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  • SubSonic Stored Procedure Issue - Data Generated at Stored Procedure is different from Data Received

    - by ShaShaIn
    Hi All, I am facing a unknown problem while using stored procedure with SubSonic. I have written a stored procedure & application code that takes first name & last name as input parameter and return last login id as ouput parameter. It creates login id as first character of first name & complete last name for no-existing login id otherwise it adds 1 in the last login id e.g. First Name - Mark, Last Name - Waugh, First Login Id - MWaugh, Second Login Id - MWaugh1, Third Login Id - MWaugh2 etc. Stored Procedure SET ANSI_NULLS OFF GO SET QUOTED_IDENTIFIER ON GO CREATE PROCEDURE [dbo].[Users_FetchLoginId] ( @FirstName nvarchar(64), @LastName nvarchar(64), @LoginId nvarchar(256) OUTPUT ) AS DECLARE @UserId nvarchar(256); SET @UserId = NULL; SET @LoginId = NULL; SELECT @UserId = LoweredUserName FROM aspnet_Users WHERE LoweredUserName LIKE (LOWER(SUBSTRING(@FirstName,1,1) + @LastName)) IF @@rowcount = 0 OR @UserId IS NULL BEGIN SET @LoginId = (SUBSTRING(@FirstName, 1, 1) + @LastName); print @LoginId RETURN 1; END ELSE BEGIN SELECT TOP 1 LoweredUserName FROM aspnet_Users WHERE LoweredUserName LIKE (LOWER(SUBSTRING(@FirstName,1,1) + @LastName + '%')) ORDER BY LoweredUserName DESC RETURN 2; END Application Code public string FetchLoginId(string firstName, string lastName) { SubSonic.StoredProcedure sp = SPs.UsersFetchLoginId( firstName, lastName, null ); sp.Command.AddReturnParameter(); sp.Execute(); if (sp.Command.Parameters.Find(delegate(QueryParameter queryParameter) { return queryParameter.Mode == ParameterDirection.ReturnValue; }).ParameterValue != System.DBNull.Value) { int returnCode = Convert.ToInt32(sp.Command.Parameters.Find(delegate(QueryParameter queryParameter) { return queryParameter.Mode == ParameterDirection.ReturnValue; }).ParameterValue, CultureInfo.InvariantCulture); if (returnCode == 1) { // UserName as First Character of First Name & Full Last Name return sp.Command.Parameters[2].ParameterValue.ToString(); } if (returnCode == 2) { DataSet ds = sp.GetDataSet(); if (null == ds || null == ds.Tables[0] || 0 == ds.Tables[0].Rows.Count) return ""; string maxLoginId = ds.Tables[0].Rows[0]["LoweredUserName"].ToString(); string initialLoginId = firstName.Substring(0, 1) + lastName; int maxLoginIdIndex = 0; int initialLoginIdLength = initialLoginId.Length; if (maxLoginId.Substring(initialLoginIdLength).Length == 0) { maxLoginIdIndex++; // UserName as Max Lowered User Name Found & Incrementer as Suffix (Here, First Incrementer i.e. 1) return (initialLoginId + maxLoginIdIndex); } if (int.TryParse(maxLoginId.Substring(initialLoginIdLength), out maxLoginIdIndex)) { if (maxLoginIdIndex > 0) { maxLoginIdIndex++; // UserName as Max Lowered User Name Found & Incrementer as Suffix return (initialLoginId + maxLoginIdIndex); } } } } Now the problem is for some input (see test data below), the login id created at sql server end correctly but at application subsonic dal side, it truncates some characters. First Name - Jenelia and Last Name - Kanupatikenalaalayampentyalavelugoplansubhramanayam [dbo].[Users_FetchLoginId] - Execute Stored Procedure Separately - Login Id Is Correct JKanupatikenalaalayampentyalavelugoplansubhramanayam public string FetchLoginId(string firstName, string lastName) - Application Code DAL Side - LginId Is Wrongly Received From Stored Procedure JKanupatikenalaalayampentyalavelugoplansubhramanay You can easily see that 2 charactes are removed. If the data is correctly generated by stored procedure then why the characters are removed when data is received in output parameter of stored procedure? Is it due to any internal known or unknown bug of SubSonic? Your help is significant. Thanks in advance...

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  • Lots of mysql Sleep processes

    - by user259284
    Hello, I am still having trouble with my mysql server. It seems that since i optimize it, the tables were growing and now sometimes is very slow again. I have no idea of how to optimize more. mySQL server has 48GB of RAM and mysqld is using about 8, most of the tables are innoDB. Site has about 2000 users online. I also run explain on every query and every one of them is indexed. mySQL processes: http://www.pik.ba/mysqlStanje.php my.cnf: # The MySQL database server configuration file. # # You can copy this to one of: # - "/etc/mysql/my.cnf" to set global options, # - "~/.my.cnf" to set user-specific options. # # One can use all long options that the program supports. # Run program with --help to get a list of available options and with # --print-defaults to see which it would actually understand and use. # # For explanations see # http://dev.mysql.com/doc/mysql/en/server-system-variables.html # This will be passed to all mysql clients # It has been reported that passwords should be enclosed with ticks/quotes # escpecially if they contain "#" chars... # Remember to edit /etc/mysql/debian.cnf when changing the socket location. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock # Here is entries for some specific programs # The following values assume you have at least 32M ram # This was formally known as [safe_mysqld]. Both versions are currently parsed. [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] # # * Basic Settings # user = mysql pid-file = /var/run/mysqld/mysqld.pid socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp language = /usr/share/mysql/english skip-external-locking # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. bind-address = 10.100.27.30 # # * Fine Tuning # key_buffer = 64M key_buffer_size = 512M max_allowed_packet = 16M thread_stack = 128K thread_cache_size = 8 # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP max_connections = 1000 table_cache = 1000 join_buffer_size = 2M tmp_table_size = 2G max_heap_table_size = 2G innodb_buffer_pool_size = 3G innodb_additional_mem_pool_size = 128M innodb_log_file_size = 100M log-slow-queries = /var/log/mysql/slow.log sort_buffer_size = 5M net_buffer_length = 5M read_buffer_size = 2M read_rnd_buffer_size = 12M thread_concurrency = 10 ft_min_word_len = 3 #thread_concurrency = 10 # # * Query Cache Configuration # query_cache_limit = 1M query_cache_size = 512M # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. #log = /var/log/mysql/mysql.log # # Error logging goes to syslog. This is a Debian improvement :) # # Here you can see queries with especially long duration #log_slow_queries = /var/log/mysql/mysql-slow.log #long_query_time = 2 #log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log expire_logs_days = 10 max_binlog_size = 100M #binlog_do_db = include_database_name #binlog_ignore_db = include_database_name # # * BerkeleyDB # # Using BerkeleyDB is now discouraged as its support will cease in 5.1.12. skip-bdb # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # You might want to disable InnoDB to shrink the mysqld process by circa 100MB. #skip-innodb # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 16M # # * NDB Cluster # # See /usr/share/doc/mysql-server-*/README.Debian for more information. # # The following configuration is read by the NDB Data Nodes (ndbd processes) # not from the NDB Management Nodes (ndb_mgmd processes). # # [MYSQL_CLUSTER] # ndb-connectstring=127.0.0.1 # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/

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  • SqlBulkCopy is slow, doesn't utilize full network speed

    - by Alex
    Hi, for that past couple of weeks I have been creating generic script that is able to copy databases. The goal is to be able to specify any database on some server and copy it to some other location, and it should only copy the specified content. The exact content to be copied over is specified in a configuration file. This script is going to be used on some 10 different databases and run weekly. And in the end we are copying only about 3%-20% of databases which are as large as 500GB. I have been using the SMO assemblies to achieve this. This is my first time working with SMO and it took a while to create generic way to copy the schema objects, filegroups ...etc. (Actually helped find some bad stored procs). Overall I have a working script which is lacking on performance (and at times times out) and was hoping you guys would be able to help. When executing the WriteToServer command to copy large amount of data ( 6GB) it reaches my timeout period of 1hr. Here is the core code for copying table data. The script is written in PowerShell. $query = ("SELECT * FROM $selectedTable " + $global:selectiveTables.Get_Item($selectedTable)).Trim() Write-LogOutput "Copying $selectedTable : '$query'" $cmd = New-Object Data.SqlClient.SqlCommand -argumentList $query, $source $cmd.CommandTimeout = 120; $bulkData = ([Data.SqlClient.SqlBulkCopy]$destination) $bulkData.DestinationTableName = $selectedTable; $bulkData.BulkCopyTimeout = $global:tableCopyDataTimeout # = 3600 $reader = $cmd.ExecuteReader(); $bulkData.WriteToServer($reader); # Takes forever here on large tables The source and target databases are located on different servers so I kept track of the network speed as well. The network utilization never went over 1% which was quite surprising to me. But when I just transfer some large files between the servers, the network utilization spikes up to 10%. I have tried setting the $bulkData.BatchSize to 5000 but nothing really changed. Increasing the BulkCopyTimeout to an even greater amount would only solve the timeout. I really would like to know why the network is not being used fully. Anyone else had this problem? Any suggestions on networking or bulk copy will be appreciated. And please let me know if you need more information. Thanks. UPDATE I have tweaked several options that increase the performance of SqlBulkCopy, such as setting the transaction logging to simple and providing a table lock to SqlBulkCopy instead of the default row lock. Also some tables are better optimized for certain batch sizes. Overall, the duration of the copy was decreased by some 15%. And what we will do is execute the copy of each database simultaneously on different servers. But I am still having a timeout issue when copying one of the databases. When copying one of the larger databases, there is a table for which I consistently get the following exception: System.Data.SqlClient.SqlException: Timeout expired. The timeout period elapsed prior to completion of the operation or the server is not responding. It is thrown about 16 after it starts copying the table which is no where near my BulkCopyTimeout. Even though I get the exception that table is fully copied in the end. Also, if I truncate that table and restart my process for that table only, the tables is copied over without any issues. But going through the process of copying that entire database fails always for that one table. I have tried executing the entire process and reseting the connection before copying that faulty table, but it still errored out. My SqlBulkCopy and Reader are closed after each table. Any suggestions as to what else could be causing the script to fail at the point each time?

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  • Is SQL Server DRI (ON DELETE CASCADE) slow?

    - by Aaronaught
    I've been analyzing a recurring "bug report" (perf issue) in one of our systems related to a particularly slow delete operation. Long story short: It seems that the CASCADE DELETE keys were largely responsible, and I'd like to know (a) if this makes sense, and (b) why it's the case. We have a schema of, let's say, widgets, those being at the root of a large graph of related tables and related-to-related tables and so on. To be perfectly clear, deleting from this table is actively discouraged; it is the "nuclear option" and users are under no illusions to the contrary. Nevertheless, it sometimes just has to be done. The schema looks something like this: Widgets | +--- Anvils (1:1) | | | +--- AnvilTestData (1:N) | +--- WidgetHistory (1:N) | +--- WidgetHistoryDetails (1:N) Nothing too scary, really. A Widget can be different types, an Anvil is a special type, so that relationship is 1:1 (or more accurately 1:0..1). Then there's a large amount of data - perhaps thousands of rows of AnvilTestData per Anvil collected over time, dealing with hardness, corrosion, exact weight, hammer compatibility, usability issues, and impact tests with cartoon heads. Then every Widget has a long, boring history of various types of transactions - production, inventory moves, sales, defect investigations, RMAs, repairs, customer complaints, etc. There might be 10-20k details for a single widget, or none at all, depending on its age. So, unsurprisingly, there's a CASCADE DELETE relationship at every level here. If a Widget needs to be deleted, it means something's gone terribly wrong and we need to erase any records of that widget ever existing, including its history, test data, etc. Again, nuclear option. Relations are all indexed, statistics are up to date. Normal queries are fast. The system tends to hum along pretty smoothly for everything except deletes. Getting to the point here, finally, for various reasons we only allow deleting one widget at a time, so a delete statement would look like this: DELETE FROM Widgets WHERE WidgetID = @WidgetID Pretty simple, innocuous looking delete... that takes over 2 minutes to run, for a widget with no data! After slogging through execution plans I was finally able to pick out the AnvilTestData and WidgetHistoryDetails deletes as the sub-operations with the highest cost. So I experimented with turning off the CASCADE (but keeping the actual FK, just setting it to NO ACTION) and rewriting the script as something very much like the following: DECLARE @AnvilID int SELECT @AnvilID = AnvilID FROM Anvils WHERE WidgetID = @WidgetID DELETE FROM AnvilTestData WHERE AnvilID = @AnvilID DELETE FROM WidgetHistory WHERE HistoryID IN ( SELECT HistoryID FROM WidgetHistory WHERE WidgetID = @WidgetID) DELETE FROM Widgets WHERE WidgetID = @WidgetID Both of these "optimizations" resulted in significant speedups, each one shaving nearly a full minute off the execution time, so that the original 2-minute deletion now takes about 5-10 seconds - at least for new widgets, without much history or test data. Just to be absolutely clear, there is still a CASCADE from WidgetHistory to WidgetHistoryDetails, where the fanout is highest, I only removed the one originating from Widgets. Further "flattening" of the cascade relationships resulted in progressively less dramatic but still noticeable speedups, to the point where deleting a new widget was almost instantaneous once all of the cascade deletes to larger tables were removed and replaced with explicit deletes. I'm using DBCC DROPCLEANBUFFERS and DBCC FREEPROCCACHE before each test. I've disabled all triggers that might be causing further slowdowns (although those would show up in the execution plan anyway). And I'm testing against older widgets, too, and noticing a significant speedup there as well; deletes that used to take 5 minutes now take 20-40 seconds. Now I'm an ardent supporter of the "SELECT ain't broken" philosophy, but there just doesn't seem to be any logical explanation for this behaviour other than crushing, mind-boggling inefficiency of the CASCADE DELETE relationships. So, my questions are: Is this a known issue with DRI in SQL Server? (I couldn't seem to find any references to this sort of thing on Google or here in SO; I suspect the answer is no.) If not, is there another explanation for the behaviour I'm seeing? If it is a known issue, why is it an issue, and are there better workarounds I could be using?

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  • Mysql 100% CPU + Slow query

    - by felipeclopes
    I'm using the RDS database from amazon with a some very big tables, and yesterday I started to face 100% CPU utilisation on the server and a bunch of slow query logs that were not happening before. I tried to check the queries that were running and faced this result from the explain command +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | businesses | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index; Using temporary; Using filesort | | 1 | SIMPLE | activities_businesses | ref | PRIMARY,index_activities_users_on_business_id,index_tweets_users_on_tweet_id_and_business_id | index_activities_users_on_business_id | 9 | const | 2252 | Using index condition; Using where | | 1 | SIMPLE | activities_b_taggings_975e9c4 | ref | taggings_idx | taggings_idx | 782 | const,myapp_production.activities_businesses.id,const | 1 | Using index condition; Using where | | 1 | SIMPLE | activities | eq_ref | PRIMARY,index_activities_on_created_at | PRIMARY | 8 | myapp_production.activities_businesses.activity_id | 1 | Using where | +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ Also checkin in the process list, I got something like this: +----+-----------------+-------------------------------------+----------------------------+---------+------+--------------+------------------------------------------------------------------------------------------------------+ | Id | User | Host | db | Command | Time | State | Info | +----+-----------------+-------------------------------------+----------------------------+---------+------+--------------+------------------------------------------------------------------------------------------------------+ | 1 | my_app | my_ip:57152 | my_app_production | Sleep | 0 | | NULL | | 2 | my_app | my_ip:57153 | my_app_production | Sleep | 2 | | NULL | | 3 | rdsadmin | localhost:49441 | NULL | Sleep | 9 | | NULL | | 6 | my_app | my_other_ip:47802 | my_app_production | Sleep | 242 | | NULL | | 7 | my_app | my_other_ip:47807 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 8 | my_app | my_other_ip:47809 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 9 | my_app | my_other_ip:47810 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 10 | my_app | my_other_ip:47811 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 11 | my_app | my_other_ip:47813 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | ... So based on the numbers, it looks like there is no reason to have a slow query, since the worst execution plan is the one that goes through 2k rows which is not much. Edit 1 Another information that might be useful is the slow query_log SET timestamp=1401457485; SELECT my_query... # User@Host: myapp[myapp] @ ip-10-195-55-233.ec2.internal [IP] Id: 435 # Query_time: 95.830497 Lock_time: 0.000178 Rows_sent: 0 Rows_examined: 1129387 Edit 2 After profiling, I got this result. The result have approximately 250 rows with two columns each. +----------------------+----------+ | state | duration | +----------------------+----------+ | Sending data | 272 | | removing tmp table | 0 | | optimizing | 0 | | Creating sort index | 0 | | init | 0 | | cleaning up | 0 | | executing | 0 | | checking permissions | 0 | | freeing items | 0 | | Creating tmp table | 0 | | query end | 0 | | statistics | 0 | | end | 0 | | System lock | 0 | | Opening tables | 0 | | logging slow query | 0 | | Sorting result | 0 | | starting | 0 | | closing tables | 0 | | preparing | 0 | +----------------------+----------+ Edit 3 Adding query as requested SELECT activities.share_count, activities.created_at FROM `activities_businesses` INNER JOIN `businesses` ON `businesses`.`id` = `activities_businesses`.`business_id` INNER JOIN `activities` ON `activities`.`id` = `activities_businesses`.`activity_id` JOIN taggings activities_b_taggings_975e9c4 ON activities_b_taggings_975e9c4.taggable_id = activities_businesses.id AND activities_b_taggings_975e9c4.taggable_type = 'ActivitiesBusiness' AND activities_b_taggings_975e9c4.tag_id = 104 AND activities_b_taggings_975e9c4.created_at >= '2014-04-30 13:36:44' WHERE ( businesses.id = 1 ) AND ( activities.created_at > '2014-04-30 13:36:44' ) AND ( activities.created_at < '2014-05-30 12:27:03' ) ORDER BY activities.created_at; Edit 4 There may be a chance that the indexes are not being applied due to difference in column type between the taggings and the activities_businesses, on the taggable_id column. mysql> SHOW COLUMNS FROM activities_businesses; +-------------+------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | activity_id | bigint(20) | YES | MUL | NULL | | | business_id | bigint(20) | YES | MUL | NULL | | +-------------+------------+------+-----+---------+----------------+ 3 rows in set (0.01 sec) mysql> SHOW COLUMNS FROM taggings; +---------------+--------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+--------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | tag_id | int(11) | YES | MUL | NULL | | | taggable_id | bigint(20) | YES | | NULL | | | taggable_type | varchar(255) | YES | | NULL | | | tagger_id | int(11) | YES | | NULL | | | tagger_type | varchar(255) | YES | | NULL | | | context | varchar(128) | YES | | NULL | | | created_at | datetime | YES | | NULL | | +---------------+--------------+------+-----+---------+----------------+ So it is examining way more rows than it shows in the explain query, probably because some indexes are not being applied. Do you guys can help m with that?

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  • Data adapter not filling my dataset

    - by Doug Ancil
    I have the following code: Imports System.Data.SqlClient Public Class Main Protected WithEvents DataGridView1 As DataGridView Dim instForm2 As New Exceptions Private Sub Button1_Click_1(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles startpayrollButton.Click Dim ssql As String = "select MAX(payrolldate) AS [payrolldate], " & _ "dateadd(dd, ((datediff(dd, '17530107', MAX(payrolldate))/7)*7)+7, '17530107') AS [Sunday]" & _ "from dbo.payroll" & _ " where payrollran = 'no'" Dim oCmd As System.Data.SqlClient.SqlCommand Dim oDr As System.Data.SqlClient.SqlDataReader oCmd = New System.Data.SqlClient.SqlCommand Try With oCmd .Connection = New System.Data.SqlClient.SqlConnection("Initial Catalog=mdr;Data Source=xxxxx;uid=xxxxx;password=xxxxx") .Connection.Open() .CommandType = CommandType.Text .CommandText = ssql oDr = .ExecuteReader() End With If oDr.Read Then payperiodstartdate = oDr.GetDateTime(1) payperiodenddate = payperiodstartdate.AddSeconds(604799) Dim ButtonDialogResult As DialogResult ButtonDialogResult = MessageBox.Show(" The Next Payroll Start Date is: " & payperiodstartdate.ToString() & System.Environment.NewLine & " Through End Date: " & payperiodenddate.ToString()) If ButtonDialogResult = Windows.Forms.DialogResult.OK Then exceptionsButton.Enabled = True startpayrollButton.Enabled = False End If End If oDr.Close() oCmd.Connection.Close() Catch ex As Exception MessageBox.Show(ex.Message) oCmd.Connection.Close() End Try End Sub Private Sub Button2_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles exceptionsButton.Click Dim connection As System.Data.SqlClient.SqlConnection Dim adapter As System.Data.SqlClient.SqlDataAdapter = New System.Data.SqlClient.SqlDataAdapter Dim connectionString As String = "Initial Catalog=mdr;Data Source=xxxxx;uid=xxxxx;password=xxxxx" Dim ds As New DataSet Dim _sql As String = "SELECT [Exceptions].Employeenumber,[Exceptions].exceptiondate, [Exceptions].starttime, [exceptions].endtime, [Exceptions].code, datediff(minute, starttime, endtime) as duration INTO scratchpad3" & _ " FROM Employees INNER JOIN Exceptions ON [Exceptions].EmployeeNumber = [Exceptions].Employeenumber" & _ " where [Exceptions].exceptiondate between @payperiodstartdate and @payperiodenddate" & _ " GROUP BY [Exceptions].Employeenumber, [Exceptions].Exceptiondate, [Exceptions].starttime, [exceptions].endtime," & _ " [Exceptions].code, [Exceptions].exceptiondate" connection = New SqlConnection(connectionString) connection.Open() Dim _CMD As SqlCommand = New SqlCommand(_sql, connection) _CMD.Parameters.AddWithValue("@payperiodstartdate", payperiodstartdate) _CMD.Parameters.AddWithValue("@payperiodenddate", payperiodenddate) adapter.SelectCommand = _CMD Try adapter.Fill(ds) If ds Is Nothing OrElse ds.Tables.Count = 0 OrElse ds.Tables(0).Rows.Count = 0 Then 'it's empty MessageBox.Show("There was no data for this time period. Press Ok to continue", "No Data") connection.Close() Exceptions.saveButton.Enabled = False Exceptions.Hide() Else connection.Close() End If Catch ex As Exception MessageBox.Show(ex.ToString) connection.Close() End Try Exceptions.Show() End Sub Private Sub payrollButton_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles payrollButton.Click Payrollfinal.Show() End Sub End Class and when I run my program and press this button Private Sub Button2_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles exceptionsButton.Click I have my date range within a time that I know that my dataset should produce a result, but when I put a line break in my code here: adapter.Fill(ds) and look at it in debug, I show a table value of 0. If I run the same query that I have to produce these results in sql analyser, I see 1 result. Can someone see why my query on my form produces a different result than the sql analyser does? Also here is my schema for my two tables: Exceptions employeenumber varchar no 50 yes no no SQL_Latin1_General_CP1_CI_AS exceptiondate datetime no 8 yes (n/a) (n/a) NULL starttime datetime no 8 yes (n/a) (n/a) NULL endtime datetime no 8 yes (n/a) (n/a) NULL duration varchar no 50 yes no no SQL_Latin1_General_CP1_CI_AS code varchar no 50 yes no no SQL_Latin1_General_CP1_CI_AS approvedby varchar no 50 yes no no SQL_Latin1_General_CP1_CI_AS approved varchar no 50 yes no no SQL_Latin1_General_CP1_CI_AS time timestamp no 8 yes (n/a) (n/a) NULL employees employeenumber varchar no 50 no no no SQL_Latin1_General_CP1_CI_AS name varchar no 50 no no no SQL_Latin1_General_CP1_CI_AS initials varchar no 50 no no no SQL_Latin1_General_CP1_CI_AS loginname1 varchar no 50 yes no no SQL_Latin1_General_CP1_CI_AS

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  • mysql_close doesn't kill locked sql requests

    - by Nikita
    I use mysqld Ver 5.1.37-2-log for debian-linux-gnu I perform mysql calls from c++ code with functions mysql_query. The problem occurs when mysql_query execute procedure, procedure locked on locked table, so mysql_query hangs. If send kill signal to application then we can see lock until table is locked. Create the following SQL table and procedure CREATE TABLE IF NOT EXISTS `tabletolock` ( `id` INT NOT NULL AUTO_INCREMENT, PRIMARY KEY (`id`) )ENGINE = InnoDB; DELIMITER $$ DROP PROCEDURE IF EXISTS `LOCK_PROCEDURE` $$ CREATE PROCEDURE `LOCK_PROCEDURE`() BEGIN SELECT id INTO @id FROM tabletolock; END $$ DELOMITER; There are sql commands to reproduce the problem: 1. in one terminal execute lock tables tabletolock write; 2. in another terminal execute call LOCK_PROCEDURE(); 3. In first terminal exeute show processlist and see | 2492 | root | localhost | syn_db | Query | 12 | Locked | SELECT id INTO @id FROM tabletolock | Then perfrom Ctrl-C in second terminal to interrupt our procudere and see processlist again. It is not changed, we already see locked select request and can teminate it by unlock tables or kill commands. Problem described is occured with mysql command line client. Also such problem exists when we use functions mysql_query and mysql_close. Example of c code: #include <iostream> #include <mysql/mysql.h> #include <mysql/errmsg.h> #include <signal.h> // g++ -Wall -g -fPIC -lmysqlclient dbtest.cpp using namespace std; MYSQL * connection = NULL; void closeconnection() { if(connection != NULL) { cout << "close connection !\n"; mysql_close(connection); mysql_thread_end(); delete connection; mysql_library_end(); } } void sigkill(int s) { closeconnection(); signal(SIGINT, NULL); raise(s); } int main(int argc, char ** argv) { signal(SIGINT, sigkill); connection = new MYSQL; mysql_init(connection); mysql_options(connection, MYSQL_READ_DEFAULT_GROUP, "nnfc"); if (!mysql_real_connect(connection, "127.0.0.1", "user", "password", "db", 3306, NULL, CLIENT_MULTI_RESULTS)) { delete connection; cout << "cannot connect\n"; return -1; } cout << "before procedure call\n"; mysql_query(connection, "CALL LOCK_PROCEDURE();"); cout << "after procedure call\n"; closeconnection(); return 0; } Compile it, and perform the folloing actions: 1. in first terminal local tables tabletolock write; 2. run program ./a.out 3. interrupt program Ctrl-C. on the screen we see that closeconnection function is called, so connection is closed. 4. in first terminal execute show processlist and see that procedure was not intrrupted. My question is how to terminate such locked calls from c code? Thank you in advance!

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  • @OneToMany association joining on the wrong field

    - by april26
    I have 2 tables, devices which contains a list of devices and dev_tags, which contains a list of asset tags for these devices. The tables join on dev_serial_num, which is the primary key of neither table. The devices are unique on their ip_address field and they have a primary key identified by dev_id. The devices "age out" after 2 weeks. Therefore, the same piece of hardware can show up more than once in devices. I mention that to explain why there is a OneToMany relationship between dev_tags and devices where it seems that this should be a OneToOne relationship. So I have my 2 entities @Entity @Table(name = "dev_tags") public class DevTags implements Serializable { private Integer tagId; private String devTagId; private String devSerialNum; private List<Devices> devices; @Id @GeneratedValue @Column(name = "tag_id") public Integer getTagId() { return tagId; } public void setTagId(Integer tagId) { this.tagId = tagId; } @Column(name="dev_tag_id") public String getDevTagId() { return devTagId; } public void setDevTagId(String devTagId) { this.devTagId = devTagId; } @Column(name="dev_serial_num") public String getDevSerialNum() { return devSerialNum; } public void setDevSerialNum(String devSerialNum) { this.devSerialNum = devSerialNum; } @OneToMany(mappedBy="devSerialNum") public List<Devices> getDevices() { return devices; } public void setDevices(List<Devices> devices) { this.devices = devices; } } and this one public class Devices implements java.io.Serializable { private Integer devId; private Integer officeId; private String devSerialNum; private String devPlatform; private String devName; private OfficeView officeView; private DevTags devTag; public Devices() { } @Id @GeneratedValue(strategy = IDENTITY) @Column(name = "dev_id", unique = true, nullable = false) public Integer getDevId() { return this.devId; } public void setDevId(Integer devId) { this.devId = devId; } @Column(name = "office_id", nullable = false, insertable=false, updatable=false) public Integer getOfficeId() { return this.officeId; } public void setOfficeId(Integer officeId) { this.officeId = officeId; } @Column(name = "dev_serial_num", nullable = false, length = 64, insertable=false, updatable=false) @NotNull @Length(max = 64) public String getDevSerialNum() { return this.devSerialNum; } public void setDevSerialNum(String devSerialNum) { this.devSerialNum = devSerialNum; } @Column(name = "dev_platform", nullable = false, length = 64) @NotNull @Length(max = 64) public String getDevPlatform() { return this.devPlatform; } public void setDevPlatform(String devPlatform) { this.devPlatform = devPlatform; } @Column(name = "dev_name") public String getDevName() { return devName; } public void setDevName(String devName) { this.devName = devName; } @ManyToOne(fetch = FetchType.LAZY) @JoinColumn(name = "office_id") public OfficeView getOfficeView() { return officeView; } public void setOfficeView(OfficeView officeView) { this.officeView = officeView; } @ManyToOne() @JoinColumn(name="dev_serial_num") public DevTags getDevTag() { return devTag; } public void setDevTag(DevTags devTag) { this.devTag = devTag; } } I messed around a lot with @JoinColumn(name=) and the mappedBy attribute of @OneToMany and I just cannot get this right. I finally got the darn thing to compile, but the query is still trying to join devices.dev_serial_num to dev_tags.tag_id, the @Id for this entity. Here is the transcript from the console: 13:12:16,970 INFO [STDOUT] Hibernate: select devices0_.office_id as office5_2_, devices0_.dev_id as dev1_2_, devices0_.dev_id as dev1_156_1_, devices0_.dev_name as dev2_156_1_, devices0_.dev_platform as dev3_156_1_, devices0_.dev_serial_num as dev4_156_1_, devices0_.office_id as office5_156_1_, devtags1_.tag_id as tag1_157_0_, devtags1_.comment as comment157_0_, devtags1_.dev_serial_num as dev3_157_0_, devtags1_.dev_tag_id as dev4_157_0_ from ond.devices devices0_ left outer join ond.dev_tags devtags1_ on devices0_.dev_serial_num=devtags1_.tag_id where devices0_.office_id=? 13:12:16,970 INFO [IntegerType] could not read column value from result set: dev4_156_1_; Invalid value for getInt() - 'FDO1129Y2U4' 13:12:16,970 WARN [JDBCExceptionReporter] SQL Error: 0, SQLState: S1009 13:12:16,970 ERROR [JDBCExceptionReporter] Invalid value for getInt() - 'FDO1129Y2U4' That value for getInt() 'FD01129Y2U4' is a serial number, definitely not an Int! What am I missing/misunderstanding here? Can I join 2 tables on any fields I want or does at least one have to be a primary key?

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  • I want to use blur function instead mouseup function

    - by yossi
    I have the Demo Table which I can click on the cell(td tag) and I can change the value on it.direct php DataBase. to do that I need to contain two tags.1 - span. 2 - input. like the below. <td class='Name'> <span id="spanName1" class="text" style="display: inline;"> Somevalue </span> <input type="text" value="Somevalue" class="edittd" id="inputName1" style="display: none; "> </td> to control on the data inside the cell I use in jquery .mouseup function. mouseup work but also make truble. I need to replace it with blur function but when I try to replace mouseup with blur the program thas not work becose, when I click on the cell I able to enter the input tag and I can change the value but I can't Successful to Leave the tag/field by clicking out side the table, which alow me to update the DataBase you can see that Demo with blur Here. what you advice me to do? $(".edittd").mouseup(function() { return false; }); //************* $(document).mouseup(function() { $('#span' + COLUME + ROW).show(); $('#input'+ COLUME + ROW ).hide(); VAL = $("#input" + COLUME + ROW).val(); $("#span" + COLUME + ROW).html(VAL); if(STATUS != VAL){ //******ajax code //dataString = $.trim(this.value); $.ajax({ type: "POST", dataType: 'html', url: "./public/php/ajax.php", data: 'COLUME='+COLUME+'&ROW='+ROW+'&VAL='+VAL, //{"dataString": dataString} cache: false, success: function(data) { $("#statuS").html(data); } }); //******end ajax $('#statuS').removeClass('statuSnoChange') .addClass('statuSChange'); $('#statuS').html('THERE IS CHANGE'); $('#tables').load('TableEdit2.php'); } else { //alert(DATASTRING+'status not true'); } });//End mouseup function I change it to: $(document).ready(function() { var COLUMES,COLUME,VALUE,VAL,ROWS,ROW,STATUS,DATASTRING; $('td').click(function() { COLUME = $(this).attr('class'); }); //**************** $('tr').click(function() { ROW = $(this).attr('id'); $('#display_Colume_Raw').html(COLUME+ROW); $('#span' + COLUME + ROW).hide(); $('#input'+ COLUME + ROW ).show(); STATUS = $("#input" + COLUME + ROW).val(); }); //******************** $(document).blur(function() { $('#span' + COLUME + ROW).show(); $('#input'+ COLUME + ROW ).hide(); VAL = $("#input" + COLUME + ROW).val(); $("#span" + COLUME + ROW).html(VAL); if(STATUS != VAL){ //******ajax code //dataString = $.trim(this.value); $.ajax({ type: "POST", dataType: 'html', url: "./public/php/ajax.php", data: 'COLUME='+COLUME+'&ROW='+ROW+'&VAL='+VAL, //{"dataString": dataString} cache: false, success: function(data) { $("#statuS").html(data); } }); //******end ajax $('#statuS').removeClass('statuSnoChange') .addClass('statuSChange'); $('#statuS').html('THERE IS CHANGE'); $('#tables').load('TableEdit2.php'); } else { //alert(DATASTRING+'status not true'); } });//End mouseup function $('#save').click (function(){ var input1,input2,input3,input4=""; input1 = $('#input1').attr('value'); input2 = $('#input2').attr('value'); input3 = $('#input3').attr('value'); input4 = $('#input4').attr('value'); $.ajax({ type: "POST", url: "./public/php/ajax.php", data: "input1="+ input1 +"&input2="+ input2 +"&input3="+ input3 +"&input4="+ input4, success: function(data){ $("#statuS").html(data); $('#tbl').hide(function(){$('div.success').fadeIn();}); $('#tables').load('TableEdit2.php'); } }); }); }); Thx

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  • Muti-Schema Privileges for a Table Trigger in an Oracle Database

    - by sisslack
    I'm trying to write a table trigger which queries another table that is outside the schema where the trigger will reside. Is this possible? It seems like I have no problem querying tables in my schema but I get: Error: ORA-00942: table or view does not exist when trying trying to query tables outside my schema. EDIT My apologies for not providing as much information as possible the first time around. I was under the impression this question was more simple. I'm trying create a trigger on a table that changes some fields on a newly inserted row based on the existence of some data that may or may not be in a table that is in another schema. The user account that I'm using to create the trigger does have the permissions to run the queries independently. In fact, I've had my trigger print the query I'm trying to run and was able to run it on it's own successfully. I should also note that I'm building the query dynamically by using the EXECUTE IMMEDIATE statement. Here's an example: CREATE OR REPLACE TRIGGER MAIN_SCHEMA.EVENTS BEFORE INSERT ON MAIN_SCHEMA.EVENTS REFERENCING OLD AS OLD NEW AS NEW FOR EACH ROW DECLARE rtn_count NUMBER := 0; table_name VARCHAR2(17) := :NEW.SOME_FIELD; key_field VARCHAR2(20) := :NEW.ANOTHER_FIELD; BEGIN CASE WHEN (key_field = 'condition_a') THEN EXECUTE IMMEDIATE 'select count(*) from OTHER_SCHEMA_A.'||table_name||' where KEY_FIELD='''||key_field||'''' INTO rtn_count; WHEN (key_field = 'condition_b') THEN EXECUTE IMMEDIATE 'select count(*) from OTHER_SCHEMA_B.'||table_name||' where KEY_FIELD='''||key_field||'''' INTO rtn_count; WHEN (key_field = 'condition_c') THEN EXECUTE IMMEDIATE 'select count(*) from OTHER_SCHEMA_C.'||table_name||' where KEY_FIELD='''||key_field||'''' INTO rtn_count; END CASE; IF (rtn_count > 0) THEN -- change some fields that are to be inserted END IF; END; The trigger seams to fail on the EXECUTE IMMEDIATE with the previously mentioned error. EDIT I have done some more research and I can offer more clarification. The user account I'm using to create this trigger is not MAIN_SCHEMA or any one of the OTHER_SCHEMA_Xs. The account I'm using (ME) is given privileges to the involved tables via the schema users themselves. For example (USER_TAB_PRIVS): GRANTOR GRANTEE TABLE_SCHEMA TABLE_NAME PRIVILEGE GRANTABLE HIERARCHY MAIN_SCHEMA ME MAIN_SCHEMA EVENTS DELETE NO NO MAIN_SCHEMA ME MAIN_SCHEMA EVENTS INSERT NO NO MAIN_SCHEMA ME MAIN_SCHEMA EVENTS SELECT NO NO MAIN_SCHEMA ME MAIN_SCHEMA EVENTS UPDATE NO NO OTHER_SCHEMA_X ME OTHER_SCHEMA_X TARGET_TBL SELECT NO NO And I have the following system privileges (USER_SYS_PRIVS): USERNAME PRIVILEGE ADMIN_OPTION ME ALTER ANY TRIGGER NO ME CREATE ANY TRIGGER NO ME UNLIMITED TABLESPACE NO And this is what I found in the Oracle documentation: To create a trigger in another user's schema, or to reference a table in another schema from a trigger in your schema, you must have the CREATE ANY TRIGGER system privilege. With this privilege, the trigger can be created in any schema and can be associated with any user's table. In addition, the user creating the trigger must also have EXECUTE privilege on the referenced procedures, functions, or packages. Here: Oracle Doc So it looks to me like this should work, but I'm not sure about the "EXECUTE privilege" it's referring to in the doc.

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  • PHP mysql multi-table search returning different table and field data row after row

    - by Kinyanjui Kamau
    Hi Guys, I am building a social networking site that is dedicated to nightclubs and night events. Among other tables, I have a users table, events table and establishments table. I am really intrigued with how Facebook in particular is able to query and return matches of not just users but also pages, ads etc row after row. Im sure most who are reading this have tried the facebook search My question is in my case, should I: Perform 3 separate LIKE %search% on each of the tables on search.php. Draw up 3 separate tables to show the results of what matches in the relevant queries which are collapsed when empty(on the same search.php) ie In search.php //query users table $query_user = "SELECT user_first_name, user_last_name, username, picture_thumb_url, avatar FROM users JOIN picture ON users.user_id = picture.user_id AND picture.avatar=1 ORDER BY users.user_id"; $result_users = mysql_query($query_user, $connections) or die(mysql_error()); $row_result_users = mysql_fetch_assoc($wid_updates); //query events table $query_event = "SELECT event_thumb_url, event_name, event_venue, event_date FROM event WHERE event_name LIKE '%".$search_value."%'"; $event = mysql_query($query_event, $connections) or die(mysql_error()); $row_event = mysql_fetch_assoc($event); $totalRows_event = mysql_num_rows($event); //query establishments table $query_establishment = "SELECT establishment_thumb_url, establishment_name, location_id, establishment_pricing FROM establishment WHERE establishment_name LIKE '%".$search_value."%'"; $establishment = mysql_query($query_establishment, $connections) or die(mysql_error()); $row_establishment = mysql_fetch_assoc($establishment); $totalRows_establishment = mysql_num_rows($establishment); My html: <table max-width="500" name="users" border="0"> <tr> <td width="50" height="50"></td> <td width="150"></td> <td width="150"></td> <td width="150"></td> </tr> </table> <table width="500" name="events" border="0"> <tr> <td width="50" height="50"><a href="#profile.php"><img src="Images/<?php echo $row_event['event_thumb_url']; ?>" border="0" height="50" width="50"/></a></td> <td width="150"><?php echo $row_event['event_name']; ?></td> <td width="150"><?php echo $row_event['event_venue']; ?></td> <td width="150"><?php echo $row_event['event_date']; ?></td> </tr> </table> <table width="500" name="establishments" border="0"> <tr> <td width="50" height="50"><a href="#profile.php"><img src="Establishment_Images/<?php echo $row_establishment['establishment_thumb_url']; ?>" border="0" height="50" width="50"/></a></td> <td width="150"><?php echo $row_establishment['establishment_name']; ?></td> <td width="150"><?php echo $row_establishment['location_id']; ?></td> <td width="150"><?php echo $row_establishment['establishment_pricing']; ?></td> </tr> </table> I haven't populated the PHP echo's for the user table. This is just to give you an idea of what I am trying to do. Any assistance?

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  • How to make MySQL utilize available system resources, or find "the real problem"?

    - by anonymous coward
    This is a MySQL 5.0.26 server, running on SuSE Enterprise 10. This may be a Serverfault question. The web user interface that uses these particular queries (below) is showing sometimes 30+, even up to 120+ seconds at the worst, to generate the pages involved. On development, when the queries are run alone, they take up to 20 seconds on the first run (with no query cache enabled) but anywhere from 2 to 7 seconds after that - I assume because the tables and indexes involved have been placed into ram. From what I can tell, the longest load times are caused by Read/Update Locking. These are MyISAM tables. So it looks like a long update comes in, followed by a couple 7 second queries, and they're just adding up. And I'm fine with that explanation. What I'm not fine with is that MySQL doesn't appear to be utilizing the hardware it's on, and while the bottleneck seems to be the database, I can't understand why. I would say "throw more hardware at it", but we did and it doesn't appear to have changed the situation. Viewing a 'top' during the slowest times never shows much cpu or memory utilization by mysqld, as if the server is having no trouble at all - but then, why are the queries taking so long? How can I make MySQL use the crap out of this hardware, or find out what I'm doing wrong? Extra Details: On the "Memory Health" tab in the MySQL Administrator (for Windows), the Key Buffer is less than 1/8th used - so all the indexes should be in RAM. I can provide a screen shot of any graphs that might help. So desperate to fix this issue. Suffice it to say, there is legacy code "generating" these queries, and they're pretty much stuck the way they are. I have tried every combination of Indexes on the tables involved, but any suggestions are welcome. Here's the current Create Table statement from development (the 'experimental' key I have added, seems to help a little, for the example query only): CREATE TABLE `registration_task` ( `id` varchar(36) NOT NULL default '', `date_entered` datetime NOT NULL default '0000-00-00 00:00:00', `date_modified` datetime NOT NULL default '0000-00-00 00:00:00', `assigned_user_id` varchar(36) default NULL, `modified_user_id` varchar(36) default NULL, `created_by` varchar(36) default NULL, `name` varchar(80) NOT NULL default '', `status` varchar(255) default NULL, `date_due` date default NULL, `time_due` time default NULL, `date_start` date default NULL, `time_start` time default NULL, `parent_id` varchar(36) NOT NULL default '', `priority` varchar(255) NOT NULL default '9', `description` text, `order_number` int(11) default '1', `task_number` int(11) default NULL, `depends_on_id` varchar(36) default NULL, `milestone_flag` varchar(255) default NULL, `estimated_effort` int(11) default NULL, `actual_effort` int(11) default NULL, `utilization` int(11) default '100', `percent_complete` int(11) default '0', `deleted` tinyint(1) NOT NULL default '0', `wf_task_id` varchar(36) default '0', `reg_field` varchar(8) default '', `date_offset` int(11) default '0', `date_source` varchar(10) default '', `date_completed` date default '0000-00-00', `completed_id` varchar(36) default NULL, `original_name` varchar(80) default NULL, PRIMARY KEY (`id`), KEY `idx_reg_task_p` (`deleted`,`parent_id`), KEY `By_Assignee` (`assigned_user_id`,`deleted`), KEY `status_assignee` (`status`,`deleted`), KEY `experimental` (`deleted`,`status`,`assigned_user_id`,`parent_id`,`date_due`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 And one of the ridiculous queries in question: SELECT users.user_name assigned_user_name, registration.FIELD001 parent_name, registration_task.status status, registration_task.date_modified date_modified, registration_task.date_due date_due, registration.FIELD240 assigned_wf, if(LENGTH(registration_task.description)>0,1,0) has_description, registration_task.* FROM registration_task LEFT JOIN users ON registration_task.assigned_user_id=users.id LEFT JOIN registration ON registration_task.parent_id=registration.id where (registration_task.status != 'Completed' AND registration.FIELD001 LIKE '%' AND registration_task.name LIKE '%' AND registration.FIELD060 LIKE 'GN001472%') AND registration_task.deleted=0 ORDER BY date_due asc LIMIT 0,20; my.cnf - '[mysqld]' section. [mysqld] port = 3306 socket = /var/lib/mysql/mysql.sock skip-locking key_buffer = 384M max_allowed_packet = 100M table_cache = 2048 sort_buffer_size = 2M net_buffer_length = 100M read_buffer_size = 2M read_rnd_buffer_size = 160M myisam_sort_buffer_size = 128M query_cache_size = 16M query_cache_limit = 1M EXPLAIN above query, without additional index: +----+-------------+-------------------+--------+--------------------------------+----------------+---------+------------------------------------------------+---------+-----------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------------+--------+--------------------------------+----------------+---------+------------------------------------------------+---------+-----------------------------+ | 1 | SIMPLE | registration_task | ref | idx_reg_task_p,status_assignee | idx_reg_task_p | 1 | const | 1067354 | Using where; Using filesort | | 1 | SIMPLE | registration | eq_ref | PRIMARY,gbl | PRIMARY | 8 | sugarcrm401.registration_task.parent_id | 1 | Using where | | 1 | SIMPLE | users | ref | PRIMARY | PRIMARY | 38 | sugarcrm401.registration_task.assigned_user_id | 1 | | +----+-------------+-------------------+--------+--------------------------------+----------------+---------+------------------------------------------------+---------+-----------------------------+ EXPLAIN above query, with 'experimental' index: +----+-------------+-------------------+--------+-----------------------------------------------------------+------------------+---------+------------------------------------------------+--------+-----------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------------+--------+-----------------------------------------------------------+------------------+---------+------------------------------------------------+--------+-----------------------------+ | 1 | SIMPLE | registration_task | range | idx_reg_task_p,status_assignee,NewIndex1,tcg_experimental | tcg_experimental | 259 | NULL | 103345 | Using where; Using filesort | | 1 | SIMPLE | registration | eq_ref | PRIMARY,gbl | PRIMARY | 8 | sugarcrm401.registration_task.parent_id | 1 | Using where | | 1 | SIMPLE | users | ref | PRIMARY | PRIMARY | 38 | sugarcrm401.registration_task.assigned_user_id | 1 | | +----+-------------+-------------------+--------+-----------------------------------------------------------+------------------+---------+------------------------------------------------+--------+-----------------------------+

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  • Which of CouchDB or MongoDB suits my needs?

    - by vonconrad
    Where I work, we use Ruby on Rails to create both backend and frontend applications. Usually, these applications interact with the same MySQL database. It works great for a majority of our data, but we have one situation which I would like to move to a NoSQL environment. We have clients, and our clients have what we call "inventories"--one or more of them. An inventory can have many thousands of items. This is currently done through two relational database tables, inventories and inventory_items. The problems start when two different inventories have different parameters: # Inventory item from inventory 1, televisions { inventory_id: 1 sku: 12345 name: Samsung LCD 40 inches model: 582903-4 brand: Samsung screen_size: 40 type: LCD price: 999.95 } # Inventory item from inventory 2, accomodation { inventory_id: 2 sku: 48cab23fa name: New York Hilton accomodation_type: hotel star_rating: 5 price_per_night: 395 } Since we obviously can't use brand or star_rating as the column name in inventory_items, our solution so far has been to use generic column names such as text_a, text_b, float_a, int_a, etc, and introduce a third table, inventory_schemas. The tables now look like this: # Inventory schema for inventory 1, televisions { inventory_id: 1 int_a: sku text_a: name text_b: model text_c: brand int_b: screen_size text_d: type float_a: price } # Inventory item from inventory 1, televisions { inventory_id: 1 int_a: 12345 text_a: Samsung LCD 40 inches text_b: 582903-4 text_c: Samsung int_a: 40 text_d: LCD float_a: 999.95 } This has worked well... up to a point. It's clunky, it's unintuitive and it lacks scalability. We have to devote resources to set up inventory schemas. Using separate tables is not an option. Enter NoSQL. With it, we could let each and every item have their own parameters and still store them together. From the research I've done, it certainly seems like a great alterative for this situation. Specifically, I've looked at CouchDB and MongoDB. Both look great. However, there are a few other bits and pieces we need to be able to do with our inventory: We need to be able to select items from only one (or several) inventories. We need to be able to filter items based on its parameters (eg. get all items from inventory 2 where type is 'hotel'). We need to be able to group items based on parameters (eg. get the lowest price from items in inventory 1 where brand is 'Samsung'). We need to (potentially) be able to retrieve thousands of items at a time. We need to be able to access the data from multiple applications; both backend (to process data) and frontend (to display data). Rapid bulk insertion is desired, though not required. Based on the structure, and the requirements, are either CouchDB or MongoDB suitable for us? If so, which one will be the best fit? Thanks for reading, and thanks in advance for answers. EDIT: One of the reasons I like CouchDB is that it would be possible for us in the frontend application to request data via JavaScript directly from the server after page load, and display the results without having to use any backend code whatsoever. This would lead to better page load and less server strain, as the fetching/processing of the data would be done client-side.

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  • HttpWebRequest and Ignoring SSL Certificate Errors

    - by Rick Strahl
    Man I can't believe this. I'm still mucking around with OFX servers and it drives me absolutely crazy how some these servers are just so unbelievably misconfigured. I've recently hit three different 3 major brokerages which fail HTTP validation with bad or corrupt certificates at least according to the .NET WebRequest class. What's somewhat odd here though is that WinInet seems to find no issue with these servers - it's only .NET's Http client that's ultra finicky. So the question then becomes how do you tell HttpWebRequest to ignore certificate errors? In WinInet there used to be a host of flags to do this, but it's not quite so easy with WebRequest. Basically you need to configure the CertificatePolicy on the ServicePointManager by creating a custom policy. Not exactly trivial. Here's the code to hook it up: public bool CreateWebRequestObject(string Url) {    try     {        this.WebRequest =  (HttpWebRequest) System.Net.WebRequest.Create(Url);         if (this.IgnoreCertificateErrors)            ServicePointManager.CertificatePolicy = delegate { return true; };}One thing to watch out for is that this an application global setting. There's one global ServicePointManager and once you set this value any subsequent requests will inherit this policy as well, which may or may not be what you want. So it's probably a good idea to set the policy when the app starts and leave it be - otherwise you may run into odd behavior in some situations especially in multi-thread situations.Another way to deal with this is in you application .config file. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} <configuration>   <system.net>     <settings>       <servicePointManager           checkCertificateName="false"           checkCertificateRevocationList="false"                />     </settings>   </system.net> </configuration> This seems to work most of the time, although I've seen some situations where it doesn't, but where the code implementation works which is frustrating. The .config settings aren't as inclusive as the programmatic code that can ignore any and all cert errors - shrug. Anyway, the code approach got me past the stopper issue. It still amazes me that theses OFX servers even require this. After all this is financial data we're talking about here. The last thing I want to do is disable extra checks on the certificates. Well I guess I shouldn't be surprised - these are the same companies that apparently don't believe in XML enough to generate valid XML (or even valid SGML for that matter)...© Rick Strahl, West Wind Technologies, 2005-2011Posted in .NET  CSharp  HTTP  

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  • SQL SERVER – Shrinking NDF and MDF Files – Readers’ Opinion

    - by pinaldave
    Previously, I had written a blog post about SQL SERVER – Shrinking NDF and MDF Files – A Safe Operation. After that, I have written the following blog post that talks about the advantage and disadvantage of Shrinking and why one should not be Shrinking a file SQL SERVER – SHRINKFILE and TRUNCATE Log File in SQL Server 2008. On this subject, SQL Server Expert Imran Mohammed left an excellent comment. I just feel that his comment is worth a big article itself. For everybody to read his wonderful explanation, I am posting this blog post here. Thanks Imran! Shrinking Database always creates performance degradation and increases fragmentation in the database. I suggest that you keep that in mind before you start reading the following comment. If you are going to say Shrinking Database is bad and evil, here I am saying it first and loud. Now, the comment of Imran is written while keeping in mind only the process showing how the Shrinking Database Operation works. Imran has already explained his understanding and requests further explanation. I have removed the Best Practices section from Imran’s comments, as there are a few corrections. Comments from Imran - Before I explain to you the concept of Shrink Database, let us understand the concept of Database Files. When we create a new database inside the SQL Server, it is typical that SQl Server creates two physical files in the Operating System: one with .MDF Extension, and another with .LDF Extension. .MDF is called as Primary Data File. .LDF is called as Transactional Log file. If you add one or more data files to a database, the physical file that will be created in the Operating System will have an extension of .NDF, which is called as Secondary Data File; whereas, when you add one or more log files to a database, the physical file that will be created in the Operating System will have the same extension as .LDF. The questions now are, “Why does a new data file have a different extension (.NDF)?”, “Why is it called as a secondary data file?” and, “Why is .MDF file called as a primary data file?” Answers: Note: The following explanation is based on my limited knowledge of SQL Server, so experts please do comment. A data file with a .MDF extension is called a Primary Data File, and the reason behind it is that it contains Database Catalogs. Catalogs mean Meta Data. Meta Data is “Data about Data”. An example for Meta Data includes system objects that store information about other objects, except the data stored by the users. sysobjects stores information about all objects in that database. sysindexes stores information about all indexes and rows of every table in that database. syscolumns stores information about all columns that each table has in that database. sysusers stores how many users that database has. Although Meta Data stores information about other objects, it is not the transactional data that a user enters; rather, it’s a system data about the data. Because Primary Data File (.MDF) contains important information about the database, it is treated as a special file. It is given the name Primary Data file because it contains the Database Catalogs. This file is present in the Primary File Group. You can always create additional objects (Tables, indexes etc.) in the Primary data file (This file is present in the Primary File group), by mentioning that you want to create this object under the Primary File Group. Any additional data file that you add to the database will have only transactional data but no Meta Data, so that’s why it is called as the Secondary Data File. It is given the extension name .NDF so that the user can easily identify whether a specific data file is a Primary Data File or a Secondary Data File(s). There are many advantages of storing data in different files that are under different file groups. You can put your read only in the tables in one file (file group) and read-write tables in another file (file group) and take a backup of only the file group that has read the write data, so that you can avoid taking the backup of a read-only data that cannot be altered. Creating additional files in different physical hard disks also improves I/O performance. A real-time scenario where we use Files could be this one: Let’s say you have created a database called MYDB in the D-Drive which has a 50 GB space. You also have 1 Database File (.MDF) and 1 Log File on D-Drive and suppose that all of that 50 GB space has been used up and you do not have any free space left but you still want to add an additional space to the database. One easy option would be to add one more physical hard disk to the server, add new data file to MYDB database and create this new data file in a new hard disk then move some of the objects from one file to another, and put the file group under which you added new file as default File group, so that any new object that is created gets into the new files, unless specified. Now that we got a basic idea of what data files are, what type of data they store and why they are named the way they are, let’s move on to the next topic, Shrinking. First of all, I disagree with the Microsoft terminology for naming this feature as “Shrinking”. Shrinking, in regular terms, means to reduce the size of a file by means of compressing it. BUT in SQL Server, Shrinking DOES NOT mean compressing. Shrinking in SQL Server means to remove an empty space from database files and release the empty space either to the Operating System or to SQL Server. Let’s examine this through an example. Let’s say you have a database “MYDB” with a size of 50 GB that has a free space of about 20 GB, which means 30GB in the database is filled with data and the 20 GB of space is free in the database because it is not currently utilized by the SQL Server (Database); it is reserved and not yet in use. If you choose to shrink the database and to release an empty space to Operating System, and MIND YOU, you can only shrink the database size to 30 GB (in our example). You cannot shrink the database to a size less than what is filled with data. So, if you have a database that is full and has no empty space in the data file and log file (you don’t have an extra disk space to set Auto growth option ON), YOU CANNOT issue the SHRINK Database/File command, because of two reasons: There is no empty space to be released because the Shrink command does not compress the database; it only removes the empty space from the database files and there is no empty space. Remember, the Shrink command is a logged operation. When we perform the Shrink operation, this information is logged in the log file. If there is no empty space in the log file, SQL Server cannot write to the log file and you cannot shrink a database. Now answering your questions: (1) Q: What are the USEDPAGES & ESTIMATEDPAGES that appear on the Results Pane after using the DBCC SHRINKDATABASE (NorthWind, 10) ? A: According to Books Online (For SQL Server 2000): UsedPages: the number of 8-KB pages currently used by the file. EstimatedPages: the number of 8-KB pages that SQL Server estimates the file could be shrunk down to. Important Note: Before asking any question, make sure you go through Books Online or search on the Google once. The reasons for doing so have many advantages: 1. If someone else already has had this question before, chances that it is already answered are more than 50 %. 2. This reduces your waiting time for the answer. (2) Q: What is the difference between Shrinking the Database using DBCC command like the one above & shrinking it from the Enterprise Manager Console by Right-Clicking the database, going to TASKS & then selecting SHRINK Option, on a SQL Server 2000 environment? A: As far as my knowledge goes, there is no difference, both will work the same way, one advantage of using this command from query analyzer is, your console won’t be freezed. You can do perform your regular activities using Enterprise Manager. (3) Q: What is this .NDF file that is discussed above? I have never heard of it. What is it used for? Is it used by end-users, DBAs or the SERVER/SYSTEM itself? A: .NDF File is a secondary data file. You never heard of it because when database is created, SQL Server creates database by default with only 1 data file (.MDF) and 1 log file (.LDF) or however your model database has been setup, because a model database is a template used every time you create a new database using the CREATE DATABASE Command. Unless you have added an extra data file, you will not see it. This file is used by the SQL Server to store data which are saved by the users. Hope this information helps. I would like to as the experts to please comment if what I understand is not what the Microsoft guys meant. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Readers Contribution, Readers Question, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • suspicious crawler activity

    - by ithkuil
    I'm noticing that I get accesses 66.249.66.198 - - [01/Jul/2011:17:13:46 +0200] "GET /img/clip.incubus.torrent.phtml HTTP/1.1" 404 143 "-" "Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)" 66.249.66.198 - - [01/Jul/2011:17:13:48 +0200] "GET /img/clip.global.deejays.download.phtml HTTP/1.1" 404 143 "-" "Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)" that files don't exist and there is no file on my site that has this content (I hope). Why is googlebot trying out these links? reverse dns and whois state that 66.249.66.198 is really googlebot.

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  • Parallelism in .NET – Part 6, Declarative Data Parallelism

    - by Reed
    When working with a problem that can be decomposed by data, we have a collection, and some operation being performed upon the collection.  I’ve demonstrated how this can be parallelized using the Task Parallel Library and imperative programming using imperative data parallelism via the Parallel class.  While this provides a huge step forward in terms of power and capabilities, in many cases, special care must still be given for relative common scenarios. C# 3.0 and Visual Basic 9.0 introduced a new, declarative programming model to .NET via the LINQ Project.  When working with collections, we can now write software that describes what we want to occur without having to explicitly state how the program should accomplish the task.  By taking advantage of LINQ, many operations become much shorter, more elegant, and easier to understand and maintain.  Version 4.0 of the .NET framework extends this concept into the parallel computation space by introducing Parallel LINQ. Before we delve into PLINQ, let’s begin with a short discussion of LINQ.  LINQ, the extensions to the .NET Framework which implement language integrated query, set, and transform operations, is implemented in many flavors.  For our purposes, we are interested in LINQ to Objects.  When dealing with parallelizing a routine, we typically are dealing with in-memory data storage.  More data-access oriented LINQ variants, such as LINQ to SQL and LINQ to Entities in the Entity Framework fall outside of our concern, since the parallelism there is the concern of the data base engine processing the query itself. LINQ (LINQ to Objects in particular) works by implementing a series of extension methods, most of which work on IEnumerable<T>.  The language enhancements use these extension methods to create a very concise, readable alternative to using traditional foreach statement.  For example, let’s revisit our minimum aggregation routine we wrote in Part 4: double min = double.MaxValue; foreach(var item in collection) { double value = item.PerformComputation(); min = System.Math.Min(min, value); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here, we’re doing a very simple computation, but writing this in an imperative style.  This can be loosely translated to English as: Create a very large number, and save it in min Loop through each item in the collection. For every item: Perform some computation, and save the result If the computation is less than min, set min to the computation Although this is fairly easy to follow, it’s quite a few lines of code, and it requires us to read through the code, step by step, line by line, in order to understand the intention of the developer. We can rework this same statement, using LINQ: double min = collection.Min(item => item.PerformComputation()); Here, we’re after the same information.  However, this is written using a declarative programming style.  When we see this code, we’d naturally translate this to English as: Save the Min value of collection, determined via calling item.PerformComputation() That’s it – instead of multiple logical steps, we have one single, declarative request.  This makes the developer’s intentions very clear, and very easy to follow.  The system is free to implement this using whatever method required. Parallel LINQ (PLINQ) extends LINQ to Objects to support parallel operations.  This is a perfect fit in many cases when you have a problem that can be decomposed by data.  To show this, let’s again refer to our minimum aggregation routine from Part 4, but this time, let’s review our final, parallelized version: // Safe, and fast! double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach( collection, // First, we provide a local state initialization delegate. () => double.MaxValue, // Next, we supply the body, which takes the original item, loop state, // and local state, and returns a new local state (item, loopState, localState) => { double value = item.PerformComputation(); return System.Math.Min(localState, value); }, // Finally, we provide an Action<TLocal>, to "merge" results together localState => { // This requires locking, but it's only once per used thread lock(syncObj) min = System.Math.Min(min, localState); } ); Here, we’re doing the same computation as above, but fully parallelized.  Describing this in English becomes quite a feat: Create a very large number, and save it in min Create a temporary object we can use for locking Call Parallel.ForEach, specifying three delegates For the first delegate: Initialize a local variable to hold the local state to a very large number For the second delegate: For each item in the collection, perform some computation, save the result If the result is less than our local state, save the result in local state For the final delegate: Take a lock on our temporary object to protect our min variable Save the min of our min and local state variables Although this solves our problem, and does it in a very efficient way, we’ve created a set of code that is quite a bit more difficult to understand and maintain. PLINQ provides us with a very nice alternative.  In order to use PLINQ, we need to learn one new extension method that works on IEnumerable<T> – ParallelEnumerable.AsParallel(). That’s all we need to learn in order to use PLINQ: one single method.  We can write our minimum aggregation in PLINQ very simply: double min = collection.AsParallel().Min(item => item.PerformComputation()); By simply adding “.AsParallel()” to our LINQ to Objects query, we converted this to using PLINQ and running this computation in parallel!  This can be loosely translated into English easily, as well: Process the collection in parallel Get the Minimum value, determined by calling PerformComputation on each item Here, our intention is very clear and easy to understand.  We just want to perform the same operation we did in serial, but run it “as parallel”.  PLINQ completely extends LINQ to Objects: the entire functionality of LINQ to Objects is available.  By simply adding a call to AsParallel(), we can specify that a collection should be processed in parallel.  This is simple, safe, and incredibly useful.

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  • April 12 EBS Webcast: Value Chain Planning 12.1.3.6 Rapid Planning Enhancements

    - by Oracle_EBS
    ADVISOR WEBCAST: 12.1.3.6 Rapid Planning EnhancementsPRODUCT FAMILY: Value Chain Planning April 12, 2012 at 11 am ET, 9 am MT, 8 am PT This one-hour session is recommended for functional users who work on the implementation of Oracle Rapid Planning, and Consultants interested in the latest Oracle Rapid Planning features and enhancements available through VCP version 12.1.3.6. This webcast will discuss Safety Stock Calculation Using Quantities, Substitution Logic, and RP-CP Collaboration.TOPICS WILL INCLUDE: Provide insight on the latest enhancements that are available in Oracle Rapid Planning. Learn what is available in this version compared to earlier versions. Version changes. A short, live demonstration (only if applicable) and question and answer period will be included. Oracle Advisor Webcasts are dedicated to building your awareness around our products and services. This session does not replace offerings from Oracle Global Support Services. Current Schedule can be found on Note 740966.1 Post Presentation Recordings can be found on Note 740964.1

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  • A Taxonomy of Numerical Methods v1

    - by JoshReuben
    Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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  • How to create Office365 SharePoint site using SharePoint2010 template

    - by ybbest
    Recently, I worked with a client that has office 365 upgraded to SharePoint 2013.But they still like to create the SharePoint site using the old SharePoint2010 template, if you like to know how , here are the steps: 1. Go to your Office 365 portal https://portal.microsoftonline.com/admin/default.aspx and then go to the SharePoint admin page. 2. Next, click settings page. 3. Change the Global experience Version Settings. 4. Finally, you will be able to create SharePoint site using 2010 template.

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  • What does this regex mean and why

    - by Kalec
    $ sed "s/\(^[a-z,0-9]*\)\(.*\)\( [a-z,0-9]*$\)/\1\2 \1/g" desired_file_name I apreciate it even if you only explain part of it or at lest structure it with words as in s\alphanumerical_at_start\something\alphanumerical_at_end\something_else\global Could someone explain what that means, why and are all regEx so ... awful ? I know that it replaces the first lowcase alphanumerical word with the last one. But could you explain bit by bit what's going on here ? what's with all the /\ and \(.*\)\ and everything else ? I'm just lost. EDIT: Here is what I do get: (^[a-z0-9]*) starting with a trough z and 0 trough 9; and [a-z,0-9]*$ is the same but the last word (however [0-9,a-z] = just first 2 characters / first character, or the entire word ?). Also: what does the * or the \(.*\)\ even mean ?

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  • Learning to Grow

    - by jack.flynn
    A Conversation with Ted Simpson of HEUG A great place to revisit Oracle OpenWorld year round is OracleWebVideo on YouTube. Oracle Magazine Senior Editor Jeff Erickson sat down with Ted Simpson at last year's Oracle OpenWorld to find out how the Higher Education Users Group (HEUG) is helping hundreds of member institutions and thousands of individuals across the globe meet the technological challenges in colleges and universities. Simpson joined HEUG back when it was a PeopleSoft special interest group. Now that higher education institutions have expanded into IT infrastructures the size of global corporations or small municipalities, his user group has also been challenged by growth.

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  • Convert a DVD Movie Directly to AVI with FairUse Wizard 2.9

    - by DigitalGeekery
    Are you looking for a way to backup your DVD movie collection to AVI?  Today we’ll show you how to rip a DVD movie directly to AVI with FairUse Wizard. About FairUse Wizard FairUse Wizard 2.9 uses the DivX, Xvid, or h.264 codec to convert DVD to an AVI file. It comes in both a free version and commercial version. The free, or “Light” version, can create files up 700MB while the commercial version can output a 1400MB file. This will allow you to back up your movies to CD, or even multiple movies on a single DVD. FairUse Wizard states that it does not work on copy protected discs, but we’ve seen it work on all but some of the most recent copy protection. For this tutorial we’re using the free Light Edition to convert a DVD to AVI. They also offer a commercial version that you can get for $29.99 and it offers even more encoding possibilities for converting video to you portable digital devices. Installation and Configuration Download and install FairUse Wizard. (Download link below). Once the install is complete, open FairUse Wizard by going to Start > All Programs >  FairUse Wizard 2 >  FairUse Wizard 2.   FairUse Wizard will open on the new project screen. Select “Create a new project” and type a project name into the text box. This will be used as the file output name.  Ex: A project name of Simpsons Movie will give you an output file of Simpsons Movie.avi.   Next, browse for a destination folder for the output file and temp files. Note that you will need a minimum of 6 GB of free disk space for the conversion process. Note: Much of that 6 GB will be used for temporary files that we will delete after the conversion process.   Click on the Options button at the bottom.   Under Preferences, choose your preferred video codec and file output size. XviD and x264 are installed by default. If you prefer to use DivX, you will have to install it separately. Also note the “Two pass” option. Checking the “Two pass” box will encode your video twice for higher quality, but will take more time. Un-checking the box will speed up the conversion process.   Under Audio track, note that English subtitles are enabled by default, so to remove the subtitles, you will need to change the dropdown list so it shows only a dash (-). You can also select “Use TV Mode” if your primary playback will be on a 4:3 TV screen. Click “Next.” Full Auto Mode vs. Manual Mode You should now be back to the initial screen. Next, we’ll need to determine whether or not we can use “Full Auto Mode” to convert the movie. The difference is that “Full Auto Mode” will automatically perform a few steps that you will otherwise have to do manually. If you choose the “Full Auto Mode” option, FairUse Wizard will look for the video on the DVD with the longest duration and assume it is the chain that it should convert to AVI. It’s possible, however, your disc may contain a few chains of similar size, such as a theatrical cut and director’s cut, and the longest chain may not be the one you wish to convert. Make sure that “Full auto mode” is not checked yet, and click “Next.”   FairUse Wizard will parse the IFO files and display all video chains longer than 60  seconds. In most cases, you will only find that the largest chain is the one closely matching the duration of the movie. In these instances, you can use “Full Auto Mode.” If you find more than one chain that are close in duration to the length of the movie, consult the literature on the DVD case, or search online, to find the actual running time of the movie. If the proper file chain is not the longest chain, you won’t be able to use “Full Auto Mode.”   Full Auto Mode To use “Full Auto Mode,” simply click the “Back” button to return to the initial screen Now, place a check in the “Full auto mode” check box. Click “Next.” You will then be prompted to chose your DVD drive, then click “OK.” FairUse Wizard will parse the IFO files… … and then prompt you to Select your drive that contains the DVD one more time before beginning the conversion process. Click “OK.”   Manual Mode If you cannot (or don’t wish to) use Full Auto Mode, choose the appropriate video chain and click “Next.” FairUse Wizard will first go through the process of indexing the video. Note: If you get a runtime error during this portion of the process, it likely means that FairUse Wizard cannot handle the copy protection, and thus cannot convert the DVD. FairUse Wizard will automatically detect a cropping region. If necessary, you can edit the cropping region by adjusting the cropping region settings to the left. Click “Next.” Next, click “Auto Detect” to choose the proper field combination. Click “OK” on the pop up window that displays your Field Mode. Then click “Next.” This next screen is mainly comprised of settings from the Options screen. You can make changes at this point such as codec or output size. Click “Next” when ready.   Video Conversion Now the video conversion process will begin. This may take a few hours depending on your system’s hardware. Note: There is a check box to “Shutdown computer when done” if you choose to run the conversion overnight or before leaving for work. The first phase will be video encoding… Then the audio… If you chose the “Two Pass” option, your video video will be encoded again on 2nd pass. Then you’re finished. Unfortunately, FairUse Wizard doesn’t clean up after itself very well. After the process is complete, you’ll want to browse to your output directory and delete all the temporary files as they take up a considerable amount of hard drive space. Now you’re ready to enjoy your movie. Conclusion FairUse Wizard is a nice way to backup your DVD movies to good quality .avi files. You can store them on your hard drive, watch them on a media PC, or burn them to disc. Many DVD players even allow for playback of DivX or XviD encoded video from a CD or DVD. For those of you with children, you can burn that AVI file to CD for your kids, and keep your original DVDs stored safely out of harms way. Download Download FairUse Wizard 2.9 LE Similar Articles Productive Geek Tips Kantaris is a Unique Media Player Based on VLCHow to Make/Edit a movie with Windows Movie Maker in Windows VistaAutomatically Mount and View ISO files in Windows 7 Media CenterTune Your ClearType Font Settings in Windows VistaAdd Images and Metadata to Windows 7 Media Center Movie Library TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Make your Joomla & Drupal Sites Mobile with OSMOBI Integrate Twitter and Delicious and Make Life Easier Design Your Web Pages Using the Golden Ratio Worldwide Growth of the Internet How to Find Your Mac Address Use My TextTools to Edit and Organize Text

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  • Webcast with Brian Griffin, Ancestry, 2013 Winner 10 Best Web Support Sites

    - by Tuula Fai
    The web is one of the fastest growing channels for providing service, support and information, as seen in The Service Council's (TSC) latest multi-channel research survey. Join TSC's Chief Customer Officer Sumair Dutta as he shares key findings from his current customer experience research from over 200 organizations. Sumair will be joined by Brian Griffin, Senior Program Manager, Global Support Experience, Ancestry.com who will show how Ancestry is using the web as a powerful tool to enhance self-service opportunities and increase customer engagement. Smarter Web Service Educast Thursday, November 14th 2 pm ET / 11 am PT Register: http://bit.ly/1cwz4Ns  

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  • SQL SERVER – Beginning of SQL Server Architecture – Terminology – Guest Post

    - by pinaldave
    SQL Server Architecture is a very deep subject. Covering it in a single post is an almost impossible task. However, this subject is very popular topic among beginners and advanced users.  I have requested my friend Anil Kumar who is expert in SQL Domain to help me write  a simple post about Beginning SQL Server Architecture. As stated earlier this subject is very deep subject and in this first article series he has covered basic terminologies. In future article he will explore the subject further down. Anil Kumar Yadav is Trainer, SQL Domain, Koenig Solutions. Koenig is a premier IT training firm that provides several IT certifications, such as Oracle 11g, Server+, RHCA, SQL Server Training, Prince2 Foundation etc. In this Article we will discuss about MS SQL Server architecture. The major components of SQL Server are: Relational Engine Storage Engine SQL OS Now we will discuss and understand each one of them. 1) Relational Engine: Also called as the query processor, Relational Engine includes the components of SQL Server that determine what your query exactly needs to do and the best way to do it. It manages the execution of queries as it requests data from the storage engine and processes the results returned. Different Tasks of Relational Engine: Query Processing Memory Management Thread and Task Management Buffer Management Distributed Query Processing 2) Storage Engine: Storage Engine is responsible for storage and retrieval of the data on to the storage system (Disk, SAN etc.). to understand more, let’s focus on the following diagram. When we talk about any database in SQL server, there are 2 types of files that are created at the disk level – Data file and Log file. Data file physically stores the data in data pages. Log files that are also known as write ahead logs, are used for storing transactions performed on the database. Let’s understand data file and log file in more details: Data File: Data File stores data in the form of Data Page (8KB) and these data pages are logically organized in extents. Extents: Extents are logical units in the database. They are a combination of 8 data pages i.e. 64 KB forms an extent. Extents can be of two types, Mixed and Uniform. Mixed extents hold different types of pages like index, System, Object data etc. On the other hand, Uniform extents are dedicated to only one type. Pages: As we should know what type of data pages can be stored in SQL Server, below mentioned are some of them: Data Page: It holds the data entered by the user but not the data which is of type text, ntext, nvarchar(max), varchar(max), varbinary(max), image and xml data. Index: It stores the index entries. Text/Image: It stores LOB ( Large Object data) like text, ntext, varchar(max), nvarchar(max),  varbinary(max), image and xml data. GAM & SGAM (Global Allocation Map & Shared Global Allocation Map): They are used for saving information related to the allocation of extents. PFS (Page Free Space): Information related to page allocation and unused space available on pages. IAM (Index Allocation Map): Information pertaining to extents that are used by a table or index per allocation unit. BCM (Bulk Changed Map): Keeps information about the extents changed in a Bulk Operation. DCM (Differential Change Map): This is the information of extents that have modified since the last BACKUP DATABASE statement as per allocation unit. Log File: It also known as write ahead log. It stores modification to the database (DML and DDL). Sufficient information is logged to be able to: Roll back transactions if requested Recover the database in case of failure Write Ahead Logging is used to create log entries Transaction logs are written in chronological order in a circular way Truncation policy for logs is based on the recovery model SQL OS: This lies between the host machine (Windows OS) and SQL Server. All the activities performed on database engine are taken care of by SQL OS. It is a highly configurable operating system with powerful API (application programming interface), enabling automatic locality and advanced parallelism. SQL OS provides various operating system services, such as memory management deals with buffer pool, log buffer and deadlock detection using the blocking and locking structure. Other services include exception handling, hosting for external components like Common Language Runtime, CLR etc. I guess this brief article gives you an idea about the various terminologies used related to SQL Server Architecture. In future articles we will explore them further. Guest Author  The author of the article is Anil Kumar Yadav is Trainer, SQL Domain, Koenig Solutions. Koenig is a premier IT training firm that provides several IT certifications, such as Oracle 11g, Server+, RHCA, SQL Server Training, Prince2 Foundation etc. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

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