Getting Started with MashZone NextGen Analytics

MashZone NextGen Analytics : Getting Started with MashZone NextGen Analytics

A Basic RAQL Query

Structure, Format and Access to Datasets with RAQL

The RAQL Query Syntax

Use Plain Functions to Update, Select or Sort Rows

Datatype Information for Loaded Datasets

The Stream/Document Boundary

Use an In-Memory Store to Store and Load Datasets for MashZone NextGen Analytics

Group and Analyze Rows

Group and Analyze Rows with Row Detail

Where to Go Next

This topic presents basic examples to help you get comfortable with the features of MashZone NextGen Analytics and the Real-Time Analytics Query Language (RAQL).

Additional query techniques for RAQL are discussed in RAQL Queries and Working with MashZone NextGen Analytics In-Memory Stores.

For some simple examples of mashups and information on the Mashup Samples project, see RAQL Samples.

About the Real-Time Analytics Query Language Examples

Many of the example datasets used in this topic or other topics illustrating RAQL are available as both:

Files in the web-apps-home/presto/WEB-INF/classes folder in the Business Analytics Server.

Hosted resources at http://mdc.jackbe.com/prestodocs/data/file-name.

In a few cases, such as examples for snapshots, you must provide some initial configuration or perform some steps in Business Analytics Hub to make the datasets used in the example available.

Note:

The example datasets used in this topic do not necessarily represent actual load or throughput requirements. Base memory settings for Business Analytics may require tuning to provide adequate performance for actual loads. For more information, see About BigMemory and the MashZone NextGen Analytics In-Memory Stores.

First let’s take a look at a simple RAQL query.

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