# JubaQL Quick Start¶

## JubaQL Requirements¶

The following components are requried to run JubaQL.

Software Version Required Notes
JDK 7
Spark 1.2.1+ [1] [2]
Jubatus 0.8.0 [3]
Only when running JubaQL in Production mode.
Jubatus on YARN 1.0   Only when running JubaQL in Production mode.
 [1] Spark 1.1.x (or earlier), 1.2.0 or 1.3.x (or later) cannot be used.
 [2] Spark must be installed on nodes that run JubaQL Gateway.
 [3] When running JubaQL in Development mode, Jubatus must be installed on nodes that run JubaQL Gateway. When running JubaQL in Production mode, Jubatus must be installed on all YARN nodes.

To build JubaQL or Jubatus on YARN, you need to install sbt command.

### Using Maven Repository¶

When using Jubatus on YARN from your Scala application, you can use the Maven repository. Add the following to the build.sbt file of your project.

// Jubatus Maven Repository

// Dependencies
libraryDependencies ++= Seq(
"us.jubat"                   %% "jubatus-on-yarn-client"    % "1.0"
)


## Development mode¶

For development purposes, it is possible to run gateway and processor without a Hadoop cluster. In this case the gateway will not start the processor using YARN but as a local process.

Get a Hadoop-enabled version of Apache Spark 1.2.2:

wget http://d3kbcqa49mib13.cloudfront.net/spark-1.2.2-bin-hadoop2.4.tgz


and unpack it

tar -xzf spark-1.2.2-bin-hadoop2.4.tgz && export SPARK_DIST="$(pwd)/spark-1.2.2-bin-hadoop2.4/"  Build JubaQLClient git clone https://github.com/jubatus/jubaql-client.git cd jubaql-client && sbt start-script && cd ..  Build JubaQLServer git clone https://github.com/jubatus/jubaql-server.git cd jubaql-server/processor && sbt assembly && cd ../.. cd jubaql-server/gateway && sbt assembly && cd ../..  ### Test the setup¶ In order to test that your setup is working correctly, you can do a simple classification using the data from the shogun example. The training data is located at ./jubaql-server/data/shogun_data.json. Start the JubaQLGateway cd jubaql-server && \ java -Dspark.distribution="$SPARK_DIST" \
-Djubaql.processor.fatjar=processor/target/scala-2.10/jubaql-processor-assembly-1.3.0.jar \
-jar gateway/target/scala-2.10/jubaql-gateway-assembly-1.3.0.jar \
-i 127.0.0.1


In a different shell, start the JubaQLClient:

./jubaql-client/target/start

• You will see the prompt jubaql> in the shell and you will in fact be able to type your commands there, but until the JubaQLProcessor is up and running correctly, you will see the message: “This session has not been registered. Wait a second.”

Run the following JubaQL commands in the client:

CREATE CLASSIFIER MODEL test (label: label) AS name WITH unigram CONFIG '{"method": "AROW", "parameter": {"regularization_weight" : 1.0}}'
CREATE DATASOURCE shogun (label string, name string) FROM (STORAGE: "file://jubaql-server/data/shogun_data.json")
UPDATE MODEL test USING train FROM shogun
START PROCESSING shogun
ANALYZE '{"name": "慶喜"}' BY MODEL test USING classify
SHUTDOWN


## Run on YARN with local gateway¶

The gateway itself is not a YARN application, it only launches a YARN application. Therefore it is also possible to run the gateway on the user’s machine, as long as the firewall permits access to the YARN cluster.

To run JubaQL with a local gateway, do the following:

• Set up a Hadoop cluster with YARN and HDFS in place, for example using Cloudera Manager or one of the Hortonworks Packages.
• Install Jubatus on all cluster nodes.
• Get JubaQL and compile it as described above. (This time, Jubatus is not required locally.)
• Install the Jubatus on YARN libraries in HDFS as described in the instructions. Make sure that the HDFS directory /jubatus-on-yarn/application-master/jubaconfig/ exists and is writeable by the user running the JubaQLProcessor application.

### Test the setup¶

To test the setup, also copy the file shogun-data.json from the JubaQL source tree’s data/ directory to /jubatus-on-yarn/sample/shogun_data.json in HDFS.

hdfs dfs -put ./jubaql-server/data/shogun_data.json /jubatus-on-yarn/sample/


Copy the files core-site.xml, yarn-site.xml, hdfs-site.xml containing your Hadoop setup description from one of your cluster nodes to some directory and point the environment variable HADOOP_CONF_DIR (e.g. /etc/hadoop/conf)to that directory.

cp core-site.xml yarn-site.xml hdfs-site.xml /etc/hadoop/conf


Get your local computer’s IP address that points towards the cluster. On Linux, given the IP address of one of your cluster nodes, this should be possible with something like

export MY_IP=$(ip route get 12.34.56.78 | grep -Po 'src \K.+')  Make sure that this IP address can be connected to from the cluster nodes and no firewall rules etc. are blocking access. Get the addresses of your Zookeeper nodes and concatenate their host:port locations with a comma export MY_ZOOKEEPER=zk1:2181,zk2:2181  Locate a temporary directory in HDFS that Spark can use for checkpointing export CHECKPOINT=hdfs:///tmp/spark  Start the JubaQLGateway cd jubaql-server && \ java -Drun.mode=production \ -Djubaql.checkpointdir=$CHECKPOINT \
-Djubaql.zookeeper=$MY_ZOOKEEPER \ -Dspark.distribution="$SPARK_DIST" \
-Djubaql.processor.fatjar=processor/target/scala-2.10/jubaql-processor-assembly-1.3.0.jar \
-jar gateway/target/scala-2.10/jubaql-gateway-assembly-1.3.0.jar \
-i \$MY_IP


In adifferent shell, start the JubaQLClient

./jubaql-client/target/start


You will see the prompt jubaql> in the shell and you will in fact be able to type your commands there, but until the JubaQLProcessor is up and running correctly, you will see the message: “This session has not been registered. Wait a second.”

In order to test that your setup is working correctly, you can do a simple classification using the shogun-data.json file you copied to HDFS before. Run the following JubaQL commands in the client:

CREATE CLASSIFIER MODEL test (label: label) AS name WITH unigram CONFIG '{"method": "AROW", "parameter": {"regularization_weight" : 1.0}}'
CREATE DATASOURCE shogun (label string, name string) FROM (STORAGE: "hdfs:///jubatus-on-yarn/sample/shogun_data.json")
UPDATE MODEL test USING train FROM shogun
START PROCESSING shogun
ANALYZE '{"name": "慶喜"}' BY MODEL test USING classify
SHUTDOWN


The JSON returned by the ANALYZE statement should indicate that the label “徳川” has the highest score. Note that the score may differ from the result in development since multiple Jubatus instances are used for training.

Note:

• When the JubaQLProcessor is started, first the files spark-assembly-1.2.2-hadoop2.4.0.jar and jubaql-processor-assembly-1.3.0.jar will be uploaded to the cluster and added to HDFS, from where they will be downloaded by each executor. It is possible to skip the upload of the Spark libraries by copying the Spark jar file to HDFS manually and adding the parameter -Dspark.yarn.jar=hdfs:///path/to/spark-assembly-1.2.2-hadoop2.4.0.jar when starting the JubaQLGateway.
• In theory, it is also possible to do the same for the JubaQLProcessor application jar file. However, at the moment we rely on extracting a log4j.xml file from that jar locally before upload, so there is no support for also storing that file in HDFS, yet.

## Run on YARN with remote gateway¶

In general, this setup is very similar to the setup in the previous section. The only difference is that the execution of the gateway takes place on a remote host. Therefore, the jar files for JubaQLProcessor and JubaQLGateway as well as the Hadoop configuration files must be copied there and the JubaQLGateway started there. Also, pass the -h hostname parameter to the JubaQLClient to connect to the remote server.