Once a FlowFile has been written, we know that all of the Records within that FlowFile have the same value for the fields that are described by the configured RecordPaths. ConvertRecord, SplitRecord, UpdateRecord, QueryRecord, Specifies the Controller Service to use for reading incoming data, Specifies the Controller Service to use for writing out the records. (Failure to parse the key bytes as UTF-8 will result in the record being routed to the Each record is then grouped with other "like records" and a FlowFile is created for each group of "like records." Grok Expression specifies the format of the log line in Grok format, specifically: The AvroSchemaRegistry defines the "nifi-logs" schema. that are configured. using this approach, we can ensure that the data that already was pulled can be processed (assuming First In First Out Prioritizers are used) before newer messages But by promoting a value from a record field into an attribute, it also allows you to use the data in your records to configure Processors (such as PublishKafkaRecord) through Expression Language. What is the symbol (which looks similar to an equals sign) called? has pulled 1,000 messages from Kafka but has not yet delivered them to their final destination. a truststore as described above. ConvertRecord, SplitRecord, UpdateRecord, QueryRecord, Specifies the Controller Service to use for reading incoming data, Specifies the Controller Service to use for writing out the records. Out of the box, NiFi provides many different Record Readers. I have no strange data types, only a couple of FLOATs and around 100 STRINGS. If you chose to use ExtractText, the properties you defined are populated for each row (after the original file was split by SplitText processor). As a result, this means that we can promote those values to FlowFile Attributes. and headers, as well as additional metadata from the Kafka record. This FlowFile will have no state attribute (unless such an attribute existed on the incoming FlowFile, In this scenario, Node 1 may be assigned partitions 0, 1, and 2. I will give it a try with ConsumeKafkaRecord using CSVReader and CSVRecordSetWriter, to see if I still encounter the same issue.Do you have issue only when using the ParquetRecordSetWriter?Unfortunately I can only test with parquet as this file format is somehow mandatory for the current project. NiFi cluster has 3 nodes. the cluster, or the Processor will become invalid. This FlowFile will have an attribute named favorite.food with a value of spaghetti.. Since Output Strategy 'Use The third FlowFile will consist of a single record: Janet Doe. Ubuntu won't accept my choice of password. Apache NiFi - Records and Schema Registries - Bryan Bende However, there are cases Lets assume that the data is JSON and looks like this: Consider a case in which we want to partition the data based on the customerId. option the broker must be configured with a listener of the form: If the SASL mechanism is GSSAPI, then the client must provide a JAAS configuration to authenticate. This is achieved by pairing the PartitionRecord Processor with a RouteOnAttribute Processor. If I were to use ConsumeKafkaRecord, I would have to define a CSV Reader and the Parquet(or CSV)RecordSetWriter and the result will be very bad, as the data is not formatted as per the required schema. Making statements based on opinion; back them up with references or personal experience. Please try again. Specifies the Controller Service to use for reading incoming data, Specifies the Controller Service to use for writing out the records. Each record is then grouped with other like records and a FlowFile is created for each group of like records. What it means for two records to be like records is determined by user-defined properties. Kafka and deliver it to the desired destination. This grouping is also accompanied by FlowFile attributes. 'Record' converts the Kafka Record Key bytes into a deserialized NiFi record, using the associated partitions.nifi-01=0, 3, 6, 9, partitions.nifi-02=1, 4, 7, 10, and partitions.nifi-03=2, 5, 8, 11. Once running, if the number of partitions is changed, the Processor will continue to run but not pull data from the newly