[Question posted by a user on YugabyteDB Community Slack]
We have created a universe with 5 data nodes(airgap installed) and 3 as the replication factor. Now we are planning to increase the disk size in all 5 nodes and increase the mount point space as well which is in use without any db downtime...can anyone please suggest the steps
Ideally, you should add new nodes with bigger disks to the cluster rather then changing disk size of the node.
You could just stop the processes, do the upgrade, bring back the processes, and wait for data movement (if any) to finish.
For a safer approach, you can make it safer by blacklisting the node (tserver and master) first to drain the node of tablet leaders.
You can refer to some commands for this here.
https://docs.yugabyte.com/preview/manage/change-cluster-config/
Related
I am using Datastax Cassandra 4.8.16. With cluster of 8 DC and 5 nodes on each DC on VM's. For last couple of weeks we observed below performance issue
1) Increase drop count on VM's.
2) LOCAL_QUORUM for some write operation not achieved.
3) Frequent Compaction of OpsCenter.rollup_state and system.hints are visible in Opscenter.
Appreciate any help finding the root cause for this.
Presence of dropped mutations means that cluster is heavily overloaded. It could be increase of the main load, so it + load from OpsCenter, overloaded system - you need to look into statistics about number of requests, latencies, etc. per nodes and per tables, to see where increase happened. Please also check the I/O statistics on machines (for example, with iostat) - sizes of the queues, read/write latencies, etc.
Also it's recommended to use a dedicated OpsCenter cluster to store metrics - it could be smaller size, and doesn't require an additional license for DSE. How it said in the OpsCenter's documentation:
Important: In production environments, DataStax strongly recommends storing data in a separate DataStax Enterprise cluster.
Regarding VMs - usually it's not really recommended setup, but heavily depends on what kind of underlying hardware - number of CPUs, RAM, disk system.
Let's imagine I have a Cassandra cluster with 3 nodes, each having 100GB of available hard disk space. Replication Factor for this cluster is set to 3 and R/W CLs are set to 2, meaning I can tolerate one of my nodes going down without sacrificing consistency or availability.
Now imagine my servers have started to fill up (80GB as an example) and I would like to add another 3 servers of the same specification to my cluster, maintaining the same CLs and RFs.
My question is: after I've added the new nodes to my cluster and run the node repair tool, is it fair to assume that each of my nodes should roughly (more or less a few GBs) contain 40GB of data each?
If not, how can I add new nodes without having the fear of running out of hard disk space?
A little background of why I'm asking this question: I am developing an app that connects to a server that runs Cassandra for its data storage. As this is only developed by me, and I have limited resources in terms of money to buy servers, I've decided that I would like to buy small, cheap "servers" instead of the more expensive rack options but I'm really worried about the nodes running out of space if the disk allocation is not (at least partially)
homogenous.
Many thanks for you help,
My question is: after I've added the new nodes to my cluster and run
the node repair tool, is it fair to assume that each of my nodes
should roughly (more or less a few GBs) 40GB of data each
After also running nodetool cleanup you should see roughly 40GB of data on each node. Cleanup removes data which the node is no longer responsible for. If you don't run this command the old data will remain on the machine.
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
I have a 4 node cluster and I have upgraded all the nodes from an older version to Cassandra 1.2.8. Total data present in the cluster is of size 8 GB. Now I need to enable vNodes on all the 4 nodes of cluster without any downtime. How can I do that?
As Nikhil said, you need to increase num_tokens and restart each node. This can be done one at once with no down time.
However, increasing num_tokens doesn't cause any data to redistribute so you're not really using vnodes. You have to redistribute it manually via shuffle (explained in the link Lyuben posted, which often leads to problems), by decommissioning each node and bootstrapping back (which will temporarily leave your cluster extremely unbalanced with one node owning all the data), or by duplicating your hardware temporarily just like creating a new data center. The latter is the only reliable method I know of but it does require extra hardware.
In the conf/cassandra.yaml you will need to comment out the initial_token parameter, and enable the num_tokens parameter (by default 256 I believe). Do this for each node. Then you will have to restart the cassandra service on each node. And wait for the data to get redistributed throughout the cluster. 8 GB should not take too much time (provided your nodes are all in the same cluster), and read requests will still be functional, though you might see degraded performance until the redistribution of data is complete.
EDIT: Here is a potential strategy to migrate your data:
Decommission two nodes of the cluster. The token-space should get distributed 50-50 between the other two nodes.
On the two decommissioned nodes, remove the existing data, and restart the Cassandra daemon with a different cluster name and with the num_token parameters enabled.
Migrate the 8 GB of data from the old cluster to the new cluster. You could write a quick script in python to achieve this. Since the volume of data is small enough, this should not take too much time.
Once the data is migrated in the new cluster, decommission the two old nodes from the old cluster. Remove the data and restart Cassandra on them, with the new cluster name and the num_tokens parameter. They will bootstrap and data will be streamed from the two existing nodes in the new cluster. Preferably, only bootstrap one node at a time.
With these steps, you should never face a situation where your service is completely down. You will be running with reduced capacity for some time, but again since 8GB is not a large volume of data you might be able to achieve this quickly enough.
TL;DR;
No you need to restart servers once the config has been edited
The problem is that enabling vnodes means a lot of the data is redistributed randomly (the docs say in a vein similar to the classic ‘nodetool move’
So there is a fair amount of documentation on how to scale up a Cassandra, but is there a good resource on how to "unscale" Cassandra and remove nodes from the cluster? Is it as simple as turning off a node, letting the cluster sync up again, and repeating?
The reason is for a site that expects high spikes of traffic, climbing from the daily few thousand hits to hundreds of thousands over a few days. The site will be "ramped up" before hand, starting up multiple instances of the web server, Cassandra, etc. After the torrent of requests subsides, the goal is to turn off the instances that are not longer used, rather than pay for servers that are just sitting around.
If you just shut the nodes down and rebalance cluster, you risk losing some data, that exist only on removed nodes and hasn't replicated yet.
Safe cluster shrink can be easily done with nodetool. At first, run:
nodetool drain
... on the node removed, to stop accepting writes and flush memtables, then:
nodetool decommission
To move node's data to other nodes, and then shut the node down, and run on some other node:
nodetool removetoken
... to remove the node from the cluster completely. The detailed documentation might be found here: http://wiki.apache.org/cassandra/NodeTool
From my experience, I'd recommend to remove nodes one-by-one, not in batches. It takes more time, but much more safe in case of network outages or hardware failures.
When you remove nodes you may have to re-balance the cluster, moving some nodes to a new token. In a planed downscale, you need to:
1 - minimize the number of moves.
2 - if you have to move a node, minimize the amount of transfered data.
There's an article about cluster balancing that may be helpful:
Balancing Your Cassandra Cluster
Also, the begining of this video is about add node and remove node operations and best strategies to minimize the cluster impact in each of these operations.
Hopefully, these 2 references will give you enough information to plan your downscale.
First, on the node, which will be removed, flush memory (memtable) to SSTables on disk:
-nodetool flush
Second, run command to leave a cluster:
-nodetool decommission
This command will assign ranges that the node was responsible for to other nodes and replicates the data appropriately.
To monitor a process you can use command:
- nodetool netstats
Found an article on how to remove nodes from Cassandra. It was helpful for me scaling down cassandra.All actions are described step-by-step there.