Big Data Connectors for Virtual Data Sources

As of JasperReports Server 5.6, virtual data sources can also connect to several flavors of big data:

Cassandra
Hadoop-Hive 1, 2, and Impala
MongoDB

Virtual data sources use the Teiid query engine internally to join the data from various sources, and to access big data stores. In the case of big data, the virtual data source extracts the connection information from the existing data source and uses an internal Teiid connector to access data. The Teiid connectors map the various structures used in each big data model to a relational model with tables and fields. This connector is distinct from what are called the native data sources for big data. For this reason, when a data source for big data is wrapped in a virtual data source, the resulting data source has the following limitations:

The Cassandra, Hadoop, and MongoDB connectors in virtual data sources do not support query parameters ($P and $X). Therefore, if you use a big data connector wrapped in a virtual data source as the data source for a stand-alone query, report or Topic, you can't include parameters to create input controls. When used in Domains and then Ad Hoc views, you can define filters to replace this functionality.
The Cassandra connector for virtual data sources does not support any aggregation functions.
The MongoDB connector for virtual data sources does not support the find operations, aggregation or map reduce functions that the native MongoDB data source allows.
The MongoDB connector for virtual data sources can't be used in stand-alone reports or Topics. It must be used in a Domain and accessed through an Ad Hoc view or report.

However, there are significant advantages to accessing big data through virtual data sources:

When wrapped in a virtual data source, you can access Cassandra, Hadoop, and MongoDB through a Domain, Domain Topic, Ad Hoc view, and Ad Hoc report.
A virtual data source can contain any mix of JDBC, JNDI, and big data connectors. When you define a Domain using this data source, you can access the tables from each store and define joins between compatible fields.
Virtual data sources that use a big data connector support query optimization, unlike the native data sources for big data. In fact, the big data connectors for virtual data sources support query optimization in Ad Hoc views and reports based on stand-alone Topics, and in Ad hoc views and reports based on Domains. The only exceptions are calculated fields, which cannot be optimized when used in Ad Hoc views or reports that are based on Topics or Domains. For more information about query optimization, see See "Ad Hoc Data Policies for Big Data".

For more information about Teiid, see http://www.jboss.org/teiid/.

Creating Big Data Connectors

To create a virtual data source that accesses a data source for big data:

1. Create a native data source for big data, or verify that it was created as described in one of the following sections:
     Cassandra Data Sources
     Hadoop-Hive Data Sources
     MongoDB Data Sources

In the case of a MongoDB data source, you must specify the schema for the tables into which the data will be mapped. If you did not define the table schema, you can edit the data source to add one, but you must restart JasperReports Server after any modifications to the schema value. For more information, see Relational Schema for MongoDB Connector.

2. Create a virtual data source as described in Virtual Data Sources.
3. In the virtual data source creation dialog, select the big data data source that you created in the first step, and save the virtual data source. You can select one or more big data sources, or any mix of big data, JDBC, and JNDI data sources.
4. Create a Domain, specify the virtual data source you just created, and then select the big data tables when you create the Domain schema. The data from the data source is mapped to tables and fields in the Domain that you can use to create joins, filters, and all other features of a Domain.

Relational Schema for MongoDB Connector

This schema defines a relational structure of tables and columns for the data in your MongoDB instance. The following URL gives the syntax for the schema text:

https://docs.jboss.org/author/display/TEIID/MongoDB+Translator

The following example shows a document from the collection named customer in MongoDB with an embedded document named address. The right side shows the corresponding schema for use in the virtual data source connector.

{
    "_id": 10,
    "name": "John Doe",
    "age": 27,
    "gender": "male",
 
    "address": {
        "_id": 10,
        "street": "123 Sesame St.",
        "city": "Anytown",
        "state": "Rhode Island",
        "zip": 12345
    }
}
 
CREATE FOREIGN TABLE customer (
    _id integer PRIMARY KEY, 
    name varchar(255), 
    age integer, 
    gender varchar(50))
OPTIONS(UPDATABLE 'TRUE');
CREATE FOREIGN TABLE address (
    _id integer PRIMARY KEY,
    street varchar(255), 
    city varchar(100), 
    state varchar(25), 
    zip integer,
    FOREIGN KEY (_id) REFERENCES customer (_id), )
OPTIONS(UPDATABLE 'TRUE',
        teiid_mongo:MERGE 'customer');

When writing your schema, keep in mind the following issues:

For embedded relations in MongoDB (both 1-to-1 and 1-to-many), the embedded document must have the same ID as the parent document.
The MongoDB translator supports automatic mapping of Teiid data types into MongoDB data types.
Not all MongoDB data types are supported. Currently, the following types are not supported:
MongoDB Arrays
MongoDB::OID
Regular Expressions
MongoDB::Code
MongoDB::MinKey and MongoDB::MaxKey
As a result, your documents should use integer IDs and not MongoDB::OID.
When you change the mapping or add a new collection in the schema, you must restart JasperReports Server.

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