Beginner Database Design & SQL Programming Using Microsoft SQL Server 2014
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Specificatii
Learn Microsoft Database Design & SQL Server 2014 Programming SQL
Server 2014 follows just in 2 years after SQL Server 2012 with very
exciting new features. One on the top: in-memory OLTP tables for
superior performance. With abundant computer memory, why keep
tables on slow disk? Developers across the world face database
issues daily. While immersed in procedural languages with loops,
RDBMS forces them to think in terms of sets without loops. It takes
transition. It takes training. It takes experience. Developers are
exposed also to Excel worksheets, or spreadsheets, as they were
called in the not so distant past. So, if you know worksheets, how
hard can databases be? After all, worksheets look pretty much like
database tables, don't they? The big difference is the connections
among well-designed tables. A database is a set of connected
tables, which represent entities in the real world. A database can
be 100 connected tables or 3000. The connection is very simple: row
A in table Alpha has affiliated data with row B in table Beta.
However, even with 200 tables and 300 connections (FOREIGN KEY
references), it takes a good amount of time to become familiar to
the point of having an acceptable working knowledge. The Cemetery
of Computer Languages is expanding. You can see tombstones like
PL/1, Forth, Ada, Pascal, LISP, RPG, APL, SNOBOL, JOVIAL, Algol -
the list goes on. For some, the future is in question:
PowerBuilder, ColdFusion, FORTRAN and COBOL. On the other hand, SQL
is running strong after 3 decades of glorious existence. What is
the difference? The basic difference is that SQL can handle large
datasets in a consistent manner based on mathematical foundations.
You can throw together a computer language easily: assignment
statements, looping, if-then conditional, 300 library functions,
and voila Here is the new language: Mars/1, named after the red
planet to be fashionable with NASA's new Mars robot. However, can
Mars/1 JOIN a table of 1 million rows with a table of 10 million
rows in a second? The success of SQL language is so compelling that
other technologies are tagged onto it like XML/XQuery, which deals
with semi-structured information objects. In SQL you are thinking
at a high level. In C# or Java, you are dealing with details - lots
of them. That is the major difference. Why is so much of the book
dedicated to database design? Why not plunge into SQL coding and
eventually the developer will get a hang of the design? Because
high-level thinking requires thinking at the database design level.
A farmer has six mules. H how do we model it in the database? We
design the Farmer and FarmAnimal tables, and then connect them with
FarmerID FOREIGN KEY in FarmAnimal referencing the FarmerID PRIMARY
KEY in the Farmer table. What is the big deal about it? It looks so
simple. In fact, how about just calling the tables Table1 and
Table2 to be more generic. Ouch Meaningful naming is the very basis
of good database design. Relational database design is truly simple
for simple well-understood models. The challenge starts in modeling
complex objects such as financial derivative instruments, airplane
passenger scheduling, or a social network website. When you need to
add 5 new tables to a 1000 table database and hook them in (define
FOREIGN KEY references) correctly, it is a huge challenge. To begin
with, some of the five new tables may already be redundant, but you
don't know that until you understand what the 1000 tables are
really storing. Frequently, learning the application area is the
biggest challenge for a developer when starting a new job. The SQL
language is simple to program and read even when touching 10
tables. Complexities abound though. The very first one: does the
SQL statement touch the right data set - 999 records and 1000 or
998? T-SQL statements are turned into Transact-SQL scripts, stored
procedures, and user-defined functions, and trigger server-side
database objects.
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