Re: Driver Parallel Lines Language Change.rar
Eui Grey
The JDBC API is the standard that defines how databases are accessed by Java applications. An application configures a datasource that references a JDBC driver. Application code can then be written against the driver, rather than the database. The driver converts the code to the database language. This means that if the correct driver is installed, an application can be used with any supported database.
One of the key concepts in computer programming is the idea of state, essentially a snapshot of various conditions in the system. Most programming languages require a considerable amount of state information, which is generally hidden from the programmer. Often, the computer itself has no idea which piece of information encodes the enduring state. This is a serious problem, as the state information needs to be shared across multiple processors in parallel processing machines. Most languages force the programmer to add extra code to indicate which data and parts of the code are important to the state. This code tends to be both expensive in terms of performance, as well as difficult to read or debug. Explicit parallelism is one of the main reasons for the poor performance of Enterprise Java Beans when building data-intensive, non-OLTP applications.[citation needed]
For parallel operation, only the list needs to be shared; it is the state of the entire program. Thus the task of maintaining state is removed from the programmer and given to the language's runtime. On machines with a single processor core where an implementation designed for parallel operation would simply introduce overhead, this overhead can be removed completely by using a different runtime.
A pioneer dataflow language was BLODI (BLOck DIagram), published in 1961 by John Larry Kelly, Jr., Carol Lochbaum and Victor A. Vyssotsky for specifying sampled data systems.[9] A BLODI specification of functional units (amplifiers, adders, delay lines, etc.) and their interconnections was compiled into a single loop that updated the entire system for one clock tick.
In a 1966 Ph.D. thesis, The On-line Graphical Specification of Computer Procedures,[10] Bert Sutherland created one of the first graphical dataflow programming frameworks in order to make parallel programming easier. Subsequent dataflow languages were often developed at the large supercomputer labs. POGOL, an otherwise conventional data-processing language developed at NSA, compiled large-scale applications composed of multiple file-to-file operations, e.g. merge, select, summarize, or transform, into efficient code that eliminated the creation of or writing to intermediate files to the greatest extent possible.[11] SISAL, a popular dataflow language developed at Lawrence Livermore National Laboratory, looks like most statement-driven languages, but variables should be assigned once. This allows the compiler to easily identify the inputs and outputs. A number of offshoots of SISAL have been developed, including SAC, Single Assignment C, which tries to remain as close to the popular C programming language as possible.
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