12.2. Processors

GeoMesa NiFi provides several processors:




Ingest data into a GeoMesa data store using a GeoMesa converter


Ingest data into a GeoMesa data store using the NiFi record API


Ingest GeoAvro files into a GeoMesa data store


Update existing records in a GeoMesa data store using the NiFi record API


Read GeoMesa Kafka messages and output them as NiFi records


Create files in a variety of geometry-enabled formats using a GeoMesa converter

Each processor (with the exception of ConvertToGeoFile) needs to be configured with a DataStoreService, which will connect to the GeoMesa back-end data source (for example, HBase or Kafka). See Data Store Services for the available services.

12.2.1. Records, Converters, and Avro

GeoMesa provides three different ingest processors. They all write to the same data stores, but they vary in how the input data is converted into GeoTools SimpleFeatures (which are necessary for ingest).

The PutGeoMesa processor uses the GeoMesa Converters framework to define SimpleFeatureTypes and the mapping from input files to SimpleFeatures. Converters can be re-used in the GeoMesa command-line tools and other non-NiFi projects. See Converter Processors for details.

The PutGeoMesaRecord processor uses the NiFi records API to define the input schema using a NiFi RecordReader. Through RecordReaders, SimpleFeatureTypes can be managed in a centralized schema registry. Similarly, records can be manipulated using standard NiFi processors before being passed to the GeoMesa processor. The use of standard NiFi APIs greatly reduces the amount of GeoMesa-specific configuration required. See Record Processors for details.

Finally, the AvroToPutGeoMesa processor will ingest GeoMesa-specific GeoAvro files without any configuration. GeoAvro is a special Avro file that has SimpleFeatureType metadata included. It can be produced using the GeoMesa command-line tools export in avro format, the ConvertToGeoFile processor, the GeoAvroRecordSetWriterFactory record writer factory, or directly through an instance of org.locationtech.geomesa.features.avro.io.AvroDataFileWriter. GeoAvro is particularly useful because it is self-describing. See Avro Processors for details.

12.2.2. Common Configuration

All types of input processors have some common configuration parameters for controlling data store writes:



DataStore Service

Controller service to manage the GeoMesa data store being used

Write Mode

Use an appending writer (for new features) or a modifying writer (to update existing features)

Identifying Attribute

When using a modifying writer, the attribute used to uniquely identify the feature. If not specified, will use the feature ID

Schema Compatibility

Controls how differences between the configured schema and the existing schema in the data store (if any) will be handled.

  • Existing will use the existing schema and drop any additional fields in the configured schema.

  • Update will update the existing schema to match the configured schema.

  • Exact requires the configured schema to match the existing schema.


Enable caching of feature writers between flow files, useful if flow files have a small number of records (see below)


How often feature writers will be flushed to the data store, if caching is enabled Feature Writer Caching

Feature writer caching can be used to improve the throughput of processing many small flow files. Instead of a new feature writer being created for each flow file, writers are cached and re-used between operations. If a writer is idle for the configured timeout, then it will be flushed to the data store and closed.

Note that if feature writer caching is enabled, features that are processed may not show up in the data store immediately. In addition, any features that have been processed but not flushed may be lost if NiFi shuts down unexpectedly. To ensure data is properly flushed, stop the processor before shutting down NiFi.

Alternatively, NiFi’s built-in MergeContent processor can be used to batch up small files.