GeoMesa Twitter provides three example projects to collect, ingest, and analyze Twitter data in GeoMesa.
You'll first need to clone and build the GeoMesa 1.0.0-SNAPSHOT from LocationTech GeoMesa Github.
Checkout, build, and install GeoMesa with maven:
git clone [email protected]:locationtech/geomesa.git
cd geomesa
mvn clean install
Next clone geomesa-twitter and build geomesa-twitter:
git clone [email protected]:geomesa/geomesa-twitter.git
cd geomesa-twitter
mvn clean install
Sign up for twitter and get developer keys...more info coming soon
Run the ingest jar to see a list of arguments for ingest:
$> java -jar twitter-ingest/target/twitter-ingest-accumulo1.5-1.0-SNAPSHOT.jar
0 [main] INFO geomesa.example.twitter.ingest.Runner - Error parsing arguments: The following options are required: --instanceId, -i --zookeepers, -z --tableName, -t --password, -p --user, -u --featureName, -f
Usage: <main class> [options] files
Options:
* --featureName, -f
featureName to assign to the data
--indexSchemaFormat
Schema for indexing data
* --instanceId, -i
Name of the Accumulo Instance
* --password, -p
Accumulo password
--shards, -s
number of shards to use for data
* --tableName, -t
Accumulo table name
--useExtendedFeatures
parse extended features or the minimal set
* --user, -u
Accumulo user name
* --zookeepers, -z
Comma separated list of zookeepers
After collecting some twitter data, you can ingest files which have one tweet as JSON per line:
java -jar twitter-ingest/target/twitter-ingest-accumulo1.5-1.0-SNAPSHOT.jar -u user -p password -z zoo1,zoo2,zoo3 -t geomesa_catalog -i my instance -f twitter tweet_file1.json tweet_file2.json tweet_file3.json
After setting up spark on your cluster, copy the shade jar over and run it:
/opt/spark/bin/spark-submit --master yarn-client --num-executors 40 --executor-cores 4 twitter-spark-accumulo1.5-1.0-SNAPSHOT.jar --deploy-mode client --class geomesa.example.twitter.spark.Runner twitter
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