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| Title | Views | Posted |
|---|---|---|
| 2941 | 11-18-2022 09:06 AM | |
| 4154 | 11-15-2022 05:46 PM | |
| 2973 | 10-12-2022 03:18 AM | |
| 2134 | 10-11-2022 08:52 AM | |
| 5227 | 10-08-2022 08:23 AM |
12-29-2025
01:46 AM
So GET requests work fine for you but POSTs fail? Perhaps your user does not have write permissions? I recommend opening devtools and looking at the Network tab to see what requests get sent when you do certain operations (starting/stopping a process group) in the UI. You should be able to replicate them with the REST API if you can do them manually in the UI.
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12-29-2025
12:46 AM
Hello team & community 🙂 I am looking into deploying many instances of a flow that is versioned in a git registry via the REST API. My current issue is that I would like to configure each instance of this flow dynamically, though if I version the flow with a Parameter Context attached to it, whenever I deploy instances of it they all end up attaching to a single Parameter Context. I understand this is the expected behaviour as described in the documentation. Therefore, I'd like to know if there is any recommended practice for situations such as mine. The best solution I could think of was perhaps configuring the processors in the flow to use parameters but not to actually attach a PC to the process group. This way I could deploy flows in two steps by first importing them and then creating a new parameter context & configuring/attaching it. I would greatly appreciate any advice for this use-case, Thank you.
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Apache NiFi
09-20-2025
09:15 AM
If "Infer Schema" isn't working this is likely a bug. Could you provide an example JSON and the error message that happens during schema inference?
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07-31-2024
11:38 AM
@Green_ I had the same issue can you please share the detailed steps of how you resolved it? As I'm new to NiFi.
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09-21-2023
12:42 AM
I am also experiencing this issue when attempting to write data to a redis in cluser mode. Did you find a solution or workaround @sofronic ?
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12-12-2022
05:49 AM
Hello Eyal, thanks once again for your interest in helping out. I have not expressed myself correctly. I believe there is no backpressure, as I confirmed visually on the nifi UI. On the upper banner I see there are globally about 5000 flowfiles circulating at a particular time. I see some of the queues have 20, 50, 100, 200 flowfiles waiting at an instant. The queue that has more queued flow files is the kafka producer processor, that has about 2000. I believe these quantities are not sufficient to trigger backpressure-caused adjustment of scheduling of tasks. Apache Benchmark sends concurrent http requests. In this case, i set each of the 5 client instances to send each 1000 requests concurrently. I have thread pool sized to 96 and assigned 16 concurrent tasks to all of the critical path processors. Despite this, I get a low core load average (between 2 and 7), the disk's IOPS are in the dozens per second (the maximum that the disks allow is 3000). I'm all out of ideas at this point. 😄 Thanks for the support!
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12-09-2022
02:00 PM
@F_Amini @Green_ Is absolutely correct here. You should be careful when increasing concurrent tasks as just blindly increasing it everywhere can have the opposite effect on throughput. I recommend stopping setting the concurrent tasks back to 1 or maybe 2 on all the processor where you have adjusted away from the default of 1 concurrent task. Then take a look at the processor further downstream in your dataflow where it has a red input connection but black (no backpressure) outbound connections. This processor s @Green_ mentioned is the processor causing all your upstream backlog. Your'll want to monitor your CPU usage as you make small incremental adjustments to this processors concurrent tasks until you see the upstream backlog start to come down. If while monitoring CPU, you see it spike pretty consistently at 100% usage across all your cores, then your dataflow has pretty much reached the max throughput it can handle for yoru specific dataflow design. At this point you need to look at other options like setting up a NiFi cluster where this work load can be spread across multiple servers or designing your datafow differently with different processors to accomplish same use case that may have a lesser impact on CPU (not always a possibility). Thanks, Matt
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12-01-2022
02:33 AM
Hi, thanks for the details. Unfortunately it is not working. I get an empty array [] as output. I have tried it with extract and split mode. I applied the schema text property as suggested with "NestedKey" and "nestedValue" as name. None gives me an output. Meanwhile I have achieved what I wanted using SplitContent and then again another jolt processor. Of course it would be more elegant if I could make it work with ForkRecord.
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11-25-2022
07:43 AM
Hi @ripo , I've tried it out in my own environment and it does not seem like ports have an 'ENABLED' state. If a port is DISABLED, you can only update it to be STOPPED. from a STOPPED state, you can either switch the port to RUNNING or back to DISABLED.
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11-22-2022
09:43 PM
@Green_ Thank you so much ! It worked as expected.
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