Short Description: A NiFi connection is where FlowFiles are temporarily held between two connected NiFi Processor components. Each connection that contains queued NiFi FlowFiles will have a footprint in the JVM heap. This article will breakdown a connection to show how NiFi manages the FlowFiles that are queued in that connection and that affects heap and performance. Article: First let me share the 10,000 foot view and then I will discuss each aspect of the following image: *** NiFi FlowFiles consist of FlowFile Content and FlowFile Attributes/metadata. FlowFile content is never held in a connections heap space. Only the FlowFile Attributes/metadata is placed in heap by a connection. The "Connection Queue": The connection queue is where all FlowFiles queued in the connection are held. To understand how these queued FlowFiles affect performance and heap usage, lets start by focusing on the "Connection Queue" dissection at the bottom of the above image. The overall size of a connection is controlled by the configured "back Pressure Object Threshold" and "Back Pressure Data Size threshold" settings the user defines per connection. Back Pressure Object Threshold and Back Pressure Data Size Threshold: The "Back Pressure Object Threshold" default setting here is 10000. The "Back Pressure Data Size Threshold" defaults to 1 GB. Both of these settings are soft limits. This means that they can be exceeded. As an example, lets assume default settings above and a connection that already contains 9,500 FlowFiles. Since the connection has not reached or exceeded object threshold yet, the processor feeding that connection will be allowed to run. If that feeding processor should produce 2,000 FlowFiles when it executes, the connection would grow to 11,500 queued FlowFiles. The preceding processor would then not be allowed to execute until the queue dropped below the configured threshold once again. The same hold true for the Data Size threshold. Data Size is based on the cumulative reported size of the content associated to each queued FlowFile. Now that we know how the overall size of "connection queue" is controlled, lets break it down it to its parts: 1. ACTIVE queue: FlowFiles enter a connection will initially begin to placed in the active queue. FlowFiles will continue to placed in to this queue until that queue has reached the global configured nifi swap threshold. All FlowFiles in the active queue are held in heap memory. The processor consuming Flowfiles from this connection will always pull FlowFiles from the active queue. The size of the active queue per connection is controlled by the following property in the nifi.properties file: nifi.queue.swap.threshold=20000 Increasing the swap threshold increase the potential heap footprint of every single connection in your dataflow(s). 2. SWAP queue: Based on above default setting, once a connection reaches 20,000 FlowFiles, new FlowFiles entering the connection are placed in the swap queue. The swap queue is also held in heap and is hard coded to 10,000 FlowFiles max. If space is freed in the active queue and no swap files exist, FlowFiles in the swap queue will be moved directly to the active queue. 3. SWAP FILES: Each time the swap queue reaches 10,000 FlowFiles, a swap file is written to disk that contains those FlowFiles. At that point new FlowFiles are again written to the swap queue. Many Swap files can be created. Using image above where connection contains 80,000 FlowFiles, there would be 30,000 FlowFiles in heap and 5 swap files. As the active queue has freed 10,000 FlowFiles, the oldest swap file are moved to the active queue until all swap files are gone. The fact that swap files must be written to and read from disk, having a lot of swap files being produced across your dataflow will affect throughput performance of your dataflow(s). 4. IN-FLIGHT queue: Unlike the above 3, the in-flight queue only exists when the processor consuming from this connection is running. The consuming processor will only pull FlowFiles from the active queue and place them in the in-flight queue until processing has successfully completed and those FlowFiles have been committed to an outbound connection from the consuming processor. This in-flight queue is also held in heap. Some processors work on 1 FlowFile at a time, others work on batches of FlowFile, and some have the potential of working on every single FlowFile on an incoming connection queue. In the last case, this could mean high heap usage while those FlowFiles are being processed. The example above is one of those potential case using the MergeContent processor. The MergeContent processor places FlowFiles from the active queue in virtual bins. How many bins an what makes a bin eligible for merge is governed buy the processor configuration. What is important to understand that is is possible that every FlowFile in the connection could make its way into the "in-flight queue". In image example, if the MergeContent were running, all 80,000 queued Flowfiles would likely be pulled in to heap via the in-flight queue. ---- Take away from this article: 1. Control heap usage by limiting size of connection queue when possible. (Of course if your intention is to merge 40,000 FlowFiles, there must be 40,000 Flowfiles in the incoming connection. However, you could have two mergeContent processors in series each merging smaller bundles with same end result with less overall heap usage.) 2. With default back pressure object threshold settings, there will be no swap files produced on most connections (remember soft limits) which will result in better throughput performance. 3. The default configured swap threshold of 20,000 is a good balance in most cases of active queue size and performance. For smaller flows you may be able to push this higher and for extremely large flows you may want to set this lower. Just understand it is a trade-off of heap usage for performance. But if your run out of heap, there will be zero performance. Thank you, Matt ... View more

Short Description: This article covers how to improve the performance of the NiFi UI. Article: Over time it has been seen that the users of NiFi have been building very large dataflows consisting of many thousands of components (processor, reporting tasks, controller services, etc). While NiFi in no way limits to any degree the number of components that can be added to the NiFi canvas, the more components a user adds, the less responsive the UI becomes. This processor explosion not only affects the responsiveness of the UI, but can also lead to unexpected node disconnections. --- What are the various states a component can have? NiFi components have multiple states that consist of stopped, started, enabled, and disabled. Beyond these states exists one of two statuses: Valid: Component configuration was successfully validated. This means that all required properties have been configured and in the case of processors all required connections have been accounted for (connected to another component or terminated) and any referenced controller services have been enabled. Invalid: Component configuration is not valid. This means that one or more required properties have not been configured and/or in the case of processors one or more connections have not been accounted for (connected to another component or terminated) and/or a referenced controller services have not been enabled. --- Why does a processors state affect UI performance? All processor components when added to the canvas are added in the "stopped" state. A user can then either start or disable that component manually. All Controller Services and Reporting tasks added by a user are by default disabled. The user can then enable these components as needed. NiFi regularly must validate these components to see if they are valid or invalid. While the validation of a few hundred to a thousand components adds up to very little time, the same does not hold true for NiFi instances consisting of thousands upon thousands of components. User may have noticed a swirling on the right hand side of the NiFi status bar that seems to never go away. In a NiFi cluster, NiFi must retrieve the flow status from every node. It is possible for a component to be valid on one node but not another (for example, processor depends on local file that does not exist on all nodes). If this validation takes too long a node may be disconnected because the request took to long. Not to mention the UI does not update until these validations have completed. --- What has NiFi done to make improvements here? The bad news: Prior to NiFi 1.1.0 there is nothing that can be done to improve performance here other then reducing the number of components you are using. This is because in versions of NiFi prior to components were validated in all four states. The good news: In NiFi 1.1.0 a change was made so that this validation only occurs on components that are in the "stopped" state and controller services or reporting tasks that are disabled. It is safe to assume that if a processor is running, it must be valid. It is also safe to assume that a Controller Service or a Reporting Task must be valid if it is enabled. Now that these "started" processors and "enabled" controller services or reporting tasks are no longer being validated, the UI performance will be much better. https://issues.apache.org/jira/browse/NIFI-2996 --- What is the important to understand here? It has also been observed that users add lots of components to the UI that are never started or are only started for short periods of time. If the number of "Stopped" processors is very high, validation is still going to take a considerable amount of time even in NiFi 1.10 or newer versions. A quick look at the NiFi status bar above your canvas will show how many stopped components you have on your canvas: To make sure the UI performance remains solid, it is important that users disable processors that are not in use on the canvas. You can use the "NiFi Summary" UI to to find stopped/invalid processors and disable them. Select the "PROCESSORS" tab and sort on the "Run Status" column. Clicking on the on the right hand side of row will take you directly to that processor. Once a component is selected on the canvas it can be disabled or enabled via the "Operate" panel or by right clicking on processor and selecting Disable or Enable for displayed context menu. ... View more