Oracle, MySQL, Cassandra, Hadoop Database Training Classes in Yuma, Arizona

Learn Oracle, MySQL, Cassandra, Hadoop Database in Yuma, Arizona and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current Oracle, MySQL, Cassandra, Hadoop Database related training offerings in Yuma, Arizona: Oracle, MySQL, Cassandra, Hadoop Database Training

We offer private customized training for groups of 3 or more attendees.

Oracle, MySQL, Cassandra, Hadoop Database Training Catalog

cost: $ 495length: 1 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1090length: 3 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1090length: 2 day(s)

Cassandra Classes

Hadoop Classes

cost: $ 1590length: 3 day(s)

Linux Unix Classes

cost: $ 1890length: 3 day(s)

Microsoft Development Classes

MySQL Classes

cost: $ 490length: 1 day(s)
cost: $ 790length: 2 day(s)
cost: $ 1290length: 4 day(s)
cost: $ 1190length: 3 day(s)

Oracle Classes

cost: $ 2090length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 1590length: 4 day(s)
cost: $ 790length: 2 day(s)
cost: $ 690length: 1 day(s)
cost: $ 2800length: 5 day(s)
cost: $ 1690length: 3 day(s)
cost: $ 2600length: 5 day(s)

SQL Server Classes

cost: $ 1290length: 3 day(s)
cost: $ 890length: 2 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 4 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2190length: 5 day(s)
cost: $ 1290length: 3 day(s)

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Structure Rule Language

To aid in the ease of rule authoring, Blaze Software, now Fair Isaac, created the proprietary Structure Rule Language (SRL), an object-oriented programming language designed to enable those with little or no background in software development to pen rules. Although the capabilities of this language are far too extensive to detail in this article, we can examine the basic rule syntax.

Rules in the SRL take the following form:

rule RuleName [at

Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...


That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance

 

I suspect that many of you are familiar with the term "hard coding a value" whereby the age of an individual or their location is written into the condition (or action) of a business rule (in this case) as shown below:

if customer.age > 21 and customer.city == 'denver'

then ...

Such coding practices are perfectly expectable provided that the conditional values, age and city, never change. They become entirely unacceptable if a need for different values could be anticipated. A classic example of where this practice occurred that caused considerable heartache in the IT industry was the Y2K issue where dates were updated using only the last 2 digits of a four digit number because the first 2 digits were hard-coded to 19 i.e. 1998, 1999. All was well provided that the date did not advance to a time beyond the 1900’s since no one could be certain of what would happen when the millennia arrived (2000). A considerably amount of work (albeit boring) and money, approximately $200 billion, went into revising systems by way of software rewrites and computer chip replacements in order to thwart any detrimental outcomes. It is obvious how a simple change or an assumption can have sweeping consequences.

You may wonder what Y2K has to do with Business Rule Management Systems (BRMS). Well, what if we considered rules themselves to be hard-coded. If we were to write 100s of rules in Java, .NET or whatever language that only worked for a given scenario or assumption, would that not constitute hard-coded logic? By hard-coded, we obviously mean compiled. For example, if a credit card company has a variety of bonus campaigns, each with their own unique list of rules that may change within a week’s time, what would be the most effective way of writing software to deal with these responsibilities?

In programming, memory leaks are a common issue, and it occurs when a computer uses memory but does not give it back to the operating system. Experienced programmers have the ability to diagnose a leak based on the symptoms. Some believe every undesired increase in memory usage is a memory leak, but this is not an accurate representation of a leak. Certain leaks only run for a short time and are virtually undetectable.

Memory Leak Consequences

Applications that suffer severe memory leaks will eventually exceed the memory resulting in a severe slowdown or a termination of the application.

How to Protect Code from Memory Leaks?

Preventing memory leaks in the first place is more convenient than trying to locate the leak later. To do this, you can use defensive programming techniques such as smart pointers for C++.  A smart pointer is safer than a raw pointer because it provides augmented behavior that raw pointers do not have. This includes garbage collection and checking for nulls.

If you are going to use a raw pointer, avoid operations that are dangerous for specific contexts. This means pointer arithmetic and pointer copying. Smart pointers use a reference count for the object being referred to. Once the reference count reaches zero, the excess goes into garbage collection. The most commonly used smart pointer is shared_ptr from the TR1 extensions of the C++ standard library.

Static Analysis

The second approach to memory leaks is referred to as static analysis and attempts to detect errors in your source-code. CodeSonar is one of the effective tools for detection. It provides checkers for the Power of Ten coding rules, and it is especially competent at procedural analysis. However, some might find it lagging for bigger code bases.

How to Handle a Memory Leak

For some memory leaks, the only solution is to read through the code to find and correct the error. Another one of the common approaches to C++ is to use RAII, which an acronym for Resource Acquisition Is Initialization. This approach means associating scoped objects using the acquired resources, which automatically releases the resources when the objects are no longer within scope. RAII has the advantage of knowing when objects exist and when they do not. This gives it a distinct advantage over garbage collection. Regardless, RAII is not always recommended because some situations require ordinary pointers to manage raw memory and increase performance. Use it with caution.

The Most Serious Leaks

Urgency of a leak depends on the situation, and where the leak has occurred in the operating system. Additionally, it becomes more urgent if the leak occurs where the memory is limited such as in embedded systems and portable devices.

To protect code from memory leaks, people have to stay vigilant and avoid codes that could result in a leak. Memory leaks continue until someone turns the system off, which makes the memory available again, but the slow process of a leak can eventually prejudice a machine that normally runs correctly.

 

Related:

The Five Principles of Performance

In Demand IT Skills

Tech Life in Arizona

Software developers in Phoenix, Arizona have ample opportunities for development positions in Fortune 1000 companies sprinkled throughout the state. Considered one of the world's largest global distributors of electronic parts, Avnet, based in Phoenix alone, provides a vital link in the technology supply chain. Other companies reigning in Arizona such as US Airway Group, Insight Enterprises, Inc., PetSmart Inc., Republic Services Inc, and First Solar Inc., are just a few examples of opportunities in the state of Arizona.
I never teach my pupils; I only attempt to provide the conditions in which they can learn. ~ Albert Einstein
other Learning Options
Software developers near Yuma have ample opportunities to meet like minded techie individuals, collaborate and expend their career choices by participating in Meet-Up Groups. The following is a list of Technology Groups in the area.
Fortune 500 and 1000 companies in Arizona that offer opportunities for Oracle, MySQL, Cassandra, Hadoop Database developers
Company Name City Industry Secondary Industry
Insight Enterprises, Inc. Tempe Computers and Electronics IT and Network Services and Support
First Solar, Inc. Tempe Energy and Utilities Alternative Energy Sources
Republic Services Inc Phoenix Energy and Utilities Waste Management and Recycling
Pinnacle West Capital Corporation Phoenix Energy and Utilities Gas and Electric Utilities
Amkor Technology, Inc. Chandler Computers and Electronics Semiconductor and Microchip Manufacturing
Freeport-McMoRan Copper and Gold Phoenix Agriculture and Mining Mining and Quarrying
US Airways Group, Inc. Tempe Travel, Recreation and Leisure Passenger Airlines
PetSmart, Inc. Phoenix Retail Retail Other
Avnet, Inc. Phoenix Computers and Electronics Instruments and Controls
ON Semiconductor Corporation Phoenix Computers and Electronics Semiconductor and Microchip Manufacturing

training details locations, tags and why hsg

A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

  • Learn from the experts.
    1. We have provided software development and other IT related training to many major corporations in Arizona since 2002.
    2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
  • Discover tips and tricks about Oracle, MySQL, Cassandra, Hadoop Database programming
  • Get your questions answered by easy to follow, organized Oracle, MySQL, Cassandra, Hadoop Database experts
  • Get up to speed with vital Oracle, MySQL, Cassandra, Hadoop Database programming tools
  • Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
  • Prepare to hit the ground running for a new job or a new position
  • See the big picture and have the instructor fill in the gaps
  • We teach with sophisticated learning tools and provide excellent supporting course material
  • Books and course material are provided in advance
  • Get a book of your choice from the HSG Store as a gift from us when you register for a class
  • Gain a lot of practical skills in a short amount of time
  • We teach what we know…software
  • We care…
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