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A pluggable storage engine is a software layer in the architecture of the MySQL server. It is responsible for abstracting the physical data layer from the logical layers of the server, and provides the low-level input/output (I/O) operations for the server. When a system is developed in a layered architecture, it provides a mechanism for streamlining and standardizing the interfaces between the layers. It is this quality that is used to measure the success of a layered architecture. A powerful feature of layered architectures is the ability to modify one layer and, provided the interfaces do not change, not alter the adjacent layers. MySQL AB has reworked the architecture of MySQL (starting in version 5.0) to incorporate this layered architecture approach. The pluggable storage engine was added in version 5.1 and is the most visible form of that endeavor. The pluggable storage engine empowers systems integrators and developers to use MySQL in environments where the data requires special

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In the PivotTable and PivotChart Wizard, if you select the External data source option in Step 1, you ll have the opportunity to create an OLAP cube from your data source in the final step of the Query Wizard or in Microsoft Query. The OLAP Cube Wizard will guide you through the process.

Compile-time declaration The compile-time declaration is a static crosscutting instruction that allows you to add compile-time warnings and errors upon detecting certain usage patterns. For example, you can declare that it is an error to call any Abstract Window Toolkit (AWT) code from an EJB. The following declaration causes the compiler to issue a warning if any part of the system calls the save() method in the Persistence class. Note the use of the call() pointcut to capture a method call:

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R2 is the same value as X. Thus, the outcome of a sequence of two XORs using the same value produces the original value. To see this feature of the XOR in ...

processing to read and write. Furthermore, the pluggable storage engine architecture allows you to create your own storage engine.

declare warning : call(void Persistence.save(Object)) : "Consider using Persistence.saveOptimized()";

Note The current release of MySQL (5.1.9-beta) does not fully support the pluggable mechanism. A number of

You have an Excel list with each region s sales on separate sheets in your workbook, and want to combine all the data into one pivot table. You created a pivot table and selected the Multiple consolidation ranges option in Step 1 of the PivotTable and PivotChart Wizard, but the pivot table doesn t look like your other pivot tables, and you can t get it to work correctly.

Aspect The aspect is the central unit of AspectJ, in the same way that a class is the central unit in Java. It contains the code that expresses the weaving rules for both dynamic and static crosscutting. Pointcuts, advice, introductions, and declarations are combined in an aspect. In addition to the AspectJ elements, aspects can contain data, methods, and nested class members, just like a normal Java class. We can merge all the code examples from this section together in an aspect as follows:

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modifications are necessary to some of the MySQL source files in order to add and recognize a new storage engine (via the handlerton, which I discuss in a moment). MySQL AB reports that these modifications will be unnecessary in future releases of the MySQL system.

public aspect ExampleAspect { before() : execution(void Account.credit(float)) { System.out.println("About to perform credit operation"); } declare parents: Account implements BankingEntity; declare warning : call(void Persistence.save(Object)) : "Consider using Persistence.saveOptimized()"; }

Creating a pivot table from multiple consolidation ranges allows you to create a pivot table from data in two or more separate lists. However, the result is not the same as a pivot table created from a single Excel list. The first field is placed in the row area, the remaining field names are placed in the column area, and the values in those columns appear in the data area. You can hide or show the column items, and use the page fields to filter the data. However, there s no setting you can change to create a pivot table from multiple consolidation ranges that s a different structure than the standard result.

One reason you would want to do this rather than convert the data to a format that can be ingested by MySQL is the cost of doing that conversion For example, suppose you have a legacy application that your organization has been using for a long time The data that the application has used is valuable to your organization and cannot be duplicated Furthermore, you may need to use the old application Rather than converting the data to a new format, you can create a storage engine that can read and write the data in the old format Other examples include cases where the data and its access methods are such that you require special data handling to ensure the most efficient means of reading and writing the data.

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