Oracle, MySQL, Cassandra, Hadoop Database Training Classes in Hawthorne, California

Learn Oracle, MySQL, Cassandra, Hadoop Database in Hawthorne, California 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 Hawthorne, California: 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: $ 1750length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1750length: 5 day(s)
cost: $ 1750length: 5 day(s)
cost: $ 1750length: 5 day(s)
cost: $ 1750length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1750length: 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: $ 1750length: 5 day(s)
cost: $ 1750length: 4 day(s)
cost: $ 1750length: 5 day(s)
cost: $ 2190length: 5 day(s)
cost: $ 1290length: 3 day(s)

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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

Once again theTIOBE Programming Community has calculated the trends in popular programming languages on the web. Evaluating the updates in the index allows developers to assess the direction of certain programming skills that are rising or faltering in their field.  According to the November 2013 report, three out of four languages currently ranking in the top twenty are languages defined by Microsoft. These are C#, SQL Server language Transact-SQL and Visual Basic.NET.  Not surprising though, the top two languages that remain steady in the number one and two spots are Java and C.

How are the calculations measured?  The information is gathered from five major search engines: Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube and Baidu.

Top 20 Programming Languages: as of November 2013


  1.  C
  2.  Java
  3.  Objective-C 
  4.  C++
  5.  C#
  6.  PHP
  7. (Visual) Basic
  8.  Python
  9. Transact-SQL
  10. Java Script
  11. Visual Basic.NET
  12. Perl
  13.  Ruby
  14. Pascal
  15. Lisp
  16. MATLAB
  17. Delphi/Object Pascal
  18. PL/SQL
  19. COBOL
  20. Assembly

Although the index is an important itemized guide of what people are searching for on the internet, it’s arguable that certain languages getting recognition is a direct result of early adopters posting tutorials and filling up discussion boards on current trends. Additionally, popular tech blogs pick up on technological shifts and broadcast related versions of the same themes.

When does the popularity of a software language matter?

  1. If you want marketable skills, knowing what employers are looking for is beneficial. As an example, languages such as Java and Objective C are highly coveted in the smart-phone apps businesses.
  2. A consistently shrinking language in usage is an indicator not only that employers are apt to pass on those skills but fall in danger of being obsolete.
  3. Focusing on languages that are compatible with other developers increases your chances to participate on projects that companies are working on.

The original article was posted by Michael Veksler on Quora

A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.

The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.

Readability is a tricky thing, and involves several aspects:

  1. Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
  2. Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
  3. Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
  4. Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
  5. Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
  6. Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
  7. As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
  8. The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.

Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.

Don’t blindly use C++ standard library without understanding what it does - learn it. You look at std::vector::push_back() documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::map, and with std::unordered_map. Knowing the difference between these two maps, you’d know when to use each one of them.

Never call new or delete directly, use std::make_unique and [cost c++]std::make_shared[/code] instead. Try to implement usique_ptr, shared_ptr, weak_ptr yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.

Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.

Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.

Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.

Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.

These are the most important things, which will make you a better programmer. The other things will follow.

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Tech Life in California

Largely influenced by several immigrant populations California has experienced several technological, entertainment and economic booms over the years. As for technology, Silicon Valley, in the southern part of San Francisco is an integral part of the world’s innovators, high-tech businesses and a myriad of techie start-ups. It also accounts for 1/3rd of all venture capital investments.
I think the lack of reusability comes in object-oriented languages, not in functional languages. Because the problem with object-oriented languages is they've got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle. Joe Armstrong - From the book: Coders at Work. 
other Learning Options
Software developers near Hawthorne 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 California that offer opportunities for Oracle, MySQL, Cassandra, Hadoop Database developers
Company Name City Industry Secondary Industry
Mattel, Inc. El Segundo Retail Sporting Goods, Hobby, Book, and Music Stores
Spectrum Group International, Inc. Irvine Retail Retail Other
Chevron Corp San Ramon Energy and Utilities Gasoline and Oil Refineries
Jacobs Engineering Group, Inc. Pasadena Real Estate and Construction Construction and Remodeling
eBay Inc. San Jose Software and Internet E-commerce and Internet Businesses
Broadcom Corporation Irvine Computers and Electronics Semiconductor and Microchip Manufacturing
Franklin Templeton Investments San Mateo Financial Services Investment Banking and Venture Capital
Pacific Life Insurance Company Newport Beach Financial Services Insurance and Risk Management
Tutor Perini Corporation Sylmar Real Estate and Construction Construction and Remodeling
SYNNEX Corporation Fremont Software and Internet Data Analytics, Management and Storage
Core-Mark International Inc South San Francisco Manufacturing Food and Dairy Product Manufacturing and Packaging
Occidental Petroleum Corporation Los Angeles Manufacturing Chemicals and Petrochemicals
Yahoo!, Inc. Sunnyvale Software and Internet Software and Internet Other
Edison International Rosemead Energy and Utilities Gas and Electric Utilities
Ingram Micro, Inc. Santa Ana Computers and Electronics Consumer Electronics, Parts and Repair
Safeway, Inc. Pleasanton Retail Grocery and Specialty Food Stores
Gilead Sciences, Inc. San Mateo Healthcare, Pharmaceuticals and Biotech Pharmaceuticals
AECOM Technology Corporation Los Angeles Real Estate and Construction Architecture,Engineering and Design
Reliance Steel and Aluminum Los Angeles Manufacturing Metals Manufacturing
Live Nation, Inc. Beverly Hills Media and Entertainment Performing Arts
Advanced Micro Devices, Inc. Sunnyvale Computers and Electronics Semiconductor and Microchip Manufacturing
Pacific Gas and Electric Corp San Francisco Energy and Utilities Gas and Electric Utilities
Electronic Arts Inc. Redwood City Software and Internet Games and Gaming
Oracle Corporation Redwood City Software and Internet Software and Internet Other
Symantec Corporation Mountain View Software and Internet Data Analytics, Management and Storage
Dole Food Company, Inc. Thousand Oaks Manufacturing Food and Dairy Product Manufacturing and Packaging
CBRE Group, Inc. Los Angeles Real Estate and Construction Real Estate Investment and Development
First American Financial Corporation Santa Ana Financial Services Financial Services Other
The Gap, Inc. San Francisco Retail Clothing and Shoes Stores
Ross Stores, Inc. Pleasanton Retail Clothing and Shoes Stores
Qualcomm Incorporated San Diego Telecommunications Wireless and Mobile
Charles Schwab Corporation San Francisco Financial Services Securities Agents and Brokers
Sempra Energy San Diego Energy and Utilities Gas and Electric Utilities
Western Digital Corporation Irvine Computers and Electronics Consumer Electronics, Parts and Repair
Health Net, Inc. Woodland Hills Healthcare, Pharmaceuticals and Biotech Healthcare, Pharmaceuticals, and Biotech Other
Allergan, Inc. Irvine Healthcare, Pharmaceuticals and Biotech Biotechnology
The Walt Disney Company Burbank Media and Entertainment Motion Picture and Recording Producers
Hewlett-Packard Company Palo Alto Computers and Electronics Consumer Electronics, Parts and Repair
URS Corporation San Francisco Real Estate and Construction Architecture,Engineering and Design
Cisco Systems, Inc. San Jose Computers and Electronics Networking Equipment and Systems
Wells Fargo and Company San Francisco Financial Services Banks
Intel Corporation Santa Clara Computers and Electronics Semiconductor and Microchip Manufacturing
Applied Materials, Inc. Santa Clara Computers and Electronics Semiconductor and Microchip Manufacturing
Sanmina Corporation San Jose Computers and Electronics Semiconductor and Microchip Manufacturing
Agilent Technologies, Inc. Santa Clara Telecommunications Telecommunications Equipment and Accessories
Avery Dennison Corporation Pasadena Manufacturing Paper and Paper Products
The Clorox Company Oakland Manufacturing Chemicals and Petrochemicals
Apple Inc. Cupertino Computers and Electronics Consumer Electronics, Parts and Repair
Amgen Inc Thousand Oaks Healthcare, Pharmaceuticals and Biotech Biotechnology
McKesson Corporation San Francisco Healthcare, Pharmaceuticals and Biotech Pharmaceuticals
DIRECTV El Segundo Telecommunications Cable Television Providers
Visa, Inc. San Mateo Financial Services Credit Cards and Related Services
Google, Inc. Mountain View Software and Internet E-commerce and Internet Businesses

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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 California 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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