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README.md
expense_reports.dset
expensereports-data.json
expensereports-mappings.json

README.md

Example - Expense Reports

This document provides the necessary steps and files for running an ElasticSearch server and consuming the services from Dashbuilder by the use of the Elastic Search data provider.

1.- Download ElasticSearch version 2.1.2 from downloads page and follow the installation instructions

2.- In order to perform data set look-ups using FIXED date interval types, groovy dynamic scripting must be enabled in your ElasticSearch server. You can do it by editing the configuration file <EL_HOME>/config/elasticsearch.yml and adding those lines at the end:

script.inline: on
script.indexed: on

3.- Run the ElasticSearch server using the command:

./<EL_HOME>/bin/elasticsearch

Next step is to create the expense reports example index and populate it with some data:

4.- Create the index mappings using the JSON definition found here

curl -XPUT http://localhost:9200/expensereports -d '<JSON_MAPPINGS_DEFINITION>'

5.- Index using bulk operation some example data found here

curl -XPUT http://localhost:9200/_bulk --data-binary @expensereports-data.json

Once index mappings and data are indexed, you can try to query the ElasticSearch server using:

curl -XGET http://localhost:9200/expensereports/_count

You should obtain a resulting value count of 50 documents.

6.- Run Dashbuilder and create a new Data Set in the Authoring area. Create it using the ElasticSearch type and the following parameters:

// Here is an example of a DataSet definition for the expense reports index.                        
{
    "uuid": "expense_reports",
    "provider": "ELASTICSEARCH",
    "name": "Elastic Expense Reports",
    "pushEnabled": true,
    "pushMaxSize": 1024,
    "isPublic": true,
    "serverURL": "localhost:9300",
    "clusterName": "elasticsearch",
    "index": "expensereports",
    "type": "expense",
    "cacheEnabled": false,
    "cacheMaxRows": 1000,
    "columns": [
                {"id": "EXPENSES_ID", "type": "number"},
                {"id": "AMOUNT", "type": "number"},
                {"id": "DEPARTMENT", "type": "label"},
                {"id": "EMPLOYEE", "type": "text"},
                {"id": "CREATION_DATE", "type": "date"},
                {"id": "CITY", "type": "label"},
            ]
}

Once the data set is created, you can start creating your data displayers and dashboards that consume the expense reports index from the ELS server node.

Have fun! :)