RouteOnAttribute based on list - apache-nifi

In my NiFi pipeline I have some flow files that ran into an issue with a Python script running on the ExecuteStreamCommand processor. When they fail, they come out as 0 byte flow files so I can't look and see what might be causing the issue nor how to fix it. Luckily, the flow file is not just gone forever: it exists in S3 with about 60 million other files. However, I do not want to mass re-pull from S3 and have to manually comb through to find each file that filed.
Instead, what I've concocted is that I can pull a specific id that's in the attributes of the failed, empty flow files and throw it into a list thanks to AttributetoJSON. What I would like to do is then re-pull from S3 and run those through a RouteOnAttribute processor that will keep flow files whose id appears in the list, and then discard those that don't. However, I'm not seeing a clear way to use the list in my RouteOnAttribute processor. Is there a way to do something like ${nameid} in [123, 345, 567, 789]?

There is in function that exactly match with your case. Check the documentation.
${nameid:in(123,345,567,789)}

Related

Need to use 1 Processor instead of 5 FetchHDFS in NiFi

I have 5 XML files in HDFS which I am fetching using Apache this is the flow nifi. First, I am using Generate Flow file processor and then I have to use 5 different FetchHdfs processors. I can't use GetHdfs because it deletes all the file from directory and I don't have permission to ingest the files back. Hence, I am searching for a way that instead of using 5 FetchHdfs, what else can I do?. All the files are in the same directory and I want to keep them so that I can test multiple times.
I am ingesting those files in TransformXML processor and converting them to JSON
Instead of the GetHDFS Processor, try the ListHDFS Processor as it lists the entire directory and doesn't delete the files ListHDFS It says in the description, "Unlike GetHDFS, this Processor does not delete any data from HDFS."
Thanks everyone for answering. I am unable to vote anyone's answer and hence I am writing what I did.
First I used the ListHDFS processor and it will list out all the filenames.
Then I used FetchHDFS and in HDFS filename, I put '${path}/${filename}'.
change the ${path} to your path of the directory and leave the ${filename} as is as this is a property of ListHDFS and that's where it is picking the filenames from.
This way, there is no need of loops or anything and as soon as the new file is uploaded in the directory, it will be picked by the ListHDFS processors.
So, leave the entire processes working.

How to implement the equivalent of the Aggregator EIP in Nifi

I'm very experienced with Apache Camel and EIPs and am struggling to understand how to implement equivalents in Nifi. I understand that Nifi uses a different paradigm (flow based programming) but I don't think what I'm trying to do is unreasonable.
In a nutshell I want the contents of each file to be sent to many rest services and I want to aggregate the responses into a single document which will stored in elasticsearch. I might also do some further processing and cleanup to improve what is stored (but this isn't my immediate issue)
The screenshot is a quick mock-up of what I'm trying to achieve but I don't understand enough about Nifi to know how to implement this pattern correctly.
If you are going to take a single piece of data and then fork to multiple parts of the flow and then converge back, there needs to be a way for MergeContent to know which pieces go together.
There are generally two ways this can be done...
The first is using MergeContent in "defragment mode". Think of this as reversing a split operation that was performed by one of the split processors like SplitText. For example, you split a file of 100 lines into 100 flow files of 1 line each, then do some stuff to each one, then want to converge back. The split processors produce a standard set of split attributes (described in the docs of the processors) and the defragment mode knows how to bin the splits accordingly and merge them back together. This probably doesn't apply to your example since you didn't start with a split processor.
The second approach is the "Correlation Attribute" in MergeConent. This tells merge content to only merge flow files together that have the same value for the attribute specified. In your example, when a file gets picked up by GetFile and sent to 3 InvokeHttp processors, there are 3 flow files created, and they all should have their "filename" attribute set to the name of the file picked up from disk. So telling MergeContent to correlate on filename should do the trick, and probably setting the min and max number of entries to the number you expect like 3, and a maximum time in case one of them fails or hangs.

NiFi: ListFile Processor is not detecting file changes sometimes

ListFile processor is not detecting any changes to a previously processed file and reprocess it. FYI, I have tried the following options already for reprocessing and only the finally mentioned hack is working. This is in a single-node NiFi I am running in my development environment.
Update Scenario: ListFile processor is not detecting file content changes and trigger automatically post-update (i.e file updates using VIM editor)
Timestamp modification Scenario: Changing the file timestamp with touch -c command changes the file timestamp but this does not cause auto-trigger of the ListFile processor either.
Stop-start Scenario: Stop-start of the whole process group in NiFi after changing the file as mentioned above also does not cause triggering of ListFile processor.
Waiting Clause: Waiting for long enough after file change also does not help - just in case we assume it will auto-trigger after some delay.
HACK: The only way I am able to trigger the re-processing of the file by ListFile processor is by changing the wildcard expression for "File Filter" in ListFile processor in a harmless, idempotent manner, for example from .*test.*\.csv to test.*\.csv and vice versa later (i.e go back and forth like this for repeated reprocessing).
Reprocessing of files with same old names and with modified data is a requirement for us. Please help!
And sometimes forced reprocessing of even an unmodified file could be required in case of unanticipated data issues upstream/downstream. Please help!
UPDATE
Still facing this sporadic behavior! Only restart of NiFi helps when the ListFile processor fails to respond to file change.
Probably this is delayed answer.
The old List processors like ListFiles/ListFtp/ListSftp etc. used only timestamp tracking strategy to identify the changed files. The processor used to cache last seen timestamp in its processor state and use it to list files with only greater timestamp.
However, this approach was very buggy. Hence they had to come up with much better strategy which is called Entity Tracking. This approach gives broad
range of monitoring on file changes. It keeps track of below parameters of each file in the specified directory.
Name
Size
Last modified timestamp
Any change in file is reflected in these key parameters. Since they are cached, any difference is treated as change, thus changed files appear in the success connection.

Apache Nifi MergeContent output data inconsistent?

Fairly new to using nifi. Need help with the design.
I am trying to create a simple flow with dummy csv files(for now) in HDFS dir and prepend some text data to each record in each flowfile.
Incoming files:
dummy1.csv
dummy2.csv
dummy3.csv
contents:
"Eldon Base for stackable storage shelf, platinum",Muhammed MacIntyre,3,-213.25,38.94,35,Nunavut,Storage & Organization,0.8
"1.7 Cubic Foot Compact ""Cube"" Office Refrigerators",BarryFrench,293,457.81,208.16,68.02,Nunavut,Appliances,0.58
"Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl",Barry French,293,46.71,8.69,2.99,Nunavut,Binders and Binder Accessories,0.39
...
Desired output:
d17a3259-0718-4c7b-bee8-924266aebcc7,Mon Jun 04 16:36:56 EDT 2018,Fellowes Recycled Storage Drawers,Allen Rosenblatt,11137,395.12,111.03,8.64,Northwest Territories,Storage & Organization,0.78
25f17667-9216-4f1d-b69c-23403cd13464,Mon Jun 04 16:36:56 EDT 2018,Satellite Sectional Post Binders,Barry Weirich,11202,79.59,43.41,2.99,Northwest Territories,Binders and Binder Accessories,0.39
ce0b569f-5d93-4a54-b55e-09c18705f973,Mon Jun 04 16:36:56 EDT 2018,Deflect-o DuraMat Antistatic Studded Beveled Mat for Medium Pile Carpeting,Doug Bickford,11456,399.37,105.34,24.49,Northwest Territories,Office Furnishings,0.61
the flow
splitText-
ReplaceText-
MergeContent-
(this may be a poor way to achieve what I am trying to get, but I saw somewhere that uuid is best bet when it comes to generating unique session id. So thought of extracting each line from incoming data to flowfile and generating uuid)
But somehow, as you can see the order of data is messing up. The first 3 rows are not the same in output. However, the test data I am using (50000 entries) seems to have the data in some other line. Multiple tests show usually the data order changes after 2001st line.
And yes, I did search similar issues here and tried using defragment method in merge but it didnt work. I would appreciate if someone can explain what is happening here and how can I get the data in the same way with unique session_id,timestamp for each record. Is there some parameter I need to change or modify to get the correct output? I am open to suggestions if there is a better way as well.
First of all thank you for such an elaborate and detailed response. I think you cleared a lot of doubts I had as to how the processor works!
The ordering of the merge is only guaranteed in defragment mode because it will put the flow files in order according to their fragment index. I'm not sure why that wouldn't be working, but if you could create a template of a flow with sample data that showed the problem it would be helpful to debug.
I will try to replicate this method using a clean template again. Could be some parameter problem and the HDFS writer not able to write.
I'm not sure if the intent of your flow is to just re-merge the original CSV that was split, or to merge together several different CSVs. Defragment mode will only re-merge the original CSV, so if ListHDFS picked up 10 CSVs, after splitting and re-merging, you should again have 10 CSVs.
Yes, that is exactly what I need. Split and join data to their corresponding files. I dont specifically (yet) need to join the outputs again.
The approach of splitting a CSV down to 1 line per flow file to manipulate each line is a common approach, however it won't perform very well if you have many large CSV files. A more efficient approach would be to try and manipulate the data in place without splitting. This can generally be done with the record-oriented processors.
I used this approach purely instinctively and did not realize this is a common method. Sometimes the datafile could be very large, that means more than a million records in a single file. Wont that be an issue with the i/o in the cluster? coz that would mean each record=one flowfile=one unique uuid. What is a comfortable number of flowfiles that nifi can handle? (i know it depends on cluster config and will try to get more info about the cluster from hdp admin)
What do you suggest by "try and manipulate the data in place without splitting" ? can you give an example or template or processor to use?
In this case you would need to define a schema for your CSV which included all the columns in your data, plus the session id and timestamp. Then using an UpdateRecord processor you would use record path expressions like /session_id = ${UUID()} and /timestamp = ${now()}. This would stream the content line by line and update each record and write it back out, keeping it all as one flow file.
This looks promising. Can you share a simple template pulling files from hdfs>processing>write hdfs files but without splitting?
I am reluctant to share the template due to restrictions. But let me see if I can create a generic templ and I will share
Thank you for your wisdom! :)

Nifi: how to avoid copying file that are partially written

I am trying to use Nifi to get a file from SFTP server. Potentially the file can be big , so my question is how to avoid getting the file while it is being written. I am planning to use ListSFTP+FetchSFTP but also okay with GetSFTP if it can avoid copying partially written files.
thank you
In addition to Andy's solid answer you can also be a bit more flexible by using the ListSFTP/FetchSFTP processor pair by doing some metadata based routing.
After ListSFTP each flowfile will have attributes such as 'file.lastModifiedTime' and others. You can read about them here https://nifi.apache.org/docs/nifi-docs/components/org.apache.nifi/nifi-standard-nar/1.3.0/org.apache.nifi.processors.standard.ListSFTP/index.html
You can put a RouteOnAttribute process in between the List and Fetch to detect objects that at least based on the reported last modified time are 'too new'. You could route those to a processor that is just a slow pass through to intentionally wait a bit. You can then run those back through the first router until they are 'old enough'. Now, this is admittedly a power user approach but it does give you a lot of flexibility and control. The approach I'm mentioning here is not fool proof as the source system may not report the last mod time correctly, it may not mean the source file is doing being written, etc.. But it gives you additional options IF you cannot do the definitely correct thing above that Andy talks about.
If you have control over the process which writes the file in, a common pattern to solve this is to initially write the file with a specific naming structure, such as beginning with .. After the successful write operation, the file is renamed without the . and it is picked up by the processor. Both GetSFTP and ListSFTP have a processor property called Ignore Dotted Files which is set to true by default and means those processors will not operate on or return files beginning with the dot character.
There is a minimum file age property you can use. The last modification time gets updated as the file is being written. Setting this value to something other than 0 will help fix the problem:

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