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/*
 * ModeShape (http://www.modeshape.org)
 * See the COPYRIGHT.txt file distributed with this work for information
 * regarding copyright ownership.  Some portions may be licensed
 * to Red Hat, Inc. under one or more contributor license agreements.
 * See the AUTHORS.txt file in the distribution for a full listing of 
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 *
 * ModeShape is free software. Unless otherwise indicated, all code in ModeShape
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 * published by the Free Software Foundation; either version 2.1 of
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 * ModeShape is distributed in the hope that it will be useful,
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 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
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 */
/**
 * 

The Query API provides a mechanism for building and executing queries. The framework * provides a reusable and extensible query engine that is capable of planning, validating, optimizing, and executing queries * against a generic back-end system. Simply subclass the {@link org.modeshape.jcr.query.process.QueryProcessor} * that creates a {@link org.modeshape.jcr.query.process.ProcessingComponent} * to operates against the back-end system, and assemble a {@link org.modeshape.jcr.query.process.QueryEngine} that can be used to provide a rich * query capability. *

*

Abstract query model

*

* At the heart of the entire query system is a single representation of what constitutes a query. The * {@link org.modeshape.jcr.query.model abstract query model} defines a language-independent vocabulary * for queries, and consists of a family of Java classes each represent the important semantic elements * needed to fully define a query. *

*

* There are two ways to construct abstract query models. The first is to programmatically construct a query * model using the {@link org.modeshape.jcr.query.QueryBuilder}, which provides a fluent API that makes it easy to create a query * with Java code. The second (and more common) approach is to use a {@link org.modeshape.jcr.query.parse.QueryParser} * that parses a query represented in a specific language (like SQL or XPath) and then creates the query's equivalent abstract query model. * There's even a {@link org.modeshape.jcr.query.parse.QueryParsers} class that can manage the parsers for multiple languages. *

*

* The abstract query model classes are immutable, making them very easily shared or reused if that is advantageous. *

*

SQL language

*

* One of the {@link org.modeshape.jcr.query.parse.QueryParser} implementation provided out of the box is * the {@link org.modeshape.jcr.query.parse.BasicSqlQueryParser}, which understands a subset of SQL. *

*

QueryEngine

*

* The {@link org.modeshape.jcr.query.process.QueryEngine} is the component that accepts and executes queries expressed as abstract query models. * Each submitted query is planned, validated, optimized, and then processed to compute and return the final * {@link org.modeshape.jcr.query.QueryResults query results}. *

*

* Note that the QueryEngine is thread-safe. *

*

Planning

*

* In the planning stage, a canonical plan is generated for each query. This plan is a tree of {@link org.modeshape.jcr.query.plan.PlanNode} * objects that each represent a different aspect of the query, and is a form that is easily manipulated by subsequent stages. * Any implementation of {@link org.modeshape.jcr.query.plan.Planner} can be used, though a {@link org.modeshape.jcr.query.plan.CanonicalPlanner} * implementation is provided and will be sufficient for most cases. In fact, the subsequent execution steps often * require the plan to be in its canonical form, so for most situations it may be best to simply reuse the CanonicalPlanner * and in other simply extend it. *

*

* Note that query plans are mutable and not thread-safe, meaning that such plans are not intended to be shared * or reused. *

*

Optimization

*

* In the optimization stage, the canonical query plan is evaluated, validated, and manipulated to produce a more * a single optimized query processing plan. The query plan is often changed in situ, although this is not required * of the {@link org.modeshape.jcr.query.optimize.Optimizer} implementations. A library of existing * {@link org.modeshape.jcr.query.optimize.OptimizerRule} classes is provided, though it's very easy to * add more optimizer rules. *

*

* The {@link org.modeshape.jcr.query.optimize.RuleBasedOptimizer} is an implementation that optimizes a query * using a stack of rules. A new stack is created for each rule, though the rules are required to be immutable and thus * often shared and reused. And, the RuleBasedOptimizer is easily subclassed to define a custom stack of rules. *

*

Validation

*

* The canonical planner or the optimization rules have access to the table and column definitions that may be * queried. The query framework does not prescribe the semantics of a table or column, but instead provides * a {@link org.modeshape.jcr.query.validate.Schemata} interface that provides access to the immutable * {@link org.modeshape.jcr.query.validate.Schemata.Table} definitions (that then contain the * {@link org.modeshape.jcr.query.validate.Schemata.Column} and {@link org.modeshape.jcr.query.validate.Schemata.Key} definitions). *

*

* The canonical planner and a number of the provided optimizer rules use the Schemata to verify that the * query is referencing an existing table and columns, whatever they are defined to be. Although any Schemata * implementaiton can be used, the query framework provides an {@link org.modeshape.jcr.query.validate.ImmutableSchemata} * class with a {@link org.modeshape.jcr.query.validate.ImmutableSchemata.Builder builder} with a fluent API * that can create the corresponding immutable table, column and key definitions. *

*

Processing

*

* In the processing stage, the optimized query plan is used to construct and assemble the * {@link org.modeshape.jcr.query.process.ProcessingComponent} that correspond to the various parts of the * quer plan. The resulting components form the basic processing engine for that query. At the bottom are * the "access" components that perform the low-level access of the tuples from the graph container. * Above these are the other components that implement various operations, such as limits, joins (using merge and * nested loop algorithms), unions, intersects, distinct, sorts, and even column projections. At the top is * a single component that produces tuples that represent the results of the query. *

*

* Once the {@link org.modeshape.jcr.query.process.QueryProcessor} creates the ProcessingComponent assembly, * the top-level component is executed. Execution involves requesting from the child processing component(s) the next batch of results, * processing each of the tuples according to the specific ProcessingComponent algorithm, and finally returning * the processed tuples. *

*

QueryResults

*

* A query over a graph of content will result in a set of nodes that matched the criteria specified in the query. * Each node contained in the results will be identified by its {@link org.modeshape.jcr.cache.NodeKey} as well * as any values for the selected properties. Typically, queries will result in a single node per row, although * joins may result in multiple rows per row. *

*/ package org.modeshape.jcr.query;




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