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  • How to Profile R Code that Includes SNOW Cluster

    - by James
    Hi, I have a nested loop that I'm using foreach, DoSNOW, and a SNOW socket cluster to solve for. How should I go about profiling the code to make sure I'm not doing something grossly inefficient. Also is there anyway to measure the data flows going between the master and nodes in a Snow cluster? Thanks, James

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  • Using an object in an if statement... (Android)

    - by James Rattray
    I have an object variable Object test = Spinner.getSelectedItem(); -It gets the selected item from the Spinner (called spinner) and names the item 'test' I want to do an if statement related to that object e.g: 'if (test = "hello") { //do something }' But it appears not to work.... Can someone give me some help? -Do I have to use a different if? or convert the object to string etc.? Thanks alot... James

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  • PHP cron script with twitter (problem with oauth)

    - by James Lin
    Hi guys, I am trying to write an php twitter script which will be run by crontab, what the script does is to get the tweets from a dedicated twitter account. I have looked at some of the php twitter oauth libraries, all of them seem to use redirect to a twitter page to get a token, then goes back to a callback link. In my case I don't want to have any user interaction at all. Could anyone please tell me what I should do? Regards James

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  • Why is System.arraycopy native in Java?

    - by James B
    I was surprised to see in the Java source that System.arraycopy is a native method. Of course the reason is because it's faster. But what native tricks is the code able to employ that make it faster? Why not just loop over the original array and copy each pointer to the new array - surely this isn't that slow and cumbersome? Thanks, -James

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  • Hive metadata permission issue

    - by Chandramohan
    We are getting this error on Hive, while creating a DB / table hive> CREATE TABLE pokes (foo INT, bar STRING); FAILED: Error in metadata: javax.jdo.JDOFatalDataStoreException: Cannot get a connection, pool error Could not create a validated object, cause: A read-only user or a user in a read-only database is not permitted to disable read-only mode on a connection. NestedThrowables: org.apache.commons.dbcp.SQLNestedException: Cannot get a connection, pool error Could not create a validated object, cause: A read-only user or a user in a read-only database is not permitted to disable read-only mode on a connection. FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask Hive log : org.apache.commons.dbcp.SQLNestedException: Cannot get a connection, pool error Could not create a validated object, cause: A read-only user or a user in a read-only database is not permitted to disable read-only mode on a connection. at org.datanucleus.jdo.NucleusJDOHelper.getJDOExceptionForNucleusException(NucleusJDOHelper.java:298) at org.datanucleus.jdo.JDOPersistenceManagerFactory.freezeConfiguration(JDOPersistenceManagerFactory.java:601) at org.datanucleus.jdo.JDOPersistenceManagerFactory.createPersistenceManagerFactory(JDOPersistenceManagerFactory.java:286) at org.datanucleus.jdo.JDOPersistenceManagerFactory.getPersistenceManagerFactory(JDOPersistenceManagerFactory.java:182) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at javax.jdo.JDOHelper$16.run(JDOHelper.java:1958) at java.security.AccessController.doPrivileged(Native Method) at javax.jdo.JDOHelper.invoke(JDOHelper.java:1953) at javax.jdo.JDOHelper.invokeGetPersistenceManagerFactoryOnImplementation(JDOHelper.java:1159) at javax.jdo.JDOHelper.getPersistenceManagerFactory(JDOHelper.java:803) at javax.jdo.JDOHelper.getPersistenceManagerFactory(JDOHelper.java:698) at org.apache.hadoop.hive.metastore.ObjectStore.getPMF(ObjectStore.java:234) at org.apache.hadoop.hive.metastore.ObjectStore.getPersistenceManager(ObjectStore.java:261) at org.apache.hadoop.hive.metastore.ObjectStore.initialize(ObjectStore.java:196) at org.apache.hadoop.hive.metastore.ObjectStore.setConf(ObjectStore.java:171) at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:62) at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:117) at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.getMS(HiveMetaStore.java:354) at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.executeWithRetry(HiveMetaStore.java:306) at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.createDefaultDB(HiveMetaStore.java:451) at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.init(HiveMetaStore.java:232) at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.<init>(HiveMetaStore.java:197) at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.<init>(HiveMetaStoreClient.java:108) at org.apache.hadoop.hive.ql.metadata.Hive.createMetaStoreClient(Hive.java:1868) at org.apache.hadoop.hive.ql.metadata.Hive.getMSC(Hive.java:1878) at org.apache.hadoop.hive.ql.metadata.Hive.createTable(Hive.java:470) ... 15 more Caused by: org.apache.commons.dbcp.SQLNestedException: Cannot get a connection, pool error Could not create a validated object, cause: A read-only user or a user in a read-only database is not permitted to disable read-only mode on a connection. at org.apache.commons.dbcp.PoolingDataSource.getConnection(PoolingDataSource.java:114) at org.datanucleus.store.rdbms.ConnectionFactoryImpl$ManagedConnectionImpl.getConnection(ConnectionFactoryImpl.java:521) at org.datanucleus.store.rdbms.RDBMSStoreManager.<init>(RDBMSStoreManager.java:290) at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:39) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:27) at java.lang.reflect.Constructor.newInstance(Constructor.java:513) at org.datanucleus.plugin.NonManagedPluginRegistry.createExecutableExtension(NonManagedPluginRegistry.java:588) at org.datanucleus.plugin.PluginManager.createExecutableExtension(PluginManager.java:300) at org.datanucleus.ObjectManagerFactoryImpl.initialiseStoreManager(ObjectManagerFactoryImpl.java:161) at org.datanucleus.jdo.JDOPersistenceManagerFactory.freezeConfiguration(JDOPersistenceManagerFactory.java:583) ... 42 more Caused by: java.util.NoSuchElementException: Could not create a validated object, cause: A read-only user or a user in a read-only database is not permitted to disable read-only mode on a connection. at org.apache.commons.pool.impl.GenericObjectPool.borrowObject(GenericObjectPool.java:1191) at org.apache.commons.dbcp.PoolingDataSource.getConnection(PoolingDataSource.java:106) ... 52 more 2011-08-11 18:02:36,964 ERROR ql.Driver (SessionState.java:printError(343)) - FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask

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  • Cannot connect to MySQL over TCP locally - Connection Timeout - Ubuntu 9.04

    - by gav
    I am running Ubuntu and am ultimately trying to connect Tomcat to my MySQL database using JDBC. It has worked previously but after a reboot the instance now fails to connect. Both Tomcat 6 and MySQL 5.0.75 are on the same machine Connection string: jdbc:mysql:///localhost:3306 I can connect to MySQL on the command line using the mysql command The my.cnf file is pretty standard (Available on request) has bind address: 127.0.0.1 I cannot Telnet to the MySQL port despite netstat saying MySQL is listening I have one IpTables rule to forward 80 - 8080 and no firewall I'm aware of. I'm pretty new to this and I'm not sure what else to test. I don't know whether I should be looking in etc/interfaces and if I did what to look for. It's weird because it used to work but after a reboot it's down so I must have changed something.... :). I realise a timeout indicates the server is not responding and I assume it's because the request isn't actually getting through. I installed MySQL via apt-get and Tomcat manually. MySqld processes root@88:/var/log/mysql# ps -ef | grep mysqld root 21753 1 0 May27 ? 00:00:00 /bin/sh /usr/bin/mysqld_safe mysql 21792 21753 0 May27 ? 00:00:00 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --user=mysql --pid-file=/var/run/mysqld/mysqld.pid --skip-external-locking --port=3306 --socket=/var/run/mysqld/mysqld.sock root 21793 21753 0 May27 ? 00:00:00 logger -p daemon.err -t mysqld_safe -i -t mysqld root 21888 13676 0 11:23 pts/1 00:00:00 grep mysqld Netstat root@88:/var/log/mysql# netstat -lnp | grep mysql tcp 0 0 0.0.0.0:3306 0.0.0.0:* LISTEN 21792/mysqld unix 2 [ ACC ] STREAM LISTENING 1926205077 21792/mysqld /var/run/mysqld/mysqld.sock Toy Connection Class root@88:~# cat TestConnect/TestConnection.java import java.sql.Connection; import java.sql.DriverManager; import java.sql.SQLException; public class TestConnection { public static void main(String args[]) throws Exception { Connection con = null; try { Class.forName("com.mysql.jdbc.Driver").newInstance(); System.out.println("Got driver"); con = DriverManager.getConnection( "jdbc:mysql:///localhost:3306", "uname", "pass"); System.out.println("Got connection"); if(!con.isClosed()) System.out.println("Successfully connected to " + "MySQL server using TCP/IP..."); } finally { if(con != null) con.close(); } } } Toy Connection Class Output Note: This is the same error I get from Tomcat. root@88:~/TestConnect# java -cp mysql-connector-java-5.1.12-bin.jar:. TestConnection Got driver Exception in thread "main" com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link failure The last packet sent successfully to the server was 1 milliseconds ago. The driver has not received any packets from the server. at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:39) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:27) at java.lang.reflect.Constructor.newInstance(Constructor.java:513) at com.mysql.jdbc.Util.handleNewInstance(Util.java:409) at com.mysql.jdbc.SQLError.createCommunicationsException(SQLError.java:1122) at TestConnection.main(TestConnection.java:14) Caused by: com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link failure The last packet sent successfully to the server was 0 milliseconds ago. The driver has not received any packets from the server. at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:39) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:27) at java.lang.reflect.Constructor.newInstance(Constructor.java:513) at com.mysql.jdbc.Util.handleNewInstance(Util.java:409) at com.mysql.jdbc.SQLError.createCommunicationsException(SQLError.java:1122) at com.mysql.jdbc.MysqlIO.<init>(MysqlIO.java:344) at com.mysql.jdbc.ConnectionImpl.createNewIO(ConnectionImpl.java:2181) ... 12 more Caused by: java.net.ConnectException: Connection timed out at java.net.PlainSocketImpl.socketConnect(Native Method) ... 13 more Telnet Output root@88:~/TestConnect# telnet localhost 3306 Trying 127.0.0.1... telnet: Unable to connect to remote host: Connection timed out

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  • CVE-2006-3744 Multiple Integer overflow vulnerabilities in ImageMagick

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2006-3744 Numeric Errors vulnerability 5.1 ImageMagick Solaris 10 SPARC: 136882-03 X86: 136883-03 This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • C#/.NET Little Wonders: The Concurrent Collections (1 of 3)

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In the next few weeks, we will discuss the concurrent collections and how they have changed the face of concurrent programming. This week’s post will begin with a general introduction and discuss the ConcurrentStack<T> and ConcurrentQueue<T>.  Then in the following post we’ll discuss the ConcurrentDictionary<T> and ConcurrentBag<T>.  Finally, we shall close on the third post with a discussion of the BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. A brief history of collections In the beginning was the .NET 1.0 Framework.  And out of this framework emerged the System.Collections namespace, and it was good.  It contained all the basic things a growing programming language needs like the ArrayList and Hashtable collections.  The main problem, of course, with these original collections is that they held items of type object which means you had to be disciplined enough to use them correctly or you could end up with runtime errors if you got an object of a type you weren't expecting. Then came .NET 2.0 and generics and our world changed forever!  With generics the C# language finally got an equivalent of the very powerful C++ templates.  As such, the System.Collections.Generic was born and we got type-safe versions of all are favorite collections.  The List<T> succeeded the ArrayList and the Dictionary<TKey,TValue> succeeded the Hashtable and so on.  The new versions of the library were not only safer because they checked types at compile-time, in many cases they were more performant as well.  So much so that it's Microsoft's recommendation that the System.Collections original collections only be used for backwards compatibility. So we as developers came to know and love the generic collections and took them into our hearts and embraced them.  The problem is, thread safety in both the original collections and the generic collections can be problematic, for very different reasons. Now, if you are only doing single-threaded development you may not care – after all, no locking is required.  Even if you do have multiple threads, if a collection is “load-once, read-many” you don’t need to do anything to protect that container from multi-threaded access, as illustrated below: 1: public static class OrderTypeTranslator 2: { 3: // because this dictionary is loaded once before it is ever accessed, we don't need to synchronize 4: // multi-threaded read access 5: private static readonly Dictionary<string, char> _translator = new Dictionary<string, char> 6: { 7: {"New", 'N'}, 8: {"Update", 'U'}, 9: {"Cancel", 'X'} 10: }; 11:  12: // the only public interface into the dictionary is for reading, so inherently thread-safe 13: public static char? Translate(string orderType) 14: { 15: char charValue; 16: if (_translator.TryGetValue(orderType, out charValue)) 17: { 18: return charValue; 19: } 20:  21: return null; 22: } 23: } Unfortunately, most of our computer science problems cannot get by with just single-threaded applications or with multi-threading in a load-once manner.  Looking at  today's trends, it's clear to see that computers are not so much getting faster because of faster processor speeds -- we've nearly reached the limits we can push through with today's technologies -- but more because we're adding more cores to the boxes.  With this new hardware paradigm, it is even more important to use multi-threaded applications to take full advantage of parallel processing to achieve higher application speeds. So let's look at how to use collections in a thread-safe manner. Using historical collections in a concurrent fashion The early .NET collections (System.Collections) had a Synchronized() static method that could be used to wrap the early collections to make them completely thread-safe.  This paradigm was dropped in the generic collections (System.Collections.Generic) because having a synchronized wrapper resulted in atomic locks for all operations, which could prove overkill in many multithreading situations.  Thus the paradigm shifted to having the user of the collection specify their own locking, usually with an external object: 1: public class OrderAggregator 2: { 3: private static readonly Dictionary<string, List<Order>> _orders = new Dictionary<string, List<Order>>(); 4: private static readonly _orderLock = new object(); 5:  6: public void Add(string accountNumber, Order newOrder) 7: { 8: List<Order> ordersForAccount; 9:  10: // a complex operation like this should all be protected 11: lock (_orderLock) 12: { 13: if (!_orders.TryGetValue(accountNumber, out ordersForAccount)) 14: { 15: _orders.Add(accountNumber, ordersForAccount = new List<Order>()); 16: } 17:  18: ordersForAccount.Add(newOrder); 19: } 20: } 21: } Notice how we’re performing several operations on the dictionary under one lock.  With the Synchronized() static methods of the early collections, you wouldn’t be able to specify this level of locking (a more macro-level).  So in the generic collections, it was decided that if a user needed synchronization, they could implement their own locking scheme instead so that they could provide synchronization as needed. The need for better concurrent access to collections Here’s the problem: it’s relatively easy to write a collection that locks itself down completely for access, but anything more complex than that can be difficult and error-prone to write, and much less to make it perform efficiently!  For example, what if you have a Dictionary that has frequent reads but in-frequent updates?  Do you want to lock down the entire Dictionary for every access?  This would be overkill and would prevent concurrent reads.  In such cases you could use something like a ReaderWriterLockSlim which allows for multiple readers in a lock, and then once a writer grabs the lock it blocks all further readers until the writer is done (in a nutshell).  This is all very complex stuff to consider. Fortunately, this is where the Concurrent Collections come in.  The Parallel Computing Platform team at Microsoft went through great pains to determine how to make a set of concurrent collections that would have the best performance characteristics for general case multi-threaded use. Now, as in all things involving threading, you should always make sure you evaluate all your container options based on the particular usage scenario and the degree of parallelism you wish to acheive. This article should not be taken to understand that these collections are always supperior to the generic collections. Each fills a particular need for a particular situation. Understanding what each container is optimized for is key to the success of your application whether it be single-threaded or multi-threaded. General points to consider with the concurrent collections The MSDN points out that the concurrent collections all support the ICollection interface. However, since the collections are already synchronized, the IsSynchronized property always returns false, and SyncRoot always returns null.  Thus you should not attempt to use these properties for synchronization purposes. Note that since the concurrent collections also may have different operations than the traditional data structures you may be used to.  Now you may ask why they did this, but it was done out of necessity to keep operations safe and atomic.  For example, in order to do a Pop() on a stack you have to know the stack is non-empty, but between the time you check the stack’s IsEmpty property and then do the Pop() another thread may have come in and made the stack empty!  This is why some of the traditional operations have been changed to make them safe for concurrent use. In addition, some properties and methods in the concurrent collections achieve concurrency by creating a snapshot of the collection, which means that some operations that were traditionally O(1) may now be O(n) in the concurrent models.  I’ll try to point these out as we talk about each collection so you can be aware of any potential performance impacts.  Finally, all the concurrent containers are safe for enumeration even while being modified, but some of the containers support this in different ways (snapshot vs. dirty iteration).  Once again I’ll highlight how thread-safe enumeration works for each collection. ConcurrentStack<T>: The thread-safe LIFO container The ConcurrentStack<T> is the thread-safe counterpart to the System.Collections.Generic.Stack<T>, which as you may remember is your standard last-in-first-out container.  If you think of algorithms that favor stack usage (for example, depth-first searches of graphs and trees) then you can see how using a thread-safe stack would be of benefit. The ConcurrentStack<T> achieves thread-safe access by using System.Threading.Interlocked operations.  This means that the multi-threaded access to the stack requires no traditional locking and is very, very fast! For the most part, the ConcurrentStack<T> behaves like it’s Stack<T> counterpart with a few differences: Pop() was removed in favor of TryPop() Returns true if an item existed and was popped and false if empty. PushRange() and TryPopRange() were added Allows you to push multiple items and pop multiple items atomically. Count takes a snapshot of the stack and then counts the items. This means it is a O(n) operation, if you just want to check for an empty stack, call IsEmpty instead which is O(1). ToArray() and GetEnumerator() both also take snapshots. This means that iteration over a stack will give you a static view at the time of the call and will not reflect updates. Pushing on a ConcurrentStack<T> works just like you’d expect except for the aforementioned PushRange() method that was added to allow you to push a range of items concurrently. 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: // but you can also push multiple items in one atomic operation (no interleaves) 7: stack.PushRange(new [] { "Second", "Third", "Fourth" }); For looking at the top item of the stack (without removing it) the Peek() method has been removed in favor of a TryPeek().  This is because in order to do a peek the stack must be non-empty, but between the time you check for empty and the time you execute the peek the stack contents may have changed.  Thus the TryPeek() was created to be an atomic check for empty, and then peek if not empty: 1: // to look at top item of stack without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (stack.TryPeek(out item)) 5: { 6: Console.WriteLine("Top item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Stack was empty."); 11: } Finally, to remove items from the stack, we have the TryPop() for single, and TryPopRange() for multiple items.  Just like the TryPeek(), these operations replace Pop() since we need to ensure atomically that the stack is non-empty before we pop from it: 1: // to remove items, use TryPop or TryPopRange to get multiple items atomically (no interleaves) 2: if (stack.TryPop(out item)) 3: { 4: Console.WriteLine("Popped " + item); 5: } 6:  7: // TryPopRange will only pop up to the number of spaces in the array, the actual number popped is returned. 8: var poppedItems = new string[2]; 9: int numPopped = stack.TryPopRange(poppedItems); 10:  11: foreach (var theItem in poppedItems.Take(numPopped)) 12: { 13: Console.WriteLine("Popped " + theItem); 14: } Finally, note that as stated before, GetEnumerator() and ToArray() gets a snapshot of the data at the time of the call.  That means if you are enumerating the stack you will get a snapshot of the stack at the time of the call.  This is illustrated below: 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: var results = stack.GetEnumerator(); 7:  8: // but you can also push multiple items in one atomic operation (no interleaves) 9: stack.PushRange(new [] { "Second", "Third", "Fourth" }); 10:  11: while(results.MoveNext()) 12: { 13: Console.WriteLine("Stack only has: " + results.Current); 14: } The only item that will be printed out in the above code is "First" because the snapshot was taken before the other items were added. This may sound like an issue, but it’s really for safety and is more correct.  You don’t want to enumerate a stack and have half a view of the stack before an update and half a view of the stack after an update, after all.  In addition, note that this is still thread-safe, whereas iterating through a non-concurrent collection while updating it in the old collections would cause an exception. ConcurrentQueue<T>: The thread-safe FIFO container The ConcurrentQueue<T> is the thread-safe counterpart of the System.Collections.Generic.Queue<T> class.  The concurrent queue uses an underlying list of small arrays and lock-free System.Threading.Interlocked operations on the head and tail arrays.  Once again, this allows us to do thread-safe operations without the need for heavy locks! The ConcurrentQueue<T> (like the ConcurrentStack<T>) has some departures from the non-concurrent counterpart.  Most notably: Dequeue() was removed in favor of TryDequeue(). Returns true if an item existed and was dequeued and false if empty. Count does not take a snapshot It subtracts the head and tail index to get the count.  This results overall in a O(1) complexity which is quite good.  It’s still recommended, however, that for empty checks you call IsEmpty instead of comparing Count to zero. ToArray() and GetEnumerator() both take snapshots. This means that iteration over a queue will give you a static view at the time of the call and will not reflect updates. The Enqueue() method on the ConcurrentQueue<T> works much the same as the generic Queue<T>: 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5: queue.Enqueue("Second"); 6: queue.Enqueue("Third"); For front item access, the TryPeek() method must be used to attempt to see the first item if the queue.  There is no Peek() method since, as you’ll remember, we can only peek on a non-empty queue, so we must have an atomic TryPeek() that checks for empty and then returns the first item if the queue is non-empty. 1: // to look at first item in queue without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (queue.TryPeek(out item)) 5: { 6: Console.WriteLine("First item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Queue was empty."); 11: } Then, to remove items you use TryDequeue().  Once again this is for the same reason we have TryPeek() and not Peek(): 1: // to remove items, use TryDequeue. If queue is empty returns false. 2: if (queue.TryDequeue(out item)) 3: { 4: Console.WriteLine("Dequeued first item " + item); 5: } Just like the concurrent stack, the ConcurrentQueue<T> takes a snapshot when you call ToArray() or GetEnumerator() which means that subsequent updates to the queue will not be seen when you iterate over the results.  Thus once again the code below will only show the first item, since the other items were added after the snapshot. 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5:  6: var iterator = queue.GetEnumerator(); 7:  8: queue.Enqueue("Second"); 9: queue.Enqueue("Third"); 10:  11: // only shows First 12: while (iterator.MoveNext()) 13: { 14: Console.WriteLine("Dequeued item " + iterator.Current); 15: } Using collections concurrently You’ll notice in the examples above I stuck to using single-threaded examples so as to make them deterministic and the results obvious.  Of course, if we used these collections in a truly multi-threaded way the results would be less deterministic, but would still be thread-safe and with no locking on your part required! For example, say you have an order processor that takes an IEnumerable<Order> and handles each other in a multi-threaded fashion, then groups the responses together in a concurrent collection for aggregation.  This can be done easily with the TPL’s Parallel.ForEach(): 1: public static IEnumerable<OrderResult> ProcessOrders(IEnumerable<Order> orderList) 2: { 3: var proxy = new OrderProxy(); 4: var results = new ConcurrentQueue<OrderResult>(); 5:  6: // notice that we can process all these in parallel and put the results 7: // into our concurrent collection without needing any external locking! 8: Parallel.ForEach(orderList, 9: order => 10: { 11: var result = proxy.PlaceOrder(order); 12:  13: results.Enqueue(result); 14: }); 15:  16: return results; 17: } Summary Obviously, if you do not need multi-threaded safety, you don’t need to use these collections, but when you do need multi-threaded collections these are just the ticket! The plethora of features (I always think of the movie The Three Amigos when I say plethora) built into these containers and the amazing way they acheive thread-safe access in an efficient manner is wonderful to behold. Stay tuned next week where we’ll continue our discussion with the ConcurrentBag<T> and the ConcurrentDictionary<TKey,TValue>. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here.   Tweet Technorati Tags: C#,.NET,Concurrent Collections,Collections,Multi-Threading,Little Wonders,BlackRabbitCoder,James Michael Hare

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  • CVE-2011-2896 Buffer overflow vulnerability in GIMP

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2011-2896 Buffer Overflow vulnerability 5.1 GIMP Image Editor Solaris 10 SPARC: 147988-01 X86: 147989-01 Solaris 11 Express snv_151a + 7079990 This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • CVE-2011-3192 and CVE-2011-0419 affect Oracle Secure Global Desktop

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2011-0419 Resource Management Errors vulnerability 4.3 Apache HTTP Server Oracle Secure Global Desktop 4.62 CVE-2011-3192 Resource Management Errors vulnerability 7.8 This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • C#/.NET Little Wonders: The ConcurrentDictionary

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In this series of posts, we will discuss how the concurrent collections have been developed to help alleviate these multi-threading concerns.  Last week’s post began with a general introduction and discussed the ConcurrentStack<T> and ConcurrentQueue<T>.  Today's post discusses the ConcurrentDictionary<T> (originally I had intended to discuss ConcurrentBag this week as well, but ConcurrentDictionary had enough information to create a very full post on its own!).  Finally next week, we shall close with a discussion of the ConcurrentBag<T> and BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. Recap As you'll recall from the previous post, the original collections were object-based containers that accomplished synchronization through a Synchronized member.  While these were convenient because you didn't have to worry about writing your own synchronization logic, they were a bit too finely grained and if you needed to perform multiple operations under one lock, the automatic synchronization didn't buy much. With the advent of .NET 2.0, the original collections were succeeded by the generic collections which are fully type-safe, but eschew automatic synchronization.  This cuts both ways in that you have a lot more control as a developer over when and how fine-grained you want to synchronize, but on the other hand if you just want simple synchronization it creates more work. With .NET 4.0, we get the best of both worlds in generic collections.  A new breed of collections was born called the concurrent collections in the System.Collections.Concurrent namespace.  These amazing collections are fine-tuned to have best overall performance for situations requiring concurrent access.  They are not meant to replace the generic collections, but to simply be an alternative to creating your own locking mechanisms. Among those concurrent collections were the ConcurrentStack<T> and ConcurrentQueue<T> which provide classic LIFO and FIFO collections with a concurrent twist.  As we saw, some of the traditional methods that required calls to be made in a certain order (like checking for not IsEmpty before calling Pop()) were replaced in favor of an umbrella operation that combined both under one lock (like TryPop()). Now, let's take a look at the next in our series of concurrent collections!For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here. ConcurrentDictionary – the fully thread-safe dictionary The ConcurrentDictionary<TKey,TValue> is the thread-safe counterpart to the generic Dictionary<TKey, TValue> collection.  Obviously, both are designed for quick – O(1) – lookups of data based on a key.  If you think of algorithms where you need lightning fast lookups of data and don’t care whether the data is maintained in any particular ordering or not, the unsorted dictionaries are generally the best way to go. Note: as a side note, there are sorted implementations of IDictionary, namely SortedDictionary and SortedList which are stored as an ordered tree and a ordered list respectively.  While these are not as fast as the non-sorted dictionaries – they are O(log2 n) – they are a great combination of both speed and ordering -- and still greatly outperform a linear search. Now, once again keep in mind that if all you need to do is load a collection once and then allow multi-threaded reading you do not need any locking.  Examples of this tend to be situations where you load a lookup or translation table once at program start, then keep it in memory for read-only reference.  In such cases locking is completely non-productive. However, most of the time when we need a concurrent dictionary we are interleaving both reads and updates.  This is where the ConcurrentDictionary really shines!  It achieves its thread-safety with no common lock to improve efficiency.  It actually uses a series of locks to provide concurrent updates, and has lockless reads!  This means that the ConcurrentDictionary gets even more efficient the higher the ratio of reads-to-writes you have. ConcurrentDictionary and Dictionary differences For the most part, the ConcurrentDictionary<TKey,TValue> behaves like it’s Dictionary<TKey,TValue> counterpart with a few differences.  Some notable examples of which are: Add() does not exist in the concurrent dictionary. This means you must use TryAdd(), AddOrUpdate(), or GetOrAdd().  It also means that you can’t use a collection initializer with the concurrent dictionary. TryAdd() replaced Add() to attempt atomic, safe adds. Because Add() only succeeds if the item doesn’t already exist, we need an atomic operation to check if the item exists, and if not add it while still under an atomic lock. TryUpdate() was added to attempt atomic, safe updates. If we want to update an item, we must make sure it exists first and that the original value is what we expected it to be.  If all these are true, we can update the item under one atomic step. TryRemove() was added to attempt atomic, safe removes. To safely attempt to remove a value we need to see if the key exists first, this checks for existence and removes under an atomic lock. AddOrUpdate() was added to attempt an thread-safe “upsert”. There are many times where you want to insert into a dictionary if the key doesn’t exist, or update the value if it does.  This allows you to make a thread-safe add-or-update. GetOrAdd() was added to attempt an thread-safe query/insert. Sometimes, you want to query for whether an item exists in the cache, and if it doesn’t insert a starting value for it.  This allows you to get the value if it exists and insert if not. Count, Keys, Values properties take a snapshot of the dictionary. Accessing these properties may interfere with add and update performance and should be used with caution. ToArray() returns a static snapshot of the dictionary. That is, the dictionary is locked, and then copied to an array as a O(n) operation.  GetEnumerator() is thread-safe and efficient, but allows dirty reads. Because reads require no locking, you can safely iterate over the contents of the dictionary.  The only downside is that, depending on timing, you may get dirty reads. Dirty reads during iteration The last point on GetEnumerator() bears some explanation.  Picture a scenario in which you call GetEnumerator() (or iterate using a foreach, etc.) and then, during that iteration the dictionary gets updated.  This may not sound like a big deal, but it can lead to inconsistent results if used incorrectly.  The problem is that items you already iterated over that are updated a split second after don’t show the update, but items that you iterate over that were updated a split second before do show the update.  Thus you may get a combination of items that are “stale” because you iterated before the update, and “fresh” because they were updated after GetEnumerator() but before the iteration reached them. Let’s illustrate with an example, let’s say you load up a concurrent dictionary like this: 1: // load up a dictionary. 2: var dictionary = new ConcurrentDictionary<string, int>(); 3:  4: dictionary["A"] = 1; 5: dictionary["B"] = 2; 6: dictionary["C"] = 3; 7: dictionary["D"] = 4; 8: dictionary["E"] = 5; 9: dictionary["F"] = 6; Then you have one task (using the wonderful TPL!) to iterate using dirty reads: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); And one task to attempt updates in a separate thread (probably): 1: // attempt updates in a separate thread 2: var updateTask = new Task(() => 3: { 4: // iterates, and updates the value by one 5: foreach (var pair in dictionary) 6: { 7: dictionary[pair.Key] = pair.Value + 1; 8: } 9: }); Now that we’ve done this, we can fire up both tasks and wait for them to complete: 1: // start both tasks 2: updateTask.Start(); 3: iterationTask.Start(); 4:  5: // wait for both to complete. 6: Task.WaitAll(updateTask, iterationTask); Now, if I you didn’t know about the dirty reads, you may have expected to see the iteration before the updates (such as A:1, B:2, C:3, D:4, E:5, F:6).  However, because the reads are dirty, we will quite possibly get a combination of some updated, some original.  My own run netted this result: 1: F:6 2: E:6 3: D:5 4: C:4 5: B:3 6: A:2 Note that, of course, iteration is not in order because ConcurrentDictionary, like Dictionary, is unordered.  Also note that both E and F show the value 6.  This is because the output task reached F before the update, but the updates for the rest of the items occurred before their output (probably because console output is very slow, comparatively). If we want to always guarantee that we will get a consistent snapshot to iterate over (that is, at the point we ask for it we see precisely what is in the dictionary and no subsequent updates during iteration), we should iterate over a call to ToArray() instead: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary.ToArray()) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); The atomic Try…() methods As you can imagine TryAdd() and TryRemove() have few surprises.  Both first check the existence of the item to determine if it can be added or removed based on whether or not the key currently exists in the dictionary: 1: // try add attempts an add and returns false if it already exists 2: if (dictionary.TryAdd("G", 7)) 3: Console.WriteLine("G did not exist, now inserted with 7"); 4: else 5: Console.WriteLine("G already existed, insert failed."); TryRemove() also has the virtue of returning the value portion of the removed entry matching the given key: 1: // attempt to remove the value, if it exists it is removed and the original is returned 2: int removedValue; 3: if (dictionary.TryRemove("C", out removedValue)) 4: Console.WriteLine("Removed C and its value was " + removedValue); 5: else 6: Console.WriteLine("C did not exist, remove failed."); Now TryUpdate() is an interesting creature.  You might think from it’s name that TryUpdate() first checks for an item’s existence, and then updates if the item exists, otherwise it returns false.  Well, note quite... It turns out when you call TryUpdate() on a concurrent dictionary, you pass it not only the new value you want it to have, but also the value you expected it to have before the update.  If the item exists in the dictionary, and it has the value you expected, it will update it to the new value atomically and return true.  If the item is not in the dictionary or does not have the value you expected, it is not modified and false is returned. 1: // attempt to update the value, if it exists and if it has the expected original value 2: if (dictionary.TryUpdate("G", 42, 7)) 3: Console.WriteLine("G existed and was 7, now it's 42."); 4: else 5: Console.WriteLine("G either didn't exist, or wasn't 7."); The composite Add methods The ConcurrentDictionary also has composite add methods that can be used to perform updates and gets, with an add if the item is not existing at the time of the update or get. The first of these, AddOrUpdate(), allows you to add a new item to the dictionary if it doesn’t exist, or update the existing item if it does.  For example, let’s say you are creating a dictionary of counts of stock ticker symbols you’ve subscribed to from a market data feed: 1: public sealed class SubscriptionManager 2: { 3: private readonly ConcurrentDictionary<string, int> _subscriptions = new ConcurrentDictionary<string, int>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public void AddSubscription(string tickerKey) 7: { 8: // add a new subscription with count of 1, or update existing count by 1 if exists 9: var resultCount = _subscriptions.AddOrUpdate(tickerKey, 1, (symbol, count) => count + 1); 10:  11: // now check the result to see if we just incremented the count, or inserted first count 12: if (resultCount == 1) 13: { 14: // subscribe to symbol... 15: } 16: } 17: } Notice the update value factory Func delegate.  If the key does not exist in the dictionary, the add value is used (in this case 1 representing the first subscription for this symbol), but if the key already exists, it passes the key and current value to the update delegate which computes the new value to be stored in the dictionary.  The return result of this operation is the value used (in our case: 1 if added, existing value + 1 if updated). Likewise, the GetOrAdd() allows you to attempt to retrieve a value from the dictionary, and if the value does not currently exist in the dictionary it will insert a value.  This can be handy in cases where perhaps you wish to cache data, and thus you would query the cache to see if the item exists, and if it doesn’t you would put the item into the cache for the first time: 1: public sealed class PriceCache 2: { 3: private readonly ConcurrentDictionary<string, double> _cache = new ConcurrentDictionary<string, double>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public double QueryPrice(string tickerKey) 7: { 8: // check for the price in the cache, if it doesn't exist it will call the delegate to create value. 9: return _cache.GetOrAdd(tickerKey, symbol => GetCurrentPrice(symbol)); 10: } 11:  12: private double GetCurrentPrice(string tickerKey) 13: { 14: // do code to calculate actual true price. 15: } 16: } There are other variations of these two methods which vary whether a value is provided or a factory delegate, but otherwise they work much the same. Oddities with the composite Add methods The AddOrUpdate() and GetOrAdd() methods are totally thread-safe, on this you may rely, but they are not atomic.  It is important to note that the methods that use delegates execute those delegates outside of the lock.  This was done intentionally so that a user delegate (of which the ConcurrentDictionary has no control of course) does not take too long and lock out other threads. This is not necessarily an issue, per se, but it is something you must consider in your design.  The main thing to consider is that your delegate may get called to generate an item, but that item may not be the one returned!  Consider this scenario: A calls GetOrAdd and sees that the key does not currently exist, so it calls the delegate.  Now thread B also calls GetOrAdd and also sees that the key does not currently exist, and for whatever reason in this race condition it’s delegate completes first and it adds its new value to the dictionary.  Now A is done and goes to get the lock, and now sees that the item now exists.  In this case even though it called the delegate to create the item, it will pitch it because an item arrived between the time it attempted to create one and it attempted to add it. Let’s illustrate, assume this totally contrived example program which has a dictionary of char to int.  And in this dictionary we want to store a char and it’s ordinal (that is, A = 1, B = 2, etc).  So for our value generator, we will simply increment the previous value in a thread-safe way (perhaps using Interlocked): 1: public static class Program 2: { 3: private static int _nextNumber = 0; 4:  5: // the holder of the char to ordinal 6: private static ConcurrentDictionary<char, int> _dictionary 7: = new ConcurrentDictionary<char, int>(); 8:  9: // get the next id value 10: public static int NextId 11: { 12: get { return Interlocked.Increment(ref _nextNumber); } 13: } Then, we add a method that will perform our insert: 1: public static void Inserter() 2: { 3: for (int i = 0; i < 26; i++) 4: { 5: _dictionary.GetOrAdd((char)('A' + i), key => NextId); 6: } 7: } Finally, we run our test by starting two tasks to do this work and get the results… 1: public static void Main() 2: { 3: // 3 tasks attempting to get/insert 4: var tasks = new List<Task> 5: { 6: new Task(Inserter), 7: new Task(Inserter) 8: }; 9:  10: tasks.ForEach(t => t.Start()); 11: Task.WaitAll(tasks.ToArray()); 12:  13: foreach (var pair in _dictionary.OrderBy(p => p.Key)) 14: { 15: Console.WriteLine(pair.Key + ":" + pair.Value); 16: } 17: } If you run this with only one task, you get the expected A:1, B:2, ..., Z:26.  But running this in parallel you will get something a bit more complex.  My run netted these results: 1: A:1 2: B:3 3: C:4 4: D:5 5: E:6 6: F:7 7: G:8 8: H:9 9: I:10 10: J:11 11: K:12 12: L:13 13: M:14 14: N:15 15: O:16 16: P:17 17: Q:18 18: R:19 19: S:20 20: T:21 21: U:22 22: V:23 23: W:24 24: X:25 25: Y:26 26: Z:27 Notice that B is 3?  This is most likely because both threads attempted to call GetOrAdd() at roughly the same time and both saw that B did not exist, thus they both called the generator and one thread got back 2 and the other got back 3.  However, only one of those threads can get the lock at a time for the actual insert, and thus the one that generated the 3 won and the 3 was inserted and the 2 got discarded.  This is why on these methods your factory delegates should be careful not to have any logic that would be unsafe if the value they generate will be pitched in favor of another item generated at roughly the same time.  As such, it is probably a good idea to keep those generators as stateless as possible. Summary The ConcurrentDictionary is a very efficient and thread-safe version of the Dictionary generic collection.  It has all the benefits of type-safety that it’s generic collection counterpart does, and in addition is extremely efficient especially when there are more reads than writes concurrently. Tweet Technorati Tags: C#, .NET, Concurrent Collections, Collections, Little Wonders, Black Rabbit Coder,James Michael Hare

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  • CVE-2010-1634 Integer Overflow vulnerability in Python

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2010-1634 Integer Overflow vulnerability 5.0 Python Solaris 10 SPARC: 143506-03 X86: 143507-03 Solaris 11 Contact Support This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • Even More Storage Options in VDI 3.4.1

    - by mprove
    Oracle Virtual Desktop Infrastructure 3.4.1 has been released to complete the storage matrix below. Storage Type VirtualBox on Solaris VirtualBox on Enterprise Linux Sun ZFS yes yes Sun ZFS (pool on Solaris) yes yes iSCSI - new in VDI 3.4 Network File System new in VDI 3.4.1 new in VDI 3.4 Local Storage new in VDI 3.4.1 new in VDI 3.4

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  • CVE-2011-2895 Buffer Overflow vulnerability in X.Org

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2011-2895 Buffer Overflow vulnerability 9.3 X.Org Solaris 10 SPARC: 125719-41 119059-60 X86: 119060-59 125720-51 Solaris 9 Contact Support Solaris 8 Contact Support This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • CVE-2004-1010 Buffer Overflow vulnerability in Zip utility

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2004-1010 Buffer Overflow vulnerability 10.0 Zip Solaris 10 SPARC: 147378-01 X86: 147379-01 Solaris 9 Contact Support This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • CVE-2011-4313 Denial of Service Vulnerability in BIND Domain Name Server

    - by chandan
    CVE DescriptionCVSSv2 Base ScoreComponentProduct and Resolution CVE-2011-4313 Denial of Service vulnerability 5 BIND DNS software Solaris 11 Contact support Solaris 10 SPARC: IDR148282-01 X86: IDR148283-01 Solaris 8 SPARC: IDR148278-01 X86: IDR148279-01 Solaris 9 SPARC: IDR148280-01 X86: IDR148281-01 This notification describes vulnerabilities fixed in third-party components that are included in Sun's product distribution.Information about vulnerabilities affecting Oracle Sun products can be found on Oracle Critical Patch Updates and Security Alerts page.

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  • Viewing at Impossible Angles

    - by kemer
    The picture of the little screwdriver with the Allen wrench head to the right is bound to invoke a little nostalgia for those readers who were Sun customers in the late 80s. This tool was a very popular give-away: it was essential for installing and removing Multibus (you youngsters will have to look that up on Wikipedia…) cards in our systems. Back then our mid-sized systems were gargantuan: it was routine for us to schlep around a 200 lb. desk side box and 90 lb. monitor to demo a piece of software your smart phone will run better today. We were very close to the hardware, and the first thing a new field sales systems engineer had to learn was how put together a system. If you were lucky, a grizzled service engineer might run you through the process once, then threaten your health and existence should you ever screw it up so that he had to fix it. Nowadays we make it much easier to learn the ins and outs of our hardware with simulations–3D animations–that take you through the process of putting together or replacing pieces of a system. Most recently, we have posted three sophisticated PDFs that take advantage of Acrobat 9 features to provide a really intelligent approach to documenting hardware installation and repair: Sun Fire X4800/X4800 M2 Animations for Chassis Components Sun Fire X4800/X4800 M2 Animations for Sub Assembly Module (SAM) Sun Fire X4800/X4800 M2 Animations for CMOD Download one of these documents and take a close look at it. You can view the hardware from any angle, including impossible ones. Each document has a number of procedures, that break down into steps. Click on a procedure, then a step and you will see it animated in the drawing. Of course hardware design has generally eliminated the need for things like our old giveaway tools: components snap and lock in. Often you can replace redundant units while the system is hot, but for heaven’s sake, you’ll want to verify that you can do that before you try it! Meanwhile, we can all look forward to a growing portfolio of these intelligent documents. We would love to hear what you think about them. –Kemer

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