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• how to get svn/cvs log record by java?

  - by Eric

  I want to cut the svn/cvs recods in pieces and then put in to database. After that i can make use of those data easily. Any java function can get out the record? and How? If possible, please provide a example. Thank you.

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• how to get svc/cvs log record by java?

  - by Eric

  I want to cut the svn/cvs recods in pieces and then put in to database. After that i can make use of those data easily. Any java function can get out the record? and How? If possible, please provide a example. Thank you.

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• How to select the last record from MySQL table using SQl syntax.

  - by Vafello

  I have a table with several records. There is an id field. I would like to select the record with the most recent id (i.e. the ighest id). Any ideas?

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• Application Composer Series: Where and When to use Groovy

  - by Richard Bingham

  This brief post is really intended as more of a reference than an article. The table below highlights two things, firstly where you can add you own custom logic via groovy code (end column), and secondly (middle column) when you might use each particular feature. Obviously this applies only where Application Composer exists, namely Fusion CRM and Oracle Sales Cloud, and is based on current (release 8) functionality. Feature Most Common Use Case Groovy Field Triggers React to run-time data changes. Only fired when the field is changed and upon submit. Y Object Triggers To extend the standard processing logic for an object, based on record creation, updates and deletes. There is a split between these firing events, with some related to UI/ADF actions and others originating in the database. UI Trigger Points: After Create - fires when a new object record is created. Commonly used to set default values for fields. Before Modify - Fires when the end-user tries to modify a field value. Could be used for generic warnings or extra security logic. Before Invalidate - Fires on the parent object when one of its child object records is created, updated, or deleted. For building in relationship logic. Before Remove - Fires when an attempt is made to delete an object record. Can be used to create conditions that prevent deletes. Database Trigger Points: Before Insert in Database - Fires before a new object is inserted into the database. Can be used to ensure a dependent record exists or check for duplicates. After Insert in Database - Fires after a new object is inserted into the database. Could be used to create a complementary record. Before Update in Database -Fires before an existing object is modified in the database. Could be used to check dependent record values. After Update in Database - Fires after an existing object is modified in the database. Could be used to update a complementary record. Before Delete in Database - Fires before an existing object is deleted from the database. Could be used to check dependent record values. After Delete in Database - Fires after an existing object is deleted from the database. Could be used to remove dependent records. After Commit in Database - Fires after the change pending for the current object (insert, update, delete) is made permanent in the current transaction. Could be used when committed data that has passed all validation is required. After Changes Posted to Database - Fires after all changes have been posted to the database, but before they are permanently committed. Could be used to make additional changes that will be saved as part of the current transaction. Y Field Validation Displays a user entered error message based groovy logic validating the field value. The message is shown only when the validation logic returns false, and the logic is triggered only when tabbing out of the field on the user interface. Y Object Validation Commonly used where validation is needed across multiple related fields on the object. Triggered on the submit UI action. Y Object Workflows All Object Workflows are fired upon either record creation or update, along with the option of adding a custom groovy firing condition. Y Field Updates - change another field when a specified one changes. Intended as an easy way to set different run-time values (e.g. pick values for LOV's) plus the value field permits groovy logic entry. Y E-Mail Notification - sends an email notification to specified users/roles. Templates support using run-time value tokens and rich text. N Task Creation - for adding standard tasks for use in the worklist functionality. N Outbound Message - will create and send an XML payload of the related object SDO to a specified endpoint. N Business Process Flow - intended for approval using the seeded process, however can also trigger custom BPMN flows. N Global Functions Utility functions that can be called from any groovy code in Application Composer (across applications). Y Object Functions Utility functions that are local to the parent object. Usually triggered from within 'Buttons and Actions' definitions in Application Composer, although can be called from other code for that object (e.g. from a trigger). Y Add Custom Fields When adding custom fields there are a few places you can include groovy logic. Y Default Value - to add logic within setting the default value when new records are entered. Y Conditionally Updateable - to add logic to set the field to read-only or not. Y Conditionally Required - to add logic to set the field to required or not. Y Formula Field - Used to provide a new aggregate field that is entirely based on groovy logic and other field values. Y Simplified UI Layouts - Advanced Expressions Used for creating dynamic layouts for simplified UI pages where fields and regions show/hide based on run-time context values and logic. Also includes support for the depends-on feature as a trigger. Y Related References This Blog: Application Composer Series Extending Sales Guide: Using Groovy Scripts Groovy Scripting Reference Guide

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• Java RegEx API "Look-behind group does not have an obvious maximum length near index ..."

  - by Foo Inc

  Hello, I'm on to some SQL where clause parsing and designed a working RegEx to find a column outside string literals using "Rad Software Regular Expression Desginer" which is using the .NET API. To make sure the designed RegEx works with Java too, I tested it by using the API of course (1.5 and 1.6). But guess what, it won't work. I got the message "Look-behind group does not have an obvious maximum length near index 28". The string that I'm trying to get parsed is Column_1='test''the''stuff''all''day''long' AND Column_2='000' AND TheVeryColumnIWantToFind = 'Column_1=''test''''the''''stuff''''all''''day''''long'' AND Column_2=''000'' AND TheVeryColumnIWantToFind = '' TheVeryColumnIWantToFind = '' AND (Column_3 is null or Column_3 = ''Not interesting'') AND ''1'' = ''1''' AND (Column_3 is null or Column_3 = 'Still not interesting') AND '1' = '1' As you may have guessed, I tried to create some kind of worst case to ensure the RegEx won't fail on more complicated SQL where clauses. The RegEx itself looks like this (?i:(?<!=\s*'(?:[^']|(?:''))*)((?<=\s*)TheVeryColumnIWantToFind(?=(?:\s+|=)))) I'm not sure if there is a more elegant RegEx (there'll most likely be one), but that's not important right now as it does the trick. To explain the RegEx in a few words: If it finds the column I'm after, it does a negative look-behind to figure out if the column name is used in a string literal. If so, it won't match. If not, it'll match. Back to the question. As I mentioned before, it won't work with Java. What will work and result in what I want? I found out, that Java does not seem to support unlimited look-behinds but still I couldn't get it to work. Isn't it right that a look-behind is always putting a limit up on itself from the search offset to the current search position? So it would result in something like "position - offset"?

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• CSS layout that fills available space

  - by Jared I

  I'm trying to do a seemingly simple webpage layout, but I'm hitting a wall. I'd like to do everything purely with CSS (no tables to much things up, and no javascript dynamically resizing things) I'd like to have: A heading with a fixed height A footer with a fixed height Left sidebar with a fixed width Right sidebar with a fixed width The whole layout always fills the entire viewport (i.e. if the user resizes the window, the layout grows to the new size) Put another way: |< Total width is 100% of viewport >| +--------------------------------------------------------------+ --- | Header with a fixed height | ^ |--------+-------------------------------------------+---------+ | | | | | | | | | Left | | Right | Total | with | Center grows in height/width | with | height | fixed | and has scrollbars if necessary | fixed | is | width | | width | 100% | | | | of | | | | viewport | | | | |--------+-------------------------------------------+---------| | Footer with a fixed height | v +--------------------------------------------------------------+ --- The parts that are giving me the most trouble are Having the sidebars and center have a height equal to the height of the viewport minus the heights of the header and footer Having the center have a width equal to the width of the viewport minus the widths of the two sidebars I have no problem requiring users to have a modern browser. I'm aware that similar questions to this have been asked before, such as Make a div fill remaining space (http://stackoverflow.com/questions/1717564) Three row tableless CSS layout with middle row that fills remaining space (http://stackoverflow.com/questions/1703455) Create 2 divs, one takes up remaining space (http://stackoverflow.com/questions/1717564) ... and the conclusion seems to be that there isn't a good solution. Those answers are somewhat old, so I'm hoping that someone knows the trick now.

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• Primary Key Identity Value Increments On Unique Key Constraint Violation

  - by Jed

  I have a SqlServer 2008 table which has a Primary Key (IsIdentity=Yes) and three other fields that make up a Unique Key constraint. In addition I have a store procedure that inserts a record into the table and I call the sproc via C# using a SqlConnection object. The C# sproc call works fine, however I have noticed interesting results when the C# sproc call violates the Unique Key constraint.... When the sproc call violates the Unique Key constraint, a SqlException is thrown - which is no surprise and cool. However, I notice that the next record that is successfully added to the table has a PK value that is not exactly one more than the previous record - For example: Say the table has five records where the PK values are 1,2,3,4, and 5. The sproc attempts to insert a sixth record, but the Unique Key constraint is violated and, so, the sixth record is not inserted. Then the sproc attempts to insert another record and this time it is successful. - This new record is given a PK value of 7 instead of 6. Is this normal behavior? If so, can you give me a reason why this is so? (If a record fails to insert, why is the PK index incremented?) If this is not normal behavior, can you give me any hints as to why I am seeing these symptoms?

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• How to implement a counter when using golang's goroutine?

  - by MrROY

  I'm trying to make a queue struct that have push and pop functions. I need to use 10 threads push and another 10 threads pop data, just like i did in the code below. Questions : 1. I need to print out how much i have pushed/popped, but i don't know how to do that. 2. Is there anyway to speed up my code ? the code is too slow for me. package main import ( "runtime" "time" ) const ( DATA_SIZE_PER_THREAD = 10000000 ) type Queue struct { records string } func (self Queue) push(record chan interface{}) { // need push counter record <- time.Now() } func (self Queue) pop(record chan interface{}) { // need pop counter <- record } func main() { runtime.GOMAXPROCS(runtime.NumCPU()) //record chan record := make(chan interface{},1000000) //finish flag chan finish := make(chan bool) queue := new(Queue) for i:=0; i<10; i++ { go func() { for j:=0; j<DATA_SIZE_PER_THREAD; j++ { queue.push(record) } finish<-true }() } for i:=0; i<10; i++ { go func() { for j:=0; j<DATA_SIZE_PER_THREAD; j++ { queue.pop(record) } finish<-true }() } for i:=0; i<20; i++ { <-finish } }

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• Linq to find pair of points with longest length?

  - by Chris

  I have the following code: foreach (Tuple<Point, Point> pair in pointsCollection) { var points = new List<Point>() { pair.Value1, pair.Value2 }; } Within this foreach, I would like to be able to determine which pair of points has the most significant length between the coordinates for each point within the pair. So, let's say that points are made up of the following pairs: (1) var points = new List<Point>() { new Point(0,100), new Point(100,100) }; (2) var points = new List<Point>() { new Point(150,100), new Point(200,100) }; So I have two sets of pairs, mentioned above. They both will plot a horizontal line. I am interested in knowing what the best approach would be to find the pair of points that have the greatest distance between, them, whether it is vertically or horizontally. In the two examples above, the first pair of points has a difference of 100 between the X coordinate, so that would be the point with the most significant difference. But if I have a collection of pairs of points, where some points will plot a vertical line, some points will plot a horizontal line, what would be the best approach for retrieving the pair from the set of points whose difference, again vertically or horizontally, is the greatest among all of the points in the collection? Thanks! Chris

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• Using RecordStore in Java J2ME

  - by me123

  Hi, I am currently doing some J2ME development. I am having a problem in that a user can add and remove elements to the record store, and if a record gets deleted, then that record is left empty and the others don't move up one. I'm trying to come up with a loop that will check if a record has anything in it (incase it has been deleted) and if it does then I want to add the contents of that record to a list. My code is similar to as follows: for (int i = 1; i <= rs.getNumRecords(); i++) { // Re-allocate if necessary if (rs.getRecordSize(i) > recData.length) recData = new byte[rs.getRecordSize(i)]; len = rs.getRecord(i, recData, 0); st = new String(recData, 0, len); System.out.println("Record #" + i + ": " + new String(recData, 0, len)); System.out.println("------------------------------"); if(st != null) { list.insert(i-1, st, null); } } When it gets to rs.getRecordSize(i), I always get a "javax.microedition.rms.InvalidRecordIDException: error finding record". I know this is due to the record being empty but I can't think of a way to get around this problem. Any help would be much appreciated. Thanks in advance.

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• Overloading operator>> to a char buffer in C++ - can I tell the stream length?

  - by exscape

  I'm on a custom C++ crash course. I've known the basics for many years, but I'm currently trying to refresh my memory and learn more. To that end, as my second task (after writing a stack class based on linked lists), I'm writing my own string class. It's gone pretty smoothly until now; I want to overload operator that I can do stuff like cin my_string;. The problem is that I don't know how to read the istream properly (or perhaps the problem is that I don't know streams...). I tried a while (!stream.eof()) loop that .read()s 128 bytes at a time, but as one might expect, it stops only on EOF. I want it to read to a newline, like you get with cin to a std::string. My string class has an alloc(size_t new_size) function that (re)allocates memory, and an append(const char *) function that does that part, but I obviously need to know the amount of memory to allocate before I can write to the buffer. Any advice on how to implement this? I tried getting the istream length with seekg() and tellg(), to no avail (it returns -1), and as I said looping until EOF (doesn't stop reading at a newline) reading one chunk at a time.

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• Length-1 arrays can be converted to python scalars error? python

  - by Randy

  from numpy import * from pylab import * from math import * def LogisticMap(a,x): return 4.*a*x*(1.-x) def CosineMap(a,x): return a*cos(x/(2.*pi)) def TentMap(a,x): if x>= 0 or x<0.5: return 2.*a*x if x>=0.5 or x<=1.: return 2.*a*(1.-x) a = 0.98 N = 40 xaxis = arange(0.0,N,1.0) Func = CosineMap subplot(211) title(str(Func.func_name) + ' at a=%g and its second iterate' %a) ylabel('X(n+1)') # set y-axis label plot(xaxis,Func(a,xaxis), 'g', antialiased=True) subplot(212) ylabel('X(n+1)') # set y-axis label xlabel('X(n)') # set x-axis label plot(xaxis,Func(a,Func(a,xaxis)), 'bo', antialiased=True) My program is supposed to take any of the three defined functions and plot it. They all take in a value x from the array xaxis from 0 to N and then return the value. I want it to plot a graph of xaxis vs f(xaxis) with f being any of the three above functions. The logisticmap function works fine, but for CosineMap i get the error "only length-1 arrays can be converted to python scalars" and for TentMap i get error "The truth value of an array with more than one element is ambiguous, use a.any() or a.all()". My tent map function is suppose to return 2*a*x if 0<=x<0.5 and it's suppose to return 2*a*(1-x) if 0.5<=0<=1.

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• Access Question

  - by kralco626

  I have a record set for inspections of many peices of equipment. The four cols of interest are equip_id,month,year,myData. My requirment is to have EXACTLY ONE Record per month for each peice of equipment. I have a quiery that makes the data unique over equip_id,month,year. So there is no more than one record for each month/year for a peice of equipment. But now I need to simulate data for the missing month. I want to simply go back in time to get the last peice of my data. So that may seem confusing, so i'll show by example. Given this: equip_id month year myData 1 1 2010 500 1 2 2010 600 1 5 2010 800 2 2 2010 300 2 4 2010 400 2 6 2010 500 I want this: equip_id month year myData 1 1 2010 500 1 2 2010 600 1 3 2010 600 1 4 2010 600 1 5 2010 800 2 2 2010 300 2 3 2010 300 2 4 2010 400 2 5 2010 400 2 6 2010 500 Notice that im filling in missing data with the data from the month ( or two months etc.) before. Also note that if the first record for equip 2 is in 2/2010 than I don't need a record for 1/2010 even though I have one for equip 1. I just need exactly one record for each month/year for each peice of equipment. So if the record does not exsist I just want to go back in time and grab the data for that record. Thanks!!!

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• Doctrine YAML not generating correctly? Or is this markup wrong?

  - by ropstah

  I'm trying to get a many-to-many relationship between Users and Settings. The models seem to be generated correctly, however the following query fails: "User_Setting" with an alias of "us" in your query does not reference the parent component it is related to. $q = new Doctrine_RawSql(); $q->select('{s.*}, {us.*}') ->from('User u CROSS JOIN Setting s LEFT JOIN User_Setting us ON us.usr_auto_key = u.usr_auto_key AND us.set_auto_key = s.set_auto_key') ->addComponent('s', 'Setting s INDEXBY s.set_auto_key') ->addComponent('us', 'User_Setting us') ->where(u.usr_auto_key = ?',$this->usr_auto_key); $this->settings = $q->execute(); Does anyone spot a problem? This is my YAML: User: connection: default tableName: User columns: usr_auto_key: type: integer(4) fixed: false unsigned: false primary: true autoincrement: true notnull: true email: type: string(100) fixed: false unsigned: false primary: false default: '' notnull: true autoincrement: false password: type: string(32) fixed: false unsigned: false primary: false default: '' notnull: true autoincrement: false relations: Setting: class: Setting foreignAlias: User refClass: User_Setting local: usr_auto_key foreign: set_auto_key Setting: connection: default tableName: Setting columns: set_auto_key: type: integer(4) fixed: false unsigned: false primary: true autoincrement: true notnull: true name: type: string(50) fixed: false unsigned: false primary: false notnull: true autoincrement: false User_Setting: connection: default tableName: User_Setting columns: usr_auto_key: type: integer(4) fixed: false unsigned: false primary: true autoincrement: false notnull: true set_auto_key: type: integer(4) fixed: false unsigned: false primary: true autoincrement: false notnull: true value: type: string(255) fixed: false unsigned: false primary: false notnull: true autoincrement: false relations: Setting: foreignAlias: User_Setting local: set_auto_key foreign: set_auto_key User: foreignAlias: User_Setting local: usr_auto_key foreign: usr_auto_key

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• how to create following Java applicatin? [on hold]

  - by Tushar Bichwe

  Write a JAVA program which performs the following listed operations: A. Create a package named MyEmpPackage which consists of following classes A class named Employee which stores information like the Emp number, first name, middle name, last name, address, designation and salary. The class should also contain appropriate get and set methods. 05 A class named AddEmployeeFrame which displays a frame consisting of appropriate controls to enter the details of a Employee and store these details in the Employee class object. The frame should also have three buttons with the caption as “Add Record” and “Delete Record” and “Exit”. 10 A class named MyCustomListener which should work as a user – defined event listener to handle required events as mentioned in following points. 05 B When the “Add Record” button is clicked, the dialog box should be appeared with asking the user “Do you really want to add record in the file”. If the user selects Yes than the record should be saved in the file. 10 When the “Exit” button is clicked, the frame should be closed. 10 [Note: Use the MyCustomListener class only to handle the appropriate events] C The “Delete Record” button should open a new frame which should take input of delete criteria using a radio button. The radio button should provide facility to delete on basis of first name, middle name or last name. 10 The new frame should also have a text box to input the delete criteria value. 10 The record should be deleted from the file and a message dialog should appear with the message that “Record is successfully Deleted”. 10 [Note: Use the MyCustomListener class only to handle the appropriate events] D Provide proper error messages and perform appropriate exceptions where ever required in all the classes 10

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• Using R to Analyze G1GC Log Files

  - by user12620111

  Using R to Analyze G1GC Log Files body, td { font-family: sans-serif; background-color: white; font-size: 12px; margin: 8px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } h1 { font-size:2.2em; } h2 { font-size:1.8em; } h3 { font-size:1.4em; } h4 { font-size:1.0em; } h5 { font-size:0.9em; } h6 { font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } pre { margin-top: 0; max-width: 95%; border: 1px solid #ccc; white-space: pre-wrap; } pre code { display: block; padding: 0.5em; } code.r, code.cpp { background-color: #F8F8F8; } table, td, th { border: none; } blockquote { color:#666666; margin:0; padding-left: 1em; border-left: 0.5em #EEE solid; } hr { height: 0px; border-bottom: none; border-top-width: thin; border-top-style: dotted; border-top-color: #999999; } @media print { * { background: transparent !important; color: black !important; filter:none !important; -ms-filter: none !important; } body { 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  Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

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• How to interpret iozone values

  - by Henno

  I ran a test to measure my I/O IOPS on Linux: iozone -s 4g -r 2k -r 4k -r 8k -r 16k -r 32k -O -b /tmp/results.xls iozone claims that output is in operations per second yet the numbers are too big for that to be plausible. I'm observing some 320 CMDs/s maximum on vmware esx console (esxtop, then v). File size set to 4194304 KB Record Size 2 KB Record Size 4 KB Record Size 8 KB Record Size 16 KB Record Size 32 KB OPS Mode. Output is in operations per second. Command line used: iozone -s 4g -r 2k -r 4k -r 8k -r 16k -r 32k -O -b tmpresults.xls Time Resolution = 0.000001 seconds. Processor cache size set to 1024 Kbytes. Processor cache line size set to 32 bytes. File stride size set to 17 * record size. random random bkwd record stride KB reclen write rewrite read reread read write read rewrite read fwrite frewrite fread freread 4194304 2 19025 5580 27581 29848 284 198 415 1103217 1498 18541 4340 24245 25618 4194304 4 15650 21942 18962 21068 252 1198 193 976164 1677 22802 23093 21089 21232 4194304 8 11121 11638 10273 10165 247 1196 202 625020^C The test ran for 15 hours before I pressed ^C. Is that ordinary expectation for such command line (dedicated 4 drive RAID10 LUN, 10k RPM SAS drives in EMC CX300)?

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• A pseudo-listener for AlwaysOn Availability Groups for SQL Server virtual machines running in Azure

  - by MikeD

  I am involved in a project that is implementing SharePoint 2013 on virtual machines hosted in Azure. The back end data tier consists of two Azure VMs running SQL Server 2012, with the SharePoint databases contained in an AlwaysOn Availability Group. I used this "Tutorial: AlwaysOn Availability Groups in Windows Azure (GUI)" to help me implement this setup.Because Azure DHCP will not assign multiple unique IP addresses to the same VM, having an AG Listener in Azure is not currently supported.  I wanted to figure out another mechanism to support a "pseudo listener" of some sort. First, I created a CNAME (alias) record in the DNS zone with a short TTL (time to live) of 5 minutes (I may yet make this even shorter). The record represents a logical name (let's say the alias is SPSQL) of the server to connect to for the databases in the availability group (AG). When Server1 was hosting the primary replica of the AG, I would set the CNAME of SPSQL to be SERVER1. When the AG failed over to Server1, I wanted to set the CNAME to SERVER2. Seemed simple enough.(It's important to point out that the connection strings for my SharePoint services should use the CNAME alias, and not the actual server name. This whole thing falls apart otherwise.)To accomplish this, I created identical SQL Agent Jobs on Server1 and Server2, with two steps:1. Step 1: Determine if this server is hosting the primary replica.This is a TSQL step using this script:declare @agName sysname = 'AGTest'set nocount on declare @primaryReplica sysnameselect @primaryReplica = agState.primary_replicafrom sys.dm_hadr_availability_group_states agState   join sys.availability_groups ag on agstate.group_id = ag.group_id   where ag.name = @AGname if not exists(   select *    from sys.dm_hadr_availability_group_states agState   join sys.availability_groups ag on agstate.group_id = ag.group_id   where @@Servername = agstate.primary_replica    and ag.name = @AGname)begin   raiserror ('Primary replica of %s is not hosted on %s, it is hosted on %s',17,1,@Agname, @@Servername, @primaryReplica) endThis script determines if the primary replica value of the AG group is the same as the server name, which means that our server is hosting the current AG (you should update the value of the @AgName variable to the name of your AG). If this is true, I want the DNS alias to point to this server. If the current server is not hosting the primary replica, then the script raises an error. Also, if the script can't be executed because it cannot connect to the server, that also will generate an error. For the job step settings, I set the On Failure option to "Quit the job reporting success". The next step in the job will set the DNS alias to this server name, and I only want to do that if I know that it is the current primary replica, otherwise I don't want to do anything. I also include the step output in the job history so I can see the error message.Job Step 2: Update the CNAME entry in DNS with this server's name.I used a PowerShell script to accomplish this:$cname = "SPSQL.contoso.com"$query = "Select * from MicrosoftDNS_CNAMEType"$dns1 = "dc01.contoso.com"$dns2 = "dc02.contoso.com"if ((Test-Connection -ComputerName $dns1 -Count 1 -Quiet) -eq $true){    $dnsServer = $dns1}elseif ((Test-Connection -ComputerName $dns2 -Count 1 -Quiet) -eq $true) {   $dnsServer = $dns2}else{  $msg = "Unable to connect to DNS servers: " + $dns1 + ", " + $dns2   Throw $msg}$record = Get-WmiObject -Namespace "root\microsoftdns" -Query $query -ComputerName $dnsServer  | ? { $_.Ownername -match $cname }$thisServer = [System.Net.Dns]::GetHostEntry("LocalHost").HostName + "."$currentServer = $record.RecordData if ($currentServer -eq $thisServer ) {     $cname + " CNAME is up to date: " + $currentServer}else{    $cname + " CNAME is being updated to " + $thisServer + ". It was " + $currentServer    $record.RecordData = $thisServer    $record.put()}This script does a few things:finds a responsive domain controller (Test-Connection does a ping and returns a Boolean value if you specify the -Quiet parameter)makes a WMI call to the domain controller to get the current CNAME record value (Get-WmiObject)gets the FQDN of this server (GetHostEntry)checks if the CNAME record is correct and updates it if necessary(You should update the values of the variables $cname, $dns1 and $dns2 for your environment.)Since my domain controllers are also hosted in Azure VMs, either one of them could be down at any point in time, so I need to find a DC that is responsive before attempting the DNS call. The other little thing here is that the CNAME record contains the FQDN of a machine, plus it ends with a period. So the comparison of the CNAME record has to take the trailing period into account. When I tested this step, I was getting ACCESS DENIED responses from PowerShell for the Get-WmiObject cmdlet that does a remote lookup on the DC. This occurred because the SQL Agent service account was not a member of the Domain Admins group, so I decided to create a SQL Credential to store the credentials for a domain administrator account and use it as a PowerShell proxy (rather than give the service account Domain Admins membership).In SQL Management Studio, right click on the Credentials node (under the server's Security node), and choose New Credential...Then, under SQL Agent-->Proxies, right click on the PowerShell node and choose New Proxy...Finally, in the job step properties for the PowerShell step, select the new proxy in the Run As drop down.I created this two step Job on both nodes of the Availability Group, but if you had more than two nodes, just create the same job on all the servers. I set the schedule for the job to execute every minute.When the server that is hosting the primary replica is running the job, the job history looks like this:The job history on the secondary server looks like this: When a failover occurs, the SQL Agent job on the new primary replica will detect that the CNAME needs to be updated within a minute. Based on the TTL of the CNAME (which I said at the beginning was 5 minutes), the SharePoint servers will get the new alias within five minutes and should be able to reconnect. I may want to shorten up the TTL to reduce the time it takes for the client connections to use the new alias. Using a DNS CNAME and a SQL Agent Job on all servers hosting AG replicas, I was able to create a pseudo-listener to automatically change the name of the server that was hosting the primary replica, for a scenario where I cannot use a regular AG listener (in this case, because the servers are all hosted in Azure).    

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• opengl problem works on droid but not droid eris and others.

  - by nathan

  This GlRenderer works fine on the moto droid, but does not work well at all on droid eris or other android phones does anyone know why? package com.ntu.way2fungames.spacehockeybase; import java.io.DataInputStream; import java.io.IOException; import java.nio.Buffer; import java.nio.FloatBuffer; import javax.microedition.khronos.egl.EGLConfig; import javax.microedition.khronos.opengles.GL10; import com.ntu.way2fungames.LoadFloatArray; import com.ntu.way2fungames.OGLTriReader; import android.content.res.AssetManager; import android.content.res.Resources; import android.opengl.GLU; import android.opengl.GLSurfaceView.Renderer; import android.os.Handler; import android.os.Message; public class GlRenderer extends Thread implements Renderer { private float drawArray[]; private float yoff; private float yoff2; private long lastRenderTime; private float[] yoffs= new float[10]; int Width; int Height; private float[] pixelVerts = new float[] { +.0f,+.0f,2, +.5f,+.5f,0, +.5f,-.5f,0, +.0f,+.0f,2, +.5f,-.5f,0, -.5f,-.5f,0, +.0f,+.0f,2, -.5f,-.5f,0, -.5f,+.5f,0, +.0f,+.0f,2, -.5f,+.5f,0, +.5f,+.5f,0, }; @Override public void run() { } private float[] arenaWalls = new float[] { 8.00f,2.00f,1f,2f,2f,1f,2.00f,8.00f,1f,8.00f,2.00f,1f,2.00f,8.00f,1f,8.00f,8.00f,1f, 2.00f,8.00f,1f,2f,2f,1f,0.00f,0.00f,0f,2.00f,8.00f,1f,0.00f,0.00f,0f,0.00f,10.00f,0f, 8.00f,8.00f,1f,2.00f,8.00f,1f,0.00f,10.00f,0f,8.00f,8.00f,1f,0.00f,10.00f,0f,10.00f,10.00f,0f, 2f,2f,1f,8.00f,2.00f,1f,10.00f,0.00f,0f,2f,2f,1f,10.00f,0.00f,0f,0.00f,0.00f,0f, 8.00f,2.00f,1f,8.00f,8.00f,1f,10.00f,10.00f,0f,8.00f,2.00f,1f,10.00f,10.00f,0f,10.00f,0.00f,0f, 10.00f,10.00f,0f,0.00f,10.00f,0f,0.00f,0.00f,0f,10.00f,10.00f,0f,0.00f,0.00f,0f,10.00f,0.00f,0f, 8.00f,6.00f,1f,8.00f,4.00f,1f,122f,4.00f,1f,8.00f,6.00f,1f,122f,4.00f,1f,122f,6.00f,1f, 8.00f,6.00f,1f,122f,6.00f,1f,120f,7.00f,0f,8.00f,6.00f,1f,120f,7.00f,0f,10.00f,7.00f,0f, 122f,4.00f,1f,8.00f,4.00f,1f,10.00f,3.00f,0f,122f,4.00f,1f,10.00f,3.00f,0f,120f,3.00f,0f, 480f,10.00f,0f,470f,10.00f,0f,470f,0.00f,0f,480f,10.00f,0f,470f,0.00f,0f,480f,0.00f,0f, 478f,2.00f,1f,478f,8.00f,1f,480f,10.00f,0f,478f,2.00f,1f,480f,10.00f,0f,480f,0.00f,0f, 472f,2f,1f,478f,2.00f,1f,480f,0.00f,0f,472f,2f,1f,480f,0.00f,0f,470f,0.00f,0f, 478f,8.00f,1f,472f,8.00f,1f,470f,10.00f,0f,478f,8.00f,1f,470f,10.00f,0f,480f,10.00f,0f, 472f,8.00f,1f,472f,2f,1f,470f,0.00f,0f,472f,8.00f,1f,470f,0.00f,0f,470f,10.00f,0f, 478f,2.00f,1f,472f,2f,1f,472f,8.00f,1f,478f,2.00f,1f,472f,8.00f,1f,478f,8.00f,1f, 478f,846f,1f,472f,846f,1f,472f,852f,1f,478f,846f,1f,472f,852f,1f,478f,852f,1f, 472f,852f,1f,472f,846f,1f,470f,844f,0f,472f,852f,1f,470f,844f,0f,470f,854f,0f, 478f,852f,1f,472f,852f,1f,470f,854f,0f,478f,852f,1f,470f,854f,0f,480f,854f,0f, 472f,846f,1f,478f,846f,1f,480f,844f,0f,472f,846f,1f,480f,844f,0f,470f,844f,0f, 478f,846f,1f,478f,852f,1f,480f,854f,0f,478f,846f,1f,480f,854f,0f,480f,844f,0f, 480f,854f,0f,470f,854f,0f,470f,844f,0f,480f,854f,0f,470f,844f,0f,480f,844f,0f, 10.00f,854f,0f,0.00f,854f,0f,0.00f,844f,0f,10.00f,854f,0f,0.00f,844f,0f,10.00f,844f,0f, 8.00f,846f,1f,8.00f,852f,1f,10.00f,854f,0f,8.00f,846f,1f,10.00f,854f,0f,10.00f,844f,0f, 2f,846f,1f,8.00f,846f,1f,10.00f,844f,0f,2f,846f,1f,10.00f,844f,0f,0.00f,844f,0f, 8.00f,852f,1f,2.00f,852f,1f,0.00f,854f,0f,8.00f,852f,1f,0.00f,854f,0f,10.00f,854f,0f, 2.00f,852f,1f,2f,846f,1f,0.00f,844f,0f,2.00f,852f,1f,0.00f,844f,0f,0.00f,854f,0f, 8.00f,846f,1f,2f,846f,1f,2.00f,852f,1f,8.00f,846f,1f,2.00f,852f,1f,8.00f,852f,1f, 6f,846f,1f,4f,846f,1f,4f,8f,1f,6f,846f,1f,4f,8f,1f,6f,8f,1f, 6f,846f,1f,6f,8f,1f,7f,10f,0f,6f,846f,1f,7f,10f,0f,7f,844f,0f, 4f,8f,1f,4f,846f,1f,3f,844f,0f,4f,8f,1f,3f,844f,0f,3f,10f,0f, 474f,8f,1f,474f,846f,1f,473f,844f,0f,474f,8f,1f,473f,844f,0f,473f,10f,0f, 476f,846f,1f,476f,8f,1f,477f,10f,0f,476f,846f,1f,477f,10f,0f,477f,844f,0f, 476f,846f,1f,474f,846f,1f,474f,8f,1f,476f,846f,1f,474f,8f,1f,476f,8f,1f, 130f,10.00f,0f,120f,10.00f,0f,120f,0.00f,0f,130f,10.00f,0f,120f,0.00f,0f,130f,0.00f,0f, 128f,2.00f,1f,128f,8.00f,1f,130f,10.00f,0f,128f,2.00f,1f,130f,10.00f,0f,130f,0.00f,0f, 122f,2f,1f,128f,2.00f,1f,130f,0.00f,0f,122f,2f,1f,130f,0.00f,0f,120f,0.00f,0f, 128f,8.00f,1f,122f,8.00f,1f,120f,10.00f,0f,128f,8.00f,1f,120f,10.00f,0f,130f,10.00f,0f, 122f,8.00f,1f,122f,2f,1f,120f,0.00f,0f,122f,8.00f,1f,120f,0.00f,0f,120f,10.00f,0f, 128f,2.00f,1f,122f,2f,1f,122f,8.00f,1f,128f,2.00f,1f,122f,8.00f,1f,128f,8.00f,1f, 352f,8.00f,1f,358f,8.00f,1f,358f,2.00f,1f,352f,8.00f,1f,358f,2.00f,1f,352f,2.00f,1f, 358f,2.00f,1f,358f,8.00f,1f,360f,10.00f,0f,358f,2.00f,1f,360f,10.00f,0f,360f,0.00f,0f, 352f,2.00f,1f,358f,2.00f,1f,360f,0.00f,0f,352f,2.00f,1f,360f,0.00f,0f,350f,0.00f,0f, 358f,8.00f,1f,352f,8.00f,1f,350f,10.00f,0f,358f,8.00f,1f,350f,10.00f,0f,360f,10.00f,0f, 352f,8.00f,1f,352f,2.00f,1f,350f,0.00f,0f,352f,8.00f,1f,350f,0.00f,0f,350f,10.00f,0f, 350f,0.00f,0f,360f,0.00f,0f,360f,10.00f,0f,350f,0.00f,0f,360f,10.00f,0f,350f,10.00f,0f, 358f,6.00f,1f,472f,6.00f,1f,470f,7.00f,0f,358f,6.00f,1f,470f,7.00f,0f,360f,7.00f,0f, 472f,4.00f,1f,358f,4.00f,1f,360f,3.00f,0f,472f,4.00f,1f,360f,3.00f,0f,470f,3.00f,0f, 472f,4.00f,1f,472f,6.00f,1f,358f,6.00f,1f,472f,4.00f,1f,358f,6.00f,1f,358f,4.00f,1f, 472f,848f,1f,472f,850f,1f,358f,850f,1f,472f,848f,1f,358f,850f,1f,358f,848f,1f, 472f,848f,1f,358f,848f,1f,360f,847f,0f,472f,848f,1f,360f,847f,0f,470f,847f,0f, 358f,850f,1f,472f,850f,1f,470f,851f,0f,358f,850f,1f,470f,851f,0f,360f,851f,0f, 350f,844f,0f,360f,844f,0f,360f,854f,0f,350f,844f,0f,360f,854f,0f,350f,854f,0f, 352f,852f,1f,352f,846f,1f,350f,844f,0f,352f,852f,1f,350f,844f,0f,350f,854f,0f, 358f,852f,1f,352f,852f,1f,350f,854f,0f,358f,852f,1f,350f,854f,0f,360f,854f,0f, 352f,846f,1f,358f,846f,1f,360f,844f,0f,352f,846f,1f,360f,844f,0f,350f,844f,0f, 358f,846f,1f,358f,852f,1f,360f,854f,0f,358f,846f,1f,360f,854f,0f,360f,844f,0f, 352f,852f,1f,358f,852f,1f,358f,846f,1f,352f,852f,1f,358f,846f,1f,352f,846f,1f, 128f,846f,1f,122f,846f,1f,122f,852f,1f,128f,846f,1f,122f,852f,1f,128f,852f,1f, 122f,852f,1f,122f,846f,1f,120f,844f,0f,122f,852f,1f,120f,844f,0f,120f,854f,0f, 128f,852f,1f,122f,852f,1f,120f,854f,0f,128f,852f,1f,120f,854f,0f,130f,854f,0f, 122f,846f,1f,128f,846f,1f,130f,844f,0f,122f,846f,1f,130f,844f,0f,120f,844f,0f, 128f,846f,1f,128f,852f,1f,130f,854f,0f,128f,846f,1f,130f,854f,0f,130f,844f,0f, 130f,854f,0f,120f,854f,0f,120f,844f,0f,130f,854f,0f,120f,844f,0f,130f,844f,0f, 122f,848f,1f,8f,848f,1f,10f,847f,0f,122f,848f,1f,10f,847f,0f,120f,847f,0f, 8f,850f,1f,122f,850f,1f,120f,851f,0f,8f,850f,1f,120f,851f,0f,10f,851f,0f, 8f,850f,1f,8f,848f,1f,122f,848f,1f,8f,850f,1f,122f,848f,1f,122f,850f,1f, 10f,847f,0f,120f,847f,0f,124.96f,829.63f,-0.50f,10f,847f,0f,124.96f,829.63f,-0.50f,19.51f,829.63f,-0.50f, 130f,844f,0f,130f,854f,0f,134.55f,836.34f,-0.50f,130f,844f,0f,134.55f,836.34f,-0.50f,134.55f,826.76f,-0.50f, 350f,844f,0f,350f,854f,0f,345.45f,836.34f,-0.50f,350f,844f,0f,345.45f,836.34f,-0.50f,345.45f,826.76f,-0.50f, 360f,847f,0f,470f,847f,0f,460.49f,829.63f,-0.50f,360f,847f,0f,460.49f,829.63f,-0.50f,355.04f,829.63f,-0.50f, 470f,7.00f,0f,360f,7.00f,0f,355.04f,24.37f,-0.50f,470f,7.00f,0f,355.04f,24.37f,-0.50f,460.49f,24.37f,-0.50f, 350f,10.00f,0f,350f,0.00f,0f,345.45f,17.66f,-0.50f,350f,10.00f,0f,345.45f,17.66f,-0.50f,345.45f,27.24f,-0.50f, 130f,10.00f,0f,130f,0.00f,0f,134.55f,17.66f,-0.50f,130f,10.00f,0f,134.55f,17.66f,-0.50f,134.55f,27.24f,-0.50f, 473f,844f,0f,473f,10f,0f,463.36f,27.24f,-0.50f,473f,844f,0f,463.36f,27.24f,-0.50f,463.36f,826.76f,-0.50f, 7f,10f,0f,7f,844f,0f,16.64f,826.76f,-0.50f,7f,10f,0f,16.64f,826.76f,-0.50f,16.64f,27.24f,-0.50f, 120f,7.00f,0f,10.00f,7.00f,0f,19.51f,24.37f,-0.50f,120f,7.00f,0f,19.51f,24.37f,-0.50f,124.96f,24.37f,-0.50f, 120f,7.00f,0f,130f,10.00f,0f,134.55f,27.24f,-0.50f,120f,7.00f,0f,134.55f,27.24f,-0.50f,124.96f,24.37f,-0.50f, 10.00f,7.00f,0f,7f,10f,0f,16.64f,27.24f,-0.50f,10.00f,7.00f,0f,16.64f,27.24f,-0.50f,19.51f,24.37f,-0.50f, 350f,10.00f,0f,360f,7.00f,0f,355.04f,24.37f,-0.50f,350f,10.00f,0f,355.04f,24.37f,-0.50f,345.45f,27.24f,-0.50f, 473f,10f,0f,470f,7.00f,0f,460.49f,24.37f,-0.50f,473f,10f,0f,460.49f,24.37f,-0.50f,463.36f,27.24f,-0.50f, 473f,844f,0f,470f,847f,0f,460.49f,829.63f,-0.50f,473f,844f,0f,460.49f,829.63f,-0.50f,463.36f,826.76f,-0.50f, 360f,847f,0f,350f,844f,0f,345.45f,826.76f,-0.50f,360f,847f,0f,345.45f,826.76f,-0.50f,355.04f,829.63f,-0.50f, 130f,844f,0f,120f,847f,0f,124.96f,829.63f,-0.50f,130f,844f,0f,124.96f,829.63f,-0.50f,134.55f,826.76f,-0.50f, 7f,844f,0f,10f,847f,0f,19.51f,829.63f,-0.50f,7f,844f,0f,19.51f,829.63f,-0.50f,16.64f,826.76f,-0.50f, 19.51f,829.63f,-0.50f,124.96f,829.63f,-0.50f,136.47f,789.37f,-2f,19.51f,829.63f,-0.50f,136.47f,789.37f,-2f,41.56f,789.37f,-2f, 134.55f,826.76f,-0.50f,134.55f,836.34f,-0.50f,145.09f,795.41f,-2f,134.55f,826.76f,-0.50f,145.09f,795.41f,-2f,145.09f,786.78f,-2f, 345.45f,826.76f,-0.50f,345.45f,836.34f,-0.50f,334.91f,795.41f,-2f,345.45f,826.76f,-0.50f,334.91f,795.41f,-2f,334.91f,786.78f,-2f, 355.04f,829.63f,-0.50f,460.49f,829.63f,-0.50f,438.44f,789.37f,-2f,355.04f,829.63f,-0.50f,438.44f,789.37f,-2f,343.53f,789.37f,-2f, 460.49f,24.37f,-0.50f,355.04f,24.37f,-0.50f,343.53f,64.63f,-2f,460.49f,24.37f,-0.50f,343.53f,64.63f,-2f,438.44f,64.63f,-2f, 345.45f,27.24f,-0.50f,345.45f,17.66f,-0.50f,334.91f,58.59f,-2f,345.45f,27.24f,-0.50f,334.91f,58.59f,-2f,334.91f,67.22f,-2f, 134.55f,27.24f,-0.50f,134.55f,17.66f,-0.50f,145.09f,58.59f,-2f,134.55f,27.24f,-0.50f,145.09f,58.59f,-2f,145.09f,67.22f,-2f, 463.36f,826.76f,-0.50f,463.36f,27.24f,-0.50f,441.03f,67.22f,-2f,463.36f,826.76f,-0.50f,441.03f,67.22f,-2f,441.03f,786.78f,-2f, 16.64f,27.24f,-0.50f,16.64f,826.76f,-0.50f,38.97f,786.78f,-2f,16.64f,27.24f,-0.50f,38.97f,786.78f,-2f,38.97f,67.22f,-2f, 124.96f,24.37f,-0.50f,19.51f,24.37f,-0.50f,41.56f,64.63f,-2f,124.96f,24.37f,-0.50f,41.56f,64.63f,-2f,136.47f,64.63f,-2f, 124.96f,24.37f,-0.50f,134.55f,27.24f,-0.50f,145.09f,67.22f,-2f,124.96f,24.37f,-0.50f,145.09f,67.22f,-2f,136.47f,64.63f,-2f, 19.51f,24.37f,-0.50f,16.64f,27.24f,-0.50f,38.97f,67.22f,-2f,19.51f,24.37f,-0.50f,38.97f,67.22f,-2f,41.56f,64.63f,-2f, 345.45f,27.24f,-0.50f,355.04f,24.37f,-0.50f,343.53f,64.63f,-2f,345.45f,27.24f,-0.50f,343.53f,64.63f,-2f,334.91f,67.22f,-2f, 463.36f,27.24f,-0.50f,460.49f,24.37f,-0.50f,438.44f,64.63f,-2f,463.36f,27.24f,-0.50f,438.44f,64.63f,-2f,441.03f,67.22f,-2f, 463.36f,826.76f,-0.50f,460.49f,829.63f,-0.50f,438.44f,789.37f,-2f,463.36f,826.76f,-0.50f,438.44f,789.37f,-2f,441.03f,786.78f,-2f, 355.04f,829.63f,-0.50f,345.45f,826.76f,-0.50f,334.91f,786.78f,-2f,355.04f,829.63f,-0.50f,334.91f,786.78f,-2f,343.53f,789.37f,-2f, 134.55f,826.76f,-0.50f,124.96f,829.63f,-0.50f,136.47f,789.37f,-2f,134.55f,826.76f,-0.50f,136.47f,789.37f,-2f,145.09f,786.78f,-2f, 16.64f,826.76f,-0.50f,19.51f,829.63f,-0.50f,41.56f,789.37f,-2f,16.64f,826.76f,-0.50f,41.56f,789.37f,-2f,38.97f,786.78f,-2f, }; private float[] backgroundData = new float[] { // # ,Scale, Speed, 300 , 1.05f, .001f, 150 , 1.07f, .002f, 075 , 1.10f, .003f, 040 , 1.12f, .006f, 20 , 1.15f, .012f, 10 , 1.25f, .025f, 05 , 1.50f, .050f, 3 , 2.00f, .100f, 2 , 3.00f, .200f, }; private float[] triangleCoords = new float[] { 0, -25, 0, -.75f, -1, 0, +.75f, -1, 0, 0, +2, 0, -.99f, -1, 0, .99f, -1, 0, }; private float[] triangleColors = new float[] { 1.0f, 1.0f, 1.0f, 0.05f, 1.0f, 1.0f, 1.0f, 0.5f, 1.0f, 1.0f, 1.0f, 0.5f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 0.5f, 1.0f, 1.0f, 1.0f, 0.5f, }; private float[] drawArray2; private FloatBuffer drawBuffer2; private float[] colorArray2; private static FloatBuffer colorBuffer; private static FloatBuffer triangleBuffer; private static FloatBuffer quadBuffer; private static FloatBuffer drawBuffer; private float[] backgroundVerts; private FloatBuffer backgroundVertsWrapped; private float[] backgroundColors; private Buffer backgroundColorsWraped; private FloatBuffer backgroundColorsWrapped; private FloatBuffer arenaWallsWrapped; private FloatBuffer arenaColorsWrapped; private FloatBuffer arena2VertsWrapped; private FloatBuffer arena2ColorsWrapped; private long wallHitStartTime; private int wallHitDrawTime; private FloatBuffer pixelVertsWrapped; private float[] wallHit; private FloatBuffer pixelColorsWrapped; //private float[] pitVerts; private Resources lResources; private FloatBuffer pitVertsWrapped; private FloatBuffer pitColorsWrapped; private boolean arena2; private long lastStartTime; private long startTime; private int state=1; private long introEndTime; protected long introTotalTime =8000; protected long introStartTime; private boolean initDone= false; private static int stateIntro = 0; private static int stateGame = 1; public GlRenderer(spacehockey nspacehockey) { lResources = nspacehockey.getResources(); nspacehockey.SetHandlerToGLRenderer(new Handler() { @Override public void handleMessage(Message m) { if (m.what ==0){ wallHit = m.getData().getFloatArray("wall hit"); wallHitStartTime =System.currentTimeMillis(); wallHitDrawTime = 1000; }else if (m.what ==1){ //state = stateIntro; introEndTime= System.currentTimeMillis()+introTotalTime ; introStartTime = System.currentTimeMillis(); } }}); } public void onSurfaceCreated(GL10 gl, EGLConfig config) { gl.glShadeModel(GL10.GL_SMOOTH); gl.glClearColor(.01f, .01f, .01f, .1f); gl.glClearDepthf(1.0f); gl.glEnable(GL10.GL_DEPTH_TEST); gl.glDepthFunc(GL10.GL_LEQUAL); gl.glHint(GL10.GL_PERSPECTIVE_CORRECTION_HINT, GL10.GL_NICEST); } private float SumOfStrideI(float[] data, int offset, int stride) { int sum= 0; for (int i=offset;i<data.length-1;i=i+stride){ sum = (int) (data[i]+sum); } return sum; } public void onDrawFrame(GL10 gl) { if (state== stateIntro){DrawIntro(gl);} if (state== stateGame){DrawGame(gl);} } private void DrawIntro(GL10 gl) { startTime = System.currentTimeMillis(); if (startTime< introEndTime){ float ptd = (float)(startTime- introStartTime)/(float)introTotalTime; float ptl = 1-ptd; gl.glClear(GL10.GL_COLOR_BUFFER_BIT);//dont move gl.glMatrixMode(GL10.GL_MODELVIEW); int setVertOff = 0; gl.glEnableClientState(GL10.GL_VERTEX_ARRAY); gl.glEnableClientState(GL10.GL_COLOR_ARRAY); gl.glColorPointer(4, GL10.GL_FLOAT, 0, backgroundColorsWrapped); for (int i = 0; i < backgroundData.length / 3; i = i + 1) { int setoff = i * 3; int setVertLen = (int) backgroundData[setoff]; yoffs[i] = (backgroundData[setoff + 2]*(90+(ptl*250))) + yoffs[i]; if (yoffs[i] > Height) {yoffs[i] = 0;} gl.glPushMatrix(); //gl.glTranslatef(0, -(Height/2), 0); //gl.glScalef(1f, 1f+(ptl*2), 1f); //gl.glTranslatef(0, +(Height/2), 0); gl.glTranslatef(0, yoffs[i], i+60); gl.glVertexPointer(3, GL10.GL_FLOAT, 0, backgroundVertsWrapped); gl.glDrawArrays(GL10.GL_TRIANGLES, (setVertOff * 2 * 3) - 0, (setVertLen * 2 * 3) - 1); gl.glTranslatef(0, -Height, 0); gl.glDrawArrays(GL10.GL_TRIANGLES, (setVertOff * 2 * 3) - 0, (setVertLen * 2 * 3) - 1); setVertOff = (int) (setVertOff + setVertLen); gl.glPopMatrix(); } gl.glDisableClientState(GL10.GL_VERTEX_ARRAY); gl.glDisableClientState(GL10.GL_COLOR_ARRAY); }else{state = stateGame;} } private void DrawGame(GL10 gl) { lastStartTime = startTime; startTime = System.currentTimeMillis(); long moveTime = startTime-lastStartTime; gl.glClear(GL10.GL_COLOR_BUFFER_BIT);//dont move gl.glMatrixMode(GL10.GL_MODELVIEW); int setVertOff = 0; gl.glEnableClientState(GL10.GL_VERTEX_ARRAY); gl.glEnableClientState(GL10.GL_COLOR_ARRAY); gl.glColorPointer(4, GL10.GL_FLOAT, 0, backgroundColorsWrapped); for (int i = 0; i < backgroundData.length / 3; i = i + 1) { int setoff = i * 3; int setVertLen = (int) backgroundData[setoff]; yoffs[i] = (backgroundData[setoff + 2]*moveTime) + yoffs[i]; if (yoffs[i] > Height) {yoffs[i] = 0;} gl.glPushMatrix(); gl.glTranslatef(0, yoffs[i], i+60); gl.glVertexPointer(3, GL10.GL_FLOAT, 0, backgroundVertsWrapped); gl.glDrawArrays(GL10.GL_TRIANGLES, (setVertOff * 6) - 0, (setVertLen *6) - 1); gl.glTranslatef(0, -Height, 0); gl.glDrawArrays(GL10.GL_TRIANGLES, (setVertOff * 6) - 0, (setVertLen *6) - 1); setVertOff = (int) (setVertOff + setVertLen); gl.glPopMatrix(); } //arena frame gl.glPushMatrix(); gl.glVertexPointer(3, GL10.GL_FLOAT, 0, arenaWallsWrapped); gl.glColorPointer(4, GL10.GL_FLOAT, 0, arenaColorsWrapped); gl.glColor4f(.1f, .5f, 1f, 1f); gl.glTranslatef(0, 0, 50); gl.glDrawArrays(GL10.GL_TRIANGLES, 0, (int)(arenaWalls.length / 3)); gl.glPopMatrix(); //arena2 frame if (arena2 == true){ gl.glLoadIdentity(); gl.glVertexPointer(3, GL10.GL_FLOAT, 0, pitVertsWrapped); gl.glColorPointer(4, GL10.GL_FLOAT, 0, pitColorsWrapped); gl.glTranslatef(0, -Height, 40); gl.glDrawArrays(GL10.GL_TRIANGLES, 0, (int)(pitVertsWrapped.capacity() / 3)); } if (wallHitStartTime != 0) { float timeRemaining = (wallHitStartTime + wallHitDrawTime)-System.currentTimeMillis(); if (timeRemaining>0) { gl.glPushMatrix(); float percentDone = 1-(timeRemaining/wallHitDrawTime); gl.glLoadIdentity(); gl.glVertexPointer(3, GL10.GL_FLOAT, 0, pixelVertsWrapped); gl.glColorPointer(4, GL10.GL_FLOAT, 0, pixelColorsWrapped); gl.glTranslatef(wallHit[0], wallHit[1], 0); gl.glScalef(8, Height*percentDone, 0); gl.glDrawArrays(GL10.GL_TRIANGLES, 0, 12); gl.glPopMatrix(); } else { wallHitStartTime = 0; } } gl.glDisableClientState(GL10.GL_VERTEX_ARRAY); gl.glDisableClientState(GL10.GL_COLOR_ARRAY); } public void init(GL10 gl) { if (arena2 == true) { AssetManager assetManager = lResources.getAssets(); try { // byte[] ba = {111,111}; DataInputStream Dis = new DataInputStream(assetManager .open("arena2.ogl")); pitVertsWrapped = LoadFloatArray.FromDataInputStream(Dis); pitColorsWrapped = MakeFakeLighting(pitVertsWrapped.array(), .25f, .50f, 1f, 200, .5f); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } } if ((Height != 854) || (Width != 480)) { arenaWalls = ScaleFloats(arenaWalls, Width / 480f, Height / 854f); } arenaWallsWrapped = FloatBuffer.wrap(arenaWalls); arenaColorsWrapped = MakeFakeLighting(arenaWalls, .03f, .16f, .33f, .33f, 3); pixelVertsWrapped = FloatBuffer.wrap(pixelVerts); pixelColorsWrapped = MakeFakeLighting(pixelVerts, .03f, .16f, .33f, .10f, 20); initDone=true; } public void onSurfaceChanged(GL10 gl, int nwidth, int nheight) { Width= nwidth; Height = nheight; // avoid division by zero if (Height == 0) Height = 1; // draw on the entire screen gl.glViewport(0, 0, Width, Height); // setup projection matrix gl.glMatrixMode(GL10.GL_PROJECTION); gl.glLoadIdentity(); gl.glOrthof(0, Width, Height, 0, 100, -100); // gl.glOrthof(-nwidth*2, nwidth*2, nheight*2,-nheight*2, 100, -100); // GLU.gluPerspective(gl, 180.0f, (float)nwidth / (float)nheight, // 1000.0f, -1000.0f); gl.glEnable(GL10.GL_BLEND); gl.glBlendFunc(GL10.GL_SRC_ALPHA, GL10.GL_ONE_MINUS_SRC_ALPHA); System.gc(); if (initDone == false){ SetupStars(); init(gl); } } public void SetupStars(){ backgroundVerts = new float[(int) SumOfStrideI(backgroundData,0,3)*triangleCoords.length]; backgroundColors = new float[(int) SumOfStrideI(backgroundData,0,3)*triangleColors.length]; int iii=0; int vc=0; float ascale=1; for (int i=0;i<backgroundColors.length-1;i=i+1){ if (iii==0){ascale = (float) Math.random();} if (vc==3){ backgroundColors[i]= (float) (triangleColors[iii]*(ascale)); }else if(vc==2){ backgroundColors[i]= (float) (triangleColors[iii]-(Math.random()*.2)); }else{ backgroundColors[i]= (float) (triangleColors[iii]-(Math.random()*.3)); } iii=iii+1;if (iii> triangleColors.length-1){iii=0;} vc=vc+1; if (vc>3){vc=0;} } int ii=0; int i =0; int set =0; while(ii<backgroundVerts.length-1){ float scale = (float) backgroundData[(set*3)+1]; int length= (int) backgroundData[(set*3)]; for (i=0;i<length;i=i+1){ if (set ==0){ AddVertsToArray(ScaleFloats(triangleCoords, scale,scale*.25f), backgroundVerts, (float)(Math.random()*Width),(float) (Math.random()*Height), ii); }else{ AddVertsToArray(ScaleFloats(triangleCoords, scale), backgroundVerts, (float)(Math.random()*Width),(float) (Math.random()*Height), ii);} ii=ii+triangleCoords.length; } set=set+1; } backgroundVertsWrapped = FloatBuffer.wrap(backgroundVerts); backgroundColorsWrapped = FloatBuffer.wrap(backgroundColors); } public void AddVertsToArray(float[] sva,float[]dva,float ox,float oy,int start){ //x for (int i=0;i<sva.length;i=i+3){ if((start+i)<dva.length){dva[start+i]= sva[i]+ox;} } //y for (int i=1;i<sva.length;i=i+3){ if((start+i)<dva.length){dva[start+i]= sva[i]+oy;} } //z for (int i=2;i<sva.length;i=i+3){ if((start+i)<dva.length){dva[start+i]= sva[i];} } } public FloatBuffer MakeFakeLighting(float[] sa,float r, float g,float b,float a,float multby){ float[] da = new float[((sa.length/3)*4)]; int vertex=0; for (int i=0;i<sa.length;i=i+3){ if (sa[i+2]>=1){ da[(vertex*4)+0]= r*multby*sa[i+2]; da[(vertex*4)+1]= g*multby*sa[i+2]; da[(vertex*4)+2]= b*multby*sa[i+2]; da[(vertex*4)+3]= a*multby*sa[i+2]; }else if (sa[i+2]<=-1){ float divisor = (multby*(-sa[i+2])); da[(vertex*4)+0]= r / divisor; da[(vertex*4)+1]= g / divisor; da[(vertex*4)+2]= b / divisor; da[(vertex*4)+3]= a / divisor; }else{ da[(vertex*4)+0]= r; da[(vertex*4)+1]= g; da[(vertex*4)+2]= b; da[(vertex*4)+3]= a; } vertex = vertex+1; } return FloatBuffer.wrap(da); } public float[] ScaleFloats(float[] va,float s){ float[] reta= new float[va.length]; for (int i=0;i<va.length;i=i+1){ reta[i]=va[i]*s; } return reta; } public float[] ScaleFloats(float[] va,float sx,float sy){ float[] reta= new float[va.length]; int cnt = 0; for (int i=0;i<va.length;i=i+1){ if (cnt==0){reta[i]=va[i]*sx;} else if (cnt==1){reta[i]=va[i]*sy;} else if (cnt==2){reta[i]=va[i];} cnt = cnt +1;if (cnt>2){cnt=0;} } return reta; } }

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• How do I make UITableViewCell's ImageView a fixed size even when the image is smaller.

  - by Robert

  I have a bunch of images I am using for cell's image views, they are all no bigger than 50x50. e.g. 40x50, 50x32, 20x37 ..... When I load the table view, the text doesn't line up because the width of the images varies. Also I would like small images to appear in the centre as opposed to on the left. Here is the code I am trying inside my 'cellForRowAtIndexPath' method cell.imageView.autoresizingMask = ( UIViewAutoresizingNone ); cell.imageView.autoresizesSubviews = NO; cell.imageView.contentMode = UIViewContentModeCenter; cell.imageView.bounds = CGRectMake(0, 0, 50, 50); cell.imageView.frame = CGRectMake(0, 0, 50, 50); cell.imageView.image = [UIImage imageWithData: imageData]; As you can see I have tried a few things, but none of them work.

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• Need to execute an ajax call incrementally after fixed time periods in javascript?

  - by Ali

  HI guys, I need to be able to make an ajax call to be made after every few minutes. Basically the ajax call would be to check on new emails in an inbox. If there are new emails it would download the emails to a database. I got all the server side code set up fine. I just need to know how do I set up on the front end the part where the ajax call is made after every few minutes plus it should be set up such that we don't end up with parallel ajax calls being made i.e if the ajax call hasn't returned a response it shouldn't start a new ajax request.

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• Table header to stay fixed at the top when user scrolls it out of view with jQuery

  - by PeterBZ

  I am trying to design an HTML table where the header will stay at the top of the page when AND ONLY when the user scrolls it out of view. For example, the table may be 500 pixels down from the page, how do I make it so that if the user scrolls the header out of view (browser detects its no longer in the windows view somehow), it will stay put at the top? Anyone can give me a Javascript solution to this? <table> <thead> <tr> <th>Col1</th> <th>Col2</th> <th>Col3</th> </tr> </thead> <tbody> <tr> <td>info</td> <td>info</td> <td>info</td> </tr> <tr> <td>info</td> <td>info</td> <td>info</td> </tr> <tr> <td>info</td> <td>info</td> <td>info</td> </tr> </tbody> </table> So in the above example, I want the <thead> to scroll with the page if it goes out of view. IMPORTANT: I am NOT looking for a solution where the <tbody> will have a scrollbar (overflow:auto).

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• Why do Asp.net timers/updatepanels leak memory and can it be fixed/worked around?

  - by KallDrexx

  I have built a suite of internal websites for our company to manage some of our processes. I have been noticing that these pages have massive memory leaks that cause the pages to be using well over 150mb of memory, which is ridiculous for a webpage that consists of a single form and a GridView that is displaying 7-10 rows of data at a time, sometimes with the data not changing for a whole day. This data does need to be refreshed on a semi-regular basis so that we always see the latest results and can act on them. After some testing it appears that the memory leak is extremely easy to reproduce, and very noticeable. I created a page with the following asp.net markup: <body> <form id="form1" runat="server"> <div> <asp:scriptmanager ID="Scriptmanager1" runat="server"></asp:scriptmanager> <asp:Timer ID="timer1" runat="server" Interval="1000" /> <asp:UpdatePanel ID="UpdatePanel1" runat="server"> <ContentTemplate> </ContentTemplate> </asp:UpdatePanel> </div> </form> </body> There is absolutely no code behind for this. This is the entirety of the page. Running this site in Chrome shows the memory usage shoot up to 25 megs in the span of 20-30 seconds. Leaving it running for a few minutes makes the memory go up to the 70 megs and such. Am I using timers and update panels wrong, or is this a pure Asp.net issue with no work around?

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• How to replace the characters in fixed positions in PHP?

  - by user198729

  I want to replace with the 4~8 characters of a string with *,how to do it? HelloWorld => Hell****ld

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• How to scroll LI items in a fixed height UL?

  - by Tahir Akram

  Here is my example HTML. And I want to have scroll for my LI items. Which are of 2 levels. Means, I want to apply class on every UL. So how can I do that. By using JQuery or CSS tweaking. PS: I am using this example. <ul id="nav" class="dropdown"> <li class="dir"> Item_Root <ul> <li class="dir"> Item_1_Level <ul> <li>Item_Level_2</li> <li>Item_Level_2</li> <li>Item_Level_2</li> <li>.... up to N items</li> </ul> </li> <li>Item_Level_1</li> <li>Item_Level_1</li> <li>Item_Level_1</li> <li>Item_Level_1</li> <li>.... up to N items</li> </ul> </li> </ul>

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