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https://issues.apache.org/jira/browse/NIFI-11449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17825392#comment-17825392
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Matt Burgess commented on NIFI-11449:
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I believe there are separate processors for AWS and GCP as well. They may not
be included with the Apache NiFi release binaries but the NARs can be added
manually from the Apache repository. Do those solve your use case or do we need
PutIceberg to support Object-backed storage as well?
> add autocommit property to PutDatabaseRecord processor
> ------------------------------------------------------
>
> Key: NIFI-11449
> URL: https://issues.apache.org/jira/browse/NIFI-11449
> Project: Apache NiFi
> Issue Type: New Feature
> Components: Extensions
> Affects Versions: 1.21.0
> Environment: Any Nifi Deployment
> Reporter: Abdelrahim Ahmad
> Priority: Blocker
> Labels: Trino, autocommit, database, iceberg, putdatabaserecord
>
> The issue is with the {{PutDatabaseRecord}} processor in Apache NiFi. When
> using the processor with the Trino-JDBC-Driver or Dremio-JDBC-Driver to write
> to an Iceberg catalog, it disables the autocommit feature. This leads to
> errors such as "{*}Catalog only supports writes using autocommit: iceberg{*}".
> the autocommit feature needs to be added in the processor to be
> enabled/disabled.
> enabling auto-commit in the Nifi PutDatabaseRecord processor is important for
> Deltalake, Iceberg, and Hudi as it ensures data consistency and integrity by
> allowing atomic writes to be performed in the underlying database. This will
> allow the process to be widely used with bigger range of databases.
> _Improving this processor will allow Nifi to be the main tool to ingest data
> into these new Technologies. So we don't have to deal with another tool to do
> so._
> +*_{color:#de350b}BUT:{color}_*+
> I have reviewed The {{PutDatabaseRecord}} processor in NiFi. It inserts
> records one by one into the database using a prepared statement, and commits
> the transaction at the end of the loop that processes each record. This
> approach can be inefficient and slow when inserting large volumes of data
> into tables that are optimized for bulk ingestion, such as Delta Lake,
> Iceberg, and Hudi tables.
> These tables use various techniques to optimize the performance of bulk
> ingestion, such as partitioning, clustering, and indexing. Inserting records
> one by one using a prepared statement can bypass these optimizations, leading
> to poor performance and potentially causing issues such as excessive disk
> usage, increased memory consumption, and decreased query performance.
> To avoid these issues, it is recommended to have a new processor, or add
> feature to the current one, to bulk insert method with AutoCommit feature
> when inserting large volumes of data into Delta Lake, Iceberg, and Hudi
> tables.
>
> P.S.: using PutSQL is not a have autoCommit but have the same performance
> problem described above..
> Thanks and best regards :)
> Abdelrahim Ahmad
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