20. GeoMesa NiFi Bundle

NiFi manages large batches and streams of files and data. GeoMesa-NiFi allows you to ingest data into GeoMesa straight from NiFi by leveraging custom processors.

20.1. Installation

20.1.1. Build and Install the Processors

Clone the project from GitHub. Pick a reasonable directory on your machine, and run:

$ git clone https://github.com/geomesa/geomesa-nifi.git
$ cd geomesa-nifi

To build the project, run

$ mvn clean install

To install the GeoMesa processors you will need to copy the geomesa-nifi-nar file from geomesa-nifi/geomesa-nifi-nar/target/geomesa-nifi-nar-$VERSION.nar into the lib/ directory of your NiFi installation.

20.1.2. Install the SFTs and Converters

The GeoMesa processors need access to SimpleFeatureTypes and converters in order to ingest data. There are two ways of providing these to the processors. We can enter the SFT specification string and converter specification string directly in a processor or we can provide these to the processors by placing the SFTs and converters in a file named reference.conf and then putting that file on the classpath. This can be achieved by wrapping this file in a JAR and placing it in the lib/ directory of the NiFi installation. For example you can wrap the reference.conf file in a JAR with this command.

$ jar cvf data-formats.jar reference.conf

To validate everything is correct, run this command. Your results should be similar.

$ jar tvf data-formats.jar
     0 Mon Mar 20 18:18:36 EDT 2017 META-INF/
    69 Mon Mar 20 18:18:36 EDT 2017 META-INF/MANIFEST.MF
 28473 Mon Mar 20 14:49:54 EDT 2017 reference.conf

20.2. Processors

GeoMesa NiFi contains several processors:

Processor Description
PutGeoMesaAccumulo Ingest data into a GeoMesa Accumulo datastore with a GeoMesa converter or from geoavro
PutGeoMesaHBase Ingest data into a GeoMesa HBase datastore with a GeoMesa converter or from geoavro
PutGeoMesaFileSystem Ingest data into a GeoMesa File System datastore with a GeoMesa converter or from geoavro
PutGeoMesaKafka Ingest data into a GeoMesa Kafka datastore with a GeoMesa converter or from geoavro
PutGeoTools Ingest data into an arbitrary GeoTools datastore using a GeoMesa converter or avro
ConvertToGeoAvro Use a GeoMesa converter to create geoavro

20.2.1. Input Configuration

Most of the processors accept similar configuration parameters for specifying the input source. Each datastore-specific processor also has additional parameters for connecting to the datastore, detailed in the following sections.

Property Description
Mode Converter or Avro file ingest mode switch.
SftName Name of the SFT on the classpath to use. This property overrides SftSpec.
ConverterName Name of converter on the classpath to use. This property overrides ConverterSpec.
FeatureNameOverride Override the feature name on ingest.
SftSpec SFT specification String. Overwritten by SftName if SftName is valid.
ConverterSpec Converter specification string. Overwritten by ConverterName if ConverterName is valid.

20.2.2. PutGeoMesaAccumulo

The PutGeoMesaAccumulo processor is used for ingesting data into an Accumulo-backed GeoMesa datastore. To use this processor, first add it to the workspace and open the properties tab of its configuration. For a description of the connection properties, see Accumulo Data Store Parameters.

20.2.2.1. GeoMesa Configuration Service

The PutGeoMesaAccumulo plugin supports NiFi Controller Services to manage common configurations. This allows the user to specify a single location to store the Accumulo connection parameters. This allows you to add new PutGeoMesaAccumulo processors without having to enter duplicate data.

To add the GeomesaConfigControllerService access the Contoller Settings from NiFi global menu and navigate to the ControllerServices tab and click the + to add a new service. Search for the GeomesaConfigControllerService and click add. Edit the new service and enter the appropriate values for the properties listed.

To use this feature, after configuring the service, select the appropriate Geomesa Config Controller Service from the drop down of the GeoMesa Configuration Service property. When a controller service is selected, the standard connection parameters (i.e. zookeeper, instance ID, etc) are not required or used.

20.2.3. PutGeoMesaHBase

The PutGeoMesaHBase processor is used for ingesting data into an HBase-backed GeoMesa datastore. To use this processor, first add it to the workspace and open the properties tab of its configuration. For a description of the connection properties, see HBase Data Store Parameters.

20.2.4. PutGeoMesaFileSystem

The PutGeoMesaFileSystem processor is used for ingesting data into a file system-backed GeoMesa datastore. To use this processor, first add it to the workspace and open the properties tab of its configuration. For a description of the connection properties, see FileSystem Data Store Parameters.

20.2.5. PutGeoMesaKafka

The PutGeoMesaKafka processor is used for ingesting data into a Kafka-backed GeoMesa datastore. This processor supports Kafka 0.9 and newer. To use this processor first add it to the workspace and open the properties tab of its configuration. For a description of the connection properties, see Kafka Data Store Parameters.

20.2.6. PutGeoTools

The PutGeoTools processor is used for ingesting data into any GeoTools compatible datastore. To use this processor first add it to the workspace and open the properties tab of its configuration.

Property Description
DataStoreName Name of the datastore to ingest data into.

This processor also accepts dynamic parameters that may be needed for the specific datastore that you’re trying to access.

20.2.7. ConvertToGeoAvro

The ConvertToGeoAvro processor leverages GeoMesa’s internal converter framework to convert features into Avro and pass them along as a flow to be used by other processors in NiFi. To use this processor first add it to the workspace and open the properties tab of its configuration.

Property Description
OutputFormat Only Avro is supported at this time.

20.3. NiFi User Notes

NiFi allows you to ingest data into GeoMesa from every source GeoMesa supports and more. Some of these sources can be tricky to setup and configure. Here we detail some of the problems we’ve encountered and how to resolve them.

20.3.1. GetHDFS Processor with Azure Integration

It is possible to use the Hadoop Azure Support to access Azure Blob Storage using HDFS. You can leverage this capability to have the GetHDFS processor pull data directly from the Azure Blob store. However, due to how the GetHDFS processor was written, the fs.defaultFS configuration property is always used when accessing wasb:// URIs. This means that the wasb:// container you want the GetHDFS processor to connect to must be hard coded in the HDFS core-site.xml config. This causes two problems. Firstly, it implies that we can only connect to one container in one account on Azure. Secondly, it causes problems when using NiFi on a server that is also running GeoMesa-Accumulo as the fs.defaultFS property needs to be set to the proper HDFS master NameNode.

There are two ways to circumvent this problem. You can maintain a core-site.xml file for each container you want to access but this is not easily scalable or maintainable in the long run. The better option is to leave the default fs.defaultFS value in the HDFS core-site.xml file. We can then leverage the Hadoop Configuration Resources property in the GetHDFS processor. Normally you would set the Hadoop Configuration Resources property to the location of the core-site.xml and the hdfs-site.xml files. Instead we are going to create an additional file and include it last in the path so that it overwrites the value of the fs.defaultFS when the configuration object is built. To do this simply create a new xml file with an appropriate name (we suggest the name of the container). Insert the fs.defaultFS property into the file and set the value.

<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>wasb://container@accountName.blob.core.windows.net/</value>
    </property>
</configuration>

20.4. Reference

For more information on setting up or using NiFi see the Apache NiFi User Guide