The PartitionRecord processor allows you to group together "like data." We define what it means for two Records to be "like data" using RecordPath. For the sake of these examples, let's assume that our input We will have administration capabilities via Apache Ambari. attempting to compile the RecordPath. As such, the tutorial needs to be done running Version 1.2.0 or later. By default, this processor will subscribe to one or more Kafka topics in such a way that the topics to consume from are randomly assigned to the nodes in the NiFi cluster. The second FlowFile will consist of a single record: Jacob Doe. Select the arrow icon next to "AvroSchemaRegistry" and select the View Details button ("i" icon) to see its properties: Close the window for the AvroSchemaRegistry. in which case its value will be unaltered). Each dynamic property represents a RecordPath that will be evaluated against each record in an incoming FlowFile. A RecordPath that points to a field in the Record. by looking at the name of the property to which each RecordPath belongs. Specifies the Controller Service to use for reading incoming data, Specifies the Controller Service to use for writing out the records. For most use cases, this is desirable. The complementary NiFi processor for sending messages is PublishKafkaRecord_1_0. Node 3 will then be assigned partitions 6 and 7. ssl.client.auth property. The Processor will not generate a FlowFile that has zero records in it. Select the View Details button ("i" icon) next to the "JsonRecordSetWriter" controller service to see its properties: Schema Write Strategy is set to "Set 'schema.name' Attribute", Schema Access Strategy property is set to "Use 'Schema Name' Property" and Schema Registry is set to AvroSchemaRegistry. Now, we could instead send the largeOrder data to some database or whatever wed like. Start the PartitionRecord processor. There have already been a couple of great blog posts introducing this topic, such as Record-Oriented Data with NiFi and Real-Time SQL on Event Streams.This post will focus on giving an overview of the record-related components and how they work together, along with an example of using an . If the broker specifies ssl.client.auth=required then the client will be required to present a certificate. The result will be that we will have two outbound FlowFiles. immediately to the FlowFile content. Pretty much every record/order would get its own FlowFile because these values are rather unique. If will contain an attribute ConsumeKafka ----> MergeContent (as I have plenty of small files I prefer to merge them in bigger files for further processing) ----> ReplaceText (I have some empty spaces and I want them removed) ---> PartitionRecord. In order to use this option the broker must be configured with a listener of the form: This option provides an encrypted connection to the broker, with optional client authentication. We can then add a property named morningPurchase with this value: And this produces two FlowFiles. In this scenario, if Node 3 somehow fails or stops pulling data from Kafka, partitions 6 and 7 may then be reassigned to the other two nodes. [NiFi][PartitionRecord] When using Partition Recor CDP Public Cloud: April 2023 Release Summary, Cloudera Machine Learning launches "Add Data" feature to simplify data ingestion, Simplify Data Access with Custom Connection Support in CML, CDP Public Cloud: March 2023 Release Summary. Once one or more RecordPath's have been added, those RecordPath's are evaluated against each Record in an incoming FlowFile. The name of the property becomes the name of the FlowFile attribute that gets added to each FlowFile. To better understand how this Processor works, we will lay out a few examples. Specifically, we can use the ifElse expression: We can use this Expression directly in our PublishKafkaRecord processor as the topic name: By doing this, we eliminate one of our PublishKafkaRecord Processors and the RouteOnAttribute Processor. This limits you to use only one user credential across the cluster. for data using KafkaConsumer API available with Kafka 2.6. So, if we have data representing a series of purchase order line items, we might want to group together data based on the customerId field. - edited For example, here is a flowfile containing only warnings: A RouteOnAttribute processor is next in the flow. We can add a property named state with a value of /locations/home/state. This limits you to use only one user credential across the cluster. The name given to the dynamic property is the name of the attribute that will be used to denote the value of the associated RecordPath. However, if the RecordPath points to a large Record field that is different for each record in a FlowFile, then heap usage may be an important consideration. Topics that are to be consumed must have the same number of partitions. Which was the first Sci-Fi story to predict obnoxious "robo calls"? We now add two properties to the PartitionRecord processor. For example, we might decide that we want to route all of our incoming data to a particular Kafka topic, depending on whether or not its a large purchase. For example, we can use a JSON Reader and an Avro Writer so that we read incoming JSON and write the results as Avro. record, partition, recordpath, rpath, segment, split, group, bin, organize. An unknown error has occurred. A custom record path property, log_level, is used to divide the records into groups based on the field level. the key is complex, such as an Avro record. Each dynamic property represents a RecordPath that will be evaluated against each record in an incoming FlowFile. Once all records in an incoming FlowFile have been partitioned, the original FlowFile is routed to this relationship. The GrokReader references the AvroSchemaRegistry controller service. are handled. See the description for Dynamic Properties for more information. Out of the box, NiFi provides many different Record Readers. Uses a JsonRecordSetWriter controller service to write the records in JSON format. However, it can validate that no The value of the property must be a valid RecordPath. The records themselves are written However, for any RecordPath whose value is not a scalar value (i.e., the value is of type Array, Map, or Record), no attribute will be added. This FlowFile will have an attribute named state with a value of NY. Janet Doe has the same value for the first element in the favorites array but has a different home address. 03-28-2023 Receives Record-oriented data (i.e., data that can be read by the configured Record Reader) and evaluates one or more RecordPaths against the each record in the incoming FlowFile. Its contents will contain: The second FlowFile will have an attribute named customerId with a value of 333333333333 and the contents: Now, it can be super helpful to be able to partition data based purely on some value in the data. Two records are considered alike if they have the same value for all configured RecordPaths. Each record is then grouped with other "like records". See the description for Dynamic Properties for more information. What it means for two records to be "like records" is determined by user-defined properties. Asking for help, clarification, or responding to other answers. The table also indicates any default values. When a message is received A very common use case is that we want to route all data that matches some criteria to one destination while all other data should go elsewhere. The "GrokReader" controller service parses the log data in Grok format and determines the data's schema. The user is required to enter at least one user-defined property whose value is a RecordPath. used. Say we want to partition data based on whether or not the purchase time was before noon. PartitionRecord allows us to achieve this easily by both partitioning/grouping the data by the timestamp (or in this case a portion of the timestamp, since we dont want to partition all the way down to the millisecond) and also gives us that attribute that we need to configure our PutS3 Processor, telling it the storage location. The third FlowFile will consist of a single record: Janet Doe. 03-28-2023 This makes it easy to route the data with RouteOnAttribute. It can be used to filter data, transform it, and create many streams from a single incoming stream. For each dynamic property that is added, an attribute may be added to the FlowFile. Now, you have two options: Route based on the attributes that have been extracted (RouteOnAttribute). For example, if we have a property named country with a value of /geo/country/name, then each outbound FlowFile will have an attribute named country with the value of the /geo/country/name field. Why did DOS-based Windows require HIMEM.SYS to boot? What it means for two records to be "like records" is determined by user-defined properties. In this case, both of these records have the same value for both the first element of the "favorites" array Dynamic Properties allow the user to specify both the name and value of a property. What should I follow, if two altimeters show different altitudes? My flow is as follows: ConsumeKafka ----> MergeContent (as I have plenty of small files I prefer to merge them in bigger files for further processing) ----> ReplaceText (I have some empty spaces and I want them removed) ---> PartitionRecord. This will then allow you to enable the GrokReader and JSONRecordSetWriter controller services. This tutorial was tested using the following environment and components: Import the template: . Then, instead of explicitly specifying the topic to send to as large-purchases or smaller-purchases we can use Expression Language to determine which topic it goes to. Each dynamic property represents a RecordPath that will be evaluated against each record in an incoming FlowFile. partitionrecord-groktojson.xml. ConvertRecord, SplitRecord, UpdateRecord, QueryRecord. The user is required to enter at least one user-defined property whose value is a RecordPath. The name of the attribute is the same as the name of this property. And we definitely, absolutely, unquestionably want to avoid splitting one FlowFile into a separate FlowFile per record! 565), Improving the copy in the close modal and post notices - 2023 edition, New blog post from our CEO Prashanth: Community is the future of AI. RouteOnAttribute sends the data to different connections based on the log level. When the value of the RecordPath is determined for a Record, an attribute is added to the outgoing FlowFile. Additionally, if partitions that are assigned You can choose to fill any random string, such as "null". The first will contain an attribute with the name Receives Record-oriented data (i.e., data that can be read by the configured Record Reader) and evaluates one or more RecordPaths against the each record in the incoming FlowFile. 'parse.failure' relationship.). This FlowFile will have no state attribute (unless such an attribute existed on the incoming FlowFile, in which case its value will be unaltered). 01:31 PM. More details about these controller services can be found below. The number of records in an outgoing FlowFile, The MIME Type that the configured Record Writer indicates is appropriate, All partitioned FlowFiles produced from the same parent FlowFile will have the same randomly generated UUID added for this attribute, A one-up number that indicates the ordering of the partitioned FlowFiles that were created from a single parent FlowFile, The number of partitioned FlowFiles generated from the parent FlowFile.