I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

• Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
• Deallocates or reclaims those objects that are no longer being referened. 
• Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
• Deallocates the memory of objects that are not marked as live.
• Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
• Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */

Learning SQL development can seem like an overwhelming task at first. However, mastering just a few key points will help ease your way through 80 percent of the day-to-day challenges when writing stored procedures and solving common problems. Here are three important SQL development factors to keep in mind:

Outer Joins
One of the most crucial things to understand in SQL server are joins. Joins are a way to retrieve data from two or more tables based on logical relationships between them. Joins dictate how Microsoft SQL Server ought to use data from one table to select the rows in another table.

In my experience inner joins are intuitive while outer joins can present additional hours of grief by overlooking associations in the other table(s). The outer join is the key to answering questions about what the database does not have. For example, if you need to make a query to display all the students who are without report-cards, you’ll need a left join to get all students coupled with a “where clause” to return the ones who have nulls for their report card table columns in the results.

Many talented Java script programmers have muddled through the SQL Server by deficient coding around the inner join. As a result, their queries can take five hours to run, whereas, properly written left joins, can take only two seconds to run.

Aggregation
Grouping results comes up in SQL a lot more than you might think. Knowing how to write a query when answering questions such as, “What’s the average grade for each teacher’s student list?” is invaluable. This kind of question cannot be answered with a single table or solely by joins.  You’ll often find you need to use joins in conjunction with group by statements. Always write the raw query first and then look at the results. Next, you have to figure out the best way to group them, rewrite your select clause and add a group by clause in the end.

Digging Through Data
I find this is the most lacking skill in many programmers. In fact, many otherwise-talented programmers holding Master’s Degrees fail to get jobs because they couldn’t analyze rows of data objectively during interviews. It’s just something that’s not taught but is crucial to get under you belt. Why? Eventually, some query is not going to perform as you may expect. And, the only way to find discrepancies is to look at rows of data, identify what join isn’t finding a match or where bad data is throwing things into chaos. Get familiar with how joins actually work, even if you have to manually walk through the logic of a large stored procedure’s tree of joins. It’s boring and time-consuming but absolutely necessary.

Take the time to master the core skills that will make you a successful SQL Programmer and avoid queries that run for five hours!

As part of our C++ Tutorials series, here is a tutorial on the tricks of the trade for using C++ I/O.  Keep in mind that an application without I/O is just a black box; no communcation is taking place. 

Tricks and Tips for using C++ I/O

Sometimes we have to repeat ourselves before we are heard. Then again there are times where we have to perform a certain action the same way several times before we can carry on with what we want to do.

Repetition is the keyword here and for humans that is something we generally try to avoid. Yet our digital friends love repetition. They never get tired and they never get bored of doing the same thing over and over again countless times.

So it’s little wonder then that all modern programming languages give us various ways in which we can perform a certain action as many times as we need.

In python we have the for statement which gives us the power to loop over large collections of data very quickly and efficiently.