19. 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.

19.1. Installation

19.1.1. Install the Processors

Pick a reasonable directory on your machine, and run:

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

To build, 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.

19.1.2. Install the SFTs and Converters

The GeoMesa processors need access to the SFTs 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

19.2. Processors

This project contains four processors:

  • PutGeoMesa - Ingest data into GeoMesa Accumulo with a GeoMesa converter or from geoavro
  • PutGeoMesaKafka - Ingest data into GeoMesa Kafka with a GeoMesa converter or from geoavro
  • PutGeoTools - Ingest data into an arbitrary GeoTools Datastore based on parameters using a GeoMesa converter or avro
  • ConvertToGeoAvro - Use a GeoMesa converter to create geoavro

19.2.1. PutGeoMesa

The PutGeoMesa 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. Descriptions of the properties are given below:

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.
instanceId Accumulo instance ID
zookeepers Comma separated list of zookeeper IPs or hostnames
user Accumulo username with create-table and write permissions
password Accumulo password for given username
visibilities Accumulo scan visibilities
tableName Name of the table to write to. If using namespaces be sure to include that in the name.
writeThreads Number of threads to use when writing data to GeoMesa, has a linear effect on CPU and memory usage
generateStats Enable stats table generation
useMock Use a mock instance of Accumulo
GeoMesa Configuration Service Configuration service to use. More about this feature below.

19.2.1.1. GeoMesa Configuration Service

The PutGeoMesa 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 PutGeoMesa 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 zookeepers, instanceId, user, password and tableName parameters are not required or used.

19.2.2. PutGeoMesaKafka

The PutGeoMesaKafka processor is used for ingesting data into a Kafka backed GeoMesa datastore. This processor only supports Kafka 0.9 and newer. To use this processor first add it to the workspace and open the properties tab of its configuration. Descriptions of the properties are given below:

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.
brokers List of Kafka brokers
zookeepers Comma separated list of zookeeper IPs or hostnames
zkpath Zookeeper path to Kafka instance
namespace Kafka namespace to use
partitions Number of partitions to use in Kafka topics
replication Replication factor to use in Kafka topics
isProducer Flag to mark if this is a producer
expirationPeriod Feature will be auto-dropped (expired) after this delay in milliseconds. Leave blank or use -1 to not drop features.
cleanUpCache Run a thread to clean up the live feature cache if set to true. False by default. Use ‘cleanUpCachePeriod’ to configure the length of time between cache cleanups. Every second by default.

19.2.3. PutGeoTools

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

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.
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.

19.2.4. 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. Descriptions of the properties are given below:

Property Description
Mode Converter or Avro file ingest mode switch.
SftName Name of the SFT on the classpath to use. This property override 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.
OutputFormat Only Avro is supported at this time.

19.3. 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.

19.3.1. 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>

19.4. Reference

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