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  • Pure Java open-source libraries for portfolio selection (= constrained, non-linear optimization)?

    - by __roland__
    Does anyone know or has experience with a pure Java library to select portfolios or do some similar kinds of quadratic programming with constraints? There seems to be a lot of tools, as already discussed elsewhere - but what I would like to use is a pure Java implementation. Since I want to call the library from within another open-source software with a BSD-ish license I would prefer LGPL over GPL. Any help is appreciated. If you don't know such libraries, which is the most simple algorithm you would suggest to implement? It has to cope with an inequality constraint (all x_i = 0) and an equality constraint (sum of all x_i = 1).

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  • Some optimization about the code (computing ranks of a vector)?

    - by user1748356
    The following code is a function (performance-critical) to compute tied ranks of a vector: mergeSort(x,inds,ci); //a sort function to sort vector x of length ci, also returns keys (inds) of x. int tj=0; double xi=x[0]; for (int j = 1; j < ci; ++j) { if (x[j] > xi) { double rankvalue = 0.5 * (j - 1 + tj); for (int k = tj; k < j; ++k) { ranks[inds[k]]=rankvalue; }; tj = j; xi = x[j]; }; }; double rankvalue = 0.5 * (ci - 1 + tj); for (int k = tj; k < ci; ++k) { ranks[inds[k]]=rankvalue; }; The problem is, the supposed performance bottleneck mergeSort(), which is O(NlogN) is several times faster than the other part of codes (which is O(N)), which suggests there is room for huge improvment with the other part of the codes, any advices?

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  • R: Are there any alternatives to loops for subsetting from an optimization standpoint?

    - by Adam
    A recurring analysis paradigm I encounter in my research is the need to subset based on all different group id values, performing statistical analysis on each group in turn, and putting the results in an output matrix for further processing/summarizing. How I typically do this in R is something like the following: data.mat <- read.csv("...") groupids <- unique(data.mat$ID) #Assume there are then 100 unique groups results <- matrix(rep("NA",300),ncol=3,nrow=100) for(i in 1:100) { tempmat <- subset(data.mat,ID==groupids[i]) #Run various stats on tempmat (correlations, regressions, etc), checking to #make sure this specific group doesn't have NAs in the variables I'm using #and assign results to x, y, and z, for example. results[i,1] <- x results[i,2] <- y results[i,3] <- z } This ends up working for me, but depending on the size of the data and the number of groups I'm working with, this can take up to three days. Besides branching out into parallel processing, is there any "trick" for making something like this run faster? For instance, converting the loops into something else (something like an apply with a function containing the stats I want to run inside the loop), or eliminating the need to actually assign the subset of data to a variable?

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  • R optimization: How can I avoid a for loop in this situation?

    - by chrisamiller
    I'm trying to do a simple genomic track intersection in R, and running into major performance problems, probably related to my use of for loops. In this situation, I have pre-defined windows at intervals of 100bp and I'm trying to calculate how much of each window is covered by the annotations in mylist. Graphically, it looks something like this: 0 100 200 300 400 500 600 windows: |-----|-----|-----|-----|-----|-----| mylist: |-| |-----------| So I wrote some code to do just that, but it's fairly slow and has become a bottleneck in my code: ##window for each 100-bp segment windows <- numeric(6) ##second track mylist = vector("list") mylist[[1]] = c(1,20) mylist[[2]] = c(120,320) ##do the intersection for(i in 1:length(mylist)){ st <- floor(mylist[[i]][1]/100)+1 sp <- floor(mylist[[i]][2]/100)+1 for(j in st:sp){ b <- max((j-1)*100, mylist[[i]][1]) e <- min(j*100, mylist[[i]][2]) windows[j] <- windows[j] + e - b + 1 } } print(windows) [1] 20 81 101 21 0 0 Naturally, this is being used on data sets that are much larger than the example I provide here. Through some profiling, I can see that the bottleneck is in the for loops, but my clumsy attempt to vectorize it using *apply functions resulted in code that runs an order of magnitude more slowly. I suppose I could write something in C, but I'd like to avoid that if possible. Can anyone suggest another approach that will speed this calculation up?

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  • Wpf. Chart optimization. More than million points

    - by Evgeny
    I have custom control - chart with size, for example, 300x300 pixels and more than one million points (maybe less) in it. And its clear that now he works very slowly. I am searching for algoritm which will show only few points with minimal visual difference. I have link to component which have functionallity exactly what i need (2 million points demo): http://www.mindscape.co.nz/demo/SilverlightElements/demopage.html#/ChartOverviewPage I will be grateful for any matherials, links or thoughts how to realize such functionallity.

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  • Python2.7: How can I speed up this bit of code (loop/lists/tuple optimization)?

    - by user89
    I repeat the following idiom again and again. I read from a large file (sometimes, up to 1.2 million records!) and store the output into an SQLite databse. Putting stuff into the SQLite DB seems to be fairly fast. def readerFunction(recordSize, recordFormat, connection, outputDirectory, outputFile, numObjects): insertString = "insert into NODE_DISP_INFO(node, analysis, timeStep, H1_translation, H2_translation, V_translation, H1_rotation, H2_rotation, V_rotation) values (?, ?, ?, ?, ?, ?, ?, ?, ?)" analysisNumber = int(outputPath[-3:]) outputFileObject = open(os.path.join(outputDirectory, outputFile), "rb") outputFileObject, numberOfRecordsInFileObject = determineNumberOfRecordsInFileObjectGivenRecordSize(recordSize, outputFileObject) numberOfRecordsPerObject = (numberOfRecordsInFileObject//numberOfObjects) loop1StartTime = time.time() for i in range(numberOfRecordsPerObject ): processedRecords = [] loop2StartTime = time.time() for j in range(numberOfObjects): fout = outputFileObject .read(recordSize) processedRecords.append(tuple([j+1, analysisNumber, i] + [x for x in list(struct.unpack(recordFormat, fout))])) loop2EndTime = time.time() print "Time taken to finish loop2: {}".format(loop2EndTime-loop2StartTime) dbInsertStartTime = time.time() connection.executemany(insertString, processedRecords) dbInsertEndTime = time.time() loop1EndTime = time.time() print "Time taken to finish loop1: {}".format(loop1EndTime-loop1StartTime) outputFileObject.close() print "Finished reading output file for analysis {}...".format(analysisNumber) When I run the code, it seems that "loop 2" and "inserting into the database" is where most execution time is spent. Average "loop 2" time is 0.003s, but it is run up to 50,000 times, in some analyses. The time spent putting stuff into the database is about the same: 0.004s. Currently, I am inserting into the database every time after loop2 finishes so that I don't have to deal with running out RAM. What could I do to speed up "loop 2"?

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  • SQL SERVER – DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28

    - by pinaldave
    The key Dynamic Management View (DMV) that helps us to understand wait stats is sys.dm_os_wait_stats; this DMV gives us all the information that we need to know regarding wait stats. However, the interpretation is left to us. This is a challenge as understanding wait stats can often be quite tricky. Anyway, we will cover few wait stats in one of the future articles. Today we will go over the basic understanding of the DMV. The Official Book OnLine Reference for DMV is over here: sys.dm_os_wait_stats. I suggest you all to refer this for all the accuracy. Following is a statement from the online book: “Specific types of wait times during query execution can indicate bottlenecks or stall points within the query. Similarly, high wait times, or wait counts server wide can indicate bottlenecks or hot spots in interaction query interactions within the server instance.” This is the statement which has inspired me to write this series. Let us first run the following statement from DMV. SELECT * FROM sys.dm_os_wait_stats ORDER BY wait_time_ms DESC GO Above statement will show us few of the columns. Here it is quick explanation of each of the column. wait_type – this is the name of the wait type. There can be three different kinds of wait types – resource, queue and external. waiting_tasks_count – this incremental counter is a good indication of frequent the wait is happening. If this number is very high, it is good indication for us to investigate that particular wait type. It is quite possible that the wait time is considerably low, but the frequency of the wait is much high. wait_time_ms – this is total wait accumulated for any type of wait. This is the total wait time and includes singal_wait_time_ms. max_wait_time_ms – this indicates the maximum wait type ever occurred for that particular wait type. Using this, one can estimate the intensity of the wait type in past. Again, it is not necessary that this max wait time will occur every time; so do not over invest yourself here. signal_wait_time_ms – this is the wait time when thread is marked as runnable and it gets to the running state. If the runnable queue is very long, you will find that this wait time becomes high. Additionally, please note that this DMV does not show current wait type or wait stats. This is cumulative view of the all the wait stats since server (instance) restarted or wait stats have been cleared. In future blog post, we will also cover two more DMVs which can be helpful to identify wait-related issues. ?sys.dm_os_waiting_tasks sys.dm_exec_requests Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Updating Data in A Columnstore Index

    - by pinaldave
    So far I have written two articles on Columnstore Indexes, and both of them got very interesting readership. In fact, just recently I got a query on my previous article on Columnstore Index. Read the following two articles to get familiar with the Columnstore Index. They will give you a reference to the question which was asked by a certain reader: SQL SERVER – Fundamentals of Columnstore Index SQL SERVER – How to Ignore Columnstore Index Usage in Query Here is the reader’s question: ” When I tried to update my table after creating the Columnstore index, it gives me an error. What should I do?” When the Columnstore index is created on the table, the table becomes Read-Only table and it does not let any insert/update/delete on the table. The basic understanding is that Columnstore Index will be created on the table that is very huge and holds lots of data. If a table is small enough, there is no need to create a Columnstore index. The regular index should just help it. The reason why Columnstore index was needed is because the table was so big that retrieving the data was taking a really, really long time. Now, updating such a huge table is always a challenge by itself. If the Columnstore Index is created on the table, and the table needs to be updated, you need to know that there are various ways to update it. The easiest way is to disable the Index and enable it. Consider the following code: USE AdventureWorks GO -- Create New Table CREATE TABLE [dbo].[MySalesOrderDetail]( [SalesOrderID] [int] NOT NULL, [SalesOrderDetailID] [int] NOT NULL, [CarrierTrackingNumber] [nvarchar](25) NULL, [OrderQty] [smallint] NOT NULL, [ProductID] [int] NOT NULL, [SpecialOfferID] [int] NOT NULL, [UnitPrice] [money] NOT NULL, [UnitPriceDiscount] [money] NOT NULL, [LineTotal] [numeric](38, 6) NOT NULL, [rowguid] [uniqueidentifier] NOT NULL, [ModifiedDate] [datetime] NOT NULL ) ON [PRIMARY] GO -- Create clustered index CREATE CLUSTERED INDEX [CL_MySalesOrderDetail] ON [dbo].[MySalesOrderDetail] ( [SalesOrderDetailID]) GO -- Create Sample Data Table -- WARNING: This Query may run upto 2-10 minutes based on your systems resources INSERT INTO [dbo].[MySalesOrderDetail] SELECT S1.* FROM Sales.SalesOrderDetail S1 GO 100 -- Create ColumnStore Index CREATE NONCLUSTERED COLUMNSTORE INDEX [IX_MySalesOrderDetail_ColumnStore] ON [MySalesOrderDetail] (UnitPrice, OrderQty, ProductID) GO -- Attempt to Update the table UPDATE [dbo].[MySalesOrderDetail] SET OrderQty = OrderQty +1 WHERE [SalesOrderID] = 43659 GO /* It will throw following error Msg 35330, Level 15, State 1, Line 2 UPDATE statement failed because data cannot be updated in a table with a columnstore index. Consider disabling the columnstore index before issuing the UPDATE statement, then rebuilding the columnstore index after UPDATE is complete. */ A similar error also shows up for Insert/Delete function. Here is the workaround. Disable the Columnstore Index and performance update, enable the Columnstore Index: -- Disable the Columnstore Index ALTER INDEX [IX_MySalesOrderDetail_ColumnStore] ON [dbo].[MySalesOrderDetail] DISABLE GO -- Attempt to Update the table UPDATE [dbo].[MySalesOrderDetail] SET OrderQty = OrderQty +1 WHERE [SalesOrderID] = 43659 GO -- Rebuild the Columnstore Index ALTER INDEX [IX_MySalesOrderDetail_ColumnStore] ON [dbo].[MySalesOrderDetail] REBUILD GO This time it will not throw an error while the update of the table goes successfully. Let us do a cleanup of our tables using this code: -- Cleanup DROP INDEX [IX_MySalesOrderDetail_ColumnStore] ON [dbo].[MySalesOrderDetail] GO TRUNCATE TABLE dbo.MySalesOrderDetail GO DROP TABLE dbo.MySalesOrderDetail GO In the next post we will see how we can use Partition to update the Columnstore Index. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – A Puzzle Part 4 – Fun with SEQUENCE in SQL Server 2012 – Guess the Next Value

    - by pinaldave
    It seems like every weekend I get a new puzzle in my mind. Before continuing I suggest you read my previous posts here where I have shared earlier puzzles. A Puzzle – Fun with SEQUENCE in SQL Server 2012 – Guess the Next Value  A Puzzle Part 2 – Fun with SEQUENCE in SQL Server 2012 – Guess the Next Value A Puzzle Part 3 – Fun with SEQUENCE in SQL Server 2012 – Guess the Next Value After reading above three posts, I am very confident that you all will be ready for the next set of puzzles now. First execute the script which I have written here. Now guess what will be the next value as requested in the query. USE TempDB GO -- Create sequence CREATE SEQUENCE dbo.SequenceID AS DECIMAL(3,0) START WITH 1 INCREMENT BY -1 MINVALUE 1 MAXVALUE 3 CYCLE NO CACHE; GO SELECT next value FOR dbo.SequenceID; -- Guess the number SELECT next value FOR dbo.SequenceID; -- Clean up DROP SEQUENCE dbo.SequenceID; GO Please note that Starting value is 1, Increment value is the negative value of -1 and Minimum value is 3. Now let us first assume how this will work out. In our example of the sequence starting value is equal to 1 and decrement value is -1, this means the value should decrement from 1 to 0. However, the minimum value is 1. This means the value cannot further decrement at all. What will happen here? The natural assumption is that it should throw an error. How many of you are assuming about query will throw an ERROR? Well, you are WRONG! Do not blame yourself, it is my fault as I have told you only half of the story. Now if you have voted for error, let us continue running above code in SQL Server Management Studio. The above script will give the following output: Isn’t it interesting that instead of error out it is giving us result value 3. To understand the answer about the same, carefully observe the original syntax of creating SEQUENCE – there is a keyword CYCLE. This keyword cycles the values between the minimum and maximum value and when one of the range is exhausted it cycles the values from the other end of the cycle. As we have negative incremental value when query reaches to the minimum value or lower end it will cycle it from the maximum value. Here the maximum value is 3 so the next logical value is 3. If your business requirement is such that if sequence reaches the maximum or minimum value, it should throw an error, you should not use the keyword cycle, and it will behave as discussed. I hope, you are enjoying the puzzles as much as I am enjoying it. If you have any interesting puzzle to share, please do share with me and I will share this on blog with due credit to you. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL SERVER – Puzzle #1 – Querying Pattern Ranges and Wild Cards

    - by Pinal Dave
    Note: Read at the end of the blog post how you can get five Joes 2 Pros Book #1 and a surprise gift. I have been blogging for almost 7 years and every other day I receive questions about Querying Pattern Ranges. The most common way to solve the problem is to use Wild Cards. However, not everyone knows how to use wild card properly. SQL Queries 2012 Joes 2 Pros Volume 1 – The SQL Queries 2012 Hands-On Tutorial for Beginners Book On Amazon | Book On Flipkart Learn SQL Server get all the five parts combo kit Kit on Amazon | Kit on Flipkart Many people know wildcards are great for finding patterns in character data. There are also some special sequences with wildcards that can give you even more power. This series from SQL Queries 2012 Joes 2 Pros® Volume 1 will show you some of these cool tricks. All supporting files are available with a free download from the www.Joes2Pros.com web site. This example is from the SQL 2012 series Volume 1 in the file SQLQueries2012Vol1Chapter2.2Setup.sql. If you need help setting up then look in the “Free Videos” section on Joes2Pros under “Getting Started” called “How to install your labs” Querying Pattern Ranges The % wildcard character represents any number of characters of any length. Let’s find all first names that end in the letter ‘A’. By using the percentage ‘%’ sign with the letter ‘A’, we achieve this goal using the code sample below: SELECT * FROM Employee WHERE FirstName LIKE '%A' To find all FirstName values beginning with the letters ‘A’ or ‘B’ we can use two predicates in our WHERE clause, by separating them with the OR statement. Finding names beginning with an ‘A’ or ‘B’ is easy and this works fine until we want a larger range of letters as in the example below for ‘A’ thru ‘K’: SELECT * FROM Employee WHERE FirstName LIKE 'A%' OR FirstName LIKE 'B%' OR FirstName LIKE 'C%' OR FirstName LIKE 'D%' OR FirstName LIKE 'E%' OR FirstName LIKE 'F%' OR FirstName LIKE 'G%' OR FirstName LIKE 'H%' OR FirstName LIKE 'I%' OR FirstName LIKE 'J%' OR FirstName LIKE 'K%' The previous query does find FirstName values beginning with the letters ‘A’ thru ‘K’. However, when a query requires a large range of letters, the LIKE operator has an even better option. Since the first letter of the FirstName field can be ‘A’, ‘B’, ‘C’, ‘D’, ‘E’, ‘F’, ‘G’, ‘H’, ‘I’, ‘J’ or ‘K’, simply list all these choices inside a set of square brackets followed by the ‘%’ wildcard, as in the example below: SELECT * FROM Employee WHERE FirstName LIKE '[ABCDEFGHIJK]%' A more elegant example of this technique recognizes that all these letters are in a continuous range, so we really only need to list the first and last letter of the range inside the square brackets, followed by the ‘%’ wildcard allowing for any number of characters after the first letter in the range. Note: A predicate that uses a range will not work with the ‘=’ operator (equals sign). It will neither raise an error, nor produce a result set. --Bad query (will not error or return any records) SELECT * FROM Employee WHERE FirstName = '[A-K]%' Question: You want to find all first names that start with the letters A-M in your Customer table and end with the letter Z. Which SQL code would you use? a. SELECT * FROM Customer WHERE FirstName LIKE 'm%z' b. SELECT * FROM Customer WHERE FirstName LIKE 'a-m%z' c. SELECT * FROM Customer WHERE FirstName LIKE 'a-m%z' d. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]%z' e. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]z%' f. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]%z' g. SELECT * FROM Customer WHERE FirstName LIKE '[a-m]z%' Contest Leave a valid answer before June 18, 2013 in the comment section. 5 winners will be selected from all the valid answers and will receive Joes 2 Pros Book #1. 1 Lucky person will get a surprise gift from Joes 2 Pros. The contest is open for all the countries where Amazon ships the book (USA, UK, Canada, India and many others). Special Note: Read all the options before you provide valid answer as there is a small trick hidden in answers. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Developer Training – 6 Online Courses to Learn SQL Server, MySQL and Technology

    - by Pinal Dave
    Video courses are the next big thing and I am so happy that I have so far authored 6 different video courses with Pluralsight. Here is the list of the courses. I have listed all of my video courses over here. Note: If you click on the courses and it does not open, you need to login to Pluralsight with a valid username and password or sign up for a FREE trial. Please leave a comment with your favorite course in the comment section. Random 10 winners will get surprise gift via email. Bonus: If you list your favorite module from the course site. SQL Server Performance: Introduction to Query Tuning SQL Server performance tuning is an in-depth topic, and an art to master. A key component of overall application performance tuning is query tuning. Writing queries in an efficient manner, and making sure they execute in the most optimal way possible, is always a challenge. The basics revolve around the details of how SQL Server carries out query execution, so the optimizations explored in this course follow along the same lines. Click to View Course SQL Server Performance: Indexing Basics Indexes are the most crucial objects of the database. They are the first stop for any DBA and Developer when it is about performance tuning. There is a good side as well evil side of the indexes. To master the art of performance tuning one has to understand the fundamentals of the indexes and the best practices associated with the same. This course is for every DBA and Developer who deals with performance tuning and wants to use indexes to improve the performance of the server. Click to View Course SQL Server Questions and Answers This course is designed to help you better understand how to use SQL Server effectively. The course presents many of the common misconceptions about SQL Server, and then carefully debunks those misconceptions with clear explanations and short but compelling demos, showing you how SQL Server really works. This course is for anyone working with SQL Server databases who wants to improve her knowledge and understanding of this complex platform. Click to View Course MySQL Fundamentals MySQL is a popular choice of database for use in web applications, and is a central component of the widely used LAMP open source web application software stack. This course covers the fundamentals of MySQL, including how to install MySQL as well as written basic data retrieval and data modification queries. Click to View Course Building a Successful Blog Expressing yourself is the most common behavior of humans. Blogging has made easy to express yourself. Just like a letter or book has a structure and formula, blogging also has structure and formula. In this introductory course on blogging we will go over a few of the basics of blogging and show the way to get started with blogging immediately. If you already have a blog, this course will be even more relevant as this will discuss many of the common questions and issue you face in your blogging routine. Click to View Course Introduction to ColdFusion ColdFusion is rapid web application development platform. In this course you will learn the basics of how to use ColdFusion platform and rapidly develop web sites. The course begins with learning basics of ColdFusion Markup Language and moves to common development language practices. From there we move to frequent database operations and advanced concepts of Forms, Sessions and Cookies. The last module sums up all the concepts covered in the course with sample application. Click to View Course Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

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  • Correct way to handle path-finding collision matrix

    - by Xander Lamkins
    Here is an example of me utilizing path finding. The red grid represents the grid utilized by my A* library to locate a distance. This picture is only an example, currently it is all calculated on the 1x1 pixel level (pretty darn laggy). I want to make it so that the farther I click, the less accurate it will be (split the map into larger grid pieces). Edit: as mentioned by Eric, this is not a required game mechanic. I am perfectly fine with any method that allows me to make this accurate while still fast. This isn't the really the topic of this question though. The problem I have is, my current library uses a two dimensional grid of integers. The higher the number in a cell, the more resistance for that grid tile. Currently I'm setting all unwalkable spots to Integer Max. Here is an example of what I want: I'm just not sure how I should set up the arrays of integers of the grid. Every time an element is added/removed to/from the game, it's collision details are updated in the table. Here is a picture of what the map looks like on my collision layer: I probably shouldn't be creating new arrays every time I have to do a path find because my game needs to support tons of PF at the same time. Should I have multiple arrays that are all updated when the dynamic elements are updated (a building is built/a building is destroyed). The problem I see with this is that it will probably make the creation and destruction of buildings a little more laggy than I would want because it would be setting the collision grid for each built in accuracy level. I would also have to add more/remove some arrays if I ever in the future changed the map size. Should I generate the new array based on an accuracy value every time I need to PF? The problem I see with this is that it will probably make any form of PF just as laggy because it will have to search through a MapWidth x MapHeight number of cells to shrink it all down. Or is there a better way? I'm certainly not the best at optimizing really anything. I've just started dealing with XNA so I'm not used to having optimization code really doing much of an affect until now... :( If you need code examples, please ask. I'll add it as an edit. EDIT: While this doesn't directly relate to the question, I figure the more information I provide, the better. To keep your units from moving as accurately to the players desired position, I've decided that once the unit PFs over to the less accurate grid piece, it will then PF on a more accurate level to the exact position requested.

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  • Does OO, TDD, and Refactoring to Smaller Functions affect Speed of Code?

    - by Dennis
    In Computer Science field, I have noticed a notable shift in thinking when it comes to programming. The advice as it stands now is write smaller, more testable code refactor existing code into smaller and smaller chunks of code until most of your methods/functions are just a few lines long write functions that only do one thing (which makes them smaller again) This is a change compared to the "old" or "bad" code practices where you have methods spanning 2500 lines, and big classes doing everything. My question is this: when it call comes down to machine code, to 1s and 0s, to assembly instructions, should I be at all concerned that my class-separated code with variety of small-to-tiny functions generates too much extra overhead? While I am not exactly familiar with how OO code and function calls are handled in ASM in the end, I do have some idea. I assume that each extra function call, object call, or include call (in some languages), generate an extra set of instructions, thereby increasing code's volume and adding various overhead, without adding actual "useful" code. I also imagine that good optimizations can be done to ASM before it is actually ran on the hardware, but that optimization can only do so much too. Hence, my question -- how much overhead (in space and speed) does well-separated code (split up across hundreds of files, classes, and methods) actually introduce compared to having "one big method that contains everything", due to this overhead? UPDATE for clarity: I am assuming that adding more and more functions and more and more objects and classes in a code will result in more and more parameter passing between smaller code pieces. It was said somewhere (quote TBD) that up to 70% of all code is made up of ASM's MOV instruction - loading CPU registers with proper variables, not the actual computation being done. In my case, you load up CPU's time with PUSH/POP instructions to provide linkage and parameter passing between various pieces of code. The smaller you make your pieces of code, the more overhead "linkage" is required. I am concerned that this linkage adds to software bloat and slow-down and I am wondering if I should be concerned about this, and how much, if any at all, because current and future generations of programmers who are building software for the next century, will have to live with and consume software built using these practices. UPDATE: Multiple files I am writing new code now that is slowly replacing old code. In particular I've noted that one of the old classes was a ~3000 line file (as mentioned earlier). Now it is becoming a set of 15-20 files located across various directories, including test files and not including PHP framework I am using to bind some things together. More files are coming as well. When it comes to disk I/O, loading multiple files is slower than loading one large file. Of course not all files are loaded, they are loaded as needed, and disk caching and memory caching options exist, and yet still I believe that loading multiple files takes more processing than loading a single file into memory. I am adding that to my concern.

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  • Sorting: TransientVO Vs Query/EO based VO

    - by Vijay Mohan
    In ADF, you can do a sorting on VO rows by invoking setSortBy("VOAttrName") API, but the tricky part is that, this API actually appends a clause to VO query at runtime and the actual sorting is performed after doing VO.executeQuery(), this goes fine for Query/EO based VO. But, how about the transient VO, wherein the rows are populated programmatically..?There is a way to it..:)you can actually specify the query mode on your transient VO, so that the sorting happens on already populated VO rows.Here are the steps to go about it..//Populate your transient VO rows.//VO.setSortBy("YourVOAttrName");//VO.setQueryMode(ViewObject.QUERY_MODE_SCAN_VIEW_ROWS);//VO.executeQuery();So, here the executeQuery() is actually the trigger which calls for VO rows sorting.QUERY_MODE_SCAN_VIEW_ROWS flag makes sure that the sorting is performed on the already populated VO cache.

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  • SQL SERVER – Faster SQL Server Databases and Applications – Power and Control with SafePeak Caching Options

    - by Pinal Dave
    Update: This blog post is written based on the SafePeak, which is available for free download. Today, I’d like to examine more closely one of my preferred technologies for accelerating SQL Server databases, SafePeak. Safepeak’s software provides a variety of advanced data caching options, techniques and tools to accelerate the performance and scalability of SQL Server databases and applications. I’d like to look more closely at some of these options, as some of these capabilities could help you address lagging database and performance on your systems. To better understand the available options, it is best to start by understanding the difference between the usual “Basic Caching” vs. SafePeak’s “Dynamic Caching”. Basic Caching Basic Caching (or the stale and static cache) is an ability to put the results from a query into cache for a certain period of time. It is based on TTL, or Time-to-live, and is designed to stay in cache no matter what happens to the data. For example, although the actual data can be modified due to DML commands (update/insert/delete), the cache will still hold the same obsolete query data. Meaning that with the Basic Caching is really static / stale cache.  As you can tell, this approach has its limitations. Dynamic Caching Dynamic Caching (or the non-stale cache) is an ability to put the results from a query into cache while maintaining the cache transaction awareness looking for possible data modifications. The modifications can come as a result of: DML commands (update/insert/delete), indirect modifications due to triggers on other tables, executions of stored procedures with internal DML commands complex cases of stored procedures with multiple levels of internal stored procedures logic. When data modification commands arrive, the caching system identifies the related cache items and evicts them from cache immediately. In the dynamic caching option the TTL setting still exists, although its importance is reduced, since the main factor for cache invalidation (or cache eviction) become the actual data updates commands. Now that we have a basic understanding of the differences between “basic” and “dynamic” caching, let’s dive in deeper. SafePeak: A comprehensive and versatile caching platform SafePeak comes with a wide range of caching options. Some of SafePeak’s caching options are automated, while others require manual configuration. Together they provide a complete solution for IT and Data managers to reach excellent performance acceleration and application scalability for  a wide range of business cases and applications. Automated caching of SQL Queries: Fully/semi-automated caching of all “read” SQL queries, containing any types of data, including Blobs, XMLs, Texts as well as all other standard data types. SafePeak automatically analyzes the incoming queries, categorizes them into SQL Patterns, identifying directly and indirectly accessed tables, views, functions and stored procedures; Automated caching of Stored Procedures: Fully or semi-automated caching of all read” stored procedures, including procedures with complex sub-procedure logic as well as procedures with complex dynamic SQL code. All procedures are analyzed in advance by SafePeak’s  Metadata-Learning process, their SQL schemas are parsed – resulting with a full understanding of the underlying code, objects dependencies (tables, views, functions, sub-procedures) enabling automated or semi-automated (manually review and activate by a mouse-click) cache activation, with full understanding of the transaction logic for cache real-time invalidation; Transaction aware cache: Automated cache awareness for SQL transactions (SQL and in-procs); Dynamic SQL Caching: Procedures with dynamic SQL are pre-parsed, enabling easy cache configuration, eliminating SQL Server load for parsing time and delivering high response time value even in most complicated use-cases; Fully Automated Caching: SQL Patterns (including SQL queries and stored procedures) that are categorized by SafePeak as “read and deterministic” are automatically activated for caching; Semi-Automated Caching: SQL Patterns categorized as “Read and Non deterministic” are patterns of SQL queries and stored procedures that contain reference to non-deterministic functions, like getdate(). Such SQL Patterns are reviewed by the SafePeak administrator and in usually most of them are activated manually for caching (point and click activation); Fully Dynamic Caching: Automated detection of all dependent tables in each SQL Pattern, with automated real-time eviction of the relevant cache items in the event of “write” commands (a DML or a stored procedure) to one of relevant tables. A default setting; Semi Dynamic Caching: A manual cache configuration option enabling reducing the sensitivity of specific SQL Patterns to “write” commands to certain tables/views. An optimization technique relevant for cases when the query data is either known to be static (like archive order details), or when the application sensitivity to fresh data is not critical and can be stale for short period of time (gaining better performance and reduced load); Scheduled Cache Eviction: A manual cache configuration option enabling scheduling SQL Pattern cache eviction based on certain time(s) during a day. A very useful optimization technique when (for example) certain SQL Patterns can be cached but are time sensitive. Example: “select customers that today is their birthday”, an SQL with getdate() function, which can and should be cached, but the data stays relevant only until 00:00 (midnight); Parsing Exceptions Management: Stored procedures that were not fully parsed by SafePeak (due to too complex dynamic SQL or unfamiliar syntax), are signed as “Dynamic Objects” with highest transaction safety settings (such as: Full global cache eviction, DDL Check = lock cache and check for schema changes, and more). The SafePeak solution points the user to the Dynamic Objects that are important for cache effectiveness, provides easy configuration interface, allowing you to improve cache hits and reduce cache global evictions. Usually this is the first configuration in a deployment; Overriding Settings of Stored Procedures: Override the settings of stored procedures (or other object types) for cache optimization. For example, in case a stored procedure SP1 has an “insert” into table T1, it will not be allowed to be cached. However, it is possible that T1 is just a “logging or instrumentation” table left by developers. By overriding the settings a user can allow caching of the problematic stored procedure; Advanced Cache Warm-Up: Creating an XML-based list of queries and stored procedure (with lists of parameters) for periodically automated pre-fetching and caching. An advanced tool allowing you to handle more rare but very performance sensitive queries pre-fetch them into cache allowing high performance for users’ data access; Configuration Driven by Deep SQL Analytics: All SQL queries are continuously logged and analyzed, providing users with deep SQL Analytics and Performance Monitoring. Reduce troubleshooting from days to minutes with database objects and SQL Patterns heat-map. The performance driven configuration helps you to focus on the most important settings that bring you the highest performance gains. Use of SafePeak SQL Analytics allows continuous performance monitoring and analysis, easy identification of bottlenecks of both real-time and historical data; Cloud Ready: Available for instant deployment on Amazon Web Services (AWS). As you can see, there are many options to configure SafePeak’s SQL Server database and application acceleration caching technology to best fit a lot of situations. If you’re not familiar with their technology, they offer free-trial software you can download that comes with a free “help session” to help get you started. You can access the free trial here. Also, SafePeak is available to use on Amazon Cloud. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Create a Very First Report with the Report Wizard

    - by Pinal Dave
    This example is from the Beginning SSRS by Kathi Kellenberger. Supporting files are available with a free download from the www.Joes2Pros.com web site. What is the report Wizard? In today’s world automation is all around you. Henry Ford began building his Model T automobiles on a moving assembly line a century ago and changed the world. The moving assembly line allowed Ford to build identical cars quickly and cheaply. Henry Ford said in his autobiography “Any customer can have a car painted any color that he wants so long as it is black.” Today you can buy a car straight from the factory with your choice of several colors and with many options like back up cameras, built-in navigation systems and heated leather seats. The assembly lines now use robots to perform some tasks along with human workers. When you order your new car, if you want something special, not offered by the manufacturer, you will have to find a way to add it later. In computer software, we also have “assembly lines” called wizards. A wizard will ask you a series of questions, often branching to specific questions based on earlier answers, until you get to the end of the wizard. These wizards are used for many things, from something simple like setting up a rule in Outlook to performing administrative tasks on a server. Often, a wizard will get you part of the way to the end result, enough to get much of the tedious work out of the way. Once you get the product from the wizard, if the wizard is not capable of doing something you need, you can tweak the results. Create a Report with the Report Wizard Let’s get started with your first report!  Launch SQL Server Data Tools (SSDT) from the Start menu under SQL Server 2012. Once SSDT is running, click New Project to launch the New Project dialog box. On the left side of the screen expand Business Intelligence and select Reporting Services. Configure the properties as shown in . Be sure to select Report Server Project Wizard as the type of report and to save the project in the C:\Joes2Pros\SSRSCompanionFiles\Chapter3\Project folder. Click OK and wait for the Report Wizard to launch. Click Next on the Welcome screen.  On the Select the Data Source screen, make sure that New data source is selected. Type JProCo as the data source name. Make sure that Microsoft SQL Server is selected in the Type dropdown. Click Edit to configure the connection string on the Connection Properties dialog box. If your SQL Server database server is installed on your local computer, type in localhost for the Server name and select the JProCo database from the Select or enter a database name dropdown. Click OK to dismiss the Connection Properties dialog box. Check Make this a shared data source and click Next. On the Design the Query screen, you can use the query builder to build a query if you wish. Since this post is not meant to teach you T-SQL queries, you will copy all queries from files that have been provided for you. In the C:\Joes2Pros\SSRSCompanionFiles\Chapter3\Resources folder open the sales by employee.sql file. Copy and paste the code from the file into the Query string Text Box. Click Next. On the Select the Report Type screen, choose Tabular and click Next. On the Design the Table screen, you have to figure out the groupings of the report. How do you do this? Well, you often need to know a bit about the data and report requirements. I often draw the report out on paper first to help me determine the groups. In the case of this report, I could group the data several ways. Do I want to see the data grouped by Year and Month? Do I want to see the data grouped by Employee or Category? The only thing I know for sure about this ahead of time is that the TotalSales goes in the Details section. Let’s assume that the CIO asked to see the data grouped first by Year and Month, then by Category. Let’s move the fields to the right-hand side. This is done by selecting Page > Group or Details >, as shown in, and click Next. On the Choose the Table Layout screen, select Stepped and check Include subtotals and Enable drilldown, as shown in. On the Choose the Style screen, choose any color scheme you wish (unlike the Model T) and click Next. I chose the default, Slate. On the Choose the Deployment Location screen, change the Deployment folder to Chapter 3 and click Next. At the Completing the Wizard screen, name your report Employee Sales and click Finish. After clicking Finish, the report and a shared data source will appear in the Solution Explorer and the report will also be visible in Design view. Click the Preview tab at the top. This report expects the user to supply a year which the report will then use as a filter. Type in a year between 2006 and 2013 and click View Report. Click the plus sign next to the Sales Year to expand the report to see the months, then expand again to see the categories and finally the details. You now have the assembly line report completed, and you probably already have some ideas on how to improve the report. Tomorrow’s Post Tomorrow’s blog post will show how to create your own data sources and data sets in SSRS. If you want to learn SSRS in easy to simple words – I strongly recommend you to get Beginning SSRS book from Joes 2 Pros. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Reporting Services, SSRS

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  • regular expression or replace function in where clause of a mysql query.

    - by Salil
    Hi All, I write a mysql query select * from table where name like '%salil%' which works fine but it will no return records with name 'sal-il', 'sa@lil'. So i want a query something like below select * from table where remove_special_character_from(name) like '%salil%' remove_special_character_from(name) is a mysql method or a regular expression which remove all the special characters from name before like executed.

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  • How to query through a DBRef in MongoDB/pymongo?

    - by Soviut
    Is it possible to query through a DBRef using a single find spec? user collection { 'age': 30 } post collection { 'user': DBRef('user', ...) } Is it possible to query for all post who's users are 30 in a single find step? If not, would it be wise to create a javascript function to handle the multi-stage operation or will that cause blocking problems?

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  • Sql query listing Fathers and childs with joins, how to distinct them?

    - by DaNieL
    Having those tables: table_n1: | t1_id | t1_name | | 1 | foo | table_n2: | t2_id | t1_id | t2_name | | 1 | 1 | bar | I need a query that gives me two result: | names | | foo | | foo / bar | But i cant figure out the right way. I wrote this one: SELECT CONCAT_WS(' / ', table_n1.t1_name, table_n2.t2_name) AS names FROM table_n1 LEFT JOIN table_n2 ON table_n2.t1_id = table_n1.t1_id that works for an half: this only return the 2° row (in the example above): | names | | foo - bar | This query return the 'father' (table_n1) name only when it doesnt have 'childs' (table_n2). How can i fix it?

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  • Is it poor practice to build an SQL query using WHERE 1=1 AND ...

    - by Rob
    I'm writing a script that builds an SQL query by concatenating the string and adding conditions to the WHERE clause as needed. Would it be better practice to use WHERE 1=1 so that the first condition is satisfied and the script can just concatenate an AND x = 'y' to the query, or should I write the extra code to check if a clause has been added and if not, add the AND ? Confusing question, I know. Let me know if I need to be more clear. Rob

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