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| e-docs > Liquid Data for WebLogic > Product Overview > Liquid Data Concepts |
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Product Overview
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This section provides an overview of core BEA Liquid Data for WebLogicTM concepts and also some usage information. It contains the following sections:
For an overview of Liquid Data components, see Liquid Data Architecture.
Liquid Data Implements the XQuery Standard
This topic describes XQuery and how Liquid Data implements the XQuery standard. It contains the following sections:
Liquid Data provides a scalable, highly available platform for building and processing XQuery queries. Data Architects can use the Data View Builder tool to create XQuery queries graphically (without needing to code queries in XML), as well as create ad hoc XQuery queries by hand. Client applications can use the Liquid Data Query API or generated Liquid Data Web services to invoke stored XQuery queries programmatically.
XQuery is a standard query language, published by the W3C (World Wide Web Consortium), that uses XML (Extensible Markup Language) notation to define query requests and handle query results. XQuery is designed to be an efficient language in which queries are concise and easily understood. XQuery is flexible enough to query a broad spectrum of data sources, including relational databases, XML documents, Web services, packaged applications, and legacy systems.
Applications of XQuery include filtering a document to produce a table of contents, providing joins across multiple data sources, grouping and aggregates, and queries based on sequential relationships in documents. Joins, in particular, represent a powerful and likely principal use of XQuery in the enterprise. The XQuery language is derived from various sources, including SQL. It even provides a For-Let-Where-Return (FLWR - pronounced "flower") expression. Developers familiar with SQL will find XQuery very easy to learn.
For more information about XQuery, see the following topics on the W3C's Web site:
This section shows an example of XQuery code and sample query results from the Avitek sample. For more information about the Avitek sample, see Running the Samples.
The following code example shows the use of XQuery coding in a sample Order query.
Listing 3-1 XQuery for the Order Query from the Avitek Sample
{-- Generated by Data View Builder 1.1 --}
<CustomerOrderReport>
{
for $PB-WL.CUSTOMER_1 in document("PB-WL")/db/CUSTOMER
where ($PB-WL.CUSTOMER_1/CUSTOMER_ID eq "CUSTOMER_1")
return
<customerOrder>
<CUSTOMER>
<FIRST_NAME>{ xf:data($PB-WL.CUSTOMER_1/FIRST_NAME) }</FIRST_NAME>
<LAST_NAME>{ xf:data($PB-WL.CUSTOMER_1/LAST_NAME) }</LAST_NAME>
<CUSTOMER_ID>{ xf:data($PB-WL.CUSTOMER_1/CUSTOMER_ID) }</CUSTOMER_ID>
<STATE>{ xf:data($PB-WL.CUSTOMER_1/STATE) }</STATE>
<EMAIL_ADDRESS>{ xf:data($PB-WL.CUSTOMER_1/EMAIL_ADDRESS) }</EMAIL_ADDRESS>
<TELEPHONE_NUMBER>{ xf:data($PB-WL.CUSTOMER_1/TELEPHONE_NUMBER)
}</TELEPHONE_NUMBER>
</CUSTOMER>
<wireless_orders>
{
for $PB-WL.CUSTOMER_ORDER_2 in document("PB-WL")/db/CUSTOMER_ORDER
where ($PB-WL.CUSTOMER_1/CUSTOMER_ID eq {--! ppright !--}
$PB-WL.CUSTOMER_ORDER_2/CUSTOMER_ID)
return
<CUSTOMER_ORDER>
<ORDER_DATE>{ xf:data($PB-WL.CUSTOMER_ORDER_2/ORDER_DATE) }
</ORDER_DATE>
<ORDER_ID>{ xf:data($PB-WL.CUSTOMER_ORDER_2/ORDER_ID) }</ORDER_ID>
<CUSTOMER_ID>{ xf:data($PB-WL.CUSTOMER_ORDER_2/CUSTOMER_ID) }
</CUSTOMER_ID>
<SHIP_METHOD>{ xf:data($PB-WL.CUSTOMER_ORDER_2/SHIP_METHOD) }
</SHIP_METHOD>
<TOTAL_ORDER_AMOUNT>
{ xf:data($PB-WL.CUSTOMER_ORDER_2/TOTAL_ORDER_AMOUNT) }
</TOTAL_ORDER_AMOUNT>
</CUSTOMER_ORDER>
}
</wireless_orders>
<broadband_orders>
{
for $XM-BB-CO.CUSTOMER_ORDER_3 in document("XM-BB-CO")/db/CUSTOMER_ORDER
where ($PB-WL.CUSTOMER_1/CUSTOMER_ID eq {--! ppright !--}
$XM-BB-CO.CUSTOMER_ORDER_3/CUSTOMER_ID)
return
<CUSTOMER_ORDER>
<ORDER_DATE>{ xf:data($XM-BB-CO.CUSTOMER_ORDER_3/ORDER_DATE) }
</ORDER_DATE>
<ORDER_ID>{ xf:data($XM-BB-CO.CUSTOMER_ORDER_3/ORDER_ID) }</ORDER_ID>
<CUSTOMER_ID>{ xf:data($XM-BB-CO.CUSTOMER_ORDER_3/CUSTOMER_ID) }
</CUSTOMER_ID>
<SHIP_METHOD>{ xf:data($XM-BB-CO.CUSTOMER_ORDER_3/SHIP_METHOD) }
</SHIP_METHOD>
<TOTAL_ORDER_AMOUNT>
{ xf:data($XM-BB-CO.CUSTOMER_ORDER_3/TOTAL_ORDER_AMOUNT) }
</TOTAL_ORDER_AMOUNT>
</CUSTOMER_ORDER>
}
</broadband_orders>
</customerOrder>
}
</CustomerOrderReport>
The following listing shows the results returned in XML format from the sample Order query.
Listing 3-2 Results for the Order Query from the Avitek Sample
<CustomerOrderReport>
<customerOrder>
<CUSTOMER>
<FIRST_NAME>JOHN_1</FIRST_NAME>
<LAST_NAME>KAY_1</LAST_NAME>
<CUSTOMER_ID>CUSTOMER_1</CUSTOMER_ID>
<STATE>TX</STATE>
<EMAIL_ADDRESS>abc@abc.com</EMAIL_ADDRESS>
<TELEPHONE_NUMBER>4081231234</TELEPHONE_NUMBER>
</CUSTOMER>
<wireless_orders>
<CUSTOMER_ORDER>
<ORDER_DATE>2002-03-06-08:00</ORDER_DATE>
<ORDER_ID>ORDER_ID_1_0</ORDER_ID>
<CUSTOMER_ID>CUSTOMER_1</CUSTOMER_ID>
<SHIP_METHOD>AIR</SHIP_METHOD>
<TOTAL_ORDER_AMOUNT>1000</TOTAL_ORDER_AMOUNT>
</CUSTOMER_ORDER>
<CUSTOMER_ORDER>
<ORDER_DATE>2002-03-06-08:00</ORDER_DATE>
<ORDER_ID>ORDER_ID_1_1</ORDER_ID>
<CUSTOMER_ID>CUSTOMER_1</CUSTOMER_ID>
<SHIP_METHOD>AIR</SHIP_METHOD>
<TOTAL_ORDER_AMOUNT>2000</TOTAL_ORDER_AMOUNT>
</CUSTOMER_ORDER>
</wireless_orders>
<broadband_orders>
<CUSTOMER_ORDER>
<ORDER_DATE>2002-04-09</ORDER_DATE>
<ORDER_ID>ORDER_ID_1_0</ORDER_ID>
<CUSTOMER_ID>CUSTOMER_1</CUSTOMER_ID>
<SHIP_METHOD>AIR</SHIP_METHOD>
<TOTAL_ORDER_AMOUNT>1000.00</TOTAL_ORDER_AMOUNT>
</CUSTOMER_ORDER>
<CUSTOMER_ORDER>
<ORDER_DATE>2002-04-09</ORDER_DATE>
<ORDER_ID>ORDER_ID_1_1</ORDER_ID>
<CUSTOMER_ID>CUSTOMER_1</CUSTOMER_ID>
<SHIP_METHOD>AIR</SHIP_METHOD>
<TOTAL_ORDER_AMOUNT>1500.00</TOTAL_ORDER_AMOUNT>
</CUSTOMER_ORDER>
</broadband_orders>
</customerOrder>
</CustomerOrderReport>
This topic introduces the following key Liquid Data concepts:
For a description of Liquid Data components, see Architecture Components.
In Liquid Data, a data source is a source of information that can be queried. Liquid Data supports querying the following types of data sources:
You use the WebLogic Administration Console to configure access to data sources. For more information, see the following topics in the Liquid Data Administration Guide:
You can use the Data View Builder to design and build queries that query the data sources you have configured, or you can hand-code the XQueries. Queries are built based on source and target schemas that describe the structure of the data queried (source) and returned (target). For more information about creating queries, see Building Queries and Data Views.
A query is a request for information based on explicit criteria. In Liquid Data, queries are created and used in compliance with the XQuery language specification. With the Data View Builder, you can create queries using drag-and-drop in source and target schemas.
Users can specify two types of queries:
A result is the information that a query yields. In Liquid Data, the query result is generated in XML format. The target schema is an XML schema or DTD that describes the shape (structure and legal elements) of the output data—that is, the result of a query. The Liquid Data server runs queries against source data and returns the result of a query the form in which you define for target data.
For more information about queries, results, and target schemas, see Overview and Key Concepts in Building Queries and Data Views.
A data view represents the result of a query that provides a filtered view on the data and information being queried. As such, the data view (query result) is dynamic—it will continue to reshape itself based on any changes that occur in the data it is querying. Data views can be re-used as data sources by saving them in the Liquid Data server repository. For more information about data views, see Overview and Key Concepts and Using Data Views as Data Sources in Building Queries and Data Views.
Liquid Data caches information about commonly executed queries for subsequent, efficient retrieval, thereby enhancing overall system performance. Liquid Data supports two types of caching:
For more information, see Configuring the Query Results Cache in the Liquid Data Administration Guide.
The following techniques help Liquid Data expedite the processing of queries more quickly and efficiently:
Custom functions are user-defined functions that performed specialized tasks. The Data View Builder provides a set of standard functions for use in creating data views and queries. In addition, users can create custom functions, which are implemented in Java code, declared in a custom functions library definition (CFLD) file (in XML format), and then configured in the Administration Console. Once configured, custom functions show up as functions available for use in the Data View Builder. For more information about custom functions, see Using Custom Functions in Invoking Liquid Data Queries Programmatically and Configuring Access to Custom Functions in the Liquid Data Administration Guide.
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