InfluxDB Enterprise cluster features
A valid license key is required in order to start
License keys restrict the number of data nodes that can be added to a cluster as well as the number of CPU cores a data node can use.
Without a valid license, the process will abort startup.
Query management works cluster wide. Specifically,
SHOW QUERIES and
KILL QUERY <ID> on
"<host>" can be run on any data node.
SHOW QUERIES will report all queries running across the cluster and the node which is running the query.
KILL QUERY can abort queries running on the local node or any other remote data node. For details on using the
SHOW QUERIES and
KILL QUERY on InfluxDB Enterprise clusters,
see Query Management.
Subscriptions used by Kapacitor work in a cluster. Writes to any node will be forwarded to subscribers across all supported subscription protocols.
Configuration and operational considerations on a cluster
It is important to understand how to configure InfluxDB Enterprise and how this impacts the continuous queries (CQ) engine’s behavior:
- Data node configuration
[continuous queries]run-interval – The interval at which InfluxDB checks to see if a CQ needs to run. Set this option to the lowest interval at which your CQs run. For example, if your most frequent CQ runs every minute, set run-interval to 1m.
- Meta node configuration
[meta]lease-duration – The default duration of the leases that data nodes acquire from the meta nodes. Leases automatically expire after the lease-duration is met. Leases ensure that only one data node is running something at a given time. For example, Continuous Queries use a lease so that all data nodes aren’t running the same CQs at once.
- Execution time of CQs – CQs are sequentially executed. Depending on the amount of work that they need to accomplish in order to complete, the configuration parameters mentioned above can have an impact on the observed behavior of CQs.
The CQ service is running on every node, but only a single node is granted exclusive access to execute CQs at any one time.
However, every time the
run-interval elapses (and assuming a node isn’t currently executing CQs), a node attempts to
acquire the CQ lease. By default the
run-interval is one second – so the data nodes are aggressively checking to see
if they can acquire the lease. On clusters where all CQs execute in an amount of time less than
(default is 1m), there’s a good chance that the first data node to acquire the lease will still hold the lease when
run-interval elapses. Other nodes will be denied the lease and when the node holding the lease requests it again,
the lease is renewed with the expiration extended to
lease-duration. So in a typical situation, we observe that a
single data node acquires the CQ lease and holds on to it. It effectively becomes the executor of CQs until it is
recycled (for any reason).
Now consider the the following case, CQs take longer to execute than the
lease-duration, so when the lease expires,
~1 second later another data node requests and is granted the lease. The original holder of the lease is busily working
on sequentially executing the list of CQs it was originally handed and the data node now holding the lease begins
executing CQs from the top of the list.
Based on this scenario, it may appear that CQs are “executing in parallel” because multiple data nodes are essentially “rolling” sequentially through the registered CQs and the lease is rolling from node to node. The “long pole” here is effectively your most complex CQ – and it likely means that at some point all nodes are attempting to execute that same complex CQ (and likely competing for resources as they overwrite points generated by that query on each node that is executing it — likely with some phased offset).
To avoid this behavior, and this is desirable because it reduces the overall load on your cluster, you should set the lease-duration to a value greater than the aggregate execution time for ALL the CQs that you are running.
Based on the current way in which CQs are configured to execute, the way to address parallelism is by using Kapacitor for the more complex CQs that you are attempting to run. See Kapacitor as a continuous query engine. However, you can keep the more simplistic and highly performant CQs within the database – but ensure that the lease duration is greater than their aggregate execution time to ensure that “extra” load is not being unnecessarily introduced on your cluster.
Meta nodes expose the
/debug/pprof endpoints for profiling and troubleshooting.
- Copy Shard support - copy a shard from one node to another
- Copy Shard Status - query the status of a copy shard request
- Kill Copy Shard - kill a running shard copy
- Remove Shard - remove a shard from a node (this deletes data)
- Truncate Shards - truncate all active shard groups and start new shards immediately (This is useful when adding nodes or changing replication factors.)
This functionality is exposed via an API on the meta service and through
Importing a OSS single server as the first data node is supported.
See OSS to cluster migration for step-by-step instructions.
The query engine skips failed nodes that hold a shard needed for queries. If there is a replica on another node, it will retry on that node.
Backup and restore
InfluxDB Enterprise clusters support backup and restore functionality starting with version 0.7.1. See Backup and restore for more information.
Support and feedback
Thank you for being part of our community! We welcome and encourage your feedback and bug reports for InfluxDB and this documentation. To find support, the following resources are available:
InfluxDB Cloud and InfluxDB Enterprise customers can contact InfluxData Support.