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Data warehousing
In addition to designing and implementing Informix® dimensional databases, you can use tools to create data warehouse applications and optimize your data warehouse queries.
Informix® Warehouse Accelerator
The Informix® Warehouse Accelerator Administration Guide includes information about installing and configuring the accelerator server, creating data marts, accelerators, and accelerated query tables (AQTs).
Data marts and AQTs
For efficient query processing, the accelerator server must have its own copy of the data. The data is stored in logical collections of related data, or data marts. A data mart specifies the collection of tables that are loaded into an accelerator and the relationships, or references, between these tables.
Types of tables for acceleration
You can load and accelerate data from tables, external tables, synonyms, views, and time series virtual tables.
Load data from views
You can use views to create a data mart and load it with data.

Data warehousing
In addition to designing and implementing Informix® dimensional databases, you can use tools to create data warehouse applications and optimize your data warehouse queries.
- Dimensional databases
  The Informix® Data Warehouse Guide provides information to help you design, implement, and manage dimensional databases, and describes the tools that you can use to create data warehouses and optimize your data warehouse queries.
- Informix® Warehouse Accelerator
  The Informix® Warehouse Accelerator Administration Guide includes information about installing and configuring the accelerator server, creating data marts, accelerators, and accelerated query tables (AQTs).
  - Overview of Informix® Warehouse Accelerator
    Informix® Warehouse Accelerator is a product that you use to improve the performance of your warehouse queries.
  - Installation
    You can install Informix® Warehouse Accelerator on the same computer as the Informix database server, on a separate computer, or on a cluster (including a high-availability cluster).
  - Configuration
    You must configure the accelerator server to work with the Informix® database server.
  - Create an accelerator
    You create an accelerator by connecting the Informix® database server to the accelerator server.
  - Data marts and AQTs
    For efficient query processing, the accelerator server must have its own copy of the data. The data is stored in logical collections of related data, or data marts. A data mart specifies the collection of tables that are loaded into an accelerator and the relationships, or references, between these tables.
    - Accelerated query tables
      Accelerated query tables, or AQTs, store information about data marts that the database server uses to determine which queries can be processed by Informix® Warehouse Accelerator.
    - Data marts
      Typically, data marts contain a subset of the tables in your database. The data marts can also contain a subset of the columns within a table. This configuration is advantageous when you are using the TCP/IP loopback optimization between Informix® and IWA, because it provides a seamless experience for the customer.
    - Create a data mart
      After you configure the accelerator server and set up the connection between an accelerator and the database server, you need to create the data marts.
    - Deploy and load the data mart
      To deploy a data mart, you specify the accelerator that will contain the data mart definition file. When you load a data mart, the related data is unloaded from the Informix® tables and transferred to the accelerator server.
    - Types of tables for acceleration
      You can load and accelerate data from tables, external tables, synonyms, views, and time series virtual tables.
      - Load data from external tables
        You can use external tables to load data directly from flat files or pipes to Informix® Warehouse Accelerator.
      - Load data from views
        You can use views to create a data mart and load it with data.
      - Load data from synonyms
        You can use synonyms to create a data mart and load it with data.
      - Load data from time series virtual tables
        You can use time series virtual tables to create a data mart and load it with data.
      - Example: in-memory acceleration of JSON
        This example shows how you can use Informix® Warehouse Accelerator to accelerate data from JSON collections.
    - Update a data mart
      You can refresh the data in a data mart. You can update the data mart definition when you change the warehouse schema.
    - Drop a data mart
      You can drop a data mart if you no longer need the data mart or if you need to update the data in a data mart.
    - Data marts for time series data
      You can create data marts that contain tables that represent time series data. Typically, such tables are fact tables in the data mart.
  - Turning on query acceleration
    Before queries can be routed to the accelerator server for processing, you must set the use_dwa session environment variable.
  - SQL administration routines
    You can use the Informix® Warehouse Accelerator functions and procedures from the command line or in an application to automate administration tasks.
  - Reversion requirements for Informix Warehouse Accelerator
  - Troubleshooting
  - Sample warehouse schema
    The Informix® Warehouse Accelerator examples use this sample warehouse schema.
  - Sysmaster interface (SMI) pseudo tables for query probing data
    The SMI tables provide a way to access probing data in a relational form, which is most convenient for further processing.

Load data from views

You can use views to create a data mart and load it with data.

The columns contained in the views must consist of data types that are supported by Informix® Warehouse Accelerator, including JSON collections. For example, you can create a view that uses functions that are not supported natively by Informix® Warehouse Accelerator, if the columns that are output in the projection list are data types that are supported by Informix® Warehouse Accelerator.

Views are a projection of a SELECT statement, which can have joins.

The following functions are not supported for data marts that contain views:

ifx_refreshMart()
ifx_setupTrickleFeed()
ifx_dropPartMart()
ifx_loadPartMart()

If the parent table is a view, you must turn off the uniqueness checking on the use_dwa environment variable, and ensure uniqueness by other means.

Queries that are to be accelerated by using a data mart that contains views, must also use the views.