原文来源：
Charles Bell.Database System Internals.In: Expert MySQL[M].Apress,Berkeley, CA,2012.455~463
原文：
CHAPTER 11
Database System Internals
This chapter presents some database-system internals concepts in preparation for studying database-system internals at a deeper level. I present more in-depth coverage of how queries are represented internally within the server and how queries are executed. I explore these topics from a more general viewpoint and then close the chapter with a discussion of how you can use the MySQL system to conduct your own experiments with the MySQL system internals. Last, Irsquo;ll introduce the database systemrsquo;s internals experiment project.
Query Execution
Most database systems use either an iterative or an interpretative execution strategy. Iterative methods provide ways to produce a sequence of calls available for processing discrete operations (e.g., join, project, etc.), but are not designed to incorporate the features of the internal representation. Translation of queries into iterative methods uses techniques of functional programming and program transformation. Several algorithms generate iterative programs from relational algebra–based query specifications.
The implementation of the query-execution mechanism creates a set of defined compiled functional primitives, formed using a high-level language, that are then linked together via a call stack or procedural call sequence. When a query-execution plan is created and selected for execution, a compiler (usually the same one used to create the database system) is used to compile the procedural calls into a binary executable. Because of the high cost of the iterative method, compiled execution plans are typically stored for reuse for similar or identical queries.
Interpretative methods, on the other hand, perform query execution using existing compiled abstractions of basic operations. The query-execution plan chosen is reconstructed as a queue of method calls that are each taken off the queue and processed; the results are then placed in memory for use with the next or subsequent calls. Implementation of this strategy is often called lazy evaluation, because the available compiled methods are not optimized for best performance; rather, they are optimized for generality.
MySQL Query Execution Revisited
Query processing and execution in MySQL is interpretive. It is implemented using a threaded architecture whereby each query is given its own thread of execution. Figure 11-1 depicts a block diagram that describes the MySQL query processing methodology.
Figure 11-1. MySQL query execution
When a client issues a query, a new thread is created, and the SQL statement is forwarded to the parser for syntactic validation (or rejection due to errors). As you saw in the previous chapter, the MySQL parser is implemented using a large Lex-YACC script that is compiled with Bison. The parser constructs a data structure used to hold the query. This data structure, or query structure, can be used to execute the query. Once the query structure is created, control passes to the query processor, which performs checks such as verifying table integrity and security access. Once the required access is granted and the tables are opened (and locked if the query is an update), control is passed to individual methods that execute the basic query operations, such as select, restrict, and project. Optimization is applied to the data structure by ordering the lists of tables and operations to form a more efficient query based on common practices. This form of optimization is called a SELECT-PROJECT-JOIN query processor. The results of the query operations are returned to the client using established communication protocols and access methods.
What Is a Compiled Query?
One often confusing area understanding what “compiled” means. A compiled query is an actual compilation of an iterative query-execution plan, but some researchers (such as C. J. Date) consider a compiled query one that has been optimized and stored for future execution. As a result, you must take care when considering using a compiled query. In this work, the use of the word compiled is avoided, because the query optimizer and execution engine do not store the query execution plan for later reuse, nor does the query execution require any compilation or assembly to work.
N Note The concept of a stored procedure is a saved plan—it is compiled, or optimized, for execution at a later date and can be run many times on data that meet its input parameters.
Exploring MySQL Internals
How can you teach someone how an optimizer works without allowing him to get his hands dirty with a project?
Furthermore, how can you be expected to know the internals of a database system without actually seeing them? I answer these questions in this section by discussing how MySQL can be used as an experimental test bed for professionals and academics alike.
Getting Started Using MySQL for Experiments
There are several ways to use MySQL to conduct experiments. For example, you could study the internal components using an interactive debugger, or you could use the MySQL system as a host for your own implementation of internaldatabase technologies. Another useful way to look at how the server behaves internally would be to turn on tracing and read the traces generated by using a server compiled with debug turned on. See Chapter 5 for more details on debug tracing.
If you are going to conduct experiments, use a dedicated server for the experiments. This is important if you plan to use MySQL to develop your own extensions. You donrsquo;t want to risk contamination of your development server by the experiments.
Experimenting with the MySQL Source
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英文原文：
CHAPTER 11
Database System Internals
This chapter presents some database-system internals concepts in preparation for studying database-system internals at a deeper level. I present more in-depth coverage of how queries are represented internally within the server and how queries are executed. I explore these topics from a more general viewpoint and then close the chapter with a discussion of how you can use the MySQL system to conduct your own experiments with the MySQL system internals. Last, Irsquo;ll introduce the database systemrsquo;s internals experiment project.
Query Execution
Most database systems use either an iterative or an interpretative execution strategy. Iterative methods provide ways to produce a sequence of calls available for processing discrete operations (e.g., join, project, etc.), but are not designed to incorporate the features of the internal representation. Translation of queries into iterative methods uses techniques of functional programming and program transformation. Several algorithms generate iterative programs from relational algebra–based query specifications.
The implementation of the query-execution mechanism creates a set of defined compiled functional primitives, formed using a high-level language, that are then linked together via a call stack or procedural call sequence. When a query-execution plan is created and selected for execution, a compiler (usually the same one used to create the database system) is used to compile the procedural calls into a binary executable. Because of the high cost of the iterative method, compiled execution plans are typically stored for reuse for similar or identical queries.
Interpretative methods, on the other hand, perform query execution using existing compiled abstractions of basic operations. The query-execution plan chosen is reconstructed as a queue of method calls that are each taken off the queue and processed; the results are then placed in memory for use with the next or subsequent calls. Implementation of this strategy is often called lazy evaluation, because the available compiled methods are not optimized for best performance; rather, they are optimized for generality.
MySQL Query Execution Revisited
Query processing and execution in MySQL is interpretive. It is implemented using a threaded architecture whereby each query is given its own thread of execution. Figure 11-1 depicts a block diagram that describes the MySQL query processing methodology.
Figure 11-1. MySQL query execution
When a client issues a query, a new thread is created, and the SQL statement is forwarded to the parser for syntactic validation (or rejection due to errors). As you saw in the previous chapter, the MySQL parser is implemented using a large Lex-YACC script that is compiled with Bison. The parser constructs a data structure used to hold the query. This data structure, or query structure, can be used to execute the query. Once the query structure is created, control passes to the query processor, which performs checks such as verifying table integrity and security access. Once the required access is granted and the tables are opened (and locked if the query is an update), control is passed to individual methods that execute the basic query operations, such as select, restrict, and project. Optimization is applied to the data structure by ordering the lists of tables and operations to form a more efficient query based on common practices. This form of optimization is called a SELECT-PROJECT-JOIN query processor. The results of the query operations are returned to the client using established communication protocols and access methods.
What Is a Compiled Query?
One often confusing area understanding what “compiled” means. A compiled query is an actual compilation of an iterative query-execution plan, but some researchers (such as C. J. Date) consider a compiled query one that has been optimized and stored for future execution. As a result, you must take care when considering using a compiled query. In this work, the use of the word compiled is avoided, because the query optimizer and execution engine do not store the query execution plan for later reuse, nor does the query execution require any compilation or assembly to work.
N Note The concept of a stored procedure is a saved plan—it is compiled, or optimized, for execution at a later date and can be run many times on data that meet its input parameters.
Exploring MySQL Internals
How can you teach someone how an optimizer works without allowing him to get his hands dirty with a project?
Furthermore, how can you be expected to know the internals of a database system without actually seeing them? I answer these questions in this section by discussing how MySQL can be used as an experimental test bed for professionals and academics alike.
Getting Started Using MySQL for Experiments
There are several ways to use MySQL to conduct experiments. For example, you could study the internal components using an interactive debugger, or you could use the MySQL system as a host for your own implementation of internaldatabase technologies. Another useful way to look at how the server behaves internally would be to turn on tracing and read the traces generated by using a server compiled with debug turned on. See Chapter 5 for more details on debug tracing.
If you are going to
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