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This readme contains prerequisite and basic installation guilelines along with end to end execution of HungryHippos application.


This document describes how to install, configure and run HungryHippos clusters.

This document also covers how to run jobs and get their results.


  1. Minimum jdk 1.8 :-

  2. Minimum Ruby 1.9 :-

  3. Chef-solo :- curl -L | bash #installs latest version of chef

  4. Vagrant 1.8.5 :-

  5. vagrant-digitalocean plugin (0.9.1) : vagrant plugin install vagrant-digitalocean; vagrant box add digital_ocean

  6. vagrant-triggers plugin (0.5.3) : vagrant plugin install vagrant-triggers

  7. git :- git need to be installed in the machine so that you can clone the project.

  8. gradle :- gradle need to be installed in the machine so that you build the project.

    apt-get install gradle .
  9. Preferred Client Configuration

    O/S : Ubuntu 14.04
    RAM: 8 GB
    HARD DISK: Depends on the size of the file to be distributed.
    No.of cores per machine: 4
  10. Preferred Server Configuration

    O/S : Ubuntu 14.04
    RAM: 8 GB
    HARD DISK: Depends on the size of the file to be distributed.
    No.of cores per machine: 4

Installation of Prerequisite softwares on Client

You can install all prerequsite softwares by running ./ or individual scripts inside the basic_install_scripts folder

  1. Go to basic_install_scripts

    cd HungryHippos/basic_install_scripts

1.1 Run to install all the prerequisite software


1.2 To install softwares individually, run respective install-*.sh.

  • To install bc , --mathlib

  • To install chef

* To install oracle-jdk 


 * To install jq , used for json parsing
  * To install ruby 


   * To install vagrant
   * To install virtual Box

NOTE :- If you have some of these softwares already installed, it is better to install rest of the softwares individually. Otherwise they will be overriden.

For other linux distributions, please follow the instructions provided by respectice software distributors.

HungryHippos Cluster setup:

STEP 1. Build the project to create and publish the jars to local maven repository.

gradle clean build publishToMavenLocal

STEP 2. Copy node-*.jar to the hhspark_automation/distr_original/lib folder

cp node/build/libs/node-*.jar hhspark_automation/distr_original/lib

STEP 3. Setting Cluster Properties

  1. Go to the scripts folder inside the hhspark_automation.

    cd hhspark_automation/scripts
  2. Create file from

 has following variables with default values

    Name Default Value Description
    NODENUM 1 Number of nodes to spawned here 1 node will be spawned
    ZOOKEEPERNUM 1 Number of nodes on which zookeeper has to be installed, ZOOKEEPERNUM should be greater than 0 and ideally should be equal to maximum number of replicas
    PROVIDER digital_ocean Nodes are created on digital_ocean. No other cloud services supported currently
    TOKEN ----------- Token id by which you can access digital ocean api. #for more details refer Token Generation
    IMAGE ubuntu-14-04-x64 Operating system to be used, check
    REGION nyc1 Node spawn location nyc1 -> NewYork Region 1, for further details check
    RAM 8GB The RAM for each node , here 8GB RAM is allocated for each node
    PRIVATE_KEY_PATH /root/.ssh/id_rsa Private sshkey path of the public key that is added in the digital ocean, if its not there please create one and add the public key of it to digital ocean , security settings. refer SSH KEY Generation
    SSH_KEY_NAME vagrant The name of the public ssh key that is added in digital ocean
  3. Create file from

 contains details regarding the port number to used for spark master and spark worker. Override those values if you want to configure some other port number.

    Name Default Value Description
    SPARK_WORKER_PORT 9090 Spark Worker's port number
    SPARK_MASTER_PORT 9091 Spark Master's port number

STEP 4. Execute ./ inside the scripts folder. It will spawn the hungryhippos cluster with required softwares.


After execution of the script.

  1. Spark-2.0.2-bin-hadoop2.7, Oracle JDK (1.8 Version) , Chef-solo (stable,12.17.44) will be downloaded and installed on all servers.

  2. Zookeeper (3.5.1 alpa) will be installed on the specified number of nodes. It will configure to be standalone or as cluster depending on the number of nodes.

  3. "ip_file.txt" file is created at ~/HungryHippos/hhspark_automation/scripts location. This file contain all the ips of nodes created in cluster. The first entry in this file is spark master-ip.

  4. User can open spark Web UI at <master-ip>:<port> for monitoring purpose. By default <port> is 8080. But there are chances that port 8080 will be occupied by some other service, in that case user can find the correct port number by logging in master node and check log file created at location /home/hhuser/spark-2.0.2-bin-hadoop2.7/logs/spark-hhuser-org.apache.spark.deploy.master.Master-1-sparkTTW-1.out . In log file user can see something like INFO Utils: Successfully started service 'MasterUI' on port 8081. So port will be 8081.

SSH_KEY Generation

Generate rsa key using below command. It will generate a private key file and a public key file.

NOTE :- Please don't input passphrase.

ssh-keygen -t rsa 

After creating the SSH_KEY( say id_rsa), its necessary to add the public key ( contents to digital ocean.

  • Login to

  • Go to settings and select security. security page will open

  • Click on "Add SSH Key"

  • Copy the content of the public key that was generated by "ssh-keygen -t rsa" command to the content box, and give it a name.

  • This name should be used to set the SSH_KEY_NAME in the

Token Generation

  • Login to

  • Click on API Tab

  • Click on Generate New Token

  • Provide token name and click on Generate Token

  • Copy the token value, as it will not be shown again.

Destroy Server (Digital ocean nodes created)

  • To destroy the server nodes execute ./ that is present inside the scripts folder.


HungryHippos Version : 0.7.0v

Sharding :

Sharding is the initial step in the enitre HungryHippos ecosystem. User will have to perform sharding prior to data publish. To perform sharding, a sample file (that represents the near distribution of the actual data file) is required which finally creates "sharding table". Data publish requires this "sharding table" during execution.

NOTE: User has to configure sharding configurations before performing the Sharding.

Configure sharding xml files :

Creating sharding-client-config.xml and sharding-server-config.xml file from template files.

cp hhspark_automation/distr/config/sharding-client-config.xml.template hhspark_automation/distr/config/sharding-client-config.xml
cp hhspark_automation/distr/config/sharding-server-config.xml.template hhspark_automation/distr/config/sharding-server-config.xml

1. sharding-client-config.xml

Assuming your input file contains lines with just two fields like below. The fields are separrated using comma i.e "," as delimiter.


Mobile is the column name given to field1 . i.e; samsung | apple | nokia
Number is the column name given to field2 . i.e; 7890566 | 865478 ..

Purpose :

The purpose of this file is to provide the data description of input file, dimensions on which sharding needs to be done and the distributed path of input file in HungryHippo file system.

A sample sharding-client-config.xml file looks like below :


Explaination :

Name Value Description
tns:sample-file-path <sample-file-path> Path of the sample file on which sharding needs to be done
tns:distributed-file-path <distributed-path> Path on HungryHippo filesystem where input file will be stored
tns:data-description - Colume elements inside it will hold the description of columns in record
tns:column - will hold the column description in record
tns:name Mobile Name of the column
tns:data-type INT, LONG, DOUBLE, STRING data-type of the column. Can contain one of the values
given here.
tns:size 0 size of data-type. max number of characters for String and 0 for other datatypes
tns:data-parser-config - By default HungryHippos CsvDataParser provided
tns:class-name HungryHippos provides it's own data parser
tns:sharding-dimensions Mobile,Number comma separeted column names which user has identified as dimensions
tns:maximum-size-of-single-block-data 80 Max size of a single record in text format
tns:bad-records-file-out <local-file-path> file path for storing records which does not fulfil the data-description given above

2. sharding-server-config.xml

The purpose of this file is to provide the number of buckets the sharding module should create for given input data file.

A sample sharding-server-config.xml file looks like below :

  xsi:schemaLocation=" sharding-server-config.xsd ">


Explaination :

Name Value description
tns:maximum-shard-file-size-in-bytes 200428800 Maximum size of the sharding file in bytes
tns:maximum-no-of-shard-buckets-size 20 Maximum number of buckets user wants to create

Note :

A bucket represents a container for a key or a combination of keys. The Sharding module creates a number of buckets mentioned in property tns:maximum-no-of-shard-buckets-size. Each record sharding module processes will be mapped to one of these buckets based on the key or combination of keys.

Sharding-module Execution

Command :

Execute the following command from project parent folder.

java -cp data-publisher/build/libs/data-publisher-0.7.0.jar com.talentica.hungryHippos.sharding.main.ShardingStarter <client-config.xml> <sharding-conf-path>

Command line arguments descriptions :

  1. client-config.xml: provide the client-config.xml file path which is available in hhspark_automation/distr/config/client-config.xml

  2. sharding-conf-path : parent folder path of sharding configuration files. i.e. hhspark_automation/distr/config

Example :

java -cp data-publisher/build/libs/data-publisher-0.7.0.jar com.talentica.hungryHippos.sharding.main.ShardingStarter  hhspark_automation/distr/config/client-config.xml hhspark_automation/distr/config

Data publish :

Data publish allows the user to publish data across the cluster of machines from client machine.This distributed data become eligible to get executed during job execution. Execute the following command to start data publish from project's parent folder.

Command :

java -cp data-publisher/build/libs/data-publisher-0.7.0.jar com.talentica.hungryHippos.master.DataPublisherStarter <client-config.xml> <input-data> <distributed-file-path> <optional-args>

Command line arguments descriptions :

  1. client-config.xml: provide the client-config.xml file path which is available in hhspark_automation/distr/config/client-config.xml
  2. input-data : provide path of input data set with file name. Currently we support text and csv files only in which fields need be comma seperated.
  3. distributed-file-path : This path should be exactly same as provided in "sharding-client-config.xml" having field name "distributed-file-path".
  4. optional-args : You can provide the optional argument for chunk size (in bytes). Otherwise 128 MB will be considered as the chunk size. The input data file is splitted into small parts called Chunks, which are published to nodes where they are processed and stored.

Example :

 java -cp data-publisher/build/libs/data-publisher-0.7.0.jar com.talentica.hungryHippos.master.DataPublisherStarter hhspark_automation/distr/config/client-config.xml ~/dataGenerator/sampledata.txt /dir/input > logs/datapub.out 2> logs/datapub.err &         

Job Execution Module :

As soon as data publish is completed, cluster machines are ready to accept the command to execute the jobs. To execute the jobs, client should write the jobs and submit it with spark submit command. Moreover, you can find the examples as to how to write the jobs in module "examples" with package com.talentica.hungryhippos.examples namely SumJob and UniqueCountJob.

Steps :

  1. In the build.gradle of your project add mavenLocal and mavenCentral in gradle repository and add the dependency for hungryhippos client api and hhrdd.
repositories {

compile 'com.talentica.hungry-hippos:client-api:0.7.0'
compile 'com.talentica.hungry-hippos:hhrdd:0.7.0'
  1. Write the job using HungryHippos custom spark implementation. Refer Examples to have an overview.

  2. Build your job jar.

  3. Transfer above created jar(say, test.jar) along with dependency jars such as "hhrdd-0.7.0.jar" available in location hhrdd/build/libs to spark "master" node in directory "/home/hhuser/distr/lib_client. Run the following commands in project parent folder:

    scp hhrdd/build/libs/hhrdd-0.7.0.jar hhuser@<master-ip>:/home/hhuser/distr/lib_client
    scp <path to test.jar>  hhuser@<master-ip>:/home/hhuser/distr/lib_client

Note :

User can get all cluster nodes' IP from file ~/HungryHippos/hhspark_automation/scripts/ip_file.txt. First entry in ip_file.txt file represents the IP of spark master node i.e. <master-ip> 5. Run the following command in spark installation directory (/home/hhuser/spark-2.0.2-bin-hadoop2.7) on spark master node:

User can follow the below command to run the above jobs or alternatively can follow the spark job submission command.

Note 1 User has to provide path to client-config path in the driver program. User has to ensure that the path to the client-config path is valid.

Note 2 User has to mention dependency-jars local:///home/hhuser/distr/lib/node-0.7.0.jar,/home/hhuser/distr/lib_client/hhrdd-0.7.0.jar.

Command :

./bin/spark-submit --class <job-main-class> --master spark://<master-ip>:<port> --jars <dependency-jars> <application-jar> [application-arguments]

Command line arguments descriptions :

8 GB Memory / 80 GB Disk / NYC1 - Ubuntu 14.04.5 x64

  1. job-main-class : main class of client written jobs. e.g com.talentica.hungryhippos.examples.SumJob
  2. master-ip : spark master ip(First Entry in file ~/HungryHippos/hhspark_automation/scripts/ip_file.txt is master-ip).
  3. port : configured spark master port number.
  4. dependency-jars : all dependency jars with comma separated such as local:///home/hhuser/distr/lib/node-0.7.0.jar,/home/hhuser/distr/lib_client/hhrdd-0.7.0.jar.
  5. application-jar : The jar where the hungryhippos job is implemented.
  6. application-arguments : Arguments passed to the main method of your main class, if any

Example :

./bin/spark-submit --class com.talentica.hungryhippos.examples.SumJob --master spark:// --jars local:///home/hhuser/distr/lib/node-0.7.0.jar,/home/hhuser/distr/lib_client/hhrdd-0.7.0.jar /home/hhuser/distr/lib_client/examples-0.7.0.jar spark:// SumJobType /dir/input /home/hhuser/distr/config/client-config.xml /dir/outputSumJob >logs/SumJob.out 2>logs/SumJob.err &

com.talentica.hungryhippos.examples.SumJob is the class where addition Job is defined. it takes 4 argument first is the spark-master ip with port , application name ,client-config and /dir/outputSumJob location to save the output file in the cluster*.


  1. go to hhspark_automation/scripts.

     cd hhspark_automation/scripts
Command Functionality
./ To download the output file of jobs
./ To kill the data distributor process running on the cluster or To remove input directory
./ To start the data distributor process on the cluster or To copy the distr directory
./ To check the nodes where data distributor is running. Failed server details is also shown
./ To destroy entire cluster