Search Results

Search found 23131 results on 926 pages for 'ms query'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 117/926 | < Previous Page | 113 114 115 116 117 118 119 120 121 122 123 124  | Next Page >

  • LINQ Query using Multiple From and Multiple Collections

    1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Text; 5:  6: namespace ConsoleApplication2 7: { 8: class Program 9: { 10: static void Main(string[] args) 11: { 12: var emps = GetEmployees(); 13: var deps = GetDepartments(); 14:  15: var results = from e in emps 16: from d in deps 17: where e.EmpNo >= 1 && d.DeptNo <= 30 18: select new { Emp = e, Dept = d }; 19: 20: foreach (var item in results) 21: { 22: Console.WriteLine("{0},{1},{2},{3}", item.Dept.DeptNo, item.Dept.DName, item.Emp.EmpNo, item.Emp.EmpName); 23: } 24: } 25:  26: private static List<Emp> GetEmployees() 27: { 28: return new List<Emp>() { 29: new Emp() { EmpNo = 1, EmpName = "Smith", DeptNo = 10 }, 30: new Emp() { EmpNo = 2, EmpName = "Narayan", DeptNo = 20 }, 31: new Emp() { EmpNo = 3, EmpName = "Rishi", DeptNo = 30 }, 32: new Emp() { EmpNo = 4, EmpName = "Guru", DeptNo = 10 }, 33: new Emp() { EmpNo = 5, EmpName = "Priya", DeptNo = 20 }, 34: new Emp() { EmpNo = 6, EmpName = "Riya", DeptNo = 10 } 35: }; 36: } 37:  38: private static List<Department> GetDepartments() 39: { 40: return new List<Department>() { 41: new Department() { DeptNo=10, DName="Accounts" }, 42: new Department() { DeptNo=20, DName="Finance" }, 43: new Department() { DeptNo=30, DName="Travel" } 44: }; 45: } 46: } 47:  48: class Emp 49: { 50: public int EmpNo { get; set; } 51: public string EmpName { get; set; } 52: public int DeptNo { get; set; } 53: } 54:  55: class Department 56: { 57: public int DeptNo { get; set; } 58: public String DName { get; set; } 59: } 60: } span.fullpost {display:none;}

    Read the article

  • UnboundLocalError: local variable 'rows' referenced before assignment

    - by patrick
    i'm trying to make a database connection by an other script. But the script didn't work propperly. and if I do a 'print' on the rows then I get the value 'null' But if I use a 'select * from incidents' query then i get the result from the table incidents. import database rows = database.database("INSERT INTO incidents VALUES(3 ,'test_title1', 'test', TO_DATE('25-07-2012', 'DD-MM-YYYY'), CURRENT_TIMESTAMP, 'sector', 50, 60)") #print database.database() print rows database.py script: import psycopg2 import sys import logfile def database(query): logfile.log(20, 'database.py', 'Executing...') con = None try: con = psycopg2.connect(database='incidents', user='ipfit5', password='tester') cur = con.cursor() #print query cur.execute(query) rows = cur.fetchall() con.commit() #test row does work #cur.execute("INSERT INTO incidents VALUES(3 ,'test_titel1', 'test', TO_DATE('25-07-2012', 'DD-MM-YYYY'), CURRENT_TIMESTAMP, 'sector', 50, 60)") except: logfile.log(40, 'database.py', 'Er is iets mis gegaan') logfile.log(40, 'database.py', str(sys.exc_info())) finally: if con: con.close() return rows

    Read the article

  • Hibernate ResultTransformer with JPA API

    - by Timo Westkämper
    Has anyone figured out a smart way to do query result transformation through a similar mechanism like specifying a ResultTransformer in Hibernate? All I can think of is transforming each result row after it has been returned by the Query. Is there any other way? For constructor projections (e.g. new DTO(arg1, arg2)) it can be defined in the JPQL query, at least for Hibernate, but how about other cases?

    Read the article

  • MS Chart in WPF, Setting the DataSource is not creating the Series

    - by Shaik Phakeer
    Hi All, Here I am trying to assign the datasource (using same code given in the sample application) and create a graph, only difference is i am doing it in WPF WindowsFormsHost. due to some reason the datasource is not being assigned properly and i am not able to see the series ("Series 1") being created. wired thing is that it is working in the Windows Forms application but not in the WPF one. am i missing something and can somebody help me? Thanks <Window x:Class="SEDC.MDM.WinUI.WindowsFormsHostWindow" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" xmlns:wf="clr-namespace:System.Windows.Forms;assembly=System.Windows.Forms" xmlns:CHR="clr- namespace:System.Windows.Forms.DataVisualization.Charting;assembly=System.Windows.Forms.Dat aVisualization" Title="HostingWfInWpf" Height="230" Width="338"> <Grid x:Name="grid1"> </Grid> </Window> private void drawChartDataBinding() { System.Windows.Forms.Integration.WindowsFormsHost host = new System.Windows.Forms.Integration.WindowsFormsHost(); string fileNameString = @"C:\Users\Shaik\MSChart\WinSamples\WinSamples\data\chartdata.mdb"; // initialize a connection string string myConnectionString = "PROVIDER=Microsoft.Jet.OLEDB.4.0;Data Source=" + fileNameString; // define the database query string mySelectQuery = "SELECT * FROM REPS;"; // create a database connection object using the connection string OleDbConnection myConnection = new OleDbConnection(myConnectionString); // create a database command on the connection using query OleDbCommand myCommand = new OleDbCommand(mySelectQuery, myConnection); Chart Chart1 = new Chart(); // set chart data source Chart1.DataSource = myCommand; // set series members names for the X and Y values Chart1.Series"Series 1".XValueMember = "Name"; Chart1.Series"Series 1".YValueMembers = "Sales"; // data bind to the selected data source Chart1.DataBind(); myCommand.Dispose(); myConnection.Close(); host.Child = Chart1; this.grid1.Children.Add(host); } Shaik

    Read the article

  • SQL SERVER Force Index Scan on Table Use No Index to Retrieve the Data Query Hint

    Recently I received the following two questions from readers and both the questions have very similar answers.Question 1: I have a unique requirement where I do not want to use any index of the table; how can I achieve this?Question 2: Currently my table uses clustered index and does seek operation; how can I convert [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

    Read the article

  • Plan Caching and Query Memory Part I – When not to use stored procedure or other plan caching mechanisms like sp_executesql or prepared statement

    - by sqlworkshops
      The most common performance mistake SQL Server developers make: SQL Server estimates memory requirement for queries at compilation time. This mechanism is fine for dynamic queries that need memory, but not for queries that cache the plan. With dynamic queries the plan is not reused for different set of parameters values / predicates and hence different amount of memory can be estimated based on different set of parameter values / predicates. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Sort with examples. It is recommended to read Plan Caching and Query Memory Part II after this article which covers Hash Match operations.   When the plan is cached by using stored procedure or other plan caching mechanisms like sp_executesql or prepared statement, SQL Server estimates memory requirement based on first set of execution parameters. Later when the same stored procedure is called with different set of parameter values, the same amount of memory is used to execute the stored procedure. This might lead to underestimation / overestimation of memory on plan reuse, overestimation of memory might not be a noticeable issue for Sort operations, but underestimation of memory will lead to spill over tempdb resulting in poor performance.   This article covers underestimation / overestimation of memory for Sort. Plan Caching and Query Memory Part II covers underestimation / overestimation for Hash Match operation. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a stored procedure does not change significantly based on predicates.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts   Enough theory, let’s see an example where we sort initially 1 month of data and then use the stored procedure to sort 6 months of data.   Let’s create a stored procedure that sorts customers by name within certain date range.   --Example provided by www.sqlworkshops.com create proc CustomersByCreationDate @CreationDateFrom datetime, @CreationDateTo datetime as begin       declare @CustomerID int, @CustomerName varchar(48), @CreationDate datetime       select @CustomerName = c.CustomerName, @CreationDate = c.CreationDate from Customers c             where c.CreationDate between @CreationDateFrom and @CreationDateTo             order by c.CustomerName       option (maxdop 1)       end go Let’s execute the stored procedure initially with 1 month date range.   set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-01-31' go The stored procedure took 48 ms to complete.     The stored procedure was granted 6656 KB based on 43199.9 rows being estimated.       The estimated number of rows, 43199.9 is similar to actual number of rows 43200 and hence the memory estimation should be ok.       There was no Sort Warnings in SQL Profiler.      Now let’s execute the stored procedure with 6 month date range. --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-06-30' go The stored procedure took 679 ms to complete.      The stored procedure was granted 6656 KB based on 43199.9 rows being estimated.      The estimated number of rows, 43199.9 is way different from the actual number of rows 259200 because the estimation is based on the first set of parameter value supplied to the stored procedure which is 1 month in our case. This underestimation will lead to sort spill over tempdb, resulting in poor performance.      There was Sort Warnings in SQL Profiler.    To monitor the amount of data written and read from tempdb, one can execute select num_of_bytes_written, num_of_bytes_read from sys.dm_io_virtual_file_stats(2, NULL) before and after the stored procedure execution, for additional information refer to the webcast: www.sqlworkshops.com/webcasts.     Let’s recompile the stored procedure and then let’s first execute the stored procedure with 6 month date range.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts for further details.   exec sp_recompile CustomersByCreationDate go --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-06-30' go Now the stored procedure took only 294 ms instead of 679 ms.    The stored procedure was granted 26832 KB of memory.      The estimated number of rows, 259200 is similar to actual number of rows of 259200. Better performance of this stored procedure is due to better estimation of memory and avoiding sort spill over tempdb.      There was no Sort Warnings in SQL Profiler.       Now let’s execute the stored procedure with 1 month date range.   --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-01-31' go The stored procedure took 49 ms to complete, similar to our very first stored procedure execution.     This stored procedure was granted more memory (26832 KB) than necessary memory (6656 KB) based on 6 months of data estimation (259200 rows) instead of 1 month of data estimation (43199.9 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is 6 months in this case. This overestimation did not affect performance, but it might affect performance of other concurrent queries requiring memory and hence overestimation is not recommended. This overestimation might affect performance Hash Match operations, refer to article Plan Caching and Query Memory Part II for further details.    Let’s recompile the stored procedure and then let’s first execute the stored procedure with 2 day date range. exec sp_recompile CustomersByCreationDate go --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-01-02' go The stored procedure took 1 ms.      The stored procedure was granted 1024 KB based on 1440 rows being estimated.      There was no Sort Warnings in SQL Profiler.      Now let’s execute the stored procedure with 6 month date range. --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-06-30' go   The stored procedure took 955 ms to complete, way higher than 679 ms or 294ms we noticed before.      The stored procedure was granted 1024 KB based on 1440 rows being estimated. But we noticed in the past this stored procedure with 6 month date range needed 26832 KB of memory to execute optimally without spill over tempdb. This is clear underestimation of memory and the reason for the very poor performance.      There was Sort Warnings in SQL Profiler. Unlike before this was a Multiple pass sort instead of Single pass sort. This occurs when granted memory is too low.      Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined date range.   Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByCreationDate go create proc CustomersByCreationDate @CreationDateFrom datetime, @CreationDateTo datetime as begin       declare @CustomerID int, @CustomerName varchar(48), @CreationDate datetime       select @CustomerName = c.CustomerName, @CreationDate = c.CreationDate from Customers c             where c.CreationDate between @CreationDateFrom and @CreationDateTo             order by c.CustomerName       option (maxdop 1, recompile)       end go Let’s execute the stored procedure initially with 1 month date range and then with 6 month date range. --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-01-30' exec CustomersByCreationDate '2001-01-01', '2001-06-30' go The stored procedure took 48ms and 291 ms in line with previous optimal execution times.      The stored procedure with 1 month date range has good estimation like before.      The stored procedure with 6 month date range also has good estimation and memory grant like before because the query was recompiled with current set of parameter values.      The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.     Let’s recreate the stored procedure with optimize for hint of 6 month date range.   --Example provided by www.sqlworkshops.com drop proc CustomersByCreationDate go create proc CustomersByCreationDate @CreationDateFrom datetime, @CreationDateTo datetime as begin       declare @CustomerID int, @CustomerName varchar(48), @CreationDate datetime       select @CustomerName = c.CustomerName, @CreationDate = c.CreationDate from Customers c             where c.CreationDate between @CreationDateFrom and @CreationDateTo             order by c.CustomerName       option (maxdop 1, optimize for (@CreationDateFrom = '2001-01-01', @CreationDateTo ='2001-06-30'))       end go Let’s execute the stored procedure initially with 1 month date range and then with 6 month date range.   --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-01-30' exec CustomersByCreationDate '2001-01-01', '2001-06-30' go The stored procedure took 48ms and 291 ms in line with previous optimal execution times.    The stored procedure with 1 month date range has overestimation of rows and memory. This is because we provided hint to optimize for 6 months of data.      The stored procedure with 6 month date range has good estimation and memory grant because we provided hint to optimize for 6 months of data.       Let’s execute the stored procedure with 12 month date range using the currently cashed plan for 6 month date range. --Example provided by www.sqlworkshops.com exec CustomersByCreationDate '2001-01-01', '2001-12-31' go The stored procedure took 1138 ms to complete.      2592000 rows were estimated based on optimize for hint value for 6 month date range. Actual number of rows is 524160 due to 12 month date range.      The stored procedure was granted enough memory to sort 6 month date range and not 12 month date range, so there will be spill over tempdb.      There was Sort Warnings in SQL Profiler.      As we see above, optimize for hint cannot guarantee enough memory and optimal performance compared to recompile hint.   This article covers underestimation / overestimation of memory for Sort. Plan Caching and Query Memory Part II covers underestimation / overestimation for Hash Match operation. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case. I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.     Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.     Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

    Read the article

  • There once was in Dublin a query

    - by Paul Nielsen
    For 6 months I’ve have been planning a secret trip to London in May as a surprise for my wife (of Irish heritage and accent) (I love how she says, "Aye laddie, kiss me I'm Irish." but that's for another blog.) The plan was to spend a week in London and then top if off with a visit to Dublin to see the Book of Kells (on my bucket list) and stay at Markree Castle at Sligo, Ireland (on her bucket list). The original plan was to have her boss assign mandatory vacation a few days before the trip (her...(read more)

    Read the article

  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

    Read the article

  • Math operations in nHibernate Criteria Query

    - by Richard Tasker
    Dear All, I am having troubles with a nHibernate query. I have a db which stores vehicle info, and the user is able to search the db by make, model, type and production dates. Make, model & type search is fine, works a treat, it is the productions dates I am having issues with. So here goes... The dates are stored as ints (StartMonth, StartYear, FinishMonth, FinishYear), when the end-user selects a date it is passed to the query as an int eg 2010006 (2010 * 100 + 6). below is part of the query I am using, FYI I am using Lambda Extensions. if (_searchCriteria.ProductionStart > 0) { query.Add<Engine>(e => ((e.StartYear * 100) + e.StartMonth) >= _searchCriteria.ProductionStart); } if (_searchCriteria.ProductionEnd > 0) { query.Add<Engine>(e => ((e.FinishYear * 100) + e.FinishMonth) <= _searchCriteria.ProductionEnd); } But when the query runs I get the following message, Could not determine member from ((e.StartYear * 100) + e.StartMonth) Any help would be great, Regards Rich

    Read the article

  • How to log error queries in mysql?

    - by user271768
    I know that there is general_log that logs all queries, but I want to find out which query has an error, and get the error message. I have tried running an error query on purpose, but it logs as a normal query and doesn't report it with error. Any ideas?

    Read the article

  • Creating a dynamic linq query

    - by Bas
    I have the following query: from p in dataContext.Repository<IPerson>() join spp1 in dataContext.Repository<ISportsPerPerson>() on p.Id equals spp1.PersonId join s1 in dataContext.Repository<ISports>() on spp1.SportsId equals s1.Id join spp2 in dataContext.Repository<ISportsPerPerson>() on p.Id equals spp2.PersonId join s2 in dataContext.Repository<ISports>() on spp2.SportsId equals s2.Id where s1.Name == "Soccer" && s2.Name == "Tennis" select new { p.Id }; It selects all the person who play Soccer and Tennis. On runtime the user can select other tags to add to the query, for instance: "Hockey". now my question is, how could I dynamically add "Hockey" to the query? If "Hockey" is added to the query, it would look like this: from p in dataContext.Repository<IPerson>() join spp1 in dataContext.Repository<ISportsPerPerson>() on p.Id equals spp1.PersonId join s1 in dataContext.Repository<ISports>() on spp1.SportsId equals s1.Id join spp2 in dataContext.Repository<ISportsPerPerson>() on p.Id equals spp2.PersonId join s2 in dataContext.Repository<ISports>() on spp2.SportsId equals s2.Id join spp3 in dataContext.Repository<ISportsPerPerson>() on p.Id equals spp3.PersonId join s3 in dataContext.Repository<ISports>() on spp3.SportsId equals s3.Id where s1.Name == "Soccer" && s2.Name == "Tennis" && s3.Name == "Hockey" select new { p.Id }; It would be preferable if the query is build up dynamically like: private void queryTagBuilder(List<string> tags) { IDataContext dataContext = new LinqToSqlContext(new L2S.DataContext()); foreach(string tag in tags) { //Build the query? } } Anyone has an idea on how to set this up correctly? Thanks in advance!

    Read the article

  • PHP: How to use mysql fulltext search and handle fulltext search result

    - by garcon1986
    Hello, I have tried to use mysql fulltext search in my intranet. I wanted to use it to search in multiple tables, and get the independant results depending on tables in the result page. This is what i did for searching. $query = " SELECT * FROM testtable t1, testtable2 t2, testtable3 t3 WHERE match(t1.firstName, t1.lastName, t1.details) against(' ".$value."') or match(t2.others, t2.information, t2.details) against(' ".$value."') or match(t3.other, t2.info, t2.details) against(' ".$value."') "; $result = mysql_query($query)or die('query error'.mysql_error()); while($row = mysql_fetch_assoc($result)){ echo $row['firstName']; echo $row['lastName']; echo $row['details'].'<br />'; } Do you have any ideas about optimizing the query and format the output of search results?

    Read the article

  • How do you think while formulating Sql Queries. Is it an experience or a concept ?

    - by Shantanu Gupta
    I have been working on sql server and front end coding and have usually faced problem formulating queries. I do understand most of the concepts of sql that are needed in formulating queries but whenever some new functionality comes into the picture that can be dont using sql query, i do usually fails resolving them. I am very comfortable with select queries using joins and all such things but when it comes to DML operation i usually fails For every query that i never done before I usually finds uncomfortable with that while creating them. Whenever I goes for an interview I usually faces this problem. Is it their some concept behind approaching on formulating sql queries. Eg. I need to create an sql query such that A table contain single column having duplicate record. I need to remove duplicate records. I know i can find the solution to this query very easily on Googling, but I want to know how everyone comes to the desired result. Is it something like Practice Makes Man Perfect i.e. once you did it, next time you will be able to formulate or their is some logic or concept behind. I could have get my answer of solving above problem simply by posting it on stackoverflow and i would have been with an answer within 5 to 10 minutes but I want to know the reason. How do you work on any new kind of query. Is it a major contribution of experience or some an implementation of concepts. Whenever I learns some new thing in coding section I tries to utilize it wherever I can use it. But here scenario seems to be changed because might be i am lagging in some concepts.

    Read the article

  • proper way to solve mysql max user connection error

    - by Rahul a common name
    Hello every one, I'm using PHP with MYSQL database as both are open source and easy to use. I'm getting problem when I execute insert and/or update of millions of row one after another while this operation perform I got the MYSQL error that: 'max_user_connections' active connections which is the best way to solve this problem. I don't want to use another database or language other then PHP. connect_db(); $query = "insert into table(mobno,status,description,date,send_deltime,sms_id,msg,send_type) values('".$to."','".$status."','".$report."','','".$timewsha1."','".$smsID."','','".$type."')"; $result = mysql_query($query) or ("Query failed : " . mysql_error()); this query will execute thousand of times. and then server give connection error.

    Read the article

  • SQL CE 3.5 and the ‘SELECT TOP’ Query

    - by stevewarren
    Finally! SQL CE 3.5 now supports the ‘TOP’ keyword. However, there is a trick to this: you must surround the number with parenthesis. For example, in regular T-SQL you would write SELECT TOP N [col] FROM [table] However, in SQL CE 3.5 you must write SELECT TOP (N) [col] FROM [table]

    Read the article

  • exec problem in sql 2005

    - by IordanTanev
    Hi, i have the situation where i have two databases whith same structure. The first have some data in its datatables. I need to create a script that will transfer the data from the first database to the second. I have created this script. DECLARE @table_name nvarchar(MAX), @query nvarchar(MAX) DECLARE @table_cursor CURSOR SET @table_cursor = CURSOR FAST_FORWARD FOR Select TABLE_NAME FROM INFORMATION_SCHEMA.TABLES OPEN @table_cursor FETCH NEXT FROM @table_cursor INTO @table_name WHILE @@FETCH_STATUS = 0 BEGIN SET @query = 'INSERT INTO ' + @table_name + ' SELECT * FROM MyDataBase.dbo.' + @table_name print @query exec @query FETCH NEXT FROM @table_cursor INTO @table_name END CLOSE @table_cursor DEALLOCATE @table_cursor The problem is that when i run th script the "print @query" statement prints statement like this INSERT INTO table SELECT * FROM MyDataBase.dbo.table When i copy this and run it from Management studio it works fine. But when the script trys to run it with exec i get this error Msg 911, Level 16, State 1, Line 21 Could not locate entry in sysdatabases for database 'INSERT INTO table SELECT * FROM MPDEV090314'. No entry found with that name. Make sure that the name is entered correctly. Hope someone can tell me whot is wront with this. Best Regards, Iordan Tanev

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 113 114 115 116 117 118 119 120 121 122 123 124  | Next Page >