I've setup a 3 machine VoltDB cluster with more or less default settings. However there seems to be a constant problem with voltdb eating up all of the RAM heap and not freeing it. The heap size is recommended 2GB.
Things that I think might be bad in my setup:
I've set 1 min async snapshots
Most of my queries are AdHoc
Event though it might not be ideal, I don't think it should lead to a problem where memory doesn't get freed.
I've setup my machines accordingly to 2.3. Configure Memory Management.
On this image you can see sudden drops in memory usage. These are server shutdowns.
Heap filling warnings
DB Monitor, current state of leader server
I would also like to note that this server is not heavily loaded.
Sadly, I couldn't find anyone with a similar problem. Most of the advice were targeted on fixing problems with optimizing memory use or decreasing the amount of memory allocated to voltdb. No one seems to have this memory leak lookalike.
We have setup Cassandra single node of 3.11 with JDK 1.8 on ec2 with instance type t2.large which has 2 CPU and 7 GB of RAM.
We facing the issue that Cassandra keeps reaching CPU 100% even we do not have that much load.
We have 7GB of RAM but Cassandra not utilizing that Memory.it only uses 1.7-1.8 GB of RAM.
What configuration needs to change to reduce CPU utilization to not reach to 100%.
what best configuration to get better performance out of Cassandra.
Right now we able to get only about 100-120 read and 50-100 write operation per sec.
Please, some one helps us to understand the issue and what ways to improve performance configuration.
I deployed a Cassandra 2.2 ring composed by 4 nodes in the cloud with 8 vCPU and 8GB of ram. I am running some tests now with cassandra-stress and YCSB tools to test its performance. I am mainly interested in read requests with a small amount of write requests (95%/5%).
Running the experiments, I noticed that even setting a high number of threads (or clients) the CPU (and disk) does not saturate, but still always around the 60% of utilisation.
I am trying to figure out where is the bottleneck in my system. From the hardware point of view it seems all ok to me.
dstat
I also looked into the Cassandra configuration file to see if there are some tuning parameters to increase the system throughput. I increase the value of concurrent_read/write parameter, but it doesn't increase the performance.
The log file also does not contain any warning.
What it could be that is limiting my system?
Thanks
You might want to consider running cassandra-stress from outside the cluster and on multiple instances as described in
Usage of the Cassandra tool cassandra-stress
The following is the screenshot of htop on my dev server [arranged by MEM% used]:
I have only one cassandra instance running, but there are so many cassandra processes in htop, which is taking up 16 gb of ram.
The server is not being used in production, hence there are no queries being run on it at the moment.
I don't understand the reason why so many cassandra processes are running on my system, and how can I control this. Any suggestions will be highly appreciated.
Cassandra is a greedy process, It wont leave the RAM unless asked for.
You do not need to worry about the used RAM. If any other process will request for RAM, Cassandra process will leave the RAM.
Cassandra typically can take upto 16 GB RAM, which is the minimum prod recommendation from a performance point of view. Along with Cassandra there are a number of other processes which get the memory allocation like the JVM heap here. And as mentioned above it is a memory intensive technology.
I'm running Datastax Enterprise in a cluster consisting of 3 nodes. They are all running under the same hardware: 2 Core Intel Xeon 2.2 Ghz, 7 GB RAM, 4 TB Raid-0
This should be enough for running a cluster with a light load, storing less than 1 GB of data.
Most of the time, everything is just fine but it appears that sometimes the running tasks related to the Repair Service in OpsCenter sometimes get stuck; this causes an instability in that node and an increase in load.
However, if the node is restarted, the stuck tasks don't show up and the load is at normal levels again.
Because of the fact that we don't have much data in our cluster we're using the min_repair_time parameter defined in opscenterd.conf to delay the repair service so that it doesn't complete too often.
It really seems a little bit weird that the tasks that says that are marked as "Complete" and are showing a progress of 100% don't go away, and yes, we've waited hours for them to go away but they won't; the only way that we've found to solve this is to restart the nodes.
Edit:
Here's the output from nodetool compactionstats
Edit 2:
I'm running under Datastax Enterprise v. 4.6.0 with Cassandra v. 2.0.11.83
Edit 3:
This is output from dstat on a node that behaving normally
This is output from dstat on a node with stucked compaction
Edit 4:
Output from iostat on node with stucked compaction, see the high "iowait"
azure storage
Azure divides disk resources among storage accounts under an individual user account. There can be many storage accounts in an individual user account.
For the purposes of running DSE [or cassandra], it is important to note that a single storage account should not should not be shared between more than two nodes if DSE [or cassandra] is configured like the examples in the scripts in this document. This document configures each node to have 16 disks. Each disk has a limit of 500 IOPS. This yields 8000 IOPS when configured in RAID-0. So, two nodes will hit 16,000 IOPS and three would exceed the limit.
See details here
So, this has been an issue that have been under investigation for a long time now and we've found a solution, however, we aren't sure what the underlaying problem that were causing the issues were but we got a clue even tho that, nothing can be confirmed.
Basically what we did was setting up a RAID-0 also known as Striping consisting of four disks, each at 1 TB of size. We should have seen somewhere 4x one disks IOPS when using the Stripe, but we didn't, so something was clearly wrong with the setup of the RAID.
We used multiple utilities to confirm that the CPU were waiting for the IO to respond most of the time when we said to ourselves that the node was "stucked". Clearly something with the IO and most probably our RAID-setup was causing this. We tried a few differences within MDADM-settings etc, but didn't manage to solve the problems using the RAID-setup.
We started investigating Azure Premium Storage (which still is in preview). This enables attaching disks to VMs whose underlaying physical storage actually are SSDs. So we said, well, SSDs => more IOPS, so let us give this a try. We did not setup any RAID using the SSDs. We are only using one single SSD-disk per VM.
We've been running the Cluster for almost 3 days now and we've stress tested it a lot but haven't been able to reproduce the issues.
I guess we didn't came down to the real cause but the conclusion is that some of the following must have been the underlaying cause for our problems.
Too slow disks (writes > IOPS)
RAID was setup incorrectly which caused the disks to function non-normally
These two problems go hand-in-hand and most likely is that we basically just was setting up the disks in the wrong way. However, SSDs = more power to the people, so we will definitely continue using SSDs.
If someone experience the same problems that we had on Azure with RAID-0 on large disks, don't hesitate to add to here.
Part of the problem you have is that you do not have a lot of memory on those systems and it is likely that even with only 1GB of data per node, your nodes are experiencing GC pressure. Check in the system.log for errors and warnings as this will provide clues as to what is happening on your cluster.
The rollups_60 table in the OpsCenter schema contains the lowest (minute level) granularity time series data for all your Cassandra, OS, and DSE metrics. These metrics are collected regardless of whether you have built charts for them in your dashboard so that you can pick up historical views when needed. It may be that this table is outgrowing your small hardware.
You can try tuning OpsCenter to avoid this kind of issues. Here are some options for configuration in your opscenterd.conf file:
Adding keyspaces (for example the opsc keyspace) to your ignored_keyspaces setting
You can also decrease the TTL on this table by tuning the 1min_ttlsetting
Sources:
Opscenter Config DataStax docs
Metrics Config DataStax Docs