Tag Archives: java

Solving The Sweet Spots Board Game

Creating the Android board game, Sweet Spots, was a fun programming exercise, although developing an algorithmic program to solve the board game is in fact more fun.

A good portion of developing a board game is about validating the game state based on the game rules, creating game control logics, and visual look-and-feel. Much of the above is just mechanical programming exercise. On the other hand, solving the game is a vastly different exercise, requiring some algorithmic programming effort.

Sweet Spots under the hood

The game solving application was written in Java, with Ant the build tool. There are only two simple Java classes that constitute the hierarchical structure of the board game: Spot and Board. Another Java class, SweetSpots, consists of the core mechanism for game solving. Source code is available at GitHub.

Spot defines the (x,y)-coordinate position of each of the NxN spots (i.e. cells) on the board of size N. It also has an integer value that represents:

  • empty (i.e. undecided spot)
  • filler (i.e. spot not chosen for treasure chest)
  • target (i.e. spot chosen for a treasure chest)

In addition, it consists of an integer zone-id (0, 1, .., N-1) that represents the N individual zones.

Board defines the board size (N). The existing board game was developed with either 1 or 2 targets (i.e. number of treasure chests) per row/column/zone for a given game. For generality, the Board class consists of separate targets-per-row, targets-per-column and targets-per-zone, although they would all be the same (i.e. 1 or 2) when applying to the existing game version. It was initially generalized to allow rectangular board dimension (i.e. MxN instead of NxN), but was later simplified to square board.

Board also consists of a variable, spots, of type Spot[][] that maintains the game state during a game, and a number of methods for game rule validation. Besides the standard constructor that takes board size and target count parameters, it also has a constructor for cloning itself to keep a snapshot of the board state.

Class SweetSpots is the class embedded with game solving logic. It takes a board-zone file along with target counts that defines a game as input and consists of necessary methods to solve the game. The board-zone file is a text file which contains the zone information of a given game in the form of a matrix with coordinates (0,0) representing the top left-most entry. For instance, a 4×4 board-zone file might have the following content:

0 1 1 2
0 0 1 2
2 2 2 2
2 3 3 2

The matrix of integers represent 4 zones, each represented by an integer (0-3):

zone 0: (0,0), (0,1), (1,1)
zone 1: (1,0), (2,0), (2,1)
zone 2: (3,0), (3,1), (0,2), (1,2), (2,2), (3,2), (0,3), (3,3)
zone 3: (1,3), (2,3)

Class SweetSpots consists of a variable boardStack which is a stack of type LinkedList. The stack maintains a dynamic list of Board instance snapshots saved at various stages of the trial-and-error routine. The trial-and-error process is performed using two key methods, boardwalk() and rollback(). Method boardwalk() walks through each of the NxN spots on the board (hence “board walk”) in accordance with the game rules. Upon failing any of the game rule validation, rollback() handles rolling back to the previous game-solving state recorded in boardStack.

Below are pseudo-code logic for methods boardwalk() and rollback().

Solving a game

Class SolveGame is a simple executable module that uses the SweetSpots class to solve a game with defined zone data.

The main flow logic boils down to the following:

To solve a game with defined zones, simply navigate to the main subdirectory of the java app and run the following command:

java -cp com.genuine.game.sweetspots.SolveGame <trace?1:0> <boardZoneFile> <boardSize> <targetsPerRow> <targetsPerCol> <targetsPerZone>

For instance, to solve a game defined in ./gamefiles/game-4-1.txt, simply navigate to the main subdirectory of the java app and run the following command from /path/to/sweetspot/java/:

java -cp build/sweetspots-r1.0.0.jar com.genuine.game.sweetspots.SolveGame 0 ./gamefiles/game-4-1.txt 4 1 1 1

Creating a game

Class CreateGame is an executable module that creates a game by generating random zone data and guaranteeing a solution via repetitive method trials in class SweetSpots.

Creating a game for a given board size (i.e. N) and target count involves:

  • generating N random contiguous zones that patition the board, and,
  • ensuring there is a solution for the generated zones

Getting slightly more granular, it involves the following steps:

  1. Assign individual zones random sizes to fill the entire board: To reduce frequency of having extreme zone size, a simplistic weighted random probability distribution, triangularProbDist(), is used for determining the size for individual zones.
  2. For each zone, assign random contiguous spots of the assigned size on the board: Within class CreateGame is a method, zoneWalk(), which essentially “walks” row-wise or column-wise randomly till the assigned zone size is reached. Failure at any point of time to proceed further to cover the entire board with the zones will promptly force a return to step #1.
  3. Transpose the board to further randomize the zone-walk result.
  4. Repeat the above steps till the zones of assigned sizes successfully fill the entire board.
  5. Ensure that there is a solution for the created zones: This is achieved by essentially employing the same game solving logic used in SolveGame.

To create a game that consists of a solution, navigate to the main subdirectory of the java app and execute the following command:

java -cp com.genuine.game.sweetspots.CreateGame <trace?1:0> <boardZoneFile> <boardSize> <targetsPerRow> <targetsPerCol> <targetsPerZone>

For instance, to create a game with 4×4 board size, go to /path/to/sweetspot/java/ and run the following command to generate the game zones in ./gamefiles/:

java -cp build/sweetspots-r1.0.0.jar com.genuine.game.sweetspots.CreateGame 0 ./gamefiles/game-4-1.txt 4 1 1 1

The generated game-zone file should look something like the following:

0 1 1 2
0 0 1 2
2 2 2 2
2 3 3 2

The above Java applications were developed back in Summer of 2013. Though some refactoring effort has been made, there is certainly room for improvement in different areas. In particular, the zone creation piece can be designed to be more robust, ideally enforcing a unique solution for the game. That would be something for a different time perhaps in the near future. Meanwhile, enjoy the board game, which can be downloaded from Google Play.

NIO-based Reactor

Over the past few years, event-based architecture with non-blocking operations has been the norm for high-concurrency server architecture. The per-connection threading (process-based) architecture is no longer favored as an efficient design, especially for handling high volume of concurrent connections. The increasing popularity of Nginx and the relative decline of Apache httpd these days demonstrated the trend.

Java New I/O

Java’s NIO (New I/O, a.k.a. Non-blocking I/O) provides a set of APIs to efficiently handle I/O operations. The key ingredients of NIO include Buffer, Channel and Selector. A NIO Buffer virtually provides direct access to the operating system’s physical memory along with a rich set of methods for alignment and paging of the selected memory that stores any primitive-type data of interest. A NIO Channel then serves as the conduit for bulk data transfers between the Buffer and the associated entity (e.g. a socket).

A socket channel can be configured in non-blocking mode and events such as reading data from the associated socket no longer block the invoking thread for more time than necessary. Together with the NIO Selector responsible for selecting those of the concurrent events that are ready to be processed, NIO APIs are well equipped to handle event-based operations in an efficient fashion. The NIO buffer-channel-selector relationship is best explained by an interesting analogy to train-platform-bell at https://blogs.oracle.com/slc/entry/javanio_vs_javaio.

Non-blocking vs Asynchronous

Note that non-blocking mode is different from asynchronous mode. In non-blocking mode, a requested operation always returns the result immediately regardless of success or failure, thus freeing the invoking thread from being blocked. In asynchronous mode, a separate thread is used to carry out the requested operation in parallel with the invoking thread. Java 7 enhanced NIO to include support for asynchronous file and socket channels.

Reactor pattern

The Reactor pattern is a popular event-based architecture. Using NIO, implementing a basic event-based server on top of Reactor pattern is pretty straight forward. Appended is a bare minimal Reactor-pattern server consisting of a Reactor class and a Handler class.

The single-threaded Reactor class houses the main dispatcher loop responsible for selecting registered events that are ready for socket read/write operations. Registered with the dispatcher during initialization, the also single-threaded Acceptor is responsible for accepting socket connections requested by clients. Finally, the Handler class takes care of the actual events (read from socket, process data, write to socket) in accordance with its operational state.

Each Handler is associated with a SocketChannel and the Selector maintained by the Reactor class. Both variables are declared immutable for performance as well as allowing access by the inner Runnable class. The handler registers with the dispatcher indicating its interested operation (read or write) and gets dispatched when the associated socket is ready for the operation. The Runnable class forms the worker thread pool and is responsible for data processing (in this simple case, echoing), leaving the Handler thread responsible for just socket read/write.

To test the server, just launch it on a host (e.g. server1.example.com) and run a few telnet instances connecting to the server port (e.g. telnet server1.example.com 9090).



Programming Exercise – Binary Tree

Like sorting algorithms, binary tree implementation is another good programming exercise. In particular, methods for traversing a tree, searching nodes in a binary search tree and many other binary tree operations form a great recipe for refreshing one’s programming skills. Appended is an implementation of a pretty comprehensive set of binary tree (and binary search tree) operations in Java.

Iterative and recursive methods for each of the operations are developed and grouped in two separate classes, BinTreeI and BinTreeR. In general, most operations are easier to be implemented using recursive methods. For instance, calculating tree height using iterative method is a rather non-trivial exercise whereas it’s almost an one-liner using recursion. Some of the operations such as searching and inserting a tree node are only applicable to binary search tree (BST), for which in-order tree traversal should be used. For generality, pre-order and post-order traversal methods are also included in the code.

Similar to the implementation of sorting algorithms in a previous blog, Java Generics and Comparable interface are used. If wanted, the underlying tree node could be further expanded to contain more complex node data such as map entries (e.g. with class type <Key extends Comparable<Key>, Value>, and Map.Entry<K,V> data).

Node.java – binary tree node

BinTree.java – base binary tree class

BinTreeR.java – binary tree class using recursive methods

BinTreeI.java – binary tree class using iterative methods

BinTreeMain.java – test application

Streaming Real-time Data Into HBase

Fast-write is generally a characteristic strength of distributed NoSQL databases such as HBase, Cassandra. Yet, for a distributed application that needs to capture rapid streams of data in a database, standard connection pooling provided by the database might not be up to the task. For instance, I didn’t get the kind of wanted performance when using HBase’s HTablePool to accommodate real-time streaming of data from a high-parallelism data dumping Storm bolt.

To dump rapid real-time streaming data into HBase, instead of HTablePool it might be more efficient to embed some queueing mechanism in the HBase storage module. An ex-colleague of mine, who is the architect at a VoIP service provider, employs the very mechanism in their production HBase database. Below is a simple implementation that has been tested performing well with a good-sized Storm topology. The code is rather self-explanatory. The HBaseStreamers class consists of a threaded inner class, Streamer, which maintains a queue of HBase Put using LinkedBlockingQueue. Key parameters are in the HBaseStreamers constructor argument list, including the ZooKeeper quorum, HBase table name, HTable auto-flush switch, number of streaming queues and streaming queue capacity.

Next, write a wrapper class similar to the following to isolate HBase specifics from the streaming application.

To test it with a distributed streaming application using Storm, write a bolt similar to the following skeleton. All that is needed is to initialize HBaseStreamers from within the bolt’s prepare() method and dump data to HBase from within bolt’s execute().

Finally, write a Storm spout to serve as the streaming data source and a Storm topology builder to put the spout and bolt together.

The parallelism/queue parameters are set to relatively small numbers in the above sample code. Once tested working, one can tweak all the various dials in accordance with the server cluster capacity. These dials include the following:

For simplicity, only HBase Put is being handled in the above implementation. It certainly can be expanded to handle also HBase Increment so as to carry out aggregation functions such as count. The primary goal of this Storm-to-HBase streaming exercise is to showcase the using of a module equipped with some “elasticity” by means of configurable queues. The queueing mechanism within HBaseStreamers provides cushioned funnels for the data streams and helps optimize the overall data intake bandwidth. Keep in mind, though, that doesn’t remove the need of administration work for a properly configured HBase-Hadoop system.