some more details with respect to the (1) VM sizing and (2) the replication factor:

(1) VM sizing:

We selected the small VMs as intial setup to run our experiments. We have also executed the same experiments (5 nodes) on larger VMs with 6 cores and 12GB memory (where 6GB was allocated to Cassandra).

We use the default CMS garbace collector (with default settings) and the debug.log and system.log does not show any suspicious GC messages.

(2) Replication factor

We set the RF to 5 as we want to emulate a scenario which is able to survive multiple-node failures. We have also tried a RF of 3 (in the 5 node cluster) but the downtime in case of a node failure persists.

I also attached two plots which show the results with the downtimes for using the larger VMs and setting the RF to 3

Any further comments much appreciated,


Am 09.11.2018 um 19:04 schrieb Durity, Sean R:

The VMs’ memory (4 GB) seems pretty small for Cassandra. What heap size are you using? Which garbage collector? Are you seeing long GC times on the nodes? The basic rule of thumb is to give the Cassandra heap 50% of the RAM on the host. 2 GB isn’t very much.


Also, I wouldn’t set the replication factor to 5 (the number of nodes). If RF is always equal to the number of nodes, you can’t really scale beyond the size of the disk on any one node (all data is on each node). A replication factor of 3 would be more like a typical production set-up.



Sean Durity


From: Daniel Seybold <daniel.seybold@xxxxxxxxxx>
Sent: Friday, November 09, 2018 5:49 AM
To: user@xxxxxxxxxxxxxxxxxxxx
Subject: [EXTERNAL] Availability issues for write/update/read workloads (up to 100s downtime) in case of a Cassandra node failure


Hi Apache Cassandra experts,

we are running a set of availability evaluations under a write/read/update workloads with Apache Cassandra and experience some unexpected results, i.e.  0 ops/s over a period up to 100s.

In order to provide a clear picture find below the details of (1) the setup and (2) the evaluation workflow

1. Setup:

Cassandra version: 3.11.2
Cluster size: 5 nodes
Replication Factor: 5
Each nodes runs in the same private OpenStack based cloud, within the same availability zone and uses the private network.
Each nodes runs as OS Ubuntu 16.04 server and has 2 cores, 4GB RAM and 50GB disk.

Yahoo Cloud Serving Benchmark 0.12
W1: 100% write
W2: 100% read
W3: 100% update

2. Evaluation Workflow:
1. allocate 5 VMs & deploy DBMS cluster
2. start a YCSB worklod (only one of W1-3) which runs up to 30 minutes
3. wait for 200s
4. trigger the selection of a  random node in the cluster and delete the VM without stopping  Cassandra before
5. analyze throughput time series over the evaluation

3. (Unexpected) Results

We expected to see a (slight) drop in the throughput as soon as the VM was deleted.
But the throughput results show that the there are periods of ~10s - 150s (not deterministic) where no operations are executed (all metrics are collected on client side)
Yet, there are no timeout exceptions on client side and also the logs on cluster side do not show anything that explains this behaviour.

I attached a series of plots which show the throughput and the downtimes over the evaluation runs. 

Do you have any explanations for this behaviour or recommendations how to reduce the  potential "downtime" ?

Thanks in advance for any help and recommendations,


M.Sc. Daniel Seybold
Universität Ulm
Institut Organisation und Management
von Informationssystemen (OMI)
Albert-Einstein-Allee 43
89081 Ulm
Phone: +49 (0)731 50-28 799

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M.Sc. Daniel Seybold

Universität Ulm
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