Stream Processing and Analytics.

##How to run locally From command line execute the following commands:

cd $STREAMLINE-HOME
mvn clean install
cd webservice
mvn package
java -cp target/webservice-0.1.0-SNAPSHOT.jar com.hortonworks.streamline.webservice.StreamlineApplication server conf/streamline-dev.yaml

This should start the webserver on localhost port 8080. If you are running storm on the same host you may get java.net.BindException: Address already in use in which case you should modify server section of streamline.yaml.

##Intellij Run -> Edit Configuration -> Application -> StreamlineApplication in the Program argument section add server $STREAMLINE-HOME/webservice/conf/streamline.yaml

Same config can be used to start debugging.

##Bootstrapping webserver with test data cd $STREAMLINE-HOME\bootstrap ./bootstrap.sh

Please see bootstrap.sh which is just bunch of curl commands in case you want to add some other objects to webservice's in memory store.

#Running storm topology First you need to populate your kafka topic, if you have not done so create your kafka topic by executing
kafka-topics.sh --create --topic nest-topic --zookeeper localhost:2181 --replication-factor 1 --partitions 3

Then run the device simulator CLI to post some sample StreamlineMessage containing nest data to your kafka topic. cd $STREAMLINE-HOME
java -cp simulator/target/simulator-0.1.0-SNAPSHOT.jar com.hortonworks.streamline.simulator.CLI -b localhost:9092 -t nest-topic -f simulator/src/main/resources/nest-streamline-messages

Sometimes the command fails with following exceptions: Exception in thread "main" kafka.common.FailedToSendMessageException: Failed to send messages after 3 tries. at kafka.producer.async.DefaultEventHandler.handle(DefaultEventHandler.scala:90) at kafka.producer.Producer.send(Producer.scala:76) at kafka.javaapi.producer.Producer.send(Producer.scala:33) at com.hortonworks.streamline.simulator.CLI.writeToKafka(CLI.java:182) at com.hortonworks.streamline.simulator.CLI.processDataFile(CLI.java:109) at com.hortonworks.streamline.simulator.CLI.main(CLI.java:74) You should verify from kafka's server.properties that the listerner port and host matches. if advertised host is actual hostname like 'HW10960.local' localhost may not work.

You can run the simulator command in a loop or run it multiple times to produce same data again and again.

##HBase set up

Before starting hbase, put the below hbase-site.xml in the hbase config directory so that hbase uses the local ZK instance running in your localhost and localfs for storage so that you dont need to start a separate HDFS server instance.

<configuration>
  <property>
    <name>hbase.rootdir</name>
    <value>file:https:///tmp/hbase</value>
  </property>
  <property>
    <name>hbase.cluster.distributed</name>
    <value>true</value>
  </property>
  <property>
    <name>hbase.zookeeper.quorum</name>
    <value>localhost</value>
  </property>
</configuration>

Now you need to create HBase tables where the StreamlineEvent and Notifications will be stored.

hbase shell

create 'nest', 'cf', 'd'

create 'Notification', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Timestamp_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Rule_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Rule_Status_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Datasource_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Datasource_Status_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Notifier_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

create 'Notifier_Status_Notification', 'ni', 'd', 'f', 's', 'e', 'r', 'nn', 'ts'

UI can be used to create/generate a topology and run that on a storm cluster.

#Accounting for bad tuples in a topology A mechanism has been added so that when messages are being played from a spout in an Streamline topology and they can't successfully be parsed then such messages end up in some persistent storage. The way it works is ParserBolt needs to be supplied with two stream ids using builder methods withParsedTuplesStreamId and withUnparsedTuplesStreamId. The former stream id is mandatory and has to be supplied to the bolt. The latter is optional and can be used tap the tuples that could not be parsed by the parser. Any subsequent component can subscribe to this stream and get the tuples that failed to parse using the field bytes. In sample topology in storm module an HdfsBolt is used to store the unparsed tuples.

#Accessing UI http:https://localhost:8080/ui/index.html