GeoMesa Lambda Quick Start

This tutorial can get you started with the GeoMesa Lambda data store. Note that the Lambda data store is for advanced use-cases - see Overview of the Lambda Data Store for details on when to use a Lambda store.

About this Tutorial

In the spirit of keeping things simple, the code in this tutorial only does a few small things:

  1. Establishes a new (static) SimpleFeatureType
  2. Prepares the Accumulo table and Kafka topic to write this type of data
  3. Creates a few thousand example SimpleFeatures
  4. Repeatedly updates these SimpleFeatures in the Lambda store through Kafka
  5. Visualize the changing data in GeoServer
  6. Persists the final SimpleFeatures to Accumulo
  7. Uses GeoServer to visualize the data (optional)

Background

Apache Kafka is “publish-subscribe messaging rethought as a distributed commit log.”

In the context of GeoMesa, Kafka is a useful tool for working with streams of geospatial data. The Lambda data store leverages a transient in-memory cache of recent updates, powered by Kafka, combined with long-term persistence to Accumulo. This allows for rapid data updates, alleviating the burden on Accumulo from constant deletes and writes.

Prerequisites

Before you begin, you must have the following installed and configured:

  • Java JDK 1.8
  • Apache Maven 3.5.2 or later
  • a GitHub client
  • a Kafka instance version 0.9.x or later
  • an Accumulo 1.9.1 or later instance
  • an Accumulo user that has both create-table and write permissions
  • the GeoMesa distributed runtime installed for your instance (see below)

Ensure your Kafka and Zookeeper instances are running. You can use Kafka’s quickstart to get Kafka/Zookeeper instances up and running quickly.

Installing the GeoMesa Distributed Runtime

Follow the instructions under Installing the Accumulo Distributed Runtime Library to install GeoMesa in your Accumulo instance.

Configure GeoServer (optional)

You can use GeoServer to access and visualize the data stored in GeoMesa. In order to use GeoServer, download and install version 2.12.x. Then follow the instructions in Installing GeoMesa Lambda in GeoServer to enable GeoMesa.

Download and Build the Tutorial

Pick a reasonable directory on your machine, and run:

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

Warning

Make sure that you download or checkout the version of the tutorials project that corresponds to your GeoMesa version. See About Tutorial Versions for more details.

To ensure that the quick start works with your environment, modify the pom.xml to set the appropriate versions for Accumulo, Hadoop, Kafka, Zookeeper, etc.

For ease of use, the project builds a bundled artifact that contains all the required dependencies in a single JAR. To build, run:

$ mvn clean install -pl geomesa-tutorials-accumulo/geomesa-tutorials-accumulo-lambda-quickstart -am

About this Tutorial

The quick start operates by writing several thousand feature updates. The same feature identifier is used for each update, so there will only be a single “live” feature at any one time. After approximately 30 seconds, the updates stop and the feature is persisted to Accumulo.

The data used is from New York City taxi activity data published by the University of Illinois. More information about the dataset is available here.

For this demo, only a single taxi is being tracked.

Running the Tutorial

On the command line, run:

$ java -cp geomesa-tutorials-accumulo/geomesa-tutorials-accumulo-lambda-quickstart/target/geomesa-tutorials-accumulo-lambda-quickstart-${geomesa.version}.jar \
    com.example.geomesa.lambda.LambdaQuickStart        \
    --lambda.accumulo.instance.id <instance>           \
    --lambda.accumulo.zookeepers <accumulo.zookeepers> \
    --lambda.accumulo.user <user>                      \
    --lambda.accumulo.password <password>              \
    --lambda.accumulo.catalog <table>                  \
    --lambda.kafka.brokers <brokers>                   \
    --lambda.kafka.zookeepers <kafka.zookeepers>       \
    --lambda.expiry 2s

where you provide the following arguments:

  • <instance> the name of your Accumulo instance
  • <accumulo.zookeepers> your Accumulo Zookeeper nodes, separated by commas
  • <user> the name of an Accumulo user that has permissions to create, read and write tables
  • <password> the password for the previously-mentioned Accumulo user
  • <table> the name of the destination table that will accept these test records. This table should either not exist or should be empty
  • <brokers> your Kafka broker instances, comma separated. For a local install, this would be localhost:9092
  • <kafka.zookeepers> your Kafka Zookeeper nodes, comma separated. For a local install, this would be localhost:2181

Warning

If you have set up the GeoMesa Accumulo distributed runtime to be isolated within a namespace (see Namespace Install) the value of <table> should include the namespace (e.g. myNamespace.geomesa).

Optionally, you can also specify that the quick start should delete its data upon completion. Use the --cleanup flag when you run to enable this behavior.

Once run, the quick start will create the Kafka topic, then pause and prompt you to register the layer in GeoServer. If you do not want to use GeoServer, you can skip this step. Otherwise, follow the instructions in the next section before returning here.

Once you continue, the tutorial should run for approximately thirty seconds. You should see the following output:

Loading datastore

Creating schema: taxiId:String,dtg:Date,geom:Point

Feature type created - register the layer 'tdrive-quickstart' in geoserver then hit <enter> to continue

Generating test data

Writing features to Kafka... refresh GeoServer layer preview to see changes
Wrote 2202 features

Waiting for expiry and persistence...
Total features: 1, features persisted to Accumulo: 0
Total features: 0, features persisted to Accumulo: 0
Total features: 1, features persisted to Accumulo: 1

Done

Visualize Data With GeoServer (optional)

You can use GeoServer to access and visualize the data stored in GeoMesa. In order to use GeoServer, download and install version 2.12.x. Then follow the instructions in Installing GeoMesa Lambda in GeoServer to enable GeoMesa.

Register the GeoMesa Store with GeoServer

Log into GeoServer using your user and password credentials. Click “Stores” and “Add new Store”. Select the Kafka/Accumulo Lambda (GeoMesa) vector data source, and fill in the required parameters.

Basic store info:

  • workspace this is dependent upon your GeoServer installation
  • data source name pick a sensible name, such as geomesa_quick_start
  • description this is strictly decorative; GeoMesa quick start

Connection parameters:

  • these are the same parameter values that you supplied on the command line when you ran the tutorial; they describe how to connect to the Kafka and Accumulo instances where your data reside

Click “Save”, and GeoServer will search Zookeeper for any GeoMesa-managed feature types.

Publish the Layer

If you have already run the command to start the tutorial, then GeoServer should recognize the tdrive-quickstart feature type, and should present that as a layer that can be published. Click on the “Publish” link. If not, then run the tutorial as described above in Running the Tutorial. When the tutorial pauses, go to “Layers” and “Add new Layer”. Select the GeoMesa Lambda store you just created, and then click “publish” on the tdrive-quickstart layer.

You will be taken to the Edit Layer screen. You will need to enter values for the data bounding boxes. For this demo, use the values MinX: 116.22366, MinY: 39.72925, MaxX: 116.58804, MaxY: 40.09298.

Click on the “Save” button when you are done.

Take a Look

Click on the “Layer Preview” link in the left-hand gutter. If you don’t see the quick-start layer on the first page of results, enter the name of the layer you just created into the search box, and press <Enter>.

At first, there will be no data displayed. Once you have reached this point, return to the quick start console and hit “<enter>” to continue the tutorial. As the data is updated in Kafka, you can refresh the layer preview page to see the feature moving around.

Transient vs Persistent Features

The layer preview will merge the results of features from Kafka with features from Accumulo. You may disable results from one of the source by using the viewparams parameter:

...&viewparams=LAMBDA_QUERY_TRANSIENT:false
...&viewparams=LAMBDA_QUERY_PERSISTENT:false

While the quick start is running, all the features should be returned from the transient store (Kafka). After the quick start finishes, all the feature should be returned from the persistent store (Accumulo). You can play with the viewparams to see the difference.

Looking at the Code

The source code is meant to be accessible for this tutorial. The logic is contained in the generic org.geomesa.example.quickstart.GeoMesaQuickStart in the geomesa-tutorials-common module, and the Kafka/Accumulo-specific org.geomesa.example.lambda.LambdaQuickStart in the geomesa-tutorials-accumulo-lambda-quickstart module. Some relevant methods are:

  • createDataStore get a datastore instance from the input configuration
  • createSchema create the schema in the datastore, as a pre-requisite to writing data
  • writeFeatures overridden in the KafkaQuickStart to simultaneously write and read features from Kafka
  • queryFeatures not used in this tutorial
  • cleanup delete the sample data and dispose of the datastore instance

Looking at the source code, you can see that normal GeoTools FeatureWriters are used; feature persistence is managed transparently for you.

The quickstart uses a small subset of taxi data. Code for parsing the data into GeoTools SimpleFeatures is contained in org.geomesa.example.data.TDriveData:

  • getSimpleFeatureType creates the SimpleFeatureType representing the data
  • getTestData parses an embedded CSV file to create SimpleFeature objects
  • getTestQueries not used in this tutorial

Re-Running the Quick Start

The quick start relies on not having any existing state when it runs. This can cause issues with older versions of Kafka, which by default do not delete topics when requested. To re-run the quick start, first ensure that your Kafka instance will delete topics by setting the configuration delete.topic.enable=true in your server properties. Then use the Lamdba command-line tools (see Setting up the Lambda Command Line Tools) to remove the quick start schema:

$ geomesa-lambda remove-schema -f tdrive-quickstart ...