Hi Richard, 

it's not related, but for the logical types timestamp-millis you should use a 
"long" instead of a "string" (cf 
https://avro.apache.org/docs/1.11.1/specification/#timestamp-millisecond-precision)
 afaik.

Best, Lars

On 21 December 2022 08:29:54 CET, Richard Beare <[email protected]> wrote:
>I have found a way to force the schema to be used, but I've missed
>something in my configuration. When I use a default generic avro writer in
>my jolttransformrecord processor the queue of 259 entries (about 1.8M) is
>processed instantly.
>If I configure my avrowriter to use the schema text property and paste the
>following into the schema text field, the performance is terrible, taking
>tens of minutes to empty the same queue. Both are on the same 25ms run
>duration. I notice that even a "run once" of that processor. I did not
>notice the same behavior on my laptop. Is there likely to be some sort of
>querying remote sites going on behind the scenes that my server is failing
>to access due to firewalls etc? It seems really strange to me that it
>should be so slow with such tiny files, and the only commonality I can find
>is the custom schema. Is there something odd about it?
>
>{
>  "type": "record",
>  "namespace": "cogstack",
>  "name": "document",
>  "fields":
>  [
>    { "name": "doc_id", "type": "string" },
>    { "name": "doc_text", "type": "string", "default": "" },
>    { "name": "processing_timestamp", "type": { "type" : "string",
>"logicalType" : "timestamp-millis" } },
>    { "name": "metadata_x_ocr_applied", "type": "boolean" },
>    { "name": "metadata_x_parsed_by", "type": "string" },
>    { "name": "metadata_content_type", "type": ["null", "string"],
>"default": null },
>    { "name": "metadata_page_count", "type": ["null", "int"], "default":
>null },
>    { "name": "metadata_creation_date", "type": ["null", { "type" :
>"string", "logicalType" : "timestamp-millis" }], "default": null },
>    { "name": "metadata_last_modified", "type": ["null", { "type" :
>"string", "logicalType" : "timestamp-millis" }], "default": null }
>  ]
>}
>}
>
>On Wed, Dec 21, 2022 at 2:05 PM Richard Beare <[email protected]>
>wrote:
>
>> I've made progress with Jolt and I think I'm close to achieving what I'm
>> after. I am missing one conceptual step, I think.
>>
>> I rearrange my json so that it conforms to the desired structure and I can
>> then write the results as avro. However, that is generic avro. How do I
>> ensure that I conform to the schema that has been defined for that part of
>> the flow?
>>
>> i.e. The part of the flow I'm replacing with jolt was a groovy script that
>> created a flowfile according to a schema. That schema is below. Is there a
>> way to utilise this definition in the jolttransformrecord processor, either
>> via specification of data types in the transform definition or by telling
>> the avro writer to use that specification. Or am I overthinking things here?
>> Thanks
>>
>> {
>>   "type": "record",
>>   "name": "document",
>>   "fields":
>>   [
>>     { "name": "doc_id", "type": "string" },
>>     { "name": "doc_text", "type": "string", "default": "" },
>>     { "name": "processing_timestamp", "type": { "type" : "string",
>> "logicalType" : "timestamp-millis" } },
>>     { "name": "metadata_x_ocr_applied", "type": "boolean" },
>>     { "name": "metadata_x_parsed_by", "type": "string" },
>>     { "name": "metadata_content_type", "type": ["null", "string"],
>> "default": null },
>>     { "name": "metadata_page_count", "type": ["null", "int"], "default":
>> null },
>>     { "name": "metadata_creation_date", "type": ["null", { "type" :
>> "string", "logicalType" : "timestamp-millis" }], "default": null },
>>     { "name": "metadata_last_modified", "type": ["null", { "type" :
>> "string", "logicalType" : "timestamp-millis" }], "default": null }
>>   ]
>> }
>>
>>
>>
>> On Wed, Dec 21, 2022 at 9:06 AM Richard Beare <[email protected]>
>> wrote:
>>
>>> Thanks - I'll have a look at that. It is helpfully to get guidance like
>>> this when the system is so large.
>>>
>>> On Wed, Dec 21, 2022 at 5:30 AM Matt Burgess <[email protected]>
>>> wrote:
>>>
>>>> Thanks Vijay! I agree those processors should do the trick but there
>>>> were things in the transformation between input and desired output
>>>> that I wasn't sure of their origin. If you are setting constants you
>>>> can use either a Shift or Default spec, if you are moving fields
>>>> around you can use a Shift spec, and in general whether you end up
>>>> with one spec or multiple, I find it's easiest to use a Chain spec (an
>>>> array of specs) in the processor configuration. You can play around
>>>> with the spec(s) at the Jolt playground [1]
>>>>
>>>> An important difference to note between JoltTransformJSON and
>>>> JoltTransformRecord is that for the former, the spec is applied to the
>>>> entire input (and it is entirely read into memory) where in
>>>> JoltTransformRecord the spec is applied to each record.
>>>>
>>>> Regards,
>>>> Matt
>>>>
>>>> [1] http://jolt-demo.appspot.com/#inception
>>>>
>>>> On Tue, Dec 20, 2022 at 10:52 AM Vijay Chhipa <[email protected]> wrote:
>>>> >
>>>> > Hi Richard
>>>> > Have you tried JoltTransformJSON or JoltTransformRecord
>>>> >
>>>> > I believe you should be able to do this
>>>> >
>>>> > Quick start here:
>>>> https://community.cloudera.com/t5/Community-Articles/Jolt-quick-reference-for-Nifi-Jolt-Processors/ta-p/244350
>>>> >
>>>> >
>>>> > On Dec 20, 2022, at 4:13 AM, Richard Beare <[email protected]>
>>>> wrote:
>>>> >
>>>> > Hi Everyone,
>>>> > Still struggling to fix this issue and may need to try some different
>>>> things.
>>>> >
>>>> > What is the recommended way of transforming a record structure? At the
>>>> moment I have a groovy script doing this but the downstream processing is
>>>> very slow, as discussed in the preceding thread.
>>>> >
>>>> > The transformation is very simple - starting structure is:
>>>> >
>>>> > {
>>>> >  "result" : {
>>>> > "text" : " document text",
>>>> >   "metadata" : {
>>>> >      "X-TIKA:Parsed-By": [
>>>> >      "org.apache.tika.parser.pdf.PDFParser"
>>>> >      ],
>>>> >     "X-OCR-Applied" : true,
>>>> >     "dcterms:created": "2018;07-24T15:04:51Z",
>>>> >     "Content-Type" : "application/pdf",
>>>> >     "Page-Count" : 2,
>>>> >   },
>>>> > "success" : true,
>>>> > "timestamp" :  "2022-12-20T09:02:27.902Z",
>>>> > "processingElapsedTime" : 6
>>>> > }
>>>> > }
>>>> >
>>>> >
>>>> > final structure is':
>>>> >
>>>> > [ {
>>>> > "doc_id" : 58,
>>>> > "doc_text" : "   ",
>>>> > "processing_timestamp" : "2022-12-20T09:02:27.902Z",
>>>> > "metadata_x_ocr_applies" : true,
>>>> > "metadata_x_parsed_by" : "org.apache.tika.parser.pdf.PDFParser",
>>>> > "metadata_content_type" : "application/pdf",
>>>> > "metadata_page_count" : 1
>>>> > "metadata_creation_date": null,
>>>> > "metadata_last_modified: nill
>>>> > }]
>>>> >
>>>> > So a kind of flattening of the structure. Is there a processor I
>>>> should be using to do this instead of a groovy script?
>>>> >
>>>> > Thanks
>>>> >
>>>> > On Wed, Dec 14, 2022 at 7:57 AM Richard Beare <[email protected]>
>>>> wrote:
>>>> >>
>>>> >> Any thoughts on this? Are there some extra steps required when
>>>> creating an avro file from a user defined schema?
>>>> >>
>>>> >> On Thu, Dec 8, 2022 at 2:56 PM Richard Beare <[email protected]>
>>>> wrote:
>>>> >>>
>>>> >>> Here's another result that I think suggests there's something wrong
>>>> with the avro files created by the groovy script, although I can't see what
>>>> the problem might be.
>>>> >>>
>>>> >>> The test is as follows. Output of the groovy script creating avro
>>>> files is passed to convertrecord, configured with an avro reader and json
>>>> writer. This is slow. The json output is then converted back to avro with
>>>> another convertrecord processor, configured with a jsontreereader and an
>>>> avro writer - this is fast, instantly emptying the queue. The result of
>>>> that is fed into the previously problematic merge processor which works
>>>> exactly as expected, producing flowfiles with 100 records each.
>>>> >>>
>>>> >>> The difference I can see between the two flow files is the way in
>>>> which the schema is specified. Perhaps some extras are required in the
>>>> groovy file to set that up?
>>>> >>>
>>>> >>> The slow one has:
>>>> >>>
>>>> >>> {"type":"record","name":"document", "fields":[{
>>>> >>>
>>>> >>> The fast one
>>>> >>>
>>>> {"type":"record","name":"nifiRecord","namespace":"org.apache.nifi","fields":
>>>> >>>
>>>> >>>
>>>> >>> Initial characters are also slightly different.
>>>> >>> Slow one:
>>>> >>>
>>>> >>> 0000000   O   b   j 001 002 026   a   v   r   o   .   s   c   h   e
>>>>  m
>>>> >>> 0000020   a 346  \n   {   "   t   y   p   e   "   :   "   r   e   c
>>>>  o
>>>> >>>
>>>> >>> Fast one
>>>> >>>
>>>> >>> 0000000   O   b   j 001 004 026   a   v   r   o   .   s   c   h   e
>>>>  m
>>>> >>> 0000020   a 362  \b   {   "   t   y   p   e   "   :   "   r   e   c
>>>>  o
>>>> >>>
>>>> >>>
>>>> >>> The groovy script is
>>>> >>> CogStack-NiFi/parse-tika-result-json-to-avro.groovy at master ·
>>>> CogStack/CogStack-NiFi · GitHub
>>>> >>>
>>>> >>> The schema is
>>>> >>> CogStack-NiFi/document.avsc at master · CogStack/CogStack-NiFi ·
>>>> GitHub
>>>> >>>
>>>> >>>
>>>> >>> On Thu, Dec 8, 2022 at 1:59 PM Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>
>>>> >>>> I'm diving into the convertrecord tests a bit deeper on the
>>>> production server.
>>>> >>>>
>>>> >>>> The first test case - 259 documents, total of 1M when in avro
>>>> format in the input queue to the convert record processor. These avro files
>>>> were not created by the groovy script - they start life as a database query
>>>> and the text field is in one of the columns. The convertrecord processor
>>>> runs very quickly - click start, press refresh and it is done. The avro
>>>> ends up like this:
>>>> >>>>
>>>> >>>> [ {
>>>> >>>>   "sampleid" : 1075,
>>>> >>>>   "typeid" : 98,
>>>> >>>>   "dct" : "2020-01-25T21:40:25.515Z",
>>>> >>>>   "filename" : "__tmp/txt/mtsamples-type-98-sample-1075.txt",
>>>> >>>>   "document" : "Text removed",
>>>> >>>>   "docid" : "9"
>>>> >>>> } ]
>>>> >>>>
>>>> >>>> In the second test, where the text fields are extracted from pdf
>>>> tika before avro files are created by the groovy script (from the tika json
>>>> output), the total queue size for the 259 documents is larger - 1.77MB, and
>>>> the performance is very different - press start, click refresh and only two
>>>> flowfiles are processed.
>>>> >>>>
>>>> >>>> [ {
>>>> >>>>   "doc_id" : "70",
>>>> >>>>   "doc_text" : "text removed",
>>>> >>>>   "processing_timestamp" : "2022-12-07T23:09:52.354Z",
>>>> >>>>   "metadata_x_ocr_applied" : true,
>>>> >>>>   "metadata_x_parsed_by" : "org.apache.tika.parser.pdf.PDFParser",
>>>> >>>>   "metadata_content_type" : "application/pdf",
>>>> >>>>   "metadata_page_count" : 1,
>>>> >>>>   "metadata_creation_date" : null,
>>>> >>>>   "metadata_last_modified" : null
>>>> >>>> } ]
>>>> >>>>
>>>> >>>> I've noticed that the second one has a content.type attribute of
>>>> 'application/json' which doesn't seem right and doesn't match the fast
>>>> case. I'll see what happens if I change that.
>>>> >>>>
>>>> >>>> On Thu, Dec 8, 2022 at 9:39 AM Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>>
>>>> >>>>> Hi All,
>>>> >>>>> Some progress on debugging options. I've found a flow that
>>>> exhibits the problem using synthetic data. However the results are host
>>>> dependent. On my laptop a "run-once" click of merge record gives me two
>>>> flowfiles of 100 records, while the same flow on the production server
>>>> produces several much smaller flowfiles. This makes me think that something
>>>> funny is happening with my storage setup that I'll need to chase.
>>>> >>>>>
>>>> >>>>> I had tested the convertrecord option (simply
>>>> avroreader->avrowriter) and it did seem slow, but I'll investigate this
>>>> further as it may be related to my storage issue.
>>>> >>>>>
>>>> >>>>>
>>>> >>>>>
>>>> >>>>> On Thu, Dec 8, 2022 at 1:23 AM Mark Payne <[email protected]>
>>>> wrote:
>>>> >>>>>>
>>>> >>>>>> > Is there something about this structure that is likely to be
>>>> causing the problem? Could there be other issues with the avro generated by
>>>> the script?
>>>> >>>>>>
>>>> >>>>>> I don’t think the structure should matter. And as long as the
>>>> avro produced is proper Avro, I don’t think it should matter. Unless
>>>> perhaps there’s some issue with the Avro library itself that’s causing it
>>>> to take a really long time to parse the Avro or something? I’d be curious -
>>>> if you take the output of your script and then you run it through a
>>>> ConvertRecord (Avro Reader -> Json Writer) is the ConvertRecord fast? Or is
>>>> it really slow to process it?
>>>> >>>>>>
>>>> >>>>>> On Dec 5, 2022, at 5:58 AM, Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>>>
>>>> >>>>>> Further - I performed another test in which I replaced the custom
>>>> json to avro script with a ConvertRecord processor - merge record appears
>>>> to work as expected in that case.
>>>> >>>>>>
>>>> >>>>>> Output of convertrecord looks like this:
>>>> >>>>>>
>>>> >>>>>> [ {
>>>> >>>>>>   "text" : "  No Alert Found \n\n",
>>>> >>>>>>   "metadata" : {
>>>> >>>>>>     "X_TIKA_Parsed_By" : null,
>>>> >>>>>>     "X_OCR_Applied" : null,
>>>> >>>>>>     "Content_Type" : null
>>>> >>>>>>   },
>>>> >>>>>>   "success" : true,
>>>> >>>>>>   "timestamp" : "2022-12-05T10:49:18.568Z",
>>>> >>>>>>   "processingElapsedTime" : 0,
>>>> >>>>>>   "doc_id" : "5.60178607E8"
>>>> >>>>>> } ]
>>>> >>>>>>
>>>> >>>>>> while the output of the script looks like:
>>>> >>>>>>
>>>> >>>>>> [ {
>>>> >>>>>>   "doc_id" : "5.61996505E8",
>>>> >>>>>>   "doc_text" : "  No Alert Found \n\n",
>>>> >>>>>>   "processing_timestamp" : "2022-11-28T01:16:46.775Z",
>>>> >>>>>>   "metadata_x_ocr_applied" : true,
>>>> >>>>>>   "metadata_x_parsed_by" :
>>>> "org.apache.tika.parser.DefaultParser;org.apache.tika.parser.microsoft.rtf.RTFParser;org.apache.tika.parser.AutoDetectParser",
>>>> >>>>>>   "metadata_content_type" : "application/rtf",
>>>> >>>>>>   "metadata_page_count" : null,
>>>> >>>>>>   "metadata_creation_date" : null,
>>>> >>>>>>   "metadata_last_modified" : null
>>>> >>>>>> } ]
>>>> >>>>>>
>>>> >>>>>> Is there something about this structure that is likely to be
>>>> causing the problem? Could there be other issues with the avro generated by
>>>> the script?
>>>> >>>>>>
>>>> >>>>>> On Mon, Dec 5, 2022 at 9:31 PM Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>>>>
>>>> >>>>>>> I've reset the backpressure to the default
>>>> >>>>>>>
>>>> >>>>>>> This remains something of a mystery. The merge with synthetic
>>>> data happily creates flowfiles with 100 records, and the join says "Records
>>>> merged due to: Bin is full" or "Records merged due to: Bin is full enough".
>>>> No timeouts in that case, even with the max bin age at 4.5 seconds. The
>>>> resulting flowfiles were about 300K.
>>>> >>>>>>>
>>>> >>>>>>> The real data is doing much the same as before, producing
>>>> flowfiles of about 30K, with 7 records or so. If I increase the maximum bin
>>>> age to 30 seconds the size and record count is higher - 12 to 15. Nothing
>>>> like the behaviour with synthetic data, where the 100 record flowfiles are
>>>> created almost instantly. Joins are always due to bin age.
>>>> >>>>>>>
>>>> >>>>>>> Can the problem relate to the structure of the avro files? Any
>>>> way to dive into that? Everything else about the mergerecord settings
>>>> appear the same, so I can't see an explanation as to why the behaviour is
>>>> different on the same hardware.
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>>
>>>> >>>>>>> On Mon, Dec 5, 2022 at 2:09 AM Mark Payne <[email protected]>
>>>> wrote:
>>>> >>>>>>>>
>>>> >>>>>>>> Hey Richard,
>>>> >>>>>>>>
>>>> >>>>>>>> So a few things that I’ve done/looked at.
>>>> >>>>>>>>
>>>> >>>>>>>> I generated some Avro data (random JSON that I downloaded from
>>>> a Random JSON Generator and then converted to Avro).
>>>> >>>>>>>>
>>>> >>>>>>>> I then ran this avro data into both the MergeRecord processors.
>>>> >>>>>>>>
>>>> >>>>>>>> Firstly, I noticed that both are very slow. Found that was
>>>> because Run Schedule was set to 5 seconds. This should *ALWAYS* be 0 secs
>>>> for MergeRecord. And really for basically all processors except for the
>>>> first one in the flow.
>>>> >>>>>>>>
>>>> >>>>>>>> I also notice that you have backpressure set on your
>>>> connections to 40,000 FlowFiles and 4 GB. This can significantly slow
>>>> things down. If you have performance concerns you definitely want
>>>> backpressure set back to the default of 10,000 FlowFiles. Otherwise, as the
>>>> queues fill up they start “swapping out” FlowFiles to disk, and this can
>>>> significantly slow things down.
>>>> >>>>>>>>
>>>> >>>>>>>> I noticed that MergeRecord is set to 1 concurrent task.
>>>> Probably worth considering increasing that, if performance is a concern.
>>>> >>>>>>>>
>>>> >>>>>>>> That said, I am seeing nice, full bins of 100 records merged
>>>> from each of the MergeRecord processors.
>>>> >>>>>>>> So it is certainly possible that if you’re seeing smaller bins
>>>> it’s becuase you’re timing out. The 4.5 seconds timeout is quite short.
>>>> Have you tried increasing that to say 30 seconds to see if it gives you
>>>> larger bins?
>>>> >>>>>>>> I also recommend that you take a look at the data provenance to
>>>> see why it’s creating the bins.
>>>> >>>>>>>>
>>>> >>>>>>>> If unclear how to do that:
>>>> >>>>>>>> Right-click on the MergeRecord processor
>>>> >>>>>>>> Go to View data provenance
>>>> >>>>>>>> Scroll down the list until you see a “JOIN” event type. You can
>>>> ignore the ATTRIBUTES_MODIFIED and DROP events for now.
>>>> >>>>>>>> Click the ‘i’ icon on the left-hand side.
>>>> >>>>>>>> This will show you details about the merge. In the Details tab,
>>>> if you scroll down, it will show you a Details field, which tells you why
>>>> the data was merged. It should either say: "Records Merged due to: Bin has
>>>> reached Max Bin Age” or “ Records Merged due to: Bin is full”
>>>> >>>>>>>>
>>>> >>>>>>>> If it is due to Max Bin Age reached, then I’d recommend
>>>> increasing number of concurrent tasks, reducing backpressure to no more
>>>> than 10,000 FlowFiles in the queue, and/or increasing the Max Bin Age.
>>>> >>>>>>>> Also worth asking - what kind of machines is this running on? A
>>>> 64 core VM with 1 TB volume will, of course, run MUCH differently than a 4
>>>> core VM with a 10 GB volume, especially in the cloud.
>>>> >>>>>>>>
>>>> >>>>>>>> If still having trouble, let me know what the provenance tells
>>>> you about the reason for merging the data, and we can go from there.
>>>> >>>>>>>>
>>>> >>>>>>>> Thanks!
>>>> >>>>>>>> -Mark
>>>> >>>>>>>>
>>>> >>>>>>>>
>>>> >>>>>>>> On Dec 3, 2022, at 4:38 PM, Mark Payne <[email protected]>
>>>> wrote:
>>>> >>>>>>>>
>>>> >>>>>>>> Richard,
>>>> >>>>>>>>
>>>> >>>>>>>> I think just the flow structure shoudl be sufficient.
>>>> >>>>>>>>
>>>> >>>>>>>> Thanks
>>>> >>>>>>>> -Mark
>>>> >>>>>>>>
>>>> >>>>>>>>
>>>> >>>>>>>> On Dec 3, 2022, at 4:32 PM, Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>>>>>
>>>> >>>>>>>> Thanks for responding,
>>>> >>>>>>>> I re-tested with max bins = 2, but the behaviour remained the
>>>> same. I can easily share a version of the functioning workflow (and data),
>>>> which is part of a public project. The problem workflow (which shares many
>>>> of the same components) is part of a health research project, so more
>>>> difficult. I definitely can't share any data from that one. Do you need to
>>>> see the data or is the overall structure sufficient at this point? Happy to
>>>> demonstrate via video conference too.
>>>> >>>>>>>>
>>>> >>>>>>>> Thanks
>>>> >>>>>>>>
>>>> >>>>>>>> On Sun, Dec 4, 2022 at 1:37 AM Mark Payne <[email protected]>
>>>> wrote:
>>>> >>>>>>>>>
>>>> >>>>>>>>> Hi Richard,
>>>> >>>>>>>>>
>>>> >>>>>>>>> Can you try increasing the Maximum Number of Bins? I think
>>>> there was an issue that was recently addressed in which the merge
>>>> processors had an issue when Max Number of Bins = 1.
>>>> >>>>>>>>>
>>>> >>>>>>>>> If you still see the same issue, please provide a copy of the
>>>> flow that can be used to replicate the issue.
>>>> >>>>>>>>>
>>>> >>>>>>>>> Thanks
>>>> >>>>>>>>> -Mark
>>>> >>>>>>>>>
>>>> >>>>>>>>>
>>>> >>>>>>>>> On Dec 3, 2022, at 5:21 AM, Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>>>>>>
>>>> >>>>>>>>> Hi,
>>>> >>>>>>>>>
>>>> >>>>>>>>> Pretty much the same - I seem to end up with flowfiles
>>>> containing about 7 records, presumably always triggered by the timeout.
>>>> >>>>>>>>>
>>>> >>>>>>>>> I had thought the timeout needed to be less than the run
>>>> schedule, but it looks like it can be the same.
>>>> >>>>>>>>>
>>>> >>>>>>>>> Here's a debug dump
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:43 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1066297 to RecordBin[size=4, full=false, isComplete=false, id=4021]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:43 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1066297 to RecordBin[size=5, full=false, isComplete=false,
>>>> id=4021]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:44 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=9e9908f6-b28e-4615-b6c8-4bd163a3bc00]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:44 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1066372 to RecordBin[size=5, full=false, isComplete=false, id=4021]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:44 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1066372 to RecordBin[size=6, full=false, isComplete=false,
>>>> id=4021]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:45 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1066575 to RecordBin[size=7, full=false, isComplete=true,
>>>> id=4021]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:46 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=9e9908f6-b28e-4615-b6c8-4bd163a3bc00]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:46 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1066612 to RecordBin[size=0, full=false, isComplete=false, id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:46 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Created
>>>> OutputStream using session StandardProcessSession[id=83204] for
>>>> RecordBin[size=0, full=false, isComplete=false, id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:46 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1066612 to RecordBin[size=1, full=false, isComplete=false,
>>>> id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:48 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1066896 to RecordBin[size=2, full=false, isComplete=false, id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:48 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1066896 to RecordBin[size=3, full=false, isComplete=false,
>>>> id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:49 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=7d4f7a2b-ea59-4b9c-a7d6-df035fa3856e]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:49 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1067051 to RecordBin[size=3, full=false, isComplete=false, id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:49 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1067051 to RecordBin[size=4, full=false, isComplete=false,
>>>> id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:52 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1067254 to RecordBin[size=7, full=false, isComplete=true,
>>>> id=4022]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:53 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=b7f4498d-647a-46d1-ad9f-badaed8591f8]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:53 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1067395 to RecordBin[size=0, full=false, isComplete=false, id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:53 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Created
>>>> OutputStream using session StandardProcessSession[id=83205] for
>>>> RecordBin[size=0, full=false, isComplete=false, id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:53 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1067395 to RecordBin[size=1, full=false, isComplete=false,
>>>> id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:54 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1068472 to RecordBin[size=1, full=false, isComplete=false, id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:54 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1068472 to RecordBin[size=2, full=false, isComplete=false,
>>>> id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:55 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=7d4f7a2b-ea59-4b9c-a7d6-df035fa3856e]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:55 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1068597 to RecordBin[size=2, full=false, isComplete=false, id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:55 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1068597 to RecordBin[size=3, full=false, isComplete=false,
>>>> id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:58 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> RecordBin[size=6, full=false, isComplete=false, id=4023] is now expired.
>>>> Completing bin.
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:58 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Marked
>>>> RecordBin[size=6, full=false, isComplete=true, id=4023] as complete because
>>>> complete() was called
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:58 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Closed
>>>> Record Writer using session StandardProcessSession[id=83205] for
>>>> RecordBin[size=6, full=false, isComplete=true, id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:58 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Completed
>>>> bin RecordBin[size=6, full=false, isComplete=true, id=4023] with 6 records
>>>> with Merged FlowFile
>>>> FlowFile[filename=6824b503-82b9-444e-a77e-9b081e878948] using input
>>>> FlowFiles [id=1067395, id=1068472, id=1068597, id=1068663, id=1068800,
>>>> id=1068845]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:13:58 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1068845 to RecordBin[size=6, full=false, isComplete=true,
>>>> id=4023]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:01 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1069272 to RecordBin[size=2, full=false, isComplete=false, id=4024]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:01 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1069272 to RecordBin[size=3, full=false, isComplete=false,
>>>> id=4024]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:02 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=b7f4498d-647a-46d1-ad9f-badaed8591f8]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:02 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1069316 to RecordBin[size=3, full=false, isComplete=false, id=4024]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:02 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1069316 to RecordBin[size=4, full=false, isComplete=false,
>>>> id=4024]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:05 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> RecordBin[size=6, full=false, isComplete=false, id=4024] is now expired.
>>>> Completing bin.
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:05 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Marked
>>>> RecordBin[size=6, full=false, isComplete=true, id=4024] as complete because
>>>> complete() was called
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:05 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Closed
>>>> Record Writer using session StandardProcessSession[id=83206] for
>>>> RecordBin[size=6, full=false, isComplete=true, id=4024]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:05 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Completed
>>>> bin RecordBin[size=6, full=false, isComplete=true, id=4024] with 6 records
>>>> with Merged FlowFile
>>>> FlowFile[filename=6c13e518-655b-4507-ad6c-d37f6b9c0a5d] using input
>>>> FlowFiles [id=1069044, id=1069103, id=1069272, id=1069316, id=1069451,
>>>> id=1069492]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:05 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1069492 to RecordBin[size=6, full=false, isComplete=true,
>>>> id=4024]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:07 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1072118 to RecordBin[size=2, full=false, isComplete=false, id=4025]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:07 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1072118 to RecordBin[size=3, full=false, isComplete=false,
>>>> id=4025]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:08 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Got Group
>>>> ID
>>>> {"type":"record","name":"document","fields":[{"name":"doc_id","type":"string"},{"name":"doc_text","type":"string","default":""},{"name":"processing_timestamp","type":{"type":"string","logicalType":"timestamp-millis"}},{"name":"metadata_x_ocr_applied","type":"boolean"},{"name":"metadata_x_parsed_by","type":"string"},{"name":"metadata_content_type","type":["null","string"],"default":null},{"name":"metadata_page_count","type":["null","int"],"default":null},{"name":"metadata_creation_date","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null},{"name":"metadata_last_modified","type":["null",{"type":"string","logicalType":"timestamp-millis"}],"default":null}]}
>>>> for FlowFile[filename=7d4f7a2b-ea59-4b9c-a7d6-df035fa3856e]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:08 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1] Migrating
>>>> id=1072197 to RecordBin[size=3, full=false, isComplete=false, id=4025]
>>>> >>>>>>>>>
>>>> >>>>>>>>> 10:14:08 UTC
>>>> >>>>>>>>> DEBUG
>>>> >>>>>>>>> 99ae16aa-0184-1000-8ccc-ee1f2ee77ca1
>>>> >>>>>>>>>
>>>> >>>>>>>>> MergeRecord[id=99ae16aa-0184-1000-8ccc-ee1f2ee77ca1]
>>>> Transferred id=1072197 to RecordBin[size=4, full=false, isComplete=false,
>>>> id=4025]
>>>> >>>>>>>>>
>>>> >>>>>>>>>
>>>> >>>>>>>>> On Sat, Dec 3, 2022 at 4:21 PM Joe Witt <[email protected]>
>>>> wrote:
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> Hello
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> Run schedule should be 0.
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> 50 should be the min number of records
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> 5 seconds is the max bin age it sounds like you want.
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> Start with these changes and let us know what youre seeing.
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> Thanks
>>>> >>>>>>>>>>
>>>> >>>>>>>>>> On Fri, Dec 2, 2022 at 10:12 PM Richard Beare <
>>>> [email protected]> wrote:
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> Hi,
>>>> >>>>>>>>>>> I'm having a great deal of trouble configuring the
>>>> mergerecord processor to deliver reasonable performance and I'm not sure
>>>> where to look to correct it. One of my upstream processors requires a
>>>> single record per flowfile, but I'd like to create larger flowfiles before
>>>> passing to the next stage. The flowfiles are independent at this stage so
>>>> there's no special processing required of the merging. I'd like to create
>>>> flowfiles of about 50 to 100 records.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> I have two tests, both running on the same nifi system. One
>>>> uses synthetic data, the other the production data. The performance of the
>>>> mergerecord processor for the synthetic data is as I'd expect, and I can't
>>>> figure out why the  production data is so much slower. Here's the
>>>> >>>>>>>>>>> configuration:
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> mergerecord has the following settings. Timer driven, 1
>>>> concurrent task, 5 second run schedule, bin packing merge strategy, min
>>>> records = 1, max records = 100, max bin age = 4.5 secs, maximum number of
>>>> bins = 1.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> In the case of synthetic data the typical flowfile size is
>>>> in the range 2 to 7KB.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> The size of flowfiles for the production case is smaller -
>>>> typically around 1KB.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> The structure in the tests is slightly different. Synthetic
>>>> is (note that I've removed the text part):
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> [ {
>>>> >>>>>>>>>>>   "sampleid" : 1075,
>>>> >>>>>>>>>>>   "typeid" : 98,
>>>> >>>>>>>>>>>   "dct" : "2020-01-25T21:40:25.515Z",
>>>> >>>>>>>>>>>   "filename" : "__tmp/txt/mtsamples-type-98-sample-1075.txt",
>>>> >>>>>>>>>>>   "document" : "Text removed - typically a few hundred
>>>> words",
>>>> >>>>>>>>>>>   "docid" : "9"
>>>> >>>>>>>>>>> } ]
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> Production is:
>>>> >>>>>>>>>>> [ {
>>>> >>>>>>>>>>>   "doc_id" : "5.60622895E8",
>>>> >>>>>>>>>>>   "doc_text" : " Text deleted - typically a few hundred
>>>> words",
>>>> >>>>>>>>>>>   "processing_timestamp" : "2022-11-27T23:56:35.601Z",
>>>> >>>>>>>>>>>   "metadata_x_ocr_applied" : true,
>>>> >>>>>>>>>>>   "metadata_x_parsed_by" :
>>>> "org.apache.tika.parser.DefaultParser;org.apache.tika.parser.microsoft.rtf.RTFParser;org.apache.tika.parser.AutoDetectParser",
>>>> >>>>>>>>>>>   "metadata_content_type" : "application/rtf",
>>>> >>>>>>>>>>>   "metadata_page_count" : null,
>>>> >>>>>>>>>>>   "metadata_creation_date" : null,
>>>> >>>>>>>>>>>   "metadata_last_modified" : null
>>>> >>>>>>>>>>> } ]
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> I load up the queue feeding the mergerecord processor with
>>>> several hundred individual flowfiles and activate it.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> The synthetic data is nicely placed into chunks of 100, with
>>>> any remainder being flushed in a smaller chunk.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> The production data is generally bundled into groups of 6
>>>> records, sometimes less. Certainly it never gets close to 100 records.
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> Any ideas as to what I should look at to track down the
>>>> difference?
>>>> >>>>>>>>>>>
>>>> >>>>>>>>>>> Thanks
>>>> >>>>>>>>>
>>>> >>>>>>>>>
>>>> >>>>>>>>
>>>> >>>>>>>>
>>>> >>>>>>
>>>> >
>>>>
>>>

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