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• Saving in mongoDb with Mongoose, unexpected elements saved

  - by guiomie

  When I write in my mongoDB with mongoose the operation is treated with success, my document is saved, but there is also all kind of weird other sutff written down. It seems to be mongoose code. What could cause this? I add stuff in a specific array with: resultReference.ref[arrayLocation].allEvents.push(theEvent); {id: 11, allEvents: [] } is the structure of a ref element, and I push theEvent in the allEvents array. I then resultReference.save() I use express, mongoose and mongoHQ for database. I tried on a local mongo server, and this annoyance is still there. I've print in my console the document to write before save() and non of this weird code is there. { id 11 allEvents [ 0 { _events { maxListeners 0 } _doc { _id {"$oid": "4eb87834f54944e263000003"} title "Test" allDay false start 2011-11-10 13:00:00 UTC end 2011-11-10 15:00:00 UTC url "/test/4eb87834f54944e263000002" color "#99CCFF" ref "4eb87834f54944e263000002" } _activePaths { paths { title "modify" allDay "modify" start "modify" end "modify" url "modify" color "modify" ref "modify" } states { init { } modify { title true allDay true start true end true url true color true ref true } require { } } stateNames [ 0 "require" 1 "modify" 2 "init" ] } _saveError null _validationError null isNew true _pres { save [ 0 function (next) { // we keep the error semaphore to make sure we don't // call `save` unnecessarily (we only need 1 error) var subdocs = 0 , error = false , self = this; var arrays = this._activePaths .map('init', 'modify', function (i) { return self.getValue(i); }) .filter(function (val) { return (val && val instanceof DocumentArray && val.length); }); if (!arrays.length) return next(); arrays.forEach(function (array) { subdocs += array.length; array.forEach(function (value) { if (!error) value.save(function (err) { if (!error) { if (err) { error = true; next(err); } else --subdocs || next(); } }); }); }); } 1 "function checkForExistingErrors(next) { if (self._saveError){ next(self._saveError); self._saveError = null; } else { next(); } }" 2 "function validation(next) { return self.validate.call(self, next); }" ] } _posts { save [ ] } save function () { var self = this , hookArgs // arguments eventually passed to the hook - are mutable , lastArg = arguments[arguments.length-1] , pres = this._pres[name] , posts = this._posts[name] , _total = pres.length , _current = -1 , _asyncsLeft = proto[name].numAsyncPres , _next = function () { if (arguments[0] instanceof Error) { return handleError(arguments[0]); } var _args = Array.prototype.slice.call(arguments) , currPre , preArgs; if (_args.length && !(arguments[0] === null && typeof lastArg === 'function')) hookArgs = _args; if (++_current < _total) { currPre = pres[_current] if (currPre.isAsync && currPre.length < 2) throw new Error("Your pre must have next and done arguments -- e.g., function (next, done, ...)"); if (currPre.length < 1) throw new Error("Your pre must have a next argument -- e.g., function (next, ...)"); preArgs = (currPre.isAsync ? [once(_next), once(_asyncsDone)] : [once(_next)]).concat(hookArgs); return currPre.apply(self, preArgs); } else if (!proto[name].numAsyncPres) { return _done.apply(self, hookArgs); } } , _done = function () { var args_ = Array.prototype.slice.call(arguments) , ret, total_, current_, next_, done_, postArgs; if (_current === _total) { ret = fn.apply(self, args_); total_ = posts.length; current_ = -1; next_ = function () { if (arguments[0] instanceof Error) { return handleError(arguments[0]); } var args_ = Array.prototype.slice.call(arguments, 1) , currPost , postArgs; if (args_.length) hookArgs = args_; if (++current_ < total_) { currPost = posts[current_] if (currPost.length < 1) throw new Error("Your post must have a next argument -- e.g., function (next, ...)"); postArgs = [once(next_)].concat(hookArgs); return currPost.apply(self, postArgs); } }; if (total_) return next_(); return ret; } }; if (_asyncsLeft) { function _asyncsDone (err) { if (err && err instanceof Error) { return handleError(err); } --_asyncsLeft || _done.apply(self, hookArgs); } } function handleError (err) { if ('function' == typeof lastArg) return lastArg(err); if (errorCb) return errorCb.call(self, err); throw err; } return _next.apply(this, arguments); } errors null } ] } ]

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• Is multithreading the right way to go for my case?

  - by Julien Lebosquain

  Hello, I'm currently designing a multi-client / server application. I'm using plain good old sockets because WCF or similar technology is not what I need. Let me explain: it isn't the classical case of a client simply calling a service; all clients can 'interact' with each other by sending a packet to the server, which will then do some action, and possible re-dispatch an answer message to one or more clients. Although doable with WCF, the application will get pretty complex with hundreds of different messages. For each connected client, I'm of course using asynchronous methods to send and receive bytes. I've got the messages fully working, everything's fine. Except that for each line of code I'm writing, my head just burns because of multithreading issues. Since there could be around 200 clients connected at the same time, I chose to go the fully multithreaded way: each received message on a socket is immediately processed on the thread pool thread it was received, not on a single consumer thread. Since each client can interact with other clients, and indirectly with shared objects on the server, I must protect almost every object that is mutable. I first went with a ReaderWriterLockSlim for each resource that must be protected, but quickly noticed that there are more writes overall than reads in the server application, and switched to the well-known Monitor to simplify the code. So far, so good. Each resource is protected, I have helper classes that I must use to get a lock and its protected resource, so I can't use an object without getting a lock. Moreover, each client has its own lock that is entered as soon as a packet is received from its socket. It's done to prevent other clients from making changes to the state of this client while it has some messages being processed, which is something that will happen frequently. Now, I don't just need to protect resources from concurrent accesses. I must keep every client in sync with the server for some collections I have. One tricky part that I'm currently struggling with is the following: I have a collection of clients. Each client has its own unique ID. When a client connects, it must receive the IDs of every connected client, and each one of them must be notified of the newcomer's ID. When a client disconnects, every other client must know it so that its ID is no longer valid for them. Every client must always have, at a given time, the same clients collection as the server so that I can assume that everybody knows everybody. This way if I'm sending a message to client #1 telling "Client #2 has done something", I know that it will always be correctly interpreted: Client 1 will never wonder "but who is Client 2 anyway?". My first attempt for handling the connection of a new client (let's call it X) was this pseudo-code (remember that newClient is already locked here): lock (clients) { foreach (var client in clients) { lock (client) { client.Send("newClient with id X has connected"); } } clients.Add(newClient); newClient.Send("the list of other clients"); } Now imagine that in the same time, another client has sent a packet that translates into a message that must be broadcasted to every connected client, the pseudo-code will be something like this (remember that the current client - let's call it Y - is already locked here): lock (clients) { foreach (var client in clients) { lock (client) { client.Send("something"); } } } An obvious deadlock occurs here: on one thread X is locked, the clients lock has been entered, started looping through the clients, and at one moment must get Y's lock... which is already acquired on the second thread, itself waiting for the clients collection lock to be released! This is not the only case like this in the server application. There are other collections which must be kept in sync with the clients, some properties on a client can be changed by another one, etc. I tried other types of locks, lock-free mechanisms and a bunch of other things. Either there were obvious deadlocks when I'm using too much locks for safety, or obvious race conditions otherwise. When I finally find a good middle point between the two, it usually comes with very subtle race conditions / dead locks and other multi-threading issues... my head hurts very quickly since for any single line of code I'm writing I have to review almost the whole application to ensure everything will behave correctly with any number of threads. So here's my final question: how would you resolve this specific case, the general case, and more importantly: aren't I going the wrong way here? I have little problems with the .NET framework, C#, simple concurrency or algorithms in general. Still, I'm lost here. I know I could use only one thread processing the incoming requests and everything will be fine. However, that won't scale well at all with more clients... But I'm thinking more and more to go this simple way. What do you think? Thanks in advance to you, StackOverflow people which have taken the time to read this huge question. I really had to explain the whole context if I want to get some help.

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• how do you make a "concurrent queue safe" lazy loader (singleton manager) in objective-c

  - by Rich

  Hi, I made this class that turns any object into a singleton, but I know that it's not "concurrent queue safe." Could someone please explain to me how to do this, or better yet, show me the code. To be clear I want to know how to use this with operation queues and dispatch queues (NSOperationQueue and Grand Central Dispatch) on iOS. Thanks in advance, Rich EDIT: I had an idea for how to do it. If someone could confirm it for me I'll do it and post the code. The idea is that proxies make queues all on their own. So if I make a mutable proxy (like Apple does in key-value coding/observing) for any object that it's supposed to return, and always return the same proxy for the same object/identifier pair (using the same kind of lazy loading technique as I used to create the singletons), the proxies would automatically queue up the any messages to the singletons, and make it totally thread safe. IMHO this seems like a lot of work to do, so I don't want to do it if it's not gonna work, or if it's gonna slow my apps down to a crawl. Here's my non-thread safe code: RMSingletonCollector.h // // RMSingletonCollector.h // RMSingletonCollector // // Created by Rich Meade-Miller on 2/11/11. // Copyright 2011 Rich Meade-Miller. All rights reserved. // #import <Foundation/Foundation.h> #import "RMWeakObjectRef.h" struct RMInitializerData { // The method may take one argument. // required SEL designatedInitializer; // data to pass to the initializer or nil. id data; }; typedef struct RMInitializerData RMInitializerData; RMInitializerData RMInitializerDataMake(SEL initializer, id data); @interface NSObject (SingletonCollector) // Returns the selector and data to pass to it (if the selector takes an argument) for use when initializing the singleton. // If you override this DO NOT call super. + (RMInitializerData)designatedInitializerForIdentifier:(NSString *)identifier; @end @interface RMSingletonCollector : NSObject { } + (id)collectionObjectForType:(NSString *)className identifier:(NSString *)identifier; + (id<RMWeakObjectReference>)referenceForObjectOfType:(NSString *)className identifier:(NSString *)identifier; + (void)destroyCollection; + (void)destroyCollectionObjectForType:(NSString *)className identifier:(NSString *)identifier; @end // ==--==--==--==--==Notifications==--==--==--==--== extern NSString *const willDestroySingletonCollection; extern NSString *const willDestroySingletonCollectionObject; RMSingletonCollector.m // // RMSingletonCollector.m // RMSingletonCollector // // Created by Rich Meade-Miller on 2/11/11. // Copyright 2011 Rich Meade-Miller. All rights reserved. // #import "RMSingletonCollector.h" #import <objc/objc-runtime.h> NSString *const willDestroySingletonCollection = @"willDestroySingletonCollection"; NSString *const willDestroySingletonCollectionObject = @"willDestroySingletonCollectionObject"; RMInitializerData RMInitializerDataMake(SEL initializer, id data) { RMInitializerData newData; newData.designatedInitializer = initializer; newData.data = data; return newData; } @implementation NSObject (SingletonCollector) + (RMInitializerData)designatedInitializerForIdentifier:(NSString *)identifier { return RMInitializerDataMake(@selector(init), nil); } @end @interface RMSingletonCollector () + (NSMutableDictionary *)singletonCollection; + (void)setSingletonCollection:(NSMutableDictionary *)newSingletonCollection; @end @implementation RMSingletonCollector static NSMutableDictionary *singletonCollection = nil; + (NSMutableDictionary *)singletonCollection { if (singletonCollection != nil) { return singletonCollection; } NSMutableDictionary *collection = [[NSMutableDictionary alloc] initWithCapacity:1]; [self setSingletonCollection:collection]; [collection release]; return singletonCollection; } + (void)setSingletonCollection:(NSMutableDictionary *)newSingletonCollection { if (newSingletonCollection != singletonCollection) { [singletonCollection release]; singletonCollection = [newSingletonCollection retain]; } } + (id)collectionObjectForType:(NSString *)className identifier:(NSString *)identifier { id obj; NSString *key; if (identifier) { key = [className stringByAppendingFormat:@".%@", identifier]; } else { key = className; } if (obj = [[self singletonCollection] objectForKey:key]) { return obj; } // dynamic creation. // get a class for Class classForName = NSClassFromString(className); if (classForName) { obj = objc_msgSend(classForName, @selector(alloc)); // if the initializer takes an argument... RMInitializerData initializerData = [classForName designatedInitializerForIdentifier:identifier]; if (initializerData.data) { // pass it. obj = objc_msgSend(obj, initializerData.designatedInitializer, initializerData.data); } else { obj = objc_msgSend(obj, initializerData.designatedInitializer); } [singletonCollection setObject:obj forKey:key]; [obj release]; } else { // raise an exception if there is no class for the specified name. NSException *exception = [NSException exceptionWithName:@"com.RMDev.RMSingletonCollector.failed_to_find_class" reason:[NSString stringWithFormat:@"SingletonCollector couldn't find class for name: %@", [className description]] userInfo:nil]; [exception raise]; [exception release]; } return obj; } + (id<RMWeakObjectReference>)referenceForObjectOfType:(NSString *)className identifier:(NSString *)identifier { id obj = [self collectionObjectForType:className identifier:identifier]; RMWeakObjectRef *objectRef = [[RMWeakObjectRef alloc] initWithObject:obj identifier:identifier]; return [objectRef autorelease]; } + (void)destroyCollection { NSDictionary *userInfo = [singletonCollection copy]; [[NSNotificationCenter defaultCenter] postNotificationName:willDestroySingletonCollection object:self userInfo:userInfo]; [userInfo release]; // release the collection and set it to nil. [self setSingletonCollection:nil]; } + (void)destroyCollectionObjectForType:(NSString *)className identifier:(NSString *)identifier { NSString *key; if (identifier) { key = [className stringByAppendingFormat:@".%@", identifier]; } else { key = className; } [[NSNotificationCenter defaultCenter] postNotificationName:willDestroySingletonCollectionObject object:[singletonCollection objectForKey:key] userInfo:nil]; [singletonCollection removeObjectForKey:key]; } @end RMWeakObjectRef.h // // RMWeakObjectRef.h // RMSingletonCollector // // Created by Rich Meade-Miller on 2/12/11. // Copyright 2011 Rich Meade-Miller. All rights reserved. // // In order to offset the performance loss from always having to search the dictionary, I made a retainable, weak object reference class. #import <Foundation/Foundation.h> @protocol RMWeakObjectReference <NSObject> @property (nonatomic, assign, readonly) id objectRef; @property (nonatomic, retain, readonly) NSString *className; @property (nonatomic, retain, readonly) NSString *objectIdentifier; @end @interface RMWeakObjectRef : NSObject <RMWeakObjectReference> { id objectRef; NSString *className; NSString *objectIdentifier; } - (RMWeakObjectRef *)initWithObject:(id)object identifier:(NSString *)identifier; - (void)objectWillBeDestroyed:(NSNotification *)notification; @end RMWeakObjectRef.m // // RMWeakObjectRef.m // RMSingletonCollector // // Created by Rich Meade-Miller on 2/12/11. // Copyright 2011 Rich Meade-Miller. All rights reserved. // #import "RMWeakObjectRef.h" #import "RMSingletonCollector.h" @implementation RMWeakObjectRef @dynamic objectRef; @synthesize className, objectIdentifier; - (RMWeakObjectRef *)initWithObject:(id)object identifier:(NSString *)identifier { if (self = [super init]) { NSString *classNameForObject = NSStringFromClass([object class]); className = classNameForObject; objectIdentifier = identifier; objectRef = object; [[NSNotificationCenter defaultCenter] addObserver:self selector:@selector(objectWillBeDestroyed:) name:willDestroySingletonCollectionObject object:object]; [[NSNotificationCenter defaultCenter] addObserver:self selector:@selector(objectWillBeDestroyed:) name:willDestroySingletonCollection object:[RMSingletonCollector class]]; } return self; } - (id)objectRef { if (objectRef) { return objectRef; } objectRef = [RMSingletonCollector collectionObjectForType:className identifier:objectIdentifier]; return objectRef; } - (void)objectWillBeDestroyed:(NSNotification *)notification { objectRef = nil; } - (void)dealloc { [[NSNotificationCenter defaultCenter] removeObserver:self]; [className release]; [super dealloc]; } @end

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• Can't figure out where race condition is occuring

  - by Nik

  I'm using Valgrind --tool=drd to check my application that uses Boost::thread. Basically, the application populates a set of "Book" values with "Kehai" values based on inputs through a socket connection. On a seperate thread, a user can connect and get the books send to them. Its fairly simple, so i figured using a boost::mutex::scoped_lock on the location that serializes the book and the location that clears out the book data should be suffice to prevent any race conditions. Here is the code: void Book::clear() { boost::mutex::scoped_lock lock(dataMutex); for(int i =NUM_KEHAI-1; i >= 0; --i) { bid[i].clear(); ask[i].clear(); } } int Book::copyChangedKehaiToString(char* dst) const { boost::mutex::scoped_lock lock(dataMutex); sprintf(dst, "%-4s%-13s",market.c_str(),meigara.c_str()); int loc = 17; for(int i = 0; i < Book::NUM_KEHAI; ++i) { if(ask[i].changed > 0) { sprintf(dst+loc,"A%i%-21s%-21s%-21s%-8s%-4s",i,ask[i].price.c_str(),ask[i].volume.c_str(),ask[i].number.c_str(),ask[i].postTime.c_str(),ask[i].status.c_str()); loc += 77; } } for(int i = 0; i < Book::NUM_KEHAI; ++i) { if(bid[i].changed > 0) { sprintf(dst+loc,"B%i%-21s%-21s%-21s%-8s%-4s",i,bid[i].price.c_str(),bid[i].volume.c_str(),bid[i].number.c_str(),bid[i].postTime.c_str(),bid[i].status.c_str()); loc += 77; } } return loc; } The clear() function and the copyChangedKehaiToString() function are called in the datagetting thread and data sending thread,respectively. Also, as a note, the class Book: struct Book { private: Book(const Book&); Book& operator=(const Book&); public: static const int NUM_KEHAI=10; struct Kehai; friend struct Book::Kehai; struct Kehai { private: Kehai& operator=(const Kehai&); public: std::string price; std::string volume; std::string number; std::string postTime; std::string status; int changed; Kehai(); void copyFrom(const Kehai& other); Kehai(const Kehai& other); inline void clear() { price.assign(""); volume.assign(""); number.assign(""); postTime.assign(""); status.assign(""); changed = -1; } }; std::vector<Kehai> bid; std::vector<Kehai> ask; tm recTime; mutable boost::mutex dataMutex; Book(); void clear(); int copyChangedKehaiToString(char * dst) const; }; When using valgrind --tool=drd, i get race condition errors such as the one below: ==26330== Conflicting store by thread 1 at 0x0658fbb0 size 4 ==26330== at 0x653AE68: std::string::_M_mutate(unsigned int, unsigned int, unsigned int) (in /usr/lib/libstdc++.so.6.0.8) ==26330== by 0x653AFC9: std::string::_M_replace_safe(unsigned int, unsigned int, char const*, unsigned int) (in /usr/lib/libstdc++.so.6.0.8) ==26330== by 0x653B064: std::string::assign(char const*, unsigned int) (in /usr/lib/libstdc++.so.6.0.8) ==26330== by 0x653B134: std::string::assign(char const*) (in /usr/lib/libstdc++.so.6.0.8) ==26330== by 0x8055D64: Book::Kehai::clear() (Book.h:50) ==26330== by 0x8094A29: Book::clear() (Book.cpp:78) ==26330== by 0x808537E: RealKernel::start() (RealKernel.cpp:86) ==26330== by 0x804D15A: main (main.cpp:164) ==26330== Allocation context: BSS section of /usr/lib/libstdc++.so.6.0.8 ==26330== Other segment start (thread 2) ==26330== at 0x400BB59: pthread_mutex_unlock (drd_pthread_intercepts.c:633) ==26330== by 0xC59565: pthread_mutex_unlock (in /lib/libc-2.5.so) ==26330== by 0x805477C: boost::mutex::unlock() (mutex.hpp:56) ==26330== by 0x80547C9: boost::unique_lock<boost::mutex>::~unique_lock() (locks.hpp:340) ==26330== by 0x80949BA: Book::copyChangedKehaiToString(char*) const (Book.cpp:134) ==26330== by 0x80937EE: BookSerializer::serializeBook(Book const&, std::string const&) (BookSerializer.cpp:41) ==26330== by 0x8092D05: BookSnapshotManager::getSnaphotDataList() (BookSnapshotManager.cpp:72) ==26330== by 0x8088179: SnapshotServer::getDataList() (SnapshotServer.cpp:246) ==26330== by 0x808870F: SnapshotServer::run() (SnapshotServer.cpp:183) ==26330== by 0x808BAF5: boost::_mfi::mf0<void, RealThread>::operator()(RealThread*) const (mem_fn_template.hpp:49) ==26330== by 0x808BB4D: void boost::_bi::list1<boost::_bi::value<RealThread*> >::operator()<boost::_mfi::mf0<void, RealThread>, boost::_bi::list0>(boost::_bi::type<void>, boost::_mfi::mf0<void, RealThread>&, boost::_bi::list0&, int) (bind.hpp:253) ==26330== by 0x808BB90: boost::_bi::bind_t<void, boost::_mfi::mf0<void, RealThread>, boost::_bi::list1<boost::_bi::value<RealThread*> > >::operator()() (bind_template.hpp:20) ==26330== Other segment end (thread 2) ==26330== at 0x400B62A: pthread_mutex_lock (drd_pthread_intercepts.c:580) ==26330== by 0xC59535: pthread_mutex_lock (in /lib/libc-2.5.so) ==26330== by 0x80546B8: boost::mutex::lock() (mutex.hpp:51) ==26330== by 0x805473B: boost::unique_lock<boost::mutex>::lock() (locks.hpp:349) ==26330== by 0x8054769: boost::unique_lock<boost::mutex>::unique_lock(boost::mutex&) (locks.hpp:227) ==26330== by 0x8094711: Book::copyChangedKehaiToString(char*) const (Book.cpp:113) ==26330== by 0x80937EE: BookSerializer::serializeBook(Book const&, std::string const&) (BookSerializer.cpp:41) ==26330== by 0x808870F: SnapshotServer::run() (SnapshotServer.cpp:183) ==26330== by 0x808BAF5: boost::_mfi::mf0<void, RealThread>::operator()(RealThread*) const (mem_fn_template.hpp:49) ==26330== by 0x808BB4D: void boost::_bi::list1<boost::_bi::value<RealThread*> >::operator()<boost::_mfi::mf0<void, RealThread>, boost::_bi::list0>(boost::_bi::type<void>, boost::_mfi::mf0<void, RealThread>&, boost::_bi::list0&, int) (bind.hpp:253) For the life of me, i can't figure out where the race condition is. As far as I can tell, clearing the kehai is done only after having taken the mutex, and the same holds true with copying it to a string. Does anyone have any ideas what could be causing this, or where I should look? Thank you kindly.

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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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• Adding Custom Object to NSMutableArray

  - by Fozz

  Developing ios app. I have an object class Product.h and .m respectively along with my picker class which implements my vehicle selection to match products to vehicle. The files product.h #import <Foundation/Foundation.h> @interface Product : NSObject { } @property (nonatomic, retain) NSString *iProductID; @property (nonatomic, retain) NSString *vchProductCode; @property (nonatomic, retain) NSString *vchPriceCode; @property (nonatomic, retain) NSString *vchHitchUPC; @property (nonatomic, retain) NSString *mHitchList; @property (nonatomic, retain) NSString *mHitchMap; @property (nonatomic, retain) NSString *fShippingWeight; @property (nonatomic, retain) NSString *vchWC; @property (nonatomic, retain) NSString *vchCapacity; @property (nonatomic, retain) NSString *txtNote1; @property (nonatomic, retain) NSString *txtNote2; @property (nonatomic, retain) NSString *txtNote3; @property (nonatomic, retain) NSString *txtNote4; @property (nonatomic, retain) NSString *vchDrilling; @property (nonatomic, retain) NSString *vchUPCList; @property (nonatomic, retain) NSString *vchExposed; @property (nonatomic, retain) NSString *vchShortDesc; @property (nonatomic, retain) NSString *iVehicleID; @property (nonatomic, retain) NSString *iProductClassID; @property (nonatomic, retain) NSString *dtDateMod; @property (nonatomic, retain) NSString *txtBullet1; @property (nonatomic, retain) NSString *txtBullet2; @property (nonatomic, retain) NSString *txtBullet3; @property (nonatomic, retain) NSString *txtBullet4; @property (nonatomic, retain) NSString *txtBullet5; @property (nonatomic, retain) NSString *iUniqueIdentifier; @property (nonatomic, retain) NSString *dtDateLastTouched; @property (nonatomic, retain) NSString *txtNote6; @property (nonatomic, retain) NSString *InstallTime; @property (nonatomic, retain) NSString *SGID; @property (nonatomic, retain) NSString *CURTID; @property (nonatomic, retain) NSString *SGRetail; @property (nonatomic, retain) NSString *SGMemPrice; @property (nonatomic, retain) NSString *InstallSheet; @property (nonatomic, retain) NSString *mHitchJobber; @property (nonatomic, retain) NSString *CatID; @property (nonatomic, retain) NSString *ParentID; -(id) initWithDict:(NSDictionary *)dic; -(NSString *) description; @end Product implementation .m #import "Product.h" @implementation Product @synthesize iProductID; @synthesize vchProductCode; @synthesize vchPriceCode; @synthesize vchHitchUPC; @synthesize mHitchList; @synthesize mHitchMap; @synthesize fShippingWeight; @synthesize vchWC; @synthesize vchCapacity; @synthesize txtNote1; @synthesize txtNote2; @synthesize txtNote3; @synthesize txtNote4; @synthesize vchDrilling; @synthesize vchUPCList; @synthesize vchExposed; @synthesize vchShortDesc; @synthesize iVehicleID; @synthesize iProductClassID; @synthesize dtDateMod; @synthesize txtBullet1; @synthesize txtBullet2; @synthesize txtBullet3; @synthesize txtBullet4; @synthesize txtBullet5; @synthesize iUniqueIdentifier; @synthesize dtDateLastTouched; @synthesize txtNote6; @synthesize InstallTime; @synthesize SGID; @synthesize CURTID; @synthesize SGRetail; @synthesize SGMemPrice; @synthesize InstallSheet; @synthesize mHitchJobber; @synthesize CatID; @synthesize ParentID; -(id) initWithDict:(NSDictionary *)dic { [super init]; //Initialize all variables self.iProductID = [[NSString alloc] initWithString:[dic objectForKey:@"iProductID"]]; self.vchProductCode = [[NSString alloc] initWithString:[dic objectForKey:@"vchProductCode"]]; self.vchPriceCode = [[NSString alloc] initWithString:[dic objectForKey:@"vchPriceCode"]]; self.vchHitchUPC = [[NSString alloc] initWithString:[dic objectForKey:@"vchHitchUPC"]]; self.mHitchList = [[NSString alloc] initWithString:[dic objectForKey:@"mHitchList"]]; self.mHitchMap = [[NSString alloc] initWithString:[dic objectForKey:@"mHitchMap"]]; self.fShippingWeight = [[NSString alloc] initWithString:[dic objectForKey:@"fShippingWeight"]]; self.vchWC = [[NSString alloc] initWithString:[dic objectForKey:@"vchWC"]]; self.vchCapacity = [[NSString alloc] initWithString:[dic objectForKey:@"vchCapacity"]]; self.txtNote1 = [[NSString alloc] initWithString:[dic objectForKey:@"txtNote1"]]; self.txtNote2 = [[NSString alloc] initWithString:[dic objectForKey:@"txtNote2"]]; self.txtNote3 = [[NSString alloc] initWithString:[dic objectForKey:@"txtNote3"]]; self.txtNote4 = [[NSString alloc] initWithString:[dic objectForKey:@"txtNote4"]]; self.vchDrilling = [[NSString alloc] initWithString:[dic objectForKey:@"vchDrilling"]]; self.vchUPCList = [[NSString alloc] initWithString:[dic objectForKey:@"vchUPCList"]]; self.vchExposed = [[NSString alloc] initWithString:[dic objectForKey:@"vchExposed"]]; self.vchShortDesc = [[NSString alloc] initWithString:[dic objectForKey:@"vchShortDesc"]]; self.iVehicleID = [[NSString alloc] initWithString:[dic objectForKey:@"iVehicleID"]]; self.iProductClassID = [[NSString alloc] initWithString:[dic objectForKey:@"iProductClassID"]]; self.dtDateMod = [[NSString alloc] initWithString:[dic objectForKey:@"dtDateMod"]]; self.txtBullet1 = [[NSString alloc] initWithString:[dic objectForKey:@"txtBullet1"]]; self.txtBullet2 = [[NSString alloc] initWithString:[dic objectForKey:@"txtBullet2"]]; self.txtBullet3 = [[NSString alloc] initWithString:[dic objectForKey:@"txtBullet3"]]; self.txtBullet4 = [[NSString alloc] initWithString:[dic objectForKey:@"txtBullet4"]]; self.txtBullet5 = [[NSString alloc] initWithString:[dic objectForKey:@"txtBullet5"]]; self.iUniqueIdentifier = [[NSString alloc] initWithString:[dic objectForKey:@"iUniqueIdentifier"]]; self.dtDateLastTouched = [[NSString alloc] initWithString:[dic objectForKey:@"dtDateLastTouched"]]; self.txtNote6 = [[NSString alloc] initWithString:[dic objectForKey:@"txtNote6"]]; self.InstallTime = [[NSString alloc] initWithString:[dic objectForKey:@"InstallTime"]]; self.SGID = [[NSString alloc] initWithString:[dic objectForKey:@"SGID"]]; self.CURTID = [[NSString alloc] initWithString:[dic objectForKey:@"CURTID"]]; self.SGRetail = [[NSString alloc] initWithString:[dic objectForKey:@"SGRetail"]]; self.SGMemPrice = [[NSString alloc] initWithString:[dic objectForKey:@"SGMemPrice"]]; self.InstallSheet = [[NSString alloc] initWithString:[dic objectForKey:@"InstallSheet"]]; self.mHitchJobber = [[NSString alloc] initWithString:[dic objectForKey:@"mHitchJobber"]]; self.CatID = [[NSString alloc] initWithString:[dic objectForKey:@"CatID"]]; self.ParentID = [[NSString alloc] initWithString:[dic objectForKey:@"ParentID"]]; return self; } -(NSString *) description { return [NSString stringWithFormat:@"iProductID = %@\n vchProductCode = %@\n vchPriceCode = %@\n vchHitchUPC = %@\n mHitchList = %@\n mHitchMap = %@\n fShippingWeight = %@\n vchWC = %@\n vchCapacity = %@\n txtNote1 = %@\n txtNote2 = %@\n txtNote3 = %@\n txtNote4 = %@\n vchDrilling = %@\n vchUPCList = %@\n vchExposed = %@\n vchShortDesc = %@\n iVehicleID = %@\n iProductClassID = %@\n dtDateMod = %@\n txtBullet1 = %@\n txtBullet2 = %@\n txtBullet3 = %@\n txtBullet4 = %@\n txtBullet4 = %@\n txtBullet5 = %@\n iUniqueIdentifier = %@\n dtDateLastTouched = %@\n txtNote6 = %@\n InstallTime = %@\n SGID = %@\n CURTID = %@\n SGRetail = %@\n SGMemPrice = %@\n InstallSheet = %@\n mHitchJobber = %@\n CatID = %@\n ParentID = %@\n", iProductID, vchProductCode, vchPriceCode, vchHitchUPC, mHitchList, mHitchMap, fShippingWeight, vchWC, vchCapacity, txtNote1, txtNote2, txtNote3, txtNote4, vchDrilling, vchUPCList, vchExposed, vchShortDesc, iVehicleID, iProductClassID, dtDateMod, txtBullet1, txtBullet2, txtBullet3, txtBullet4,txtBullet5, iUniqueIdentifier, dtDateLastTouched,txtNote6,InstallTime,SGID,CURTID,SGRetail,SGMemPrice,InstallSheet,mHitchJobber,CatID, ParentID]; } @end Ignoring the fact that its really long I also tried to just set the property but then my product didnt have any values. So I alloc'd for all properties, not sure which is "correct" the use of product picker.h #import <UIKit/UIKit.h> @class Vehicle; @class Product; @interface Picker : UITableViewController <NSXMLParserDelegate> { NSString *currentRow; NSString *currentElement; Vehicle *vehicle; } @property (nonatomic, retain) NSMutableArray *dataArray; //@property (readwrite, copy) NSString *currentRow; //@property (readwrite, copy) NSString *currentElement; -(void) getYears:(NSString *)string; -(void) getMakes:(NSString *)year; -(void) getModels:(NSString *)year: (NSString *)make; -(void) getStyles:(NSString *)year: (NSString *)make: (NSString *)model; -(void) getHitch:(NSString *)year: (NSString *)make: (NSString *)model: (NSString *)style; -(void) parser:(NSXMLParser *)parser didEndElement:(NSString *)elementName namespaceURI:(NSString *)namespaceURI qualifiedName:(NSString *)qName; -(void) parser:(NSXMLParser *)parser foundCharacters:(NSString *)string; -(void) parser:(NSXMLParser *)parser didStartElement:(NSString *)elementName namespaceURI:(NSString *)namespaceURI qualifiedName:(NSString *)qName attributes:(NSDictionary *)attributeDict; @end The implementation .m #import "Product.h" #import "Picker.h" #import "KioskAppDelegate.h" #import "JSON.h" #import "Vehicle.h" @implementation Picker @synthesize dataArray; -(void) getHitch:(NSString *)year: (NSString *)make: (NSString *)model: (NSString *)style{ currentRow = [NSString stringWithString:@"z:row"]; currentElement = [NSString stringWithString:@"gethitch"]; //Reinitialize data array [self.dataArray removeAllObjects]; [self.dataArray release]; self.dataArray = [[NSArray alloc] initWithObjects:nil]; //Build url & string NSString *thisString = [[NSString alloc] initWithString:@""]; thisString = [NSString stringWithFormat:@"http://api.curthitch.biz/AJAX_CURT.aspx?action=GetHitch&dataType=json&year=%@&make=%@&model=%@&style=%@",year,make,model,style]; //Request NSURLRequest *request = [NSURLRequest requestWithURL:[NSURL URLWithString:thisString]]; //Perform request and fill data with json NSData *response = [NSURLConnection sendSynchronousRequest:request returningResponse:nil error:nil]; //Get string from data NSString *json_string = [[NSString alloc] initWithData:response encoding:NSUTF8StringEncoding]; //set up parser SBJsonParser *parser = [[SBJsonParser alloc] init]; //parse json into object NSArray *tempArray = [parser objectWithString:json_string error:nil]; for (NSDictionary *dic in tempArray) { Product *tempProduct = [[Product alloc] initWithDict:dic]; NSLog(@"is tempProduct valid %@", (tempProduct) ? @"YES" : @"NO"); [self.dataArray addObject:tempProduct]; } } @end So I stripped out all the table methods and misc crap that doesnt matter. In the end my problem is adding the "tempProduct" object to the mutable array dataArray so that I can customize the table cells. Using the json framework im parsing out some json which returns an array of NSDictionary objects. Stepping through that my dictionary objects look good, I populate my custom object with properties for all my fields which goes through fine, and the values look right. However I cant add this to the array, I've tried several different implementations doesn't work. Not sure what I'm doing wrong. In some instances doing a po tempProduct prints the description and sometimes it does not. same with right clicking on the variable and choosing print description. Actual error message 2011-02-22 15:53:56.058 Kiosk[8547:207] -[__NSArrayI addObject:]: unrecognized selector sent to instance 0x4e1ba40 2011-02-22 15:53:56.060 Kiosk[8547:207] *** Terminating app due to uncaught exception 'NSInvalidArgumentException', reason: '-[__NSArrayI addObject:]: unrecognized selector sent to instance 0x4e1ba40' *** Call stack at first throw: ( 0 CoreFoundation 0x00dbabe9 __exceptionPreprocess + 185 1 libobjc.A.dylib 0x00f0f5c2 objc_exception_throw + 47 2 CoreFoundation 0x00dbc6fb -[NSObject(NSObject) doesNotRecognizeSelector:] + 187 3 CoreFoundation 0x00d2c366 ___forwarding___ + 966 4 CoreFoundation 0x00d2bf22 _CF_forwarding_prep_0 + 50 5 Kiosk 0x00003ead -[Picker getHitch::::] + 1091 6 Kiosk 0x00003007 -[Picker tableView:didSelectRowAtIndexPath:] + 1407 7 UIKit 0x0009b794 -[UITableView _selectRowAtIndexPath:animated:scrollPosition:notifyDelegate:] + 1140 8 UIKit 0x00091d50 -[UITableView _userSelectRowAtPendingSelectionIndexPath:] + 219 9 Foundation 0x007937f6 __NSFireDelayedPerform + 441 10 CoreFoundation 0x00d9bfe3 __CFRUNLOOP_IS_CALLING_OUT_TO_A_TIMER_CALLBACK_FUNCTION__ + 19 11 CoreFoundation 0x00d9d594 __CFRunLoopDoTimer + 1220 12 CoreFoundation 0x00cf9cc9 __CFRunLoopRun + 1817 13 CoreFoundation 0x00cf9240 CFRunLoopRunSpecific + 208 14 CoreFoundation 0x00cf9161 CFRunLoopRunInMode + 97 15 GraphicsServices 0x0102e268 GSEventRunModal + 217 16 GraphicsServices 0x0102e32d GSEventRun + 115 17 UIKit 0x0003442e UIApplicationMain + 1160 18 Kiosk 0x0000239a main + 104 19 Kiosk 0x00002329 start + 53 ) terminate called after throwing an instance of 'NSException'

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