Otto, I am not currently proposing that there be a unified flow comparison capability - or that there not be one. I think that's more of an implementation detail. I do believe there's a good chance that we can map a FlowSnippetDTO into a VersionedProcessGroup object, in which case we could use the same mechanism (VersionedFlowComparator) for performing the comparisons. This would be nice because it's much easier to maintain and gives us a great API for knowing exactly what changed (if anything) with each component. The devil's in the details, though, so I would not suggest that we can definitely use that but that would certainly be the goal, yes.
On Jun 7, 2018, at 10:14 AM, Otto Fowler <ottobackwa...@gmail.com<mailto:ottobackwa...@gmail.com>> wrote: Great write up. While I am not an expert on clustering, it would seem that having one method of comparing flows, perhaps with different strategies within that would be more maintainable as well. Are you proposing that there is a unified flow comparison capability/implementation/service that is shared between clustering and versioned use cases? On June 7, 2018 at 09:46:27, Mark Payne (marka...@hotmail.com<mailto:marka...@hotmail.com>) wrote: Hi all, Over the past couple of months, I have been doing a lot of testing with large scale flows and talking to others who are using large scale flows in production. ("Large scale" flows in this case means several thousand to tens of thousands of Processors). While NiFi does a really good job of handling the data flow, one area that needs some improvement is around NiFi's clustering. So for the 1.7.0 version of NiFi, we have spent quite a bit of time focusing improving the clustering mechanism to hold up to more demanding flows. The focus really can be broken down into three focus areas: UI sluggishness [1] [2] [3], Cluster Stability [4] [2] [5] [3], and User Experience [5] [6] [7] (note that many of these JIRA's are listed under more than 1 category.) With the above-mentioned JIRA's, I think we have significantly improved the stability and user experience around clustering. Local testing shows that in some cases, requests that previously took 15+ seconds (such as instantiating a template with several thousand processors) now take around 1 second. This provides a better user experience and also improves our cluster stability because it prevents nodes from dropping out the cluster due to timeouts. There is, however, another important area that I believe is ripe for improvement in our current model. That is the mechanism used when a node joins a cluster, in order to determine if the cluster's flow can be inherited by the node. While the above work will improve stability considerably, we need to be very mindful that failures will still occur. And we need to be good at recovering from those. The way that we do this currently is that we download the flow from the cluster, and then we "fingerprint" the flow. We then "fingerprint" our own flow and see if they match. What we mean by fingerprinting is that we go through the flow and pick out which elements should make a flow uninheritable and concatenate all of those together into one long String. The original purpose of this was to ensure that we don't lose any data when we join a node back to a cluster. When this was developed, though, we took a very strict approach of enforcing that the node's flow must match the cluster's flow - with only a few exceptions. For example, the position of a processor on the graph could be different; we simply inherit the cluster's value. The run status of a processor can be different; we simply inherit the cluster's value. This fingerprinting approach has its benefit - it forces the user to be mindful of any differences between the node and cluster. However, it has several downsides as well. If a node fails to perform some update, it cannot join back to the cluster until the discrepancy is addressed. Additionally, it is difficult to understand just what the discrepancy is because the best info that we can provide is a segment of the fingerprint where the flows differ, and this is not very clear. It's also difficult to understand exactly which flow differences are relevant and which are not. The class that performs the fingerprinting is rather complex, and updates are rather error-prone because it is easy to forget to update the fingerprint when a new "feature" is added to a component. Worse still is that if a component gains a "collection" of objects, it is easy to forget to sort that collection, which results in incorrect fingerprinting that prevents a node from joining a cluster when it should be able to. Most importantly, though, the current approach requires manual user intervention when the flow differs, and almost always the solution that is suggested/used is to shut down the node, remove the flow.xml.gz, the users.xml, and authorizations.xml, and then restart. This will cause the node to inherit the cluster's flow. Clearly, this isn't ideal. I'd like to propose a far simpler approach to determining flow inheritability. Because the main goal of checking inheritability was to ensure that there is no data loss, I would propose that we use the same mechanism for inheriting a cluster flow as we do for updating to a new version of a Versioned Flow. We would first determine which connections would be removed from the flow if we inherit the cluster's flow. If there are no connections removed, then the flow is inheritable. If there are any connections removed, we will stop each removed connection's source and destination. We will then check if any connection has any queued data. If so, then we will restart all components that we started and fail. This is critical because the only way we can lose data when inheriting a flow is if we remove a connection with data queued. Otherwise, we determine that inheriting the flow will not cause data loss and therefore the flow is inheritable. This approach will still ensure that we have no data loss. It also results in a more resilient recovery that requires no human intervention (unless inheriting the flow would cause data loss - in that case, I believe human intervention is still warranted. But we will be able to inform the user of which connection(s) have data and would be removed so that they can address the concern.) Another added benefit of this approach is that it would allow automation tools to provision a node NiFi node with a "seed flow" and if it joins a cluster with a flow, it will simply inherit the cluster's flow instead of using the seed flow. Currently, in order to do this, the automation tools would have to determine if a cluster already exists and if so not provide the seeded flow. I think this may be more important as users start running more and more on Kubernetes. While I believe 1.7.0 will provide some great benefits to our clustering model, I do think that we can do better with respect to determining flow inheritance. The proposed inheritance model provides a mechanism that results in a user experience that more closely aligns with user expectations in my opinion. It would result in NiFi being more stable and reliable. However, it is a large enough departure from how we have been doing things to-date that I thought it appropriate to start a DISCUSS thread to ensure that everyone is on the same page first. Any thoughts? Thanks -Mark [1] NIFI-5241 [2] NIFI-950 [3] NIFI-5112 [4] NIFI-5204 [5] NIFI-5208 [6] NIFI-5186 [7] NIFI-5153
