Data structures algorithms in golang pdf download

Put "4","4" fmt. TreeSets TreeSets are used in marketing and customer relationship management applications. TreeSet is a set that has a binary tree with unique elements. The elements are sorted in a natural order. In the following code snippet, TreeSet creation, insertion, search, and stringify operations are presented.

TreeSet allows only one null value if the set is empty. The elements are sorted and stored as elements. InsertElement treeNode. The InsertTreeNode method takes treeNodes as the parameter. RemoveNode treeNode. The RUnlock method of the tree's lock instance is deferred. RLock defer tree. RUnlock inOrderTraverseTree tree. The inOrderTraverseTree method takes treeNode and function as parameters. The method recursively calls the inOrderTraverseTree method with function and then leftNode and rightNode in separate calls.

The Lock method on the tree's lock instance is invoked first, and the Unlock method is deferred. Lock defer tree. Unlock preOrderTraverseTree tree. The preOrderTraverseTree method takes treeNode and function as parameters. SearchNode treeNode. InsertTreeNode node1,node2,node3, node4, node5 treeset.

Synchronized TreeSets Operations that are performed on synchronized TreeSets are synchronized across multiple calls that access the elements of TreeSets. Synchronization in TreeSets is achieved using a sync. RWMutex lock. Unlock removeNode tree. InsertTreeNode node1, node2, node3, node4, node5 treeset. String In the next section, we will take a look at sequences. Sequences A sequence is a set of numbers that are grouped in a particular order.

The number of elements in the stream can be infinite, and these sequences are called streams. A subsequence is a sequence that's created from another sequence.

The relative positions of the elements in a subsequence will remain the same after deleting some of the elements in a sequence. In the following sections, we will take a look at different sequences such as the Farey sequence, Fibonacci sequence, look-and-say, and Thue—Morse.

Farey sequence A Farey sequence consists of reduced fractions with values between zero and one. The denominators of the fractions are less than or equal to m, and organized in ascending order. This sequence is called a Farey series. String method The fraction class has the numerator and denominator integer properties.

The g function takes an l or an r fraction, and num int as arguments to print the reduced fraction as a series. Merge The merge sort algorithm is a comparison-based method that was invented by John Von Neumann.

Each element in the adjacent list is compared for sorting. The performance of the algorithm is in the order of O n log n. This algorithm is the best algorithm for sorting a linked list. Seed time. MergeSorter method The MergeSorter method takes an array of integer elements as a parameter, and two subarrays of elements are recursively passed to the MergeSorter method.

Interpolation The interpolation search algorithm searches for the element in a sorted collection. The algorithm finds the input element at an estimated position by diminishing the search space before or after the estimated position. The time complexity of the search algorithm is of the order O log log n.

The following code snippet implements the interpolation search algorithm. The InterpolationSearch function takes the array of integer elements and the integer element to be found as parameters. Recursion Recursion is an algorithm in which one of the steps invokes the currently running method or function.

This algorithm acquires the outcome for the input by applying basic tasks and then returns the value. This method was briefly discussed in the Divide and conquer algorithms section of Chapter 1, Data Structures and Algorithms.

During recursion, if the base condition is not reached, then a stack overflow condition may arise. A recursion algorithm is implemented in the following code snippet. The Factor method takes the num as a parameter and returns the factorial of num. A Stack instance is initialized, and references are added to the stack by invoking the Push method. Push reference1 stack. Push reference2 stack. Push reference3 stack. Push reference4 fmt. Println stack.

Pop , stack. Memory blocks, disk space, and objects are good examples of resources. This technique tracks each object as a resource. The metrics that are tracked are the number of references held by different objects. The objects are recovered when they can never be referenced again.

The number of references is used for runtime optimizations. Deutsch-Bobrow came up with the strategy of reference counting. This strategy was related to the number of updated references that were produced by references that were put in local variables.

Henry Baker came up with a method that includes references in local variables that are deferred until needed. In the following subsections, the simple, deferred, one-bit, and weighted techniques of reference counting will be discussed. Simple reference counting Reference counting is related to keeping the number of references, pointers, and handles to a resource such as an object, block of memory, or disk space.

This technique is related to the number of references to de-allocated objects that are never referenced again. The collection technique tracks, for each object, a tally of the number of references to the object. The references are held by other objects. The object gets removed when the number of references to the object is zero.

The removed object becomes inaccessible. The removal of a reference can prompt countless connected references to be purged. The algorithm is time-consuming because of the size of the object graph and slow access speed. In the following code snippets, we can see a simple reference-counting algorithm being implemented. AddUint32 referenceCounter. The newReferenceCounter method is invoked, and a reference is added by invoking the Add method.

The count reference is printed at the end. Add fmt. Deferred reference counting Deferred reference counting is a procedure in which references from different objects to a given object are checked and program-variable references are overlooked.

If the tally of the references is zero, that object will not be considered. This algorithm helps reduce the overhead of keeping counts up to date. Deferred reference counting is supported by many compilers. One-bit reference counting The one-bit reference counting technique utilizes a solitary bit flag to show whether an object has one or more references. The flag is stored as part of the object pointer. There is no requirement to spare any object for extra space in this technique.

This technique is viable since the majority of objects have a reference count of 1. Weighted reference counting The weighted reference counting technique tallies the number of references to an object, and each reference is delegated a weight. This technique tracks the total weight of the references to an object. Weighted reference counting was invented by Bevan, Watson, and Watson in In the garbage collection style, the heap consists of a graph of connected objects, which are white.

This technique visits the objects and checks whether they are specifically available by the application. Globals and objects on the stack are shaded gray in this technique. Every gray object is darkened to black and filtered for pointers to other objects. Any white object found in the output is turned gray. This calculation is rehashed until there are no gray objects. White objects that are left out are inaccessible.

A mutator in this algorithm handles concurrency by changing the pointers while the collector is running. It also takes care of the condition so that no black object points to a white object. The mark algorithm has the following steps: 1. Mark the root object 2. Mark the root bit as true if the value of the bit is false 3. For every reference of root, mark the reference, as in the first step The following code snippet shows the marking algorithm.

A generation of objects will be expired and collected by the algorithm based on their age. The algorithm promotes objects to older generations based on the age of the object in the garbage collection cycle. The entire heap needs to be scavenged, even if a generation is collected. Let's say generation 3 is collected; in this case, generations are also scavenged. Cache management Cache management consists of managing static, dynamic, and variable information: Static information never changes Dynamic information changes frequently Variable information changes less frequently than dynamic information The object cache is stored in various data structures, such as maps and trees.

Maps have a key as an identifier and a value, which is an object. Cache objects can be related to memory, disks, pools, and streams. Caches have attributes related to time to live, group, and region. A region consists of a collection of mapped keyvalues. Regions can be independent of other regions. Cache configuration consists of defaults, regions, and auxiliaries.

A typical cache manager has the following features: Memory management Thread pool controls Grouping of elements Configurable runtime parameters Region data separation and configuration Remote synchronization Remote store recovery Event handling Remote server chaining and failover Custom event logging [ ] Memory Management Chapter 10 Custom event queue injection Key pattern-matching retrieval Network-efficient multi-key retrieval The CacheObject class and the Cache class are described in the following sections.

The IfExpired method IfExpired checks whether the cache object has expired. RWMutex mutex. The GetObject method of the Cache class returns the value of cacheKey. The RLock method on the mutex object of the cache is invoked, and the RUnlock method is deferred before returning the value of cacheKey.

If the object has expired, the key value will be an empty string. RLock defer cache. The Lock method on the mutex object of the cache is invoked, and the Unlock method is deferred. The created cacheObject is set as a value to map objects with the cacheKey key.

Lock defer cache. Unlock cache. Add timeToLive. The main method The main method creates the cache by invoking the NewCache method. The key and value are set on the cache by invoking setValue. The value is accessed by calling the GetObject method of the Cache class. GetObject "name" fmt. Space allocation Each function has stack frames associated with individual memory space.

Functions have access to the memory inside the frame, and a frame pointer points to the memory's location. Transition between frames occurs when the function is invoked. Data is transferred by value from one frame to another during the transition. Stack frame creation and memory allocation is demonstrated in the following code. The addOne function takes num and increments it by one. The number value and address are printed before and after invoking the addOne function.

Pointers Pointers have an address that is 4 or 8 bytes long, depending on whether you have a bit or bit architecture. The stack's main frame consists of the number 17 with the address 0xc After adding one, a new frame with num equal to 18 and an address of 0xc is created.

The main method prints the stack's main frame after invoking the addOne function. The code in the following sections demonstrates memory space allocation with pointers instead of actual values passed into a function. The AddOne and main methods of pointers are shown in the following sections.

The function prints the value, address, and pointer of num. The pointer to the number is passed to the addOne function. The number value and address is printed before and after invoking the addOne function.

In this example, the address of the number is the same as the value of num in the addOne function. Pointers share the address of the variable for the function to access for reads and writes within the stack frame. Pointer types are specific to every type that is declared.

Pointers provide indirect memory access outside the function's stack frame. Concepts — Go memory management In Go, programmers don't need to worry about coding a variable's value placement in memory and space allocation.

Garbage collection in Go is overseen by the memory manager. The GOGC variable is used to set a value for the initial garbage collection target percentage. Garbage collection is activated when the proportion of freshly allotted data to the live data that remains after the previous garbage collection reaches the target percentage. The default value of the GOGC variable is This setting can be turned off, which stops garbage collection.

The current implementation of garbage collection in Go uses the mark-and-sweep algorithm. Some of the best practices that you can follow to improve memory management are as follows: Small objects can be combined into larger objects Local variables that have escaped from their declaration scope can be promoted into heap allocations Slice array pre-allocation can be performed to improve memory Use int8, instead of int, because int8 is a smaller data type Objects that do not have any pointers will not be scanned by the garbage collector FreeLists can be used to reuse transient objects and reduce the number of allocations [ ] Memory Management Chapter 10 Profiling Profiling in Go can be enabled by using the cpuprofile and memprofile flags.

The Go testing package has support for benchmarking and profiling. The flag. Parse method reads the command-line flags. The CPU profiling output is written to a file. StartCPUProfile file defer pprof. We looked at reference counting algorithms, including simple, deferred, one-bit, and weighted. The mark-and-sweep and generational collection algorithms were also presented with code examples. The next chapter will cover the next steps we can take after going through this book. Which factors are considered when choosing a garbage collection algorithm?

In which reference counting algorithm are program-variable references ignored? What is the type of reference counting algorithm in which a single-bit flag is used for counting? In which reference counting algorithm is a weight assigned to each reference? Who invented weighted reference counting? Which garbage collection algorithm was proposed by Dijkstra?

What class handles concurrency when the mark-and-sweep collector is running? What are the criteria for promoting objects to older generations? Draw a flow chart for the cache management algorithm. How do you get indirect memory access outside a method's stack frame? Tips and techniques are provided to help you keep yourself up to date with the latest on data structures and algorithms. Technical requirements Install Go version 1. Learning outcomes The learning outcomes from this book are as follows: Improve a web or mobile application's performance using the correct data structures and algorithms.

Understand how an algorithm solves a problem and how the correct data structure is chosen for a problem. Get a grasp of the various techniques for writing pseudocode for an algorithm, allowing you to ace white-boarding sessions and interview assignments. Discover the pitfalls in selecting data structures and algorithms by predicting how fast and efficient an algorithm or data structure is. In the following section, the key takeaway points, papers, and articles to be referred to, along with tips and techniques, are discussed.

Next Steps Key takeaways The key takeaways for the reader are as follows: How to choose the correct algorithm and data structures for a problem. How to compare the complexity and data structures of different algorithms for code performance and efficiency. How to apply best practices to improve and increase the performance of an application.

Real-world problems, solutions, and best practices associated with web and mobile software solutions are provided in the book as code examples. Next steps In this section, papers and articles are provided as further reading for each chapter.

Golang program for implementation of Shell Sort. Golang program for implementation of Insertion Sort. Golang program for implementation of Comb Sort. Golang program for implementation of Merge Sort. Golang program for implementation of Radix Sort. Golang program for implementation of Pancake Sort.

Golang program to implement Binary Tree. Golang program for implementation of Rabin-Karp. Golang program for implementation of Linked List. Golang program for implementation of Median of Medians. Golang program for implementation of Longest Common Sub-sequence. Golang program for implementation of Levenshtein distance.

Golang program for implementation of Floyd—Warshall Algorithm. Golang program for implementation of Tower of Hanoi Algorithm. Golang program for implementation of Huffman Coding Algorithm. Golang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications.

Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving. If you feel this book is for you, get your copy today! Following is what you need for this book: This book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage. With the following software and hardware list you can run all code files present in the book Chapter Click here to download it.

Bhagvan Kommadi , the founder of Quantica Computacao and Architect Corner, has around 18 years' experience in the industry, ranging from large-scale enterprise development to incubating software product startups.

He has developed Go-based blockchain solutions in the retail, education, banking, and financial service sectors. He has experience of building high-transactional applications using Java, Python, Go, Ruby, and JavaScript frameworks. Learn Q Programming.