Member since
11-16-2015
888
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647
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245
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My Accepted Solutions
Title | Views | Posted |
---|---|---|
388 | 02-22-2024 12:38 PM | |
719 | 02-02-2023 07:07 AM | |
1997 | 12-07-2021 09:19 AM | |
3310 | 03-20-2020 12:34 PM | |
11227 | 01-27-2020 07:57 AM |
02-23-2024
11:51 AM
1 Kudo
https://issues.apache.org/jira/browse/NIFI-12839
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02-22-2024
12:38 PM
I think this is a bug, I'm looking into it. Looks like it's using your 1.0-SNAPSHOT version for NiFi dependencies when it should be using nifiVersion. To get things going, use 2.0.0-M2 for your version for now, then you can go back into the helloworld module and change the version back to what you want.
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06-13-2023
02:59 PM
1 Kudo
Tracking here: https://issues.apache.org/jira/browse/NIFI-11682
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06-13-2023
01:57 PM
1 Kudo
It looks like this is a regression from https://issues.apache.org/jira/browse/NIFI-9607 but will need a different solution than just restoring the code changes as it would fail the behavior the aforementioned Jira was meant to fix.
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06-13-2023
01:49 PM
I was finally able to reproduce the issue, looking into a fix now
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05-23-2023
09:15 AM
As far as I know, InferAvroSchema is not a supported processor. However there are record-based processors and an AvroReader controller service you can use with those processors. AvroReader has a (default) option to Infer Schema. This should achieve the same effect, and record-based processors are often more performant.
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03-16-2023
10:34 AM
In Oracle an UPSERT is done by a MERGE, so alternatively you could store your data in a new temporary table and then run ExecuteSQL/PutSQL with a MERGE command to merge from the temp table into the target table.
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02-02-2023
07:07 AM
I'm not a Hive expert but I did author the original PutHive3Streaming processor for NiFi. My recommendation is setting Records Per Transaction greater than the number of records in a FlowFile (unless we are talking about super-huge files), and transactions per batch to 1. This makes the transaction semantics similar to how NiFi FlowFile sessions work (rollback, failure, success, e.g.). If the number of records is huge and is causing throughput problems, try dividing that number by 100 and making transactions per batch 100. When you multiply the two numbers together it should be greater than the total number of records in the FlowFile in order to avoid overhead with the Hive Metastore by requesting a large number of batches/transactions.
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12-20-2022
05:52 AM
I wasn't able to reproduce this, I remember trying your example and the UPSERT worked for me, so I'm not sure what's going on
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