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  • Unit Testing Interfaces in Python

    - by Nicholas Mancuso
    I am currently learning python in preperation for a class over the summer and have gotten started by implementing different types of heaps and priority based data structures. I began to write a unit test suite for the project but ran into difficulties into creating a generic unit test that only tests the interface and is oblivious of the actual implementation. I am wondering if it is possible to do something like this.. suite = HeapTestSuite(BinaryHeap()) suite.run() suite = HeapTestSuite(BinomialHeap()) suite.run() What I am currently doing just feels... wrong (multiple inheritance? ACK!).. class TestHeap: def reset_heap(self): self.heap = None def test_insert(self): self.reset_heap() #test that insert doesnt throw an exception... for x in self.inseq: self.heap.insert(x) def test_delete(self): #assert we get the first value we put in self.reset_heap() self.heap.insert(5) self.assertEquals(5, self.heap.delete_min()) #harder test. put in sequence in and check that it comes out right self.reset_heap() for x in self.inseq: self.heap.insert(x) for x in xrange(len(self.inseq)): val = self.heap.delete_min() self.assertEquals(val, x) class BinaryHeapTest(TestHeap, unittest.TestCase): def setUp(self): self.inseq = range(99, -1, -1) self.heap = BinaryHeap() def reset_heap(self): self.heap = BinaryHeap() class BinomialHeapTest(TestHeap, unittest.TestCase): def setUp(self): self.inseq = range(99, -1, -1) self.heap = BinomialHeap() def reset_heap(self): self.heap = BinomialHeap() if __name__ == '__main__': unittest.main()

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  • which sql consumes less memory

    - by prmatta
    Yesterday I asked a question on how to re-write sql to do selects and inserts in batches. I needed to do this to try and consume less virtual memory, since I need to move millions of rows here. The object is to move rows from Table B into Table A. Here are the ways I can think of doing this: SQL #1) INSERT INTO A (x, y, z) SELECT x, y, z FROM B b WHERE ... SQL #2) FOREACH SELECT x,y,z FROM B b WHERE ... INSERT INTO A(x,y,z); END FOREACH; SQL #3) FOREACH SELECT FIRST 2000 x,y,z FROM B b WHERE ... INSERT INTO A(x,y,z); END FOREACH; SQL #4) FOREACH SELECT FIRST 2000 x,y,z FROM B b WHERE ... AND NOT EXISTS IN (SELECT * FROM A) INSERT INTO A(x,y,z); END FOREACH; Are any of the above incorrect? The database is informix 11.5.

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  • What does the destructor do silently?

    - by zhanwu
    Considering the following code which looks like that the destructor doesn't do any real job, valgrind showed me clearly that it has memory leak without using the destructor. Any body can explain me what does the destructor do in this case? #include <iostream> using namespace std; class A { private: int value; A* follower; public: A(int); ~A(); void insert(int); }; A::A(int n) { value = n; follower = NULL; } A::~A() { if (follower != NULL) delete follower; cout << "do nothing!" << endl; } void A::insert(int n) { if (this->follower == NULL) { A* f = new A(n); this->follower = f; } else this->follower->insert(n); } int main(int argc, char* argv[]) { A* objectA = new A(1); int i; for (i = 0; i < 10; i++) objectA->insert(i); delete objectA; }

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  • In Lua, can I easily select the Nth result without custom functions?

    - by romkyns
    Suppose I am inserting a string into a table as follows: table.insert(tbl, mystring) and that mystring is generated by replacing all occurrences of "a" with "b" in input: mystring = string.gsub(input, "a", "b") The obvious way to combine the two into one statement doesn't work, because gsub returns two results: table.insert(tbl, string.gsub(input, "a", "b")) -- error! -- (second result of gsub is passed into table.insert) which, I suppose, is the price paid for supporting multiple return values. The question is, is there a standard, built-in way to select just the first return value? When I found select I thought that was exactly what it did, but alas, it actually selects all results from N onwards, and so doesn't help in this scenario. Now I know I can define my own select as follows: function select1(n, ...) return arg[n] end table.insert(tbl, select1(1, string.gsub(input, "a", "b"))) but this doesn't look right, since I'd expect a built-in way of doing this. So, am I missing some built-in construct? If not, do Lua developers tend to use a separate variable to extract the correct argument or write their own select1 functions?

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  • Mysql dropping inserts with triggers

    - by user2891127
    Using mysql 5.5. I have two tables. One has a whitelist of hashes. When I insert a new row into the other table, I want to first compare the hash in the insert statement to the whitelist. If it's in the whitelist, I don't want to do the insert (less data to plow through later). The inserts are generated from another program and are text files with sql statements. I've been playing with triggers, and almost have it working: BEGIN IF (select count(md5hash) from whitelist where md5hash=new.md5hash) 0 THEN SIGNAL SQLSTATE '45000' SET MESSAGE_TEXT = 'Already Whitelisted'; END IF; END But there's a problem. The Signal throwing up the error stops the import. I want to skip that line, not stop the whole import. Some searching didn't find any way to silently skip the import. My next idea was to create a duplicate table definition, and redirect the insert to that dup table. But the old and new don't seem to apply to table names. Other then adding an ignore column to my table then doing a mass drop based on that column after the import, is there any way to achieve my goal?

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  • Pair equal operator overloading for inserting into set

    - by Petwoip
    I am trying to add a pair<int,int> to a set. If a pair shares the same two values as another in the set, it should not be inserted. Here's my non-working code: typedef std::pair<int, int> PairInt; template<> bool std::operator==(const PairInt& l, const PairInt& r) { return (l.first == r.first && l.second == r.second) || (l.first == r.second && l.second == r.first); } int main() { std::set<PairInt> intSet; intSet.insert(PairInt(1,3)); intSet.insert(PairInt(1,4)); intSet.insert(PairInt(1,4)); intSet.insert(PairInt(4,1)); } At the moment, the (4,1) pair gets added even though there is already a (1,4) pair. The final contents of the set are: (1 3) (1 4) (4 1) and I want it to be (1 3) (1 4) I've tried putting breakpoints in the overloaded method, but they never get reached. What have I done wrong?

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  • What does Postgres do when BEGIN is run on a connection in autocommit mode?

    - by DNS
    I'm trying to better understand the concept of 'autocommit' when working with a Postgres (psycopg) connection. Let's say I have a fresh connection, set its isolation level to ISOLATION_LEVEL_AUTOCOMMIT, then run this SQL directly, without using the cursor begin/rollback methods (as an exercise; not saying I actually want to do this): INSERT A INSERT B BEGIN INSERT C INSERT D ROLLBACK What happens to INSERTs C & D? Is autocommit is purely an internal setting in psycopg that affects how it issues BEGINs? In that case, the above SQL is unafected; INSERTs A & B are committed as soon as they're done, while C & D are run in a transaction and rolled back. What isolation level is that transaction run under? Or is autocommit a real setting on the connection itself? In that case, how does it affect the handling of BEGIN? Is it ignored, or does it override the autocommit setting to actually start a transaction? What isolation level is that transaction run under? Or am I completely off-target?

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  • Stored Procedure, 'incorrect syntax error'

    - by jacksonSD
    Attempting to figure out sp's, and I'm getting this error: "Msg 156, Level 15, State 1, Line 5 Incorrect syntax near the keyword 'Procedure'." the error seems to be on the if, but I can drop other existing tables with stored procedures the exact same way so I'm not clear on why this isn't working. can anyone shed some light? Begin Set nocount on Begin Try Create Procedure uspRecycle as if OBJECT_ID('Recycle') is not null Drop Table Recycle create table Recycle (RecycleID integer constraint PK_integer primary key, RecycleType nchar(10) not null, RecycleDescription nvarchar(100) null) insert into Recycle (RecycleID,RecycleType,RecycleDescription) values ('1','Compost','Product is compostable, instructions included in packaging') insert into Recycle (RecycleID,RecycleType,RecycleDescription) values ('2','Return','Product is returnable to company for 100% reuse') insert into Recycle (RecycleID,RecycleType,RecycleDescription) values ('3','Scrap','Product is returnable and will be reclaimed and reprocessed') insert into Recycle (RecycleID,RecycleType,RecycleDescription) values ('4','None','Product is not recycleable') End Try Begin Catch DECLARE @ErrMsg nvarchar(4000); SELECT @ErrMsg = ERROR_MESSAGE(); Throw 50001, @ErrMsg, 1; End Catch -- checking to see if table exists and is loaded: If (Select count(*) from Recycle) >1 begin Print 'Recycle table created and loaded '; Print getdate() End set nocount off End

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  • Parallel features in .Net 4.0

    - by Jonathan.Peppers
    I have been going over the practicality of some of the new parallel features in .Net 4.0. Say I have code like so: foreach (var item in myEnumerable) myDatabase.Insert(item.ConvertToDatabase()); Imagine myDatabase.Insert is performing some work to insert to a SQL database. Theoretically you could write: Parallel.ForEach(myEnumerable, item => myDatabase.Insert(item.ConvertToDatabase())); And automatically you get code that takes advantage of multiple cores. But what if myEnumerable can only be interacted with by a single thread? Will the Parallel class enumerate by a single thread and only dispatch the result to worker threads in the loop? What if myDatabase can only be interacted with by a single thread? It would certainly not be better to make a database connection per iteration of the loop. Finally, what if my "var item" happens to be a UserControl or something that must be interacted with on the UI thread? What design pattern should I follow to solve these problems? It's looking to me that switching over to Parallel/PLinq/etc is not exactly easy when you are dealing with real-world applications.

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  • SQL SERVER – How to Recover SQL Database Data Deleted by Accident

    - by Pinal Dave
    In Repair a SQL Server database using a transaction log explorer, I showed how to use ApexSQL Log, a SQL Server transaction log viewer, to recover a SQL Server database after a disaster. In this blog, I’ll show you how to use another SQL Server disaster recovery tool from ApexSQL in a situation when data is accidentally deleted. You can download ApexSQL Recover here, install, and play along. With a good SQL Server disaster recovery strategy, data recovery is not a problem. You have a reliable full database backup with valid data, a full database backup and subsequent differential database backups, or a full database backup and a chain of transaction log backups. But not all situations are ideal. Here we’ll address some sub-optimal scenarios, where you can still successfully recover data. If you have only a full database backup This is the least optimal SQL Server disaster recovery strategy, as it doesn’t ensure minimal data loss. For example, data was deleted on Wednesday. Your last full database backup was created on Sunday, three days before the records were deleted. By using the full database backup created on Sunday, you will be able to recover SQL database records that existed in the table on Sunday. If there were any records inserted into the table on Monday or Tuesday, they will be lost forever. The same goes for records modified in this period. This method will not bring back modified records, only the old records that existed on Sunday. If you restore this full database backup, all your changes (intentional and accidental) will be lost and the database will be reverted to the state it had on Sunday. What you have to do is compare the records that were in the table on Sunday to the records on Wednesday, create a synchronization script, and execute it against the Wednesday database. If you have a full database backup followed by differential database backups Let’s say the situation is the same as in the example above, only you create a differential database backup every night. Use the full database backup created on Sunday, and the last differential database backup (created on Tuesday). In this scenario, you will lose only the data inserted and updated after the differential backup created on Tuesday. If you have a full database backup and a chain of transaction log backups This is the SQL Server disaster recovery strategy that provides minimal data loss. With a full chain of transaction logs, you can recover the SQL database to an exact point in time. To provide optimal results, you have to know exactly when the records were deleted, because restoring to a later point will not bring back the records. This method requires restoring the full database backup first. If you have any differential log backup created after the last full database backup, restore the most recent one. Then, restore transaction log backups, one by one, it the order they were created starting with the first created after the restored differential database backup. Now, the table will be in the state before the records were deleted. You have to identify the deleted records, script them and run the script against the original database. Although this method is reliable, it is time-consuming and requires a lot of space on disk. How to easily recover deleted records? The following solution enables you to recover SQL database records even if you have no full or differential database backups and no transaction log backups. To understand how ApexSQL Recover works, I’ll explain what happens when table data is deleted. Table data is stored in data pages. When you delete table records, they are not immediately deleted from the data pages, but marked to be overwritten by new records. Such records are not shown as existing anymore, but ApexSQL Recover can read them and create undo script for them. How long will deleted records stay in the MDF file? It depends on many factors, as time passes it’s less likely that the records will not be overwritten. The more transactions occur after the deletion, the more chances the records will be overwritten and permanently lost. Therefore, it’s recommended to create a copy of the database MDF and LDF files immediately (if you cannot take your database offline until the issue is solved) and run ApexSQL Recover on them. Note that a full database backup will not help here, as the records marked for overwriting are not included in the backup. First, I’ll delete some records from the Person.EmailAddress table in the AdventureWorks database.   I can delete these records in SQL Server Management Studio, or execute a script such as DELETE FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 Then, I’ll start ApexSQL Recover and select From DELETE operation in the Recovery tab.   In the Select the database to recover step, first select the SQL Server instance. If it’s not shown in the drop-down list, click the Server icon right to the Server drop-down list and browse for the SQL Server instance, or type the instance name manually. Specify the authentication type and select the database in the Database drop-down list.   In the next step, you’re prompted to add additional data sources. As this can be a tricky step, especially for new users, ApexSQL Recover offers help via the Help me decide option.   The Help me decide option guides you through a series of questions about the database transaction log and advises what files to add. If you know that you have no transaction log backups or detached transaction logs, or the online transaction log file has been truncated after the data was deleted, select No additional transaction logs are available. If you know that you have transaction log backups that contain the delete transactions you want to recover, click Add transaction logs. The online transaction log is listed and selected automatically.   Click Add if to add transaction log backups. It would be best if you have a full transaction log chain, as explained above. The next step for this option is to specify the time range.   Selecting a small time range for the time of deletion will create the recovery script just for the accidentally deleted records. A wide time range might script the records deleted on purpose, and you don’t want that. If needed, you can check the script generated and manually remove such records. After that, for all data sources options, the next step is to select the tables. Be careful here, if you deleted some data from other tables on purpose, and don’t want to recover them, don’t select all tables, as ApexSQL Recover will create the INSERT script for them too.   The next step offers two options: to create a recovery script that will insert the deleted records back into the Person.EmailAddress table, or to create a new database, create the Person.EmailAddress table in it, and insert the deleted records. I’ll select the first one.   The recovery process is completed and 11 records are found and scripted, as expected.   To see the script, click View script. ApexSQL Recover has its own script editor, where you can review, modify, and execute the recovery script. The insert into statements look like: INSERT INTO Person.EmailAddress( BusinessEntityID, EmailAddressID, EmailAddress, rowguid, ModifiedDate) VALUES( 70, 70, N'[email protected]' COLLATE SQL_Latin1_General_CP1_CI_AS, 'd62c5b4e-c91f-403f-b630-7b7e0fda70ce', '20030109 00:00:00.000' ); To execute the script, click Execute in the menu.   If you want to check whether the records are really back, execute SELECT * FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 As shown, ApexSQL Recover recovers SQL database data after accidental deletes even without the database backup that contains the deleted data and relevant transaction log backups. ApexSQL Recover reads the deleted data from the database data file, so this method can be used even for databases in the Simple recovery model. Besides recovering SQL database records from a DELETE statement, ApexSQL Recover can help when the records are lost due to a DROP TABLE, or TRUNCATE statement, as well as repair a corrupted MDF file that cannot be attached to as SQL Server instance. You can find more information about how to recover SQL database lost data and repair a SQL Server database on ApexSQL Solution center. There are solutions for various situations when data needs to be recovered. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Getting MySQL work with Entity Framework 4.0

    - by DigiMortal
    Does MySQL work with Entity Framework 4.0? The answer is: yes, it works! I just put up one experimental project to play with MySQL and Entity Framework 4.0 and in this posting I will show you how to get MySQL data to EF. Also I will give some suggestions how to deploy your applications to hosting and cloud environments. MySQL stuff As you may guess you need MySQL running somewhere. I have MySQL installed to my development machine so I can also develop stuff when I’m offline. The other thing you need is MySQL Connector for .NET Framework. Currently there is available development version of MySQL Connector/NET 6.3.5 that supports Visual Studio 2010. Before you start download MySQL and Connector/NET: MySQL Community Server Connector/NET 6.3.5 If you are not big fan of phpMyAdmin then you can try out free desktop client for MySQL – HeidiSQL. I am using it and I am really happy with this program. NB! If you just put up MySQL then create also database with couple of table there. To use all features of Entity Framework 4.0 I suggest you to use InnoDB or other engine that has support for foreign keys. Connecting MySQL to Entity Framework 4.0 Now create simple console project using Visual Studio 2010 and go through the following steps. 1. Add new ADO.NET Entity Data Model to your project. For model insert the name that is informative and that you are able later recognize. Now you can choose how you want to create your model. Select “Generate from database” and click OK. 2. Set up database connection Change data connection and select MySQL Database as data source. You may also need to set provider – there is only one choice. Select it if data provider combo shows empty value. Click OK and insert connection information you are asked about. Don’t forget to click test connection button to see if your connection data is okay. If everything works then click OK. 3. Insert context name Now you should see the following dialog. Insert your data model name for application configuration file and click OK. Click next button. 4. Select tables for model Now you can select tables and views your classes are based on. I have small database with events data. Uncheck the checkbox “Include foreign key columns in the model” – it is damn annoying to get them away from model later. Also insert informative and easy to remember name for your model. Click finish button. 5. Define your classes Now it’s time to define your classes. Here you can see what Entity Framework generated for you. Relations were detected automatically – that’s why we needed foreign keys. The names of classes and their members are not nice yet. After some modifications my class model looks like on the following diagram. Note that I removed attendees navigation property from person class. Now my classes look nice and they follow conventions I am using when naming classes and their members. NB! Don’t forget to see properties of classes (properties windows) and modify their set names if set names contain numbers (I changed set name for Entity from Entity1 to Entities). 6. Let’s test! Now let’s write simple testing program to see if MySQL data runs through Entity Framework 4.0 as expected. My program looks for events where I attended. using(var context = new MySqlEntities()) {     var myEvents = from e in context.Events                     from a in e.Attendees                     where a.Person.FirstName == "Gunnar" &&                             a.Person.LastName == "Peipman"                     select e;       Console.WriteLine("My events: ");       foreach(var e in myEvents)     {         Console.WriteLine(e.Title);     } }   Console.ReadKey(); And when I run it I get the result shown on screenshot on right. I checked out from database and these results are correct. At first run connector seems to work slow but this is only the effect of first run. As connector is loaded to memory by Entity Framework it works fast from this point on. Now let’s see what we have to do to get our program work in hosting and cloud environments where MySQL connector is not installed. Deploying application to hosting and cloud environments If your hosting or cloud environment has no MySQL connector installed you have to provide MySQL connector assemblies with your project. Add the following assemblies to your project’s bin folder and include them to your project (otherwise they are not packaged by WebDeploy and Azure tools): MySQL.Data MySQL.Data.Entity MySQL.Web You can also add references to these assemblies and mark references as local so these assemblies are copied to binary folder of your application. If you have references to these assemblies then you don’t have to include them to your project from bin folder. Also add the following block to your application configuration file. <?xml version="1.0" encoding="utf-8"?> <configuration> ...   <system.data>     <DbProviderFactories>         <add              name=”MySQL Data Provider”              invariant=”MySql.Data.MySqlClient”              description=”.Net Framework Data Provider for MySQL”              type=”MySql.Data.MySqlClient.MySqlClientFactory, MySql.Data,                   Version=6.2.0.0, Culture=neutral,                   PublicKeyToken=c5687fc88969c44d”          />     </DbProviderFactories>   </system.data> ... </configuration> Conclusion It was not hard to get MySQL connector installed and MySQL connected to Entity Framework 4.0. To use full power of Entity Framework we used InnoDB engine because it supports foreign keys. It was also easy to query our model. To get our project online we needed some easy modifications to our project and configuration files.

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • Creating A SharePoint Parent/Child List Relationship&ndash; SharePoint 2010 Edition

    - by Mark Rackley
    Hey blog readers… It has been almost 2 years since I posted my most read blog on creating a Parent/Child list relationship in SharePoint 2007: Creating a SharePoint List Parent / Child Relationship - Out of the Box And then a year ago I improved on my method and redid the blog post… still for SharePoint 2007: Creating a SharePoint List Parent/Child Relationship – VIDEO REMIX Since then many of you have been asking me how to get this to work in SharePoint 2010, and frankly I have just not had time to look into it. I wish I could have jumped into this sooner, but have just recently began to look at it. Well.. after all this time I have actually come up with two solutions that work, neither of them are as clean as I’d like them to be, but I wanted to get something in your hands that you can start using today. Hopefully in the coming weeks and months I’ll be able to improve upon this further and give you guys some better options. For the most part, the process is identical to the 2007 process, but you have probably found out that the list view web parts in 2010 behave differently, and getting the Parent ID to your new child form can be a pain in the rear (at least that’s what I’ve discovered). Anyway, like I said, I have found a couple of solutions that work. If you know of a better one, please let us know as it bugs me that this not as eloquent as my 2007 implementation. Getting on the same page First thing I’d recommend is recreating this blog: Creating a SharePoint List Parent/Child Relationship – VIDEO REMIX in SharePoint 2010… There are some vague differences, but it’s basically the same…  Here’s a quick video of me doing this in SP 2010: Creating Lists necessary for this blog post Now that you have the lists created, lets set up the New Time form to use a QueryString variable to populate the Parent ID field: Creating parameters in Child’s new item form to set parent ID Did I talk fast enough through both of those videos? Hopefully by now that stuff is old hat to you, but I wanted to make sure everyone could get on the same page.  Okay… let’s get started. Solution 1 – XSLTListView with Javascript This solution is the more elegant of the two, however it does require the use of a little javascript.  The other solution does not use javascript, but it also doesn’t use the pretty new SP 2010 pop-ups.  I’ll let you decide which you like better. The basic steps of this solution are: Inserted a Related Item View Insert a ContentEditorWebPart Insert script in ContentEditorWebPart that pulls the ID from the Query string and calls the method to insert a new item on the child entry form Hide the toolbar from data view to remove “add new item” link. Again, you don’t HAVE to use a CEWP, you could just put the javascript directly in the page using SPD.  Anyway, here is how I did it: Using Related Item View / JavaScript Here’s the JavaScript I used in my Content Editor Web Part: <script type="text/javascript"> function NewTime() { // Get the Query String values and split them out into the vals array var vals = new Object(); var qs = location.search.substring(1, location.search.length); var args = qs.split("&"); for (var i=0; i < args.length; i++) { var nameVal = args[i].split("="); var temp = unescape(nameVal[1]).split('+'); nameVal[1] = temp.join(' '); vals[nameVal[0]] = nameVal[1]; } var issueID = vals["ID"]; //use this to bring up the pretty pop up NewItem2(event,"http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID=" + issueID); //use this to open a new window //window.location="http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID=" + issueID; } </script> Solution 2 – DataFormWebPart and exact same 2007 Process This solution is a little more of a hack, but it also MUCH more close to the process we did in SP 2007. So, if you don’t mind not having the pretty pop-up and prefer the comforts of what you are used to, you can give this one a try.  The basics steps are: Insert a DataFormWebPart instead of the List Data View Create a Parameter on DataFormWebPart to store “ID” Query String Variable Filter DataFormWebPart using Parameter Insert a link at bottom of DataForm Web part that points to the Child’s new item form and passes in the Parent Id using the Parameter. See.. like I told you, exact same process as in 2007 (except using the DataFormWeb Part). The DataFormWebPart also requires a lot more work to make it look “pretty” but it’s just table rows and cells, and can be configured pretty painlessly.  Here is that video: Using DataForm Web Part One quick update… if you change the link in this solution from: <tr> <td><a href="http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID={$IssueIDParam}">Click here to create new item...</a> </td> </tr> to: <tr> <td> <a href="javascript:NewItem2(event,'http://sp2010dev:1234/Lists/Time/NewForm.aspx?IssueID={$IssueIDParam}');">Click here to create new item...</a> </td> </tr> It will open up in the pretty pop up and act the same as solution one… So… both Solutions will now behave the same to the end user. Just depends on which you want to implement. That’s all for now… Remember in both solutions when you have them working, you can make the “IssueID” invisible to users by using the “ms-hidden” class (it’s my previous blog post on the subject up there). That’s basically all there is to it! No pithy or witty closing this time… I am sorry it took me so long to dive into this and I hope your questions are answered. As I become more polished myself I will try to come up with a cleaner solution that will make everyone happy… As always, thanks for taking the time to stop by.

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  • SQL Server Split() Function

    - by HighAltitudeCoder
    Title goes here   Ever wanted a dbo.Split() function, but not had the time to debug it completely?  Let me guess - you are probably working on a stored procedure with 50 or more parameters; two or three of them are parameters of differing types, while the other 47 or so all of the same type (id1, id2, id3, id4, id5...).  Worse, you've found several other similar stored procedures with the ONLY DIFFERENCE being the number of like parameters taped to the end of the parameter list. If this is the situation you find yourself in now, you may be wondering, "why am I working with three different copies of what is basically the same stored procedure, and why am I having to maintain changes in three different places?  Can't I have one stored procedure that accomplishes the job of all three? My answer to you: YES!  Here is the Split() function I've created.    /******************************************************************************                                       Split.sql   ******************************************************************************/ /******************************************************************************   Split a delimited string into sub-components and return them as a table.   Parameter 1: Input string which is to be split into parts. Parameter 2: Delimiter which determines the split points in input string. Works with space or spaces as delimiter. Split() is apostrophe-safe.   SYNTAX: SELECT * FROM Split('Dvorak,Debussy,Chopin,Holst', ',') SELECT * FROM Split('Denver|Seattle|San Diego|New York', '|') SELECT * FROM Split('Denver is the super-awesomest city of them all.', ' ')   ******************************************************************************/ USE AdventureWorks GO   IF EXISTS       (SELECT *       FROM sysobjects       WHERE xtype = 'TF'       AND name = 'Split'       ) BEGIN       DROP FUNCTION Split END GO   CREATE FUNCTION Split (       @InputString                  VARCHAR(8000),       @Delimiter                    VARCHAR(50) )   RETURNS @Items TABLE (       Item                          VARCHAR(8000) )   AS BEGIN       IF @Delimiter = ' '       BEGIN             SET @Delimiter = ','             SET @InputString = REPLACE(@InputString, ' ', @Delimiter)       END         IF (@Delimiter IS NULL OR @Delimiter = '')             SET @Delimiter = ','   --INSERT INTO @Items VALUES (@Delimiter) -- Diagnostic --INSERT INTO @Items VALUES (@InputString) -- Diagnostic         DECLARE @Item                 VARCHAR(8000)       DECLARE @ItemList       VARCHAR(8000)       DECLARE @DelimIndex     INT         SET @ItemList = @InputString       SET @DelimIndex = CHARINDEX(@Delimiter, @ItemList, 0)       WHILE (@DelimIndex != 0)       BEGIN             SET @Item = SUBSTRING(@ItemList, 0, @DelimIndex)             INSERT INTO @Items VALUES (@Item)               -- Set @ItemList = @ItemList minus one less item             SET @ItemList = SUBSTRING(@ItemList, @DelimIndex+1, LEN(@ItemList)-@DelimIndex)             SET @DelimIndex = CHARINDEX(@Delimiter, @ItemList, 0)       END -- End WHILE         IF @Item IS NOT NULL -- At least one delimiter was encountered in @InputString       BEGIN             SET @Item = @ItemList             INSERT INTO @Items VALUES (@Item)       END         -- No delimiters were encountered in @InputString, so just return @InputString       ELSE INSERT INTO @Items VALUES (@InputString)         RETURN   END -- End Function GO   ---- Set Permissions --GRANT SELECT ON Split TO UserRole1 --GRANT SELECT ON Split TO UserRole2 --GO   The syntax is basically as follows: SELECT <fields> FROM Table 1 JOIN Table 2 ON ... JOIN Table 3 ON ... WHERE LOGICAL CONDITION A AND LOGICAL CONDITION B AND LOGICAL CONDITION C AND TABLE2.Id IN (SELECT * FROM Split(@IdList, ',')) @IdList is a parameter passed into the stored procedure, and the comma (',') is the delimiter you have chosen to split the parameter list on. You can also use it like this: SELECT <fields> FROM Table 1 JOIN Table 2 ON ... JOIN Table 3 ON ... WHERE LOGICAL CONDITION A AND LOGICAL CONDITION B AND LOGICAL CONDITION C HAVING COUNT(SELECT * FROM Split(@IdList, ',') Similarly, it can be used in other aggregate functions at run-time: SELECT MIN(SELECT * FROM Split(@IdList, ','), <fields> FROM Table 1 JOIN Table 2 ON ... JOIN Table 3 ON ... WHERE LOGICAL CONDITION A AND LOGICAL CONDITION B AND LOGICAL CONDITION C GROUP BY <fields> Now that I've (hopefully effectively) explained the benefits to using this function and implementing it in one or more of your database objects, let me warn you of a caveat that you are likely to encounter.  You may have a team member who waits until the right moment to ask you a pointed question: "Doesn't this function just do the same thing as using the IN function?  Why didn't you just use that instead?  In other words, why bother with this function?" What's happening is, one or more team members has failed to understand the reason for implementing this kind of function in the first place.  (Note: this is THE MOST IMPORTANT ASPECT OF THIS POST). Allow me to outline a few pros to implementing this function, so you may effectively parry this question.  Touche. 1) Code consolidation.  You don't have to maintain what is basically the same code and logic, but with varying numbers of the same parameter in several SQL objects.  I'm not going to go into the cons related to using this function, because the afore mentioned team member is probably more than adept at pointing these out.  Remember, the real positive contribution is ou are decreasing the liklihood that your team fails to update all (x) duplicate copies of what are basically the same stored procedure, and so on...  This is the classic downside to duplicate code.  It is a virus, and you should kill it. You might be better off rejecting your team member's question, and responding with your own: "Would you rather maintain the same logic in multiple different stored procedures, and hope that the team doesn't forget to always update all of them at the same time?".  In his head, he might be thinking "yes, I would like to maintain several different copies of the same stored procedure", although you probably will not get such a direct response.  2) Added flexibility - you can use the Split function elsewhere, and for splitting your data in different ways.  Plus, you can use any kind of delimiter you wish.  How can you know today the ways in which you might want to examine your data tomorrow?  Segue to my next point. 3) Because the function takes a delimiter parameter, you can split the data in any number of ways.  This greatly increases the utility of such a function and enables your team to work with the data in a variety of different ways in the future.  You can split on a single char, symbol, word, or group of words.  You can split on spaces.  (The list goes on... test it out). Finally, you can dynamically define the behavior of a stored procedure (or other SQL object) at run time, through the use of this function.  Rather than have several objects that accomplish almost the same thing, why not have only one instead?

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  • Create Auto Customization Criteria OAF Search Page

    - by PRajkumar
    1. Create a New Workspace and Project Right click Workspaces and click create new OAworkspace and name it as PRajkumarCustSearch. Automatically a new OA Project will also be created. Name the project as CustSearchDemo and package as prajkumar.oracle.apps.fnd.custsearchdemo   2. Create a New Application Module (AM) Right Click on CustSearchDemo > New > ADF Business Components > Application Module Name -- CustSearchAM Package -- prajkumar.oracle.apps.fnd.custsearchdemo.server   3. Enable Passivation for the Root UI Application Module (AM) Right Click on CustSearchAM > Edit SearchAM > Custom Properties > Name – RETENTION_LEVEL Value – MANAGE_STATE Click add > Apply > OK   4. Create Test Table and insert data some data in it (For Testing Purpose)   CREATE TABLE xx_custsearch_demo (   -- ---------------------     -- Data Columns     -- ---------------------     column1                  VARCHAR2(100),     column2                  VARCHAR2(100),     column3                  VARCHAR2(100),     column4                  VARCHAR2(100),     -- ---------------------     -- Who Columns     -- ---------------------     last_update_date    DATE         NOT NULL,     last_updated_by     NUMBER   NOT NULL,     creation_date          DATE         NOT NULL,     created_by               NUMBER   NOT NULL,     last_update_login   NUMBER  );   INSERT INTO xx_custsearch_demo VALUES('v1','v2','v3','v4',SYSDATE,0,SYSDATE,0,0); INSERT INTO xx_custsearch_demo VALUES('v1','v3','v4','v5',SYSDATE,0,SYSDATE,0,0); INSERT INTO xx_custsearch_demo VALUES('v2','v3','v4','v5',SYSDATE,0,SYSDATE,0,0); INSERT INTO xx_custsearch_demo VALUES('v3','v4','v5','v6',SYSDATE,0,SYSDATE,0,0); Now we have 4 records in our custom table   5. Create a New Entity Object (EO) Right click on SearchDemo > New > ADF Business Components > Entity Object Name – CustSearchEO Package -- prajkumar.oracle.apps.fnd.custsearchdemo.schema.server Database Objects -- XX_CUSTSEARCH_DEMO   Note – By default ROWID will be the primary key if we will not make any column to be primary key   Check the Accessors, Create Method, Validation Method and Remove Method   6. Create a New View Object (VO) Right click on CustSearchDemo > New > ADF Business Components > View Object Name -- CustSearchVO Package -- prajkumar.oracle.apps.fnd.custsearchdemo.server   In Step2 in Entity Page select CustSearchEO and shuttle them to selected list   In Step3 in Attributes Window select columns Column1, Column2, Column3, Column4, and shuttle them to selected list   In Java page deselect Generate Java file for View Object Class: CustSearchVOImpl and Select Generate Java File for View Row Class: CustSearchVORowImpl   7. Add Your View Object to Root UI Application Module Select Right click on CustSearchAM > Application Modules > Data Model Select CustSearchVO and shuttle to Data Model list   8. Create a New Page Right click on CustSearchDemo > New > Web Tier > OA Components > Page Name -- CustSearchPG Package -- prajkumar.oracle.apps.fnd.custsearchdemo.webui   9. Select the CustSearchPG and go to the strcuture pane where a default region has been created   10. Select region1 and set the following properties: ID -- PageLayoutRN Region Style -- PageLayout AM Definition -- prajkumar.oracle.apps.fnd.custsearchdemo.server.CustSearchAM Window Title – AutoCustomize Search Page Window Title – AutoCustomization Search Page Auto Footer -- True   11. Add a Query Bean to Your Page Right click on PageLayoutRN > New > Region Select new region region1 and set following properties ID – QueryRN Region Style – query Construction Mode – autoCustomizationCriteria Include Simple Panel – False Include Views Panel – False Include Advanced Panel – False   12. Create a New Region of style table Right Click on QueryRN > New > Region Using Wizard Application Module – prajkumar.oracle.apps.fnd.custsearchdemo.server.CustSearchAM Available View Usages – CustSearchVO1   In Step2 in Region Properties set following properties Region ID – CustSearchTable Region Style – Table   In Step3 in View Attributes shuttle all the items (Column1, Column2, Column3, Column4) available in “Available View Attributes” to Selected View Attributes: In Step4 in Region Items page set style to “messageStyledText” for all items   13. Select CustSearchTable in Structure Panel and set property Width to 100%   14. Include Simple Search Panel Right Click on QueryRN > New > simpleSearchPanel Automatically region2 (header Region) and region1 (MessageComponentLayout Region) created Set Following Properties for region2 Id – SimpleSearchHeader Text -- Simple Search   15. Now right click on message Component Layout Region (SimpleSearchMappings) and create two message text input beans and set the below properties to each   Message TextInputBean1 Id – SearchColumn1 Search Allowed – True Data Type – VARCHAR2 Maximum Length – CSS Class – OraFieldText Prompt – Column1   Message TextInputBean2 Id – SearchColumn2 Search Allowed -- True Data Type – VARCHAR2 Maximum Length – 100 CSS Class – OraFieldText Prompt – Column2   16. Now Right Click on query Components and create simple Search Mappings. Then automatically SimpleSearchMappings and QueryCriteriaMap1 created   17.  Now select the QueryCriteriaMap1 and set the below properties Id – SearchColumn1Map Search Item – SearchColumn1 Result Item – Column1   18. Now again right click on simpleSearchMappings -> New -> queryCriteriaMap, and then set the below properties Id – SearchColumn2Map Search Item – SearchColumn2 Result Item – Column2   19. Congratulation you have successfully finished Auto Customization Search page. Run Your CustSearchPG page and Test Your Work            

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  • Online ALTER TABLE in MySQL 5.6

    - by Marko Mäkelä
    This is the low-level view of data dictionary language (DDL) operations in the InnoDB storage engine in MySQL 5.6. John Russell gave a more high-level view in his blog post April 2012 Labs Release – Online DDL Improvements. MySQL before the InnoDB Plugin Traditionally, the MySQL storage engine interface has taken a minimalistic approach to data definition language. The only natively supported operations were CREATE TABLE, DROP TABLE and RENAME TABLE. Consider the following example: CREATE TABLE t(a INT); INSERT INTO t VALUES (1),(2),(3); CREATE INDEX a ON t(a); DROP TABLE t; The CREATE INDEX statement would be executed roughly as follows: CREATE TABLE temp(a INT, INDEX(a)); INSERT INTO temp SELECT * FROM t; RENAME TABLE t TO temp2; RENAME TABLE temp TO t; DROP TABLE temp2; You could imagine that the database could crash when copying all rows from the original table to the new one. For example, it could run out of file space. Then, on restart, InnoDB would roll back the huge INSERT transaction. To fix things a little, a hack was added to ha_innobase::write_row for committing the transaction every 10,000 rows. Still, it was frustrating that even a simple DROP INDEX would make the table unavailable for modifications for a long time. Fast Index Creation in the InnoDB Plugin of MySQL 5.1 MySQL 5.1 introduced a new interface for CREATE INDEX and DROP INDEX. The old table-copying approach can still be forced by SET old_alter_table=0. This interface is used in MySQL 5.5 and in the InnoDB Plugin for MySQL 5.1. Apart from the ability to do a quick DROP INDEX, the main advantage is that InnoDB will execute a merge-sort algorithm before inserting the index records into each index that is being created. This should speed up the insert into the secondary index B-trees and potentially result in a better B-tree fill factor. The 5.1 ALTER TABLE interface was not perfect. For example, DROP FOREIGN KEY still invoked the table copy. Renaming columns could conflict with InnoDB foreign key constraints. Combining ADD KEY and DROP KEY in ALTER TABLE was problematic and not atomic inside the storage engine. The ALTER TABLE interface in MySQL 5.6 The ALTER TABLE storage engine interface was completely rewritten in MySQL 5.6. Instead of introducing a method call for every conceivable operation, MySQL 5.6 introduced a handful of methods, and data structures that keep track of the requested changes. In MySQL 5.6, online ALTER TABLE operation can be requested by specifying LOCK=NONE. Also LOCK=SHARED and LOCK=EXCLUSIVE are available. The old-style table copying can be requested by ALGORITHM=COPY. That one will require at least LOCK=SHARED. From the InnoDB point of view, anything that is possible with LOCK=EXCLUSIVE is also possible with LOCK=SHARED. Most ALGORITHM=INPLACE operations inside InnoDB can be executed online (LOCK=NONE). InnoDB will always require an exclusive table lock in two phases of the operation. The execution phases are tied to a number of methods: handler::check_if_supported_inplace_alter Checks if the storage engine can perform all requested operations, and if so, what kind of locking is needed. handler::prepare_inplace_alter_table InnoDB uses this method to set up the data dictionary cache for upcoming CREATE INDEX operation. We need stubs for the new indexes, so that we can keep track of changes to the table during online index creation. Also, crash recovery would drop any indexes that were incomplete at the time of the crash. handler::inplace_alter_table In InnoDB, this method is used for creating secondary indexes or for rebuilding the table. This is the ‘main’ phase that can be executed online (with concurrent writes to the table). handler::commit_inplace_alter_table This is where the operation is committed or rolled back. Here, InnoDB would drop any indexes, rename any columns, drop or add foreign keys, and finalize a table rebuild or index creation. It would also discard any logs that were set up for online index creation or table rebuild. The prepare and commit phases require an exclusive lock, blocking all access to the table. If MySQL times out while upgrading the table meta-data lock for the commit phase, it will roll back the ALTER TABLE operation. In MySQL 5.6, data definition language operations are still not fully atomic, because the data dictionary is split. Part of it is inside InnoDB data dictionary tables. Part of the information is only available in the *.frm file, which is not covered by any crash recovery log. But, there is a single commit phase inside the storage engine. Online Secondary Index Creation It may occur that an index needs to be created on a new column to speed up queries. But, it may be unacceptable to block modifications on the table while creating the index. It turns out that it is conceptually not so hard to support online index creation. All we need is some more execution phases: Set up a stub for the index, for logging changes. Scan the table for index records. Sort the index records. Bulk load the index records. Apply the logged changes. Replace the stub with the actual index. Threads that modify the table will log the operations to the logs of each index that is being created. Errors, such as log overflow or uniqueness violations, will only be flagged by the ALTER TABLE thread. The log is conceptually similar to the InnoDB change buffer. The bulk load of index records will bypass record locking. We still generate redo log for writing the index pages. It would suffice to log page allocations only, and to flush the index pages from the buffer pool to the file system upon completion. Native ALTER TABLE Starting with MySQL 5.6, InnoDB supports most ALTER TABLE operations natively. The notable exceptions are changes to the column type, ADD FOREIGN KEY except when foreign_key_checks=0, and changes to tables that contain FULLTEXT indexes. The keyword ALGORITHM=INPLACE is somewhat misleading, because certain operations cannot be performed in-place. For example, changing the ROW_FORMAT of a table requires a rebuild. Online operation (LOCK=NONE) is not allowed in the following cases: when adding an AUTO_INCREMENT column, when the table contains FULLTEXT indexes or a hidden FTS_DOC_ID column, or when there are FOREIGN KEY constraints referring to the table, with ON…CASCADE or ON…SET NULL option. The FOREIGN KEY limitations are needed, because MySQL does not acquire meta-data locks on the child or parent tables when executing SQL statements. Theoretically, InnoDB could support operations like ADD COLUMN and DROP COLUMN in-place, by lazily converting the table to a newer format. This would require that the data dictionary keep multiple versions of the table definition. For simplicity, we will copy the entire table, even for DROP COLUMN. The bulk copying of the table will bypass record locking and undo logging. For facilitating online operation, a temporary log will be associated with the clustered index of table. Threads that modify the table will also write the changes to the log. When altering the table, we skip all records that have been marked for deletion. In this way, we can simply discard any undo log records that were not yet purged from the original table. Off-page columns, or BLOBs, are an important consideration. We suspend the purge of delete-marked records if it would free any off-page columns from the old table. This is because the BLOBs can be needed when applying changes from the log. We have special logging for handling the ROLLBACK of an INSERT that inserted new off-page columns. This is because the columns will be freed at rollback.

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  • Looking into Enum Support in Entity Framework 5.0 Code First

    - by nikolaosk
    In this post I will show you with a hands-on demo the enum support that is available in Visual Studio 2012, .Net Framework 4.5 and Entity Framework 5.0. You can have a look at this post to learn about the support of multilple diagrams per model that exists in Entity Framework 5.0. We will demonstrate this with a step by step example. I will use Visual Studio 2012 Ultimate. You can also use Visual Studio 2012 Express Edition. Before I move on to the actual demo I must say that in EF 5.0 an enumeration can have the following types. Byte Int16 Int32 Int64 Sbyte Obviously I cannot go into much detail on what EF is and what it does. I will give again a short introduction.The .Net framework provides support for Object Relational Mapping through EF. So EF is a an ORM tool and it is now the main data access technology that microsoft works on. I use it quite extensively in my projects. Through EF we have many things out of the box provided for us. We have the automatic generation of SQL code.It maps relational data to strongly types objects.All the changes made to the objects in the memory are persisted in a transactional way back to the data store. You can find in this post an example on how to use the Entity Framework to retrieve data from an SQL Server Database using the "Database/Schema First" approach. In this approach we make all the changes at the database level and then we update the model with those changes. In this post you can see an example on how to use the "Model First" approach when working with ASP.Net and the Entity Framework. This model was firstly introduced in EF version 4.0 and we could start with a blank model and then create a database from that model.When we made changes to the model , we could recreate the database from the new model. You can search in my blog, because I have posted many posts regarding ASP.Net and EF. I assume you have a working knowledge of C# and know a few things about EF. The Code First approach is the more code-centric than the other two. Basically we write POCO classes and then we persist to a database using something called DBContext. Code First relies on DbContext. We create 2,3 classes (e.g Person,Product) with properties and then these classes interact with the DbContext class. We can create a new database based upon our POCOS classes and have tables generated from those classes.We do not have an .edmx file in this approach.By using this approach we can write much easier unit tests. DbContext is a new context class and is smaller,lightweight wrapper for the main context class which is ObjectContext (Schema First and Model First). Let's begin building our sample application. 1) Launch Visual Studio. Create an ASP.Net Empty Web application. Choose an appropriate name for your application. 2) Add a web form, default.aspx page to the application. 3) Now we need to make sure the Entity Framework is included in our project. Go to Solution Explorer, right-click on the project name.Then select Manage NuGet Packages...In the Manage NuGet Packages dialog, select the Online tab and choose the EntityFramework package.Finally click Install. Have a look at the picture below   4) Create a new folder. Name it CodeFirst . 5) Add a new item in your application, a class file. Name it Footballer.cs. This is going to be a simple POCO class.Place it in the CodeFirst folder. The code follows public class Footballer { public int FootballerID { get; set; } public string FirstName { get; set; } public string LastName { get; set; } public double Weight { get; set; } public double Height { get; set; } public DateTime JoinedTheClub { get; set; } public int Age { get; set; } public List<Training> Trainings { get; set; } public FootballPositions Positions { get; set; } }    Now I am going to define my enum values in the same class file, Footballer.cs    public enum FootballPositions    {        Defender,        Midfielder,        Striker    } 6) Now we need to create the Training class. Add a new class to your application and place it in the CodeFirst folder.The code for the class follows.     public class Training     {         public int TrainingID { get; set; }         public int TrainingDuration { get; set; }         public string TrainingLocation { get; set; }     }   7) Then we need to create a context class that inherits from DbContext.Add a new class to the CodeFirst folder.Name it FootballerDBContext.Now that we have the entity classes created, we must let the model know.I will have to use the DbSet<T> property.The code for this class follows       public class FootballerDBContext:DbContext     {         public DbSet<Footballer> Footballers { get; set; }         public DbSet<Training> Trainings { get; set; }     } Do not forget to add  (using System.Data.Entity;) in the beginning of the class file 8) We must take care of the connection string. It is very easy to create one in the web.config.It does not matter that we do not have a database yet.When we run the DbContext and query against it,it will use a connection string in the web.config and will create the database based on the classes. In my case the connection string inside the web.config, looks like this      <connectionStrings>    <add name="CodeFirstDBContext"  connectionString="server=.\SqlExpress;integrated security=true;"  providerName="System.Data.SqlClient"/>                       </connectionStrings>   9) Now it is time to create Linq to Entities queries to retrieve data from the database . Add a new class to your application in the CodeFirst folder.Name the file DALfootballer.cs We will create a simple public method to retrieve the footballers. The code for the class follows public class DALfootballer     {         FootballerDBContext ctx = new FootballerDBContext();         public List<Footballer> GetFootballers()         {             var query = from player in ctx.Footballers where player.FirstName=="Jamie" select player;             return query.ToList();         }     }   10) Place a GridView control on the Default.aspx page and leave the default name.Add an ObjectDataSource control on the Default.aspx page and leave the default name. Set the DatasourceID property of the GridView control to the ID of the ObjectDataSource control.(DataSourceID="ObjectDataSource1" ). Let's configure the ObjectDataSource control. Click on the smart tag item of the ObjectDataSource control and select Configure Data Source. In the Wizzard that pops up select the DALFootballer class and then in the next step choose the GetFootballers() method.Click Finish to complete the steps of the wizzard. Build your application.  11)  Let's create an Insert method in order to insert data into the tables. I will create an Insert() method and for simplicity reasons I will place it in the Default.aspx.cs file. private void Insert()        {            var footballers = new List<Footballer>            {                new Footballer {                                 FirstName = "Steven",LastName="Gerrard", Height=1.85, Weight=85,Age=32, JoinedTheClub=DateTime.Parse("12/12/1999"),Positions=FootballPositions.Midfielder,                Trainings = new List<Training>                             {                                     new Training {TrainingDuration = 3, TrainingLocation="MelWood"},                    new Training {TrainingDuration = 2, TrainingLocation="Anfield"},                    new Training {TrainingDuration = 2, TrainingLocation="MelWood"},                }                            },                            new Footballer {                                  FirstName = "Jamie",LastName="Garragher", Height=1.89, Weight=89,Age=34, JoinedTheClub=DateTime.Parse("12/02/2000"),Positions=FootballPositions.Defender,                Trainings = new List<Training>                                             {                                 new Training {TrainingDuration = 3, TrainingLocation="MelWood"},                new Training {TrainingDuration = 5, TrainingLocation="Anfield"},                new Training {TrainingDuration = 6, TrainingLocation="Anfield"},                }                           }                    };            footballers.ForEach(foot => ctx.Footballers.Add(foot));            ctx.SaveChanges();        }   12) In the Page_Load() event handling routine I called the Insert() method.        protected void Page_Load(object sender, EventArgs e)        {                   Insert();                }  13) Run your application and you will see that the following result,hopefully. You can see clearly that the data is returned along with the enum value.  14) You must have also a look at the database.Launch SSMS and see the database and its objects (data) created from EF Code First.Have a look at the picture below. Hopefully now you have seen the support that exists in EF 5.0 for enums.Hope it helps !!!

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  • MERGE Bug with Filtered Indexes

    - by Paul White
    A MERGE statement can fail, and incorrectly report a unique key violation when: The target table uses a unique filtered index; and No key column of the filtered index is updated; and A column from the filtering condition is updated; and Transient key violations are possible Example Tables Say we have two tables, one that is the target of a MERGE statement, and another that contains updates to be applied to the target.  The target table contains three columns, an integer primary key, a single character alternate key, and a status code column.  A filtered unique index exists on the alternate key, but is only enforced where the status code is ‘a’: CREATE TABLE #Target ( pk integer NOT NULL, ak character(1) NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) );   CREATE UNIQUE INDEX uq1 ON #Target (ak) INCLUDE (status_code) WHERE status_code = 'a'; The changes table contains just an integer primary key (to identify the target row to change) and the new status code: CREATE TABLE #Changes ( pk integer NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) ); Sample Data The sample data for the example is: INSERT #Target (pk, ak, status_code) VALUES (1, 'A', 'a'), (2, 'B', 'a'), (3, 'C', 'a'), (4, 'A', 'd');   INSERT #Changes (pk, status_code) VALUES (1, 'd'), (4, 'a');          Target                     Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ a           ¦    ¦  1 ¦ d           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ d           ¦ +-----------------------+ The target table’s alternate key (ak) column is unique, for rows where status_code = ‘a’.  Applying the changes to the target will change row 1 from status ‘a’ to status ‘d’, and row 4 from status ‘d’ to status ‘a’.  The result of applying all the changes will still satisfy the filtered unique index, because the ‘A’ in row 1 will be deleted from the index and the ‘A’ in row 4 will be added. Merge Test One Let’s now execute a MERGE statement to apply the changes: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; The MERGE changes the two target rows as expected.  The updated target table now contains: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦ <—changed from ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦ <—changed from ‘d’ +-----------------------+ Merge Test Two Now let’s repopulate the changes table to reverse the updates we just performed: TRUNCATE TABLE #Changes;   INSERT #Changes (pk, status_code) VALUES (1, 'a'), (4, 'd'); This will change row 1 back to status ‘a’ and row 4 back to status ‘d’.  As a reminder, the current state of the tables is:          Target                        Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ d           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ a           ¦ +-----------------------+ We execute the same MERGE statement: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; However this time we receive the following message: Msg 2601, Level 14, State 1, Line 1 Cannot insert duplicate key row in object 'dbo.#Target' with unique index 'uq1'. The duplicate key value is (A). The statement has been terminated. Applying the changes using UPDATE Let’s now rewrite the MERGE to use UPDATE instead: UPDATE t SET status_code = c.status_code FROM #Target AS t JOIN #Changes AS c ON t.pk = c.pk WHERE c.status_code <> t.status_code; This query succeeds where the MERGE failed.  The two rows are updated as expected: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ a           ¦ <—changed back to ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ d           ¦ <—changed back to ‘d’ +-----------------------+ What went wrong with the MERGE? In this test, the MERGE query execution happens to apply the changes in the order of the ‘pk’ column. In test one, this was not a problem: row 1 is removed from the unique filtered index by changing status_code from ‘a’ to ‘d’ before row 4 is added.  At no point does the table contain two rows where ak = ‘A’ and status_code = ‘a’. In test two, however, the first change was to change row 1 from status ‘d’ to status ‘a’.  This change means there would be two rows in the filtered unique index where ak = ‘A’ (both row 1 and row 4 meet the index filtering criteria ‘status_code = a’). The storage engine does not allow the query processor to violate a unique key (unless IGNORE_DUP_KEY is ON, but that is a different story, and doesn’t apply to MERGE in any case).  This strict rule applies regardless of the fact that if all changes were applied, there would be no unique key violation (row 4 would eventually be changed from ‘a’ to ‘d’, removing it from the filtered unique index, and resolving the key violation). Why it went wrong The query optimizer usually detects when this sort of temporary uniqueness violation could occur, and builds a plan that avoids the issue.  I wrote about this a couple of years ago in my post Beware Sneaky Reads with Unique Indexes (you can read more about the details on pages 495-497 of Microsoft SQL Server 2008 Internals or in Craig Freedman’s blog post on maintaining unique indexes).  To summarize though, the optimizer introduces Split, Filter, Sort, and Collapse operators into the query plan to: Split each row update into delete followed by an inserts Filter out rows that would not change the index (due to the filter on the index, or a non-updating update) Sort the resulting stream by index key, with deletes before inserts Collapse delete/insert pairs on the same index key back into an update The effect of all this is that only net changes are applied to an index (as one or more insert, update, and/or delete operations).  In this case, the net effect is a single update of the filtered unique index: changing the row for ak = ‘A’ from pk = 4 to pk = 1.  In case that is less than 100% clear, let’s look at the operation in test two again:          Target                     Changes                   Result +-----------------------+    +------------------+    +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦    ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦    ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ d           ¦    ¦  1 ¦ A  ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦    ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+    ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦                            ¦  4 ¦ A  ¦ d           ¦ +-----------------------+                            +-----------------------+ From the filtered index’s point of view (filtered for status_code = ‘a’ and shown in nonclustered index key order) the overall effect of the query is:   Before           After +---------+    +---------+ ¦ pk ¦ ak ¦    ¦ pk ¦ ak ¦ ¦----+----¦    ¦----+----¦ ¦  4 ¦ A  ¦    ¦  1 ¦ A  ¦ ¦  2 ¦ B  ¦    ¦  2 ¦ B  ¦ ¦  3 ¦ C  ¦    ¦  3 ¦ C  ¦ +---------+    +---------+ The single net change there is a change of pk from 4 to 1 for the nonclustered index entry ak = ‘A’.  This is the magic performed by the split, sort, and collapse.  Notice in particular how the original changes to the index key (on the ‘ak’ column) have been transformed into an update of a non-key column (pk is included in the nonclustered index).  By not updating any nonclustered index keys, we are guaranteed to avoid transient key violations. The Execution Plans The estimated MERGE execution plan that produces the incorrect key-violation error looks like this (click to enlarge in a new window): The successful UPDATE execution plan is (click to enlarge in a new window): The MERGE execution plan is a narrow (per-row) update.  The single Clustered Index Merge operator maintains both the clustered index and the filtered nonclustered index.  The UPDATE plan is a wide (per-index) update.  The clustered index is maintained first, then the Split, Filter, Sort, Collapse sequence is applied before the nonclustered index is separately maintained. There is always a wide update plan for any query that modifies the database. The narrow form is a performance optimization where the number of rows is expected to be relatively small, and is not available for all operations.  One of the operations that should disallow a narrow plan is maintaining a unique index where intermediate key violations could occur. Workarounds The MERGE can be made to work (producing a wide update plan with split, sort, and collapse) by: Adding all columns referenced in the filtered index’s WHERE clause to the index key (INCLUDE is not sufficient); or Executing the query with trace flag 8790 set e.g. OPTION (QUERYTRACEON 8790). Undocumented trace flag 8790 forces a wide update plan for any data-changing query (remember that a wide update plan is always possible).  Either change will produce a successfully-executing wide update plan for the MERGE that failed previously. Conclusion The optimizer fails to spot the possibility of transient unique key violations with MERGE under the conditions listed at the start of this post.  It incorrectly chooses a narrow plan for the MERGE, which cannot provide the protection of a split/sort/collapse sequence for the nonclustered index maintenance. The MERGE plan may fail at execution time depending on the order in which rows are processed, and the distribution of data in the database.  Worse, a previously solid MERGE query may suddenly start to fail unpredictably if a filtered unique index is added to the merge target table at any point. Connect bug filed here Tests performed on SQL Server 2012 SP1 CUI (build 11.0.3321) x64 Developer Edition © 2012 Paul White – All Rights Reserved Twitter: @SQL_Kiwi Email: [email protected]

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  • Can this Query be corrected or different table structure needed? (database dumps provided)

    - by sandeepan
    This is a bit lengthy but I have provided sufficient details and kept things very clear. Please see if you can help. (I will surely accept answer if it solves my problem) I am sure a person experienced with this can surely help or suggest me to decide the tables structure. About the system:- There are tutors who create classes A tags based search approach is being followed Tag relations are created/edited when new tutors registers/edits profile data and when tutors create classes (this makes tutors and classes searcheable).For simplicity, let us consider only tutor name and class name are the fields which are matched against search keywords. In this example, I am considering - tutor "Sandeepan Nath" has created a class called "first class" tutor "Bob Cratchit" has created a class called "new class" Desired search results- AND logic to be appied on the search keywords and match against class and tutor data(class name + tutor name), in other words, All those classes be shown such that all the search terms are present in the class name or its tutor name. Example to be clear - Searching "first class" returns class with id_wc = 1. Working Searching "Sandeepan class" should also return class with id_wc = 1. Not working in System 2. Problem with profile editing and searching To tell in one sentence, I am facing a conflict between the ease of profile edition (edition of tag relations when tutor profiles are edited) and the ease of search logic. In the beginning, we had one table structure and search was easy but tag edition logic was very clumsy and unmaintainable(Check System 1 in the section below) . So we created separate tag relations tables to make profile edition simpler but search has become difficult. Please dump the tables so that you can run the search query I have given below and see the results. System 1 (previous system - search easy - profile edition difficult):- Only one table called All_Tag_Relations table had the all the tag relations. The tags table below is common to both systems 1 and 2. CREATE TABLE IF NOT EXISTS `all_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) unsigned DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `all_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`, `id_wc`) VALUES (1, 1, 1, NULL), (2, 2, 1, NULL), (3, 1, 1, 1), (4, 2, 1, 1), (5, 3, 1, 1), (6, 4, 1, 1), (7, 6, 2, NULL), (8, 7, 2, NULL), (9, 6, 2, 2), (10, 7, 2, 2), (11, 5, 2, 2), (12, 4, 2, 2); CREATE TABLE IF NOT EXISTS `tags` ( `id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT, `tag` varchar(255) DEFAULT NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`), KEY `tag_4` (`tag`), FULLTEXT KEY `tag_5` (`tag`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=8 ; INSERT INTO `tags` (`id_tag`, `tag`) VALUES (1, 'Sandeepan'), (2, 'Nath'), (3, 'first'), (4, 'class'), (5, 'new'), (6, 'Bob'), (7, 'Cratchit'); Please note that for every class, the tag rels of its tutor have to be duplicated. Example, for class with id_wc=1, the tag rel records with id_tag_rel = 3 and 4 are actually extras if you compare with the tag rel records with id_tag_rel = 1 and 2. System 2 (present system - profile edition easy, search difficult) Two separate tables Tutors_Tag_Relations and Webclasses_Tag_Relations have the corresponding tag relations data (Please dump into a separate database)- CREATE TABLE IF NOT EXISTS `tutors_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `tutors_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`) VALUES (1, 1, 1), (2, 2, 1), (3, 6, 2), (4, 7, 2); CREATE TABLE IF NOT EXISTS `webclasses_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `webclasses_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `webclasses_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`, `id_wc`) VALUES (1, 3, 1, 1), (2, 4, 1, 1), (3, 5, 2, 2), (4, 4, 2, 2); CREATE TABLE IF NOT EXISTS `tags` ( `id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT, `tag` varchar(255) DEFAULT NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`), KEY `tag_4` (`tag`), FULLTEXT KEY `tag_5` (`tag`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=8 ; INSERT INTO `tags` (`id_tag`, `tag`) VALUES (1, 'Sandeepan'), (2, 'Nath'), (3, 'first'), (4, 'class'), (5, 'new'), (6, 'Bob'), (7, 'Cratchit'); CREATE TABLE IF NOT EXISTS `all_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) unsigned DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; insert into All_Tag_Relations select NULL,id_tag,id_tutor,NULL from Tutors_Tag_Relations; insert into All_Tag_Relations select NULL,id_tag,id_tutor,id_wc from Webclasses_Tag_Relations; Here you can see how easily tutor first name can be edited only in one place. But search has become really difficult, so on being advised to use a Temporary table, I am creating one at every search request, then dumping all the necessary data and then searching from it, I am creating this All_Tag_Relations table at search run time. Here I am just dumping all the data from the two tables Tutors_Tag_Relations and Webclasses_Tag_Relations. But, I am still not able to get classes if I search with tutor name This is the query which searches "first class". Running them on both the systems shows correct results (returns the class with id_wc = 1). SELECT wtagrels.id_wc,SUM(DISTINCT( wtagrels.id_tag =3)) AS key_1_total_matches, SUM(DISTINCT( wtagrels.id_tag =4)) AS key_2_total_matches FROM all_tag_relations AS wtagrels WHERE ( wtagrels.id_tag =3 OR wtagrels.id_tag =4 ) GROUP BY wtagrels.id_wc HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 LIMIT 0, 20 But, searching for "Sandeepan class" works only with the 1st system Here is the query which searches "Sandeepan class" SELECT wtagrels.id_wc,SUM(DISTINCT( wtagrels.id_tag =1)) AS key_1_total_matches, SUM(DISTINCT( wtagrels.id_tag =4)) AS key_2_total_matches FROM all_tag_relations AS wtagrels WHERE ( wtagrels.id_tag =1 OR wtagrels.id_tag =4 ) GROUP BY wtagrels.id_wc HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 LIMIT 0, 20 Can anybody alter this query and somehow do a proper join or something to get correct results. That solves my problem in a nice way. As you can figure out, the reason why it does not work in system 2 is that in system 1, for every class, one additional tag relation linking class and tutor name is present. e.g. for class first class, (records with id_tag_rel 3 and 4) which returns the class on searching with tutor name. So, you see the trade-off between the search and profile edition difficulty with the two systems. How do I overcome both. I have to reach a conclusion soon. So far my reasoning is it is definitely not good from a code maintainability point of view to follow the single tag rel table structure of system one, because in a real system while editing a field like "tutor qualifications", there can be as many records in tag rels table as there are words in qualification of a tutor (one word in a field = one tag relation). Now suppose a tutor has 100 classes. When he edits his qualification, all the tag rel rows corresponding to him are deleted and then as many copies are to be created (as per the new qualification data) as there are classes. This becomes particularly difficult if later more searcheable fields are added. The code cannot be robust. Is the best solution to follow system 2 (edition has to be in one table - no extra work for each and every class) and somehow re-create the all_tag_relations table like system 1 (from the tables tutor_tag_relations and webclasses_tag_relations), creating the extra tutor tag rels for each and every class by a tutor (which is currently missing in system 2's temporary all_tag_relations table). That would be a time consuming logic script. I doubt that table can be recreated without resorting to PHP sript (mysql alone cannot do that). But the problem is that running all this at search time will make search definitely slow. So, how do such systems work? How are such situations handled? I thought about we can run a cron which initiates that PHP script, say every 1 minute and replaces the existing all_tag_relations table as per new tag rels from tutor_tag_relations and webclasses_tag_relations (replaces means creates a new table, deletes the original and renames the new one as all_tag_relations, otherwise search won't work during that period- or is there any better way to that?). Anyway, the result would be that any changes by tutors will reflect in search in the next 1 minute and not immediately. An alternateve would be to initate that PHP script every time a tutor edits his profile. But here again, since many users may edit their profiles concurrently, will the creation of so many tables be a burden and can mysql make the server slow? Any help would be appreciated and working solution will be accepted as answer. Thanks, Sandeepan

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  • Need help with implementing collision detection using the Separating Axis Theorem

    - by Eddie Ringle
    So, after hours of Googling and reading, I've found that the basic process of detecting a collision using SAT is: for each edge of poly A project A and B onto the normal for this edge if intervals do not overlap, return false end for for each edge of poly B project A and B onto the normal for this edge if intervals do not overlap, return false end for However, as many ways as I try to implement this in code, I just cannot get it to detect the collision. My current code is as follows: for (unsigned int i = 0; i < asteroids.size(); i++) { if (asteroids.valid(i)) { asteroids[i]->Update(); // Player-Asteroid collision detection bool collision = true; SDL_Rect asteroidBox = asteroids[i]->boundingBox; // Bullet-Asteroid collision detection for (unsigned int j = 0; j < player.bullets.size(); j++) { if (player.bullets.valid(j)) { Bullet b = player.bullets[j]; collision = true; if (b.x + (b.w / 2.0f) < asteroidBox.x - (asteroidBox.w / 2.0f)) collision = false; if (b.x - (b.w / 2.0f) > asteroidBox.x + (asteroidBox.w / 2.0f)) collision = false; if (b.y - (b.h / 2.0f) > asteroidBox.y + (asteroidBox.h / 2.0f)) collision = false; if (b.y + (b.h / 2.0f) < asteroidBox.y - (asteroidBox.h / 2.0f)) collision = false; if (collision) { bool realCollision = false; float min1, max1, min2, max2; // Create a list of vertices for the bullet CrissCross::Data::LList<Vector2D *> bullVerts; bullVerts.insert(new Vector2D(b.x - b.w / 2.0f, b.y + b.h / 2.0f)); bullVerts.insert(new Vector2D(b.x - b.w / 2.0f, b.y - b.h / 2.0f)); bullVerts.insert(new Vector2D(b.x + b.w / 2.0f, b.y - b.h / 2.0f)); bullVerts.insert(new Vector2D(b.x + b.w / 2.0f, b.y + b.h / 2.0f)); // Create a list of vectors of the edges of the bullet and the asteroid CrissCross::Data::LList<Vector2D *> bullEdges; CrissCross::Data::LList<Vector2D *> asteroidEdges; for (int k = 0; k < 4; k++) { int n = (k == 3) ? 0 : k + 1; bullEdges.insert(new Vector2D(bullVerts[k]->x - bullVerts[n]->x, bullVerts[k]->y - bullVerts[n]->y)); asteroidEdges.insert(new Vector2D(asteroids[i]->vertices[k]->x - asteroids[i]->vertices[n]->x, asteroids[i]->vertices[k]->y - asteroids[i]->vertices[n]->y)); } for (unsigned int k = 0; k < asteroidEdges.size(); k++) { Vector2D *axis = asteroidEdges[k]->getPerpendicular(); min1 = max1 = axis->dotProduct(asteroids[i]->vertices[0]); for (unsigned int l = 1; l < asteroids[i]->vertices.size(); l++) { float test = axis->dotProduct(asteroids[i]->vertices[l]); min1 = (test < min1) ? test : min1; max1 = (test > max1) ? test : max1; } min2 = max2 = axis->dotProduct(bullVerts[0]); for (unsigned int l = 1; l < bullVerts.size(); l++) { float test = axis->dotProduct(bullVerts[l]); min2 = (test < min2) ? test : min2; max2 = (test > max2) ? test : max2; } delete axis; axis = NULL; if ( (min1 - max2) > 0 || (min2 - max1) > 0 ) { realCollision = false; break; } else { realCollision = true; } } if (realCollision == false) { for (unsigned int k = 0; k < bullEdges.size(); k++) { Vector2D *axis = bullEdges[k]->getPerpendicular(); min1 = max1 = axis->dotProduct(asteroids[i]->vertices[0]); for (unsigned int l = 1; l < asteroids[i]->vertices.size(); l++) { float test = axis->dotProduct(asteroids[i]->vertices[l]); min1 = (test < min1) ? test : min1; max1 = (test > max1) ? test : max1; } min2 = max2 = axis->dotProduct(bullVerts[0]); for (unsigned int l = 1; l < bullVerts.size(); l++) { float test = axis->dotProduct(bullVerts[l]); min2 = (test < min2) ? test : min2; max2 = (test > max2) ? test : max2; } delete axis; axis = NULL; if ( (min1 - max2) > 0 || (min2 - max1) > 0 ) { realCollision = false; break; } else { realCollision = true; } } } if (realCollision) { player.bullets.remove(j); int numAsteroids; float newDegree; srand ( j + asteroidBox.x ); if ( asteroids[i]->degree == 90.0f ) { if ( rand() % 2 == 1 ) { numAsteroids = 3; newDegree = 30.0f; } else { numAsteroids = 2; newDegree = 45.0f; } for ( int k = 0; k < numAsteroids; k++) asteroids.insert(new Asteroid(asteroidBox.x + (10 * k), asteroidBox.y + (10 * k), newDegree)); } delete asteroids[i]; asteroids.remove(i); } while (bullVerts.size()) { delete bullVerts[0]; bullVerts.remove(0); } while (bullEdges.size()) { delete bullEdges[0]; bullEdges.remove(0); } while (asteroidEdges.size()) { delete asteroidEdges[0]; asteroidEdges.remove(0); } } } } } } bullEdges is a list of vectors of the edges of a bullet, asteroidEdges is similar, and bullVerts and asteroids[i].vertices are, obviously, lists of vectors of each vertex for the respective bullet or asteroid. Honestly, I'm not looking for code corrections, just a fresh set of eyes.

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  • Can this Query can be corrected or different table structure needed? (question is clear, detailed, d

    - by sandeepan
    This is a bit lengthy but I have provided sufficient details and kept things very clear. Please see if you can help. (I will surely accept answer if it solves my problem) I am sure a person experienced with this can surely help or suggest me to decide the tables structure. About the system:- There are tutors who create classes A tags based search approach is being followed Tag relations are created/edited when new tutors registers/edits profile data and when tutors create classes (this makes tutors and classes searcheable).For simplicity, let us consider only tutor name and class name are the fields which are matched against search keywords. In this example, I am considering - tutor "Sandeepan Nath" has created a class called "first class" tutor "Bob Cratchit" has created a class called "new class" Desired search results- AND logic to be appied on the search keywords and match against class and tutor data(class name + tutor name), in other words, All those classes be shown such that all the search terms are present in the class name or its tutor name. Example to be clear - Searching "first class" returns class with id_wc = 1. Working Searching "Sandeepan class" should also return class with id_wc = 1. Not working in System 2. Problem with profile editing and searching To tell in one sentence, I am facing a conflict between the ease of profile edition (edition of tag relations when tutor profiles are edited) and the ease of search logic. In the beginning, we had one table structure and search was easy but tag edition logic was very clumsy and unmaintainable(Check System 1 in the section below) . So we created separate tag relations tables to make profile edition simpler but search has become difficult. Please dump the tables so that you can run the search query I have given below and see the results. System 1 (previous system - search easy - profile edition difficult):- Only one table called All_Tag_Relations table had the all the tag relations. The tags table below is common to both systems 1 and 2. CREATE TABLE IF NOT EXISTS `all_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) unsigned DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `all_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`, `id_wc`) VALUES (1, 1, 1, NULL), (2, 2, 1, NULL), (3, 1, 1, 1), (4, 2, 1, 1), (5, 3, 1, 1), (6, 4, 1, 1), (7, 6, 2, NULL), (8, 7, 2, NULL), (9, 6, 2, 2), (10, 7, 2, 2), (11, 5, 2, 2), (12, 4, 2, 2); CREATE TABLE IF NOT EXISTS `tags` ( `id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT, `tag` varchar(255) DEFAULT NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`), KEY `tag_4` (`tag`), FULLTEXT KEY `tag_5` (`tag`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=8 ; INSERT INTO `tags` (`id_tag`, `tag`) VALUES (1, 'Sandeepan'), (2, 'Nath'), (3, 'first'), (4, 'class'), (5, 'new'), (6, 'Bob'), (7, 'Cratchit'); Please note that for every class, the tag rels of its tutor have to be duplicated. Example, for class with id_wc=1, the tag rel records with id_tag_rel = 3 and 4 are actually extras if you compare with the tag rel records with id_tag_rel = 1 and 2. System 2 (present system - profile edition easy, search difficult) Two separate tables Tutors_Tag_Relations and Webclasses_Tag_Relations have the corresponding tag relations data (Please dump into a separate database)- CREATE TABLE IF NOT EXISTS `tutors_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `tutors_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`) VALUES (1, 1, 1), (2, 2, 1), (3, 6, 2), (4, 7, 2); CREATE TABLE IF NOT EXISTS `webclasses_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `webclasses_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `webclasses_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`, `id_wc`) VALUES (1, 3, 1, 1), (2, 4, 1, 1), (3, 5, 2, 2), (4, 4, 2, 2); CREATE TABLE IF NOT EXISTS `tags` ( `id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT, `tag` varchar(255) DEFAULT NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`), KEY `tag_4` (`tag`), FULLTEXT KEY `tag_5` (`tag`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=8 ; INSERT INTO `tags` (`id_tag`, `tag`) VALUES (1, 'Sandeepan'), (2, 'Nath'), (3, 'first'), (4, 'class'), (5, 'new'), (6, 'Bob'), (7, 'Cratchit'); CREATE TABLE IF NOT EXISTS `all_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) unsigned DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; insert into All_Tag_Relations select NULL,id_tag,id_tutor,NULL from Tutors_Tag_Relations; insert into All_Tag_Relations select NULL,id_tag,id_tutor,id_wc from Webclasses_Tag_Relations; Here you can see how easily tutor first name can be edited only in one place. But search has become really difficult, so on being advised to use a Temporary table, I am creating one at every search request, then dumping all the necessary data and then searching from it, I am creating this All_Tag_Relations table at search run time. Here I am just dumping all the data from the two tables Tutors_Tag_Relations and Webclasses_Tag_Relations. But, I am still not able to get classes if I search with tutor name This is the query which searches "first class". Running them on both the systems shows correct results (returns the class with id_wc = 1). SELECT wtagrels.id_wc,SUM(DISTINCT( wtagrels.id_tag =3)) AS key_1_total_matches, SUM(DISTINCT( wtagrels.id_tag =4)) AS key_2_total_matches FROM all_tag_relations AS wtagrels WHERE ( wtagrels.id_tag =3 OR wtagrels.id_tag =4 ) GROUP BY wtagrels.id_wc HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 LIMIT 0, 20 But, searching for "Sandeepan class" works only with the 1st system Here is the query which searches "Sandeepan class" SELECT wtagrels.id_wc,SUM(DISTINCT( wtagrels.id_tag =1)) AS key_1_total_matches, SUM(DISTINCT( wtagrels.id_tag =4)) AS key_2_total_matches FROM all_tag_relations AS wtagrels WHERE ( wtagrels.id_tag =1 OR wtagrels.id_tag =4 ) GROUP BY wtagrels.id_wc HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 LIMIT 0, 20 Can anybody alter this query and somehow do a proper join or something to get correct results. That solves my problem in a nice way. As you can figure out, the reason why it does not work in system 2 is that in system 1, for every class, one additional tag relation linking class and tutor name is present. e.g. for class first class, (records with id_tag_rel 3 and 4) which returns the class on searching with tutor name. So, you see the trade-off between the search and profile edition difficulty with the two systems. How do I overcome both. I have to reach a conclusion soon. So far my reasoning is it is definitely not good from a code maintainability point of view to follow the single tag rel table structure of system one, because in a real system while editing a field like "tutor qualifications", there can be as many records in tag rels table as there are words in qualification of a tutor (one word in a field = one tag relation). Now suppose a tutor has 100 classes. When he edits his qualification, all the tag rel rows corresponding to him are deleted and then as many copies are to be created (as per the new qualification data) as there are classes. This becomes particularly difficult if later more searcheable fields are added. The code cannot be robust. Is the best solution to follow system 2 (edition has to be in one table - no extra work for each and every class) and somehow re-create the all_tag_relations table like system 1 (from the tables tutor_tag_relations and webclasses_tag_relations), creating the extra tutor tag rels for each and every class by a tutor (which is currently missing in system 2's temporary all_tag_relations table). That would be a time consuming logic script. I doubt that table can be recreated without resorting to PHP sript (mysql alone cannot do that). But the problem is that running all this at search time will make search definitely slow. So, how do such systems work? How are such situations handled? I thought about we can run a cron which initiates that PHP script, say every 1 minute and replaces the existing all_tag_relations table as per new tag rels from tutor_tag_relations and webclasses_tag_relations (replaces means creates a new table, deletes the original and renames the new one as all_tag_relations, otherwise search won't work during that period- or is there any better way to that?). Anyway, the result would be that any changes by tutors will reflect in search in the next 1 minute and not immediately. An alternateve would be to initate that PHP script every time a tutor edits his profile. But here again, since many users may edit their profiles concurrently, will the creation of so many tables be a burden and can mysql make the server slow? Any help would be appreciated and working solution will be accepted as answer. Thanks, Sandeepan

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  • could not bind socket while haproxy restart

    - by shreyas
    I m restarting HAproxy by following command haproxy -f /etc/haproxy/haproxy.cfg -p /var/run/haproxy.pid -sf $(cat /var/run/haproxy.pid) but i get following message [ALERT] 183/225022 (9278) : Starting proxy appli1-rewrite: cannot bind socket [ALERT] 183/225022 (9278) : Starting proxy appli2-insert: cannot bind socket [ALERT] 183/225022 (9278) : Starting proxy appli3-relais: cannot bind socket [ALERT] 183/225022 (9278) : Starting proxy appli4-backup: cannot bind socket [ALERT] 183/225022 (9278) : Starting proxy ssl-relay: cannot bind socket [ALERT] 183/225022 (9278) : Starting proxy appli5-backup: cannot bind socket my haproxy.cfg file looks likefollowing global log 127.0.0.1 local0 log 127.0.0.1 local1 notice #log loghost local0 info maxconn 4096 #chroot /usr/share/haproxy user haproxy group haproxy daemon #debug #quiet defaults log global mode http option httplog option dontlognull retries 3 option redispatch maxconn 2000 contimeout 5000 clitimeout 50000 srvtimeout 50000 listen appli1-rewrite 0.0.0.0:10001 cookie SERVERID rewrite balance roundrobin server app1_1 192.168.34.23:8080 cookie app1inst1 check inter 2000 rise 2 fall 5 server app1_2 192.168.34.32:8080 cookie app1inst2 check inter 2000 rise 2 fall 5 server app1_3 192.168.34.27:8080 cookie app1inst3 check inter 2000 rise 2 fall 5 server app1_4 192.168.34.42:8080 cookie app1inst4 check inter 2000 rise 2 fall 5 listen appli2-insert 0.0.0.0:10002 option httpchk balance roundrobin cookie SERVERID insert indirect nocache server inst1 192.168.114.56:80 cookie server01 check inter 2000 fall 3 server inst2 192.168.114.56:81 cookie server02 check inter 2000 fall 3 capture cookie vgnvisitor= len 32 option httpclose # disable keep-alive rspidel ^Set-cookie:\ IP= # do not let this cookie tell our internal IP address listen appli3-relais 0.0.0.0:10003 dispatch 192.168.135.17:80 listen appli4-backup 0.0.0.0:10004 option httpchk /index.html option persist balance roundrobin server inst1 192.168.114.56:80 check inter 2000 fall 3 server inst2 192.168.114.56:81 check inter 2000 fall 3 backup listen ssl-relay 0.0.0.0:8443 option ssl-hello-chk balance source server inst1 192.168.110.56:443 check inter 2000 fall 3 server inst2 192.168.110.57:443 check inter 2000 fall 3 server back1 192.168.120.58:443 backup listen appli5-backup 0.0.0.0:10005 option httpchk * balance roundrobin cookie SERVERID insert indirect nocache server inst1 192.168.114.56:80 cookie server01 check inter 2000 fall 3 server inst2 192.168.114.56:81 cookie server02 check inter 2000 fall 3 server inst3 192.168.114.57:80 backup check inter 2000 fall 3 capture cookie ASPSESSION len 32 srvtimeout 20000 option httpclose # disable keep-alive option checkcache # block response if set-cookie & cacheable rspidel ^Set-cookie:\ IP= # do not let this cookie tell our internal IP address #errorloc 502 http://192.168.114.58/error502.html #errorfile 503 /etc/haproxy/errors/503.http errorfile 400 /etc/haproxy/errors/400.http errorfile 403 /etc/haproxy/errors/403.http errorfile 408 /etc/haproxy/errors/408.http errorfile 500 /etc/haproxy/errors/500.http errorfile 502 /etc/haproxy/errors/502.http errorfile 503 /etc/haproxy/errors/503.http errorfile 504 /etc/haproxy/errors/504.http what is wrong with my aproach

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  • Configure a SPF rule on Ubuntu

    - by TiuTalk
    Where I can create/insert the SPF rules to allow a external server to authenticate and send e-mails using the domain name of my server running Ubuntu? I need to insert this rule: v=spf1 ip4:111.111.111.111/29 ip4:111.111.111.111/24 a mx ~all Thanks :)

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  • Benchmark MySQL Cluster using flexAsynch: No free node id found for mysqld(API)?

    - by quanta
    I am going to benchmark MySQL Cluster using flexAsynch follow this guide, details as below: mkdir /usr/local/mysqlc732/ cd /usr/local/src/mysql-cluster-gpl-7.3.2 cmake . -DCMAKE_INSTALL_PREFIX=/usr/local/mysqlc732/ -DWITH_NDB_TEST=ON make make install Everything works fine until this step: # /usr/local/mysqlc732/bin/flexAsynch -t 1 -p 80 -l 2 -o 100 -c 100 -n FLEXASYNCH - Starting normal mode Perform benchmark of insert, update and delete transactions 1 number of concurrent threads 80 number of parallel operation per thread 100 transaction(s) per round 2 iterations Load Factor is 80% 25 attributes per table 1 is the number of 32 bit words per attribute Tables are with logging Transactions are executed with hint provided No force send is used, adaptive algorithm used Key Errors are disallowed Temporary Resource Errors are allowed Insufficient Space Errors are disallowed Node Recovery Errors are allowed Overload Errors are allowed Timeout Errors are allowed Internal NDB Errors are allowed User logic reported Errors are allowed Application Errors are disallowed Using table name TAB0 NDBT_ProgramExit: 1 - Failed ndb_cluster.log: WARNING -- Failed to allocate nodeid for API at 127.0.0.1. Returned eror: 'No free node id found for mysqld(API).' I also have recompiled with -DWITH_DEBUG=1 -DWITH_NDB_DEBUG=1. How can I run flexAsynch in the debug mode? # /usr/local/mysqlc732/bin/flexAsynch -h FLEXASYNCH Perform benchmark of insert, update and delete transactions Arguments: -t Number of threads to start, default 1 -p Number of parallel transactions per thread, default 32 -o Number of transactions per loop, default 500 -l Number of loops to run, default 1, 0=infinite -load_factor Number Load factor in index in percent (40 -> 99) -a Number of attributes, default 25 -c Number of operations per transaction -s Size of each attribute, default 1 (PK is always of size 1, independent of this value) -simple Use simple read to read from database -dirty Use dirty read to read from database -write Use writeTuple in insert and update -n Use standard table names -no_table_create Don't create tables in db -temp Create table(s) without logging -no_hint Don't give hint on where to execute transaction coordinator -adaptive Use adaptive send algorithm (default) -force Force send when communicating -non_adaptive Send at a 10 millisecond interval -local 1 = each thread its own node, 2 = round robin on node per parallel trans 3 = random node per parallel trans -ndbrecord Use NDB Record -r Number of extra loops -insert Only run inserts on standard table -read Only run reads on standard table -update Only run updates on standard table -delete Only run deletes on standard table -create_table Only run Create Table of standard table -drop_table Only run Drop Table on standard table -warmup_time Warmup Time before measurement starts -execution_time Execution Time where measurement is done -cooldown_time Cooldown time after measurement completed -table Number of standard table, default 0

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