Search Results

Search found 28685 results on 1148 pages for 'query performance'.

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 53/1148 | < Previous Page | 49 50 51 52 53 54 55 56 57 58 59 60  | Next Page >

  • Calculating RAM Performance? Example: DDR3-2133 CL9-11-10-28 1.65V vs DDR3-1600 CL10-10-10-30 1.5V

    - by user1131467
    How do you calculate the relative performance of PC RAM? For example, what is the relative performance of the following: G.Skill Ripjaws Z 8 x 4GB Kit, DDR3-2133, [email protected] G.Skill Ripjaws Z 4 x 8GB Kit, DDR3-1600, [email protected] If it's relevant, when they are used in a top of the line ASUS Rampage IV Extreme motherboard and Intel i7 3960X? By performance, I mean relative: read latency write latency read bandwidth write bandwidth Please include working. (I mean how did you arrive at the figures based on timing and DDR3-speed)

    Read the article

  • PPT Leveraging Azure for Performance Testing

    - by Tarun Arora
    I have recently presented a session on “How you can leverage Azure for Performance Testing” your application.  It goes without saying that performance testing your application not only gives you the confidence that the application will work under heavy levels of stress but also gives you the ability to test how scalable the architecture of your application is. It is important to know how much is too much for your application! Working with various clients in the industry I have realized that the biggest barrier in Load Testing & Performance Testing adoption is the high infrastructure and administration cost that comes with this phase of testing. In the session I tried to demonstrate how you can use the power of Windows Azure to effectively abstract the administration cost of infrastructure management and lower the total cost of Load & Performance Testing. You can view the session presentation here, http://www.slideshare.net/aroratarun/leveraging-azure-for-performance-testing  I’ll be adding a video on this subject shortly… If you have any feedback or further suggestions to add to the goodness of this solution please get in touch.

    Read the article

  • Harping on Metadata Performance: New Benchmarks

    <b>Linux Magazine:</b> "Metadata performance is perhaps the most neglected facet of storage performance. In previous articles we&#8217;ve looked into how best to improve metadata performance without too much luck. Could that be a function of the benchmark? Hmmm..."

    Read the article

  • Nvidia Powermizer Performance Levels

    - by jeffrey
    Is there anyway to configure Nvidia Powerimizer performance levels? My current setup has 3 power levels with the lowest one being 50mhz. The problem with this it that it lags compiz when it goes to the lowest performance level 0. Minimizing, maximizing, dragging windows, etc. are all sluggish when it's at the lowest level. Once powermizer leaves level 0 everything is very smooth and runs great. Is there anyway for me to remove level 0 and just run Level the two higher levels 1/2? I don't want to complete disable powermizer, but I can't stand the lagging once powermizer goes into performance level 0. Setting the option "prefer maximum performance" fixes the problem as it disables powermizer, but the GPU is overkill at stock speeds for most desktop use @ 850mhz. intel i5 2500k asus gene-z z68 evga 560ti fpb (driver 295.40) ubuntu 12.04 LTS x64

    Read the article

  • The Schema returned by the new query differ from the base query

    - by sochandara
    I am working on class project which required to work with Windows Application and this issue occurred to me that i don understand how to solved it can anybody help please? I want to show the NATIONALITYNAME instead of showing NATIONALITYID in the grid view SELECT COACH.COACHID, COACH.COACHFIRSTNAME, COACH.COACHLASTNAME, NATIONALITY.NATIONALITY FROM COACH INNER JOIN NATIONALITY ON COACH.NATIONALITYID = NATIONALITY.NATIONALITYID Error Message: "The Schema returned by the new query differ from the base query"![alt text][1]

    Read the article

  • the shema return by the new query differ from the base query

    - by sochandara
    I am working on class project which required to work with Windows Application and this issue occurred to me that i don understand how to solved it can anybody help please? I want to show the NATIONALITYNAME instead of showing NATIONALITYID in the grid view SELECT COACH.COACHID , COACH.COACHFIRSTNAME , COACH.COACHLASTNAME , NATIONALITY.NATIONALITY FROM COACH INNER JOIN NATIONALITY ON COACH.NATIONALITYID = NATIONALITY.NATIONALITYID Error Message: "The Schema returned by the new query differ from the base query"

    Read the article

  • MySQL enters another value that the one given by PHP

    - by Tristan
    Hello, The big problem : mysql does not stores the information i told him to via PHP Example (this req is an echo just before the query) : INSERT INTO serveur (GSP_nom , IPserv, port, tickrate, membre, nomPays, finContrat, type, jeux, slot, ipClient, email) VALUES ( 'ckras', '88.191.88.57', '37060', '100' , '', 'Allemagne','20110519', '2', '4','99' ,'82.220.201.183','[email protected]'); But on the MySQL i have : 403 ckras 88.191.88.57 32767 100 Allemagne 20110519 1 2010-04-25 00:51:47 2 4 99 82.220.201.183 [email protected] port : 37060 (right value) //// 32767 (MySQL's drug?) Any help would be appreciated, i'm worse than stuck and i'm ** off PS: *There is no trigger on the mysql as far as i know / there is no controll on the port which means that nowhere i modify the "port" value and this script works for 80% of the time ( it seems that as soon as the users enters a port = 30000 it causes that bug), an user first reported to me this error today and the script was running since 3 months* Thanks

    Read the article

  • Fastest way to do a weighted tag search in SQL Server

    - by Hasan Khan
    My table is as follows ObjectID bigint Tag nvarchar(50) Weight float Type tinyint I want to get search for all objects that has tags 'big' or 'large' I want the objectid in order of sum of weights (so objects having both the tags will be on top) select objectid, row_number() over (order by sum(weight) desc) as rowid from tags where tag in ('big', 'large') and type=0 group by objectid the reason for row_number() is that i want paging over results. The query in its current form is very slow, takes a minute to execute over 16 million tags. What should I do to make it faster? I have a non clustered index (objectid, tag, type) Any suggestions?

    Read the article

  • Trouble with a query

    - by Mark Allison
    Hi there, I'm having trouble with a query in SQL Server 2008 on some forex trading data. I have a trades table and an orders table. A trade needs to comprise of 2 or more orders. DDL schema and sample data below. What I want to do is write a query that shows the profit/loss in pips for each trade. A pip is 1/1000th of a currency. So the difference between USD 1.3441 and 1.3442 is 1 pip in forex-speak. A trade usually has one entry order and multiple exit orders. So for example if I buy 3 lots of the currency pair GBP/USD at the exchange rate of 1.6100 and then sell 1 lot at 1.6150, 1 lot at 1.6200 and 1 lot at 1.6250 then the profit is (1.6150 - 1.6100) + (1.6200 - 1.6100) + (1.6250 - 1.6100), or 50 + 100 + 150 = 300 pips profit. The trade could also go the other way (Shorting). For example the currency pair can be sold first before it's bought back later at a cheaper price. I would like a query that returns the following: tradeId, currencyPair, profitInPips It seems like a pretty straightforward query, but it's eluding me right now. Here's my DDL and sample data: CREATE TABLE [dbo].[trades]( [tradeId] [int] IDENTITY(1,1) NOT NULL, [currencyPair] [char](6) NOT NULL, CONSTRAINT [PK_trades] PRIMARY KEY CLUSTERED ( [tradeId] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] ) ON [PRIMARY] GO SET ANSI_PADDING OFF GO SET IDENTITY_INSERT [dbo].[trades] ON INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (1, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (2, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (3, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (4, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (5, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (6, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (7, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (8, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (9, N'GBPUSD') INSERT [dbo].[trades] ([tradeId], [currencyPair]) VALUES (10, N'GBPUSD') SET IDENTITY_INSERT [dbo].[trades] OFF GO CREATE TABLE [dbo].[orders]( [orderId] [int] IDENTITY(1,1) NOT NULL, [tradeId] [int] NOT NULL, [amount] [decimal](18, 1) NOT NULL, [buySell] [char](1) NOT NULL, [rate] [decimal](18, 6) NOT NULL, [orderDateTime] [datetime] NOT NULL, CONSTRAINT [PK_orders] PRIMARY KEY CLUSTERED ( [orderId] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] ) ON [PRIMARY] GO SET ANSI_PADDING OFF GO SET IDENTITY_INSERT [dbo].[orders] ON INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (1, 1, CAST(3.0 AS Decimal(18, 1)), N'S', CAST(1.606500 AS Decimal(18, 6)), CAST(0x00009CF40083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (2, 1, CAST(3.0 AS Decimal(18, 1)), N'B', CAST(1.615500 AS Decimal(18, 6)), CAST(0x00009CF400A4CB80 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (3, 2, CAST(3.0 AS Decimal(18, 1)), N'S', CAST(1.608000 AS Decimal(18, 6)), CAST(0x00009CF500000000 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (4, 2, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.603000 AS Decimal(18, 6)), CAST(0x00009CF50083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (5, 2, CAST(2.0 AS Decimal(18, 1)), N'B', CAST(1.605500 AS Decimal(18, 6)), CAST(0x00009CF50107AC00 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (6, 3, CAST(3.0 AS Decimal(18, 1)), N'S', CAST(1.595500 AS Decimal(18, 6)), CAST(0x00009CF70083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (7, 3, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.590500 AS Decimal(18, 6)), CAST(0x00009CF700C5C100 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (8, 3, CAST(2.0 AS Decimal(18, 1)), N'B', CAST(1.594500 AS Decimal(18, 6)), CAST(0x00009CF701499700 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (9, 4, CAST(3.0 AS Decimal(18, 1)), N'B', CAST(1.611000 AS Decimal(18, 6)), CAST(0x00009CFB0083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (10, 4, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.616000 AS Decimal(18, 6)), CAST(0x00009CFB00A4CB80 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (11, 4, CAST(2.0 AS Decimal(18, 1)), N'S', CAST(1.611500 AS Decimal(18, 6)), CAST(0x00009CFB0107AC00 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (12, 5, CAST(3.0 AS Decimal(18, 1)), N'B', CAST(1.613000 AS Decimal(18, 6)), CAST(0x00009CFC0083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (13, 5, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.618000 AS Decimal(18, 6)), CAST(0x00009CFC0107AC00 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (14, 5, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.623000 AS Decimal(18, 6)), CAST(0x00009CFC0083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (15, 5, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.628000 AS Decimal(18, 6)), CAST(0x00009CFD00C5C100 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (16, 6, CAST(3.0 AS Decimal(18, 1)), N'B', CAST(1.632000 AS Decimal(18, 6)), CAST(0x00009D020083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (17, 6, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.637000 AS Decimal(18, 6)), CAST(0x00009D0200A4CB80 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (18, 6, CAST(2.0 AS Decimal(18, 1)), N'S', CAST(1.630000 AS Decimal(18, 6)), CAST(0x00009D0200C5C100 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (19, 7, CAST(3.0 AS Decimal(18, 1)), N'B', CAST(1.634500 AS Decimal(18, 6)), CAST(0x00009D0201499700 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (20, 7, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.639500 AS Decimal(18, 6)), CAST(0x00009D0300000000 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (21, 7, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.644500 AS Decimal(18, 6)), CAST(0x00009D030083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (22, 7, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.637500 AS Decimal(18, 6)), CAST(0x00009D0300C5C100 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (23, 8, CAST(3.0 AS Decimal(18, 1)), N'S', CAST(1.625000 AS Decimal(18, 6)), CAST(0x00009D0400C5C100 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (24, 8, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.620000 AS Decimal(18, 6)), CAST(0x00009D050083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (25, 8, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.615000 AS Decimal(18, 6)), CAST(0x00009D0500A4CB80 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (26, 8, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.623000 AS Decimal(18, 6)), CAST(0x00009D050107AC00 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (27, 9, CAST(3.0 AS Decimal(18, 1)), N'S', CAST(1.618000 AS Decimal(18, 6)), CAST(0x00009D0600C5C100 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (28, 9, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.613000 AS Decimal(18, 6)), CAST(0x00009D0600D63BC0 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (29, 9, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.608000 AS Decimal(18, 6)), CAST(0x00009D0600E6B680 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (30, 9, CAST(1.0 AS Decimal(18, 1)), N'B', CAST(1.613300 AS Decimal(18, 6)), CAST(0x00009D0601391C40 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (31, 10, CAST(3.0 AS Decimal(18, 1)), N'B', CAST(1.614500 AS Decimal(18, 6)), CAST(0x00009D090083D600 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (32, 10, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.619500 AS Decimal(18, 6)), CAST(0x00009D090107AC00 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (33, 10, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.624500 AS Decimal(18, 6)), CAST(0x00009D0901499700 AS DateTime)) INSERT [dbo].[orders] ([orderId], [tradeId], [amount], [buySell], [rate], [orderDateTime]) VALUES (34, 10, CAST(1.0 AS Decimal(18, 1)), N'S', CAST(1.619000 AS Decimal(18, 6)), CAST(0x00009D0A0083D600 AS DateTime)) SET IDENTITY_INSERT [dbo].[orders] OFF /****** Object: ForeignKey [FK_orders_trades] Script Date: 04/02/2010 15:05:31 ******/ ALTER TABLE [dbo].[orders] WITH CHECK ADD CONSTRAINT [FK_orders_trades] FOREIGN KEY([tradeId]) REFERENCES [dbo].[trades] ([tradeId]) GO ALTER TABLE [dbo].[orders] CHECK CONSTRAINT [FK_orders_trades] GO Thanks in advance for any help!

    Read the article

  • Delphi: Fast(er) widestring concatenation

    - by Ian Boyd
    i have a function who's job is to convert an ADO Recordset into html: class function RecordsetToHtml(const rs: _Recordset): WideString; And the guts of the function involves a lot of wide string concatenation: while not rs.EOF do begin Result := Result+CRLF+ '<TR>'; for i := 0 to rs.Fields.Count-1 do Result := Result+'<TD>'+VarAsString(rs.Fields[i].Value)+'</TD>'; Result := Result+'</TR>'; rs.MoveNext; end; With a few thousand results, the function takes, what any user would feel, is too long to run. The Delphi Sampling Profiler shows that 99.3% of the time is spent in widestring concatenation (@WStrCatN and @WstrCat). Can anyone think of a way to improve widestring concatenation? i don't think Delphi 5 has any kind of string builder. And Format doesn't support Unicode. And to make sure nobody tries to weasel out: pretend you are implementing the interface: IRecordsetToHtml = interface(IUnknown) function RecordsetToHtml(const rs: _Recordset): WideString; end; Update One I thought of using an IXMLDOMDocument, to build up the HTML as xml. But then i realized that the final HTML would be xhtml and not html - a subtle, but important, difference. Update Two Microsoft knowledge base article: How To Improve String Concatenation Performance

    Read the article

  • Update table instantly or “Bulk” Update in database later? And is it advisable?

    - by Mestika
    Hi, I have a question regarding a semi-constant update in a database. In short it is regarding a checkout function on a web page, which each time the checkout function is evoked it do five steps. I want to try to optimize this function and have my eye on a step where I update a table each time the checkout is performed. I take the information retrieved from the shopping cart and then update the table in question. I do have some indexes on the table, the gain from those are greater than leaving them so this is a cost I’m willing to take. Now, my question is. Could it in some way regarding to performance be better to not update the table instantly but collect every checkout items and save them in some way (maybe in a file) and then at a specific time (or several times) at day take this file and then update the table with the new information. Then I started thinking about if there was a possibility to use some sort of Bulk Update to take a file, hashmap, array (or?) and then update it. And I’m using IBM DB2 version 9.7 Mestika

    Read the article

  • Developer Training – 6 Online Courses to Learn SQL Server, MySQL and Technology

    - by Pinal Dave
    Video courses are the next big thing and I am so happy that I have so far authored 6 different video courses with Pluralsight. Here is the list of the courses. I have listed all of my video courses over here. Note: If you click on the courses and it does not open, you need to login to Pluralsight with a valid username and password or sign up for a FREE trial. Please leave a comment with your favorite course in the comment section. Random 10 winners will get surprise gift via email. Bonus: If you list your favorite module from the course site. SQL Server Performance: Introduction to Query Tuning SQL Server performance tuning is an in-depth topic, and an art to master. A key component of overall application performance tuning is query tuning. Writing queries in an efficient manner, and making sure they execute in the most optimal way possible, is always a challenge. The basics revolve around the details of how SQL Server carries out query execution, so the optimizations explored in this course follow along the same lines. Click to View Course SQL Server Performance: Indexing Basics Indexes are the most crucial objects of the database. They are the first stop for any DBA and Developer when it is about performance tuning. There is a good side as well evil side of the indexes. To master the art of performance tuning one has to understand the fundamentals of the indexes and the best practices associated with the same. This course is for every DBA and Developer who deals with performance tuning and wants to use indexes to improve the performance of the server. Click to View Course SQL Server Questions and Answers This course is designed to help you better understand how to use SQL Server effectively. The course presents many of the common misconceptions about SQL Server, and then carefully debunks those misconceptions with clear explanations and short but compelling demos, showing you how SQL Server really works. This course is for anyone working with SQL Server databases who wants to improve her knowledge and understanding of this complex platform. Click to View Course MySQL Fundamentals MySQL is a popular choice of database for use in web applications, and is a central component of the widely used LAMP open source web application software stack. This course covers the fundamentals of MySQL, including how to install MySQL as well as written basic data retrieval and data modification queries. Click to View Course Building a Successful Blog Expressing yourself is the most common behavior of humans. Blogging has made easy to express yourself. Just like a letter or book has a structure and formula, blogging also has structure and formula. In this introductory course on blogging we will go over a few of the basics of blogging and show the way to get started with blogging immediately. If you already have a blog, this course will be even more relevant as this will discuss many of the common questions and issue you face in your blogging routine. Click to View Course Introduction to ColdFusion ColdFusion is rapid web application development platform. In this course you will learn the basics of how to use ColdFusion platform and rapidly develop web sites. The course begins with learning basics of ColdFusion Markup Language and moves to common development language practices. From there we move to frequent database operations and advanced concepts of Forms, Sessions and Cookies. The last module sums up all the concepts covered in the course with sample application. Click to View Course Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

    Read the article

  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario Conventional Structures Columnstore ? SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

    Read the article

  • C# XDocument Attribute Performance Concerns

    - by Dested
    I have a loaded XDocument that I need to grab all the attributes that equal a certain value and is of a certain element efficiently. My current IEnumerable<XElement> vm; if (!cacher2.TryGetValue(name,out vm)) { vm = project.Descendants(XName.Get(name)); cacher2.Add(name, vm); } XElement[] abdl = (vm.Where(a => a.Attribute(attribute).Value == ab)).ToArray(); cacher2 is a Dictionary<string,IEnumerable<XElement>> The ToArray is so I can evaluate the expression now. I dont think this causes any real speed concerns. The problem is the Where itself. I am searching through anywhere from 1 to 10k items. Any help?

    Read the article

  • Improving long-polling Ajax performance

    - by Bears will eat you
    I'm writing a webapp (Firefox-compatible only) which uses long polling (via jQuery's ajax abilities) to send more-or-less constant updates from the server to the client. I'm concerned about the effects of leaving this running for long periods of time, say, all day or overnight. The basic code skeleton is this: function processResults(xml) { // do stuff with the xml from the server } function fetch() { setTimeout(function () { $.ajax({ type: 'GET', url: 'foo/bar/baz', dataType: 'xml', success: function (xml) { processResults(xml); fetch(); }, error: function (xhr, type, exception) { if (xhr.status === 0) { console.log('XMLHttpRequest cancelled'); } else { console.debug(xhr); fetch(); } } }); }, 500); } (The half-second "sleep" is so that the client doesn't hammer the server if the updates are coming back to the client quickly - which they usually are.) After leaving this running overnight, it tends to make Firefox crawl. I'd been thinking that this could be partially caused by a large stack depth since I've basically written an infinitely recursive function. However, if I use Firebug and throw a breakpoint into fetch, it looks like this is not the case. The stack that Firebug shows me is only about 4 or 5 frames deep, even after an hour. One of the solutions I'm considering is changing my recursive function to an iterative one, but I can't figure out how I would insert the delay in between Ajax requests without spinning. I've looked at the JS 1.7 "yield" keyword but I can't quite wrap my head around it, to figure out if it's what I need here. Is the best solution just to do a hard refresh on the page periodically, say, once every hour? Is there a better/leaner long-polling design pattern that won't put a hurt on the browser even after running for 8 or 12 hours? Or should I just skip the long polling altogether and use a different "constant update" pattern since I usually know how frequently the server will have a response for me?

    Read the article

  • Slow Performance -- ASP .NET ASPNET_WP.EXE and CSC.EXE Running After Clicking Redirect Link

    - by Dan7el
    I click on a link from one page that does a redirect to another page (Response.Redirect(page.aspx)). The browser churns for about 30 seconds and the page displays. I'm trying to track down why it takes so long to load the page. The page hosts two other custom controls. I have commented out the lines of code for each and both controls, and the page still takes about 30 seconds to load. I've set breakpoints on the Page_Load event for each of the controls as well as page.aspx and it also takes about 30 seconds from clicking the link with the Response.Redirect to the first break point. I loaded up task manager and clicked on the link. I notice aspnet_wp.exe and csc.exe run during this 30 second time frame. I'm wondering if there are some sort of code-behind shinanigans going on while I'm waiting for the page to load. This only occurs the first time I click on the link. Afterwards, it's not as slow. I've googled but there's not a lot of useful information about this. Anyone have any ideas? Thanks, ---Dan---

    Read the article

  • NHibernate query with Projections.Cast to DateTime

    - by stiank81
    I'm experimenting with using a string for storing different kind of data types in a database. When I do queries I need to cast the strings to the right type in the query itself. I'm using .Net with NHibernate, and was glad to learn that there exists functionality for this. Consider the simple class: public class Foo { public string Text { get; set; } } I successfully use Projections.Cast to cast to numeric values, e.g. the following query correctly returns all Foos with an interger stored as int - between 1-10. var result = Session.CreateCriteria<Foo>() .Add(Restrictions.Between(Projections.Cast(NHibernateUtil.Int32, Projections.Property("Text")), 1, 10)) .List<Foo>(); Now if I try using this for DateTime I'm not able to make it work no matter what I try. Why?! var date = new DateTime(2010, 5, 21, 11, 30, 00); AddFooToDb(new Foo { Text = date.ToString() } ); // Will add it to the database... var result = Session .CreateCriteria<Foo>() .Add(Restrictions.Eq(Projections.Cast(NHibernateUtil.DateTime, Projections.Property("Text")), date)) .List<Foo>();

    Read the article

  • Updating multiple Sprites - AS3 performance best practices

    - by dani
    Within the container "BubbleContainer" I have multiple "Bubble sprites". Each bubble's graphics object (a circle) is updated on a timer event. Let's say I have 50 Bubble sprites and each circle's radius should be updated with a mathematical formula. How do I organize this logic? How do I update all Bubble sprites within the BubbleContainer? (should I call a bubble.update() function or make a temporary reference to the graphics object?) Where do I put the Math logic? (as static functions?)

    Read the article

  • MySql query optimization help

    - by rohitgu
    I have few queries and am not able to figure out how to optimize them, QUERY 1 select * from t_twitter_tracking where classified is null and tweetType='ENGLISH' order by id limit 500; QUERY 2 Select count(*) as cnt, DATE_FORMAT(CONVERT_TZ(wrdTrk.createdOnGMTDate,'+00:00','+05:30'),'%Y-%m-%d') as dat from t_twitter_tracking wrdTrk where wrdTrk.word like ('dell') and CONVERT_TZ(wrdTrk.createdOnGMTDate,'+00:00','+05:30') between '2010-12-12 00:00:00' and '2010-12-26 00:00:00' group by dat; Both these queries run on the same table, CREATE TABLE `t_twitter_tracking` ( `id` BIGINT(20) NOT NULL AUTO_INCREMENT, `word` VARCHAR(200) NOT NULL, `tweetId` BIGINT(100) NOT NULL, `twtText` VARCHAR(800) NULL DEFAULT NULL, `language` TEXT NULL, `links` TEXT NULL, `tweetType` VARCHAR(20) NULL DEFAULT NULL, `source` TEXT NULL, `sourceStripped` TEXT NULL, `isTruncated` VARCHAR(40) NULL DEFAULT NULL, `inReplyToStatusId` BIGINT(30) NULL DEFAULT NULL, `inReplyToUserId` INT(11) NULL DEFAULT NULL, `rtUsrProfilePicUrl` TEXT NULL, `isFavorited` VARCHAR(40) NULL DEFAULT NULL, `inReplyToScreenName` VARCHAR(40) NULL DEFAULT NULL, `latitude` BIGINT(100) NOT NULL, `longitude` BIGINT(100) NOT NULL, `retweetedStatus` VARCHAR(40) NULL DEFAULT NULL, `statusInReplyToStatusId` BIGINT(100) NOT NULL, `statusInReplyToUserId` BIGINT(100) NOT NULL, `statusFavorited` VARCHAR(40) NULL DEFAULT NULL, `statusInReplyToScreenName` TEXT NULL, `screenName` TEXT NULL, `profilePicUrl` TEXT NULL, `twitterId` BIGINT(100) NOT NULL, `name` TEXT NULL, `location` VARCHAR(100) NULL DEFAULT NULL, `bio` TEXT NULL, `url` TEXT NULL COLLATE 'latin1_swedish_ci', `utcOffset` INT(11) NULL DEFAULT NULL, `timeZone` VARCHAR(100) NULL DEFAULT NULL, `frenCnt` BIGINT(20) NULL DEFAULT '0', `createdAt` DATETIME NULL DEFAULT NULL, `createdOnGMT` VARCHAR(40) NULL DEFAULT NULL, `createdOnServerTime` DATETIME NULL DEFAULT NULL, `follCnt` BIGINT(20) NULL DEFAULT '0', `favCnt` BIGINT(20) NULL DEFAULT '0', `totStatusCnt` BIGINT(20) NULL DEFAULT NULL, `usrCrtDate` VARCHAR(200) NULL DEFAULT NULL, `humanSentiment` VARCHAR(30) NULL DEFAULT NULL, `replied` BIT(1) NULL DEFAULT NULL, `replyMsg` TEXT NULL, `classified` INT(32) NULL DEFAULT NULL, `createdOnGMTDate` DATETIME NULL DEFAULT NULL, `locationDetail` TEXT NULL, `geonameid` INT(11) NULL DEFAULT NULL, `country` VARCHAR(255) NULL DEFAULT NULL, `continent` CHAR(2) NULL DEFAULT NULL, `placeLongitude` FLOAT NULL DEFAULT NULL, `placeLatitude` FLOAT NULL DEFAULT NULL, PRIMARY KEY (`id`), INDEX `id` (`id`, `word`), INDEX `createdOnGMT_index` (`createdOnGMT`) USING BTREE, INDEX `word_index` (`word`) USING BTREE, INDEX `location_index` (`location`) USING BTREE, INDEX `classified_index` (`classified`) USING BTREE, INDEX `tweetType_index` (`tweetType`) USING BTREE, INDEX `getunclassified_index` (`classified`, `tweetType`) USING BTREE, INDEX `timeline_index` (`word`, `createdOnGMTDate`, `classified`) USING BTREE, INDEX `createdOnGMTDate_index` (`createdOnGMTDate`) USING BTREE, INDEX `locdetail_index` (`country`, `id`) USING BTREE, FULLTEXT INDEX `twtText_index` (`twtText`) ) COLLATE='utf8_general_ci' ENGINE=MyISAM ROW_FORMAT=DEFAULT AUTO_INCREMENT=12608048; The table has more than 10 million records. How can I optimize it?

    Read the article

  • jQuery selector performance

    - by rahul
    I have the following two code blocks. Code block 1 var checkboxes = $("div.c1 > input:checkbox.c2", "#main"); var totalCheckboxes = checkboxes.length; var checkedCheckboxes = checkboxes.filter(":checked").length; Code block 2 var totalCheckBoxes = $("div.c1 > input:checkbox.c2", "#main").length; var checkedCheckBoxes = $("div.c1 > input:checkbox.c2:checked", "#main").length; Which one of the above will be faster? Thanks, Rahul

    Read the article

  • Performance penalty of typecasting and boxing/unboxing types in C# when storing generic values

    - by kitsune
    I have a set-up similar to WPF's DependencyProperty and DependencyObject system. My properties however are generic. A BucketProperty has a static GlobalIndex (defined in BucketPropertyBase) which tracks all BucketProperties. A Bucket can have many BucketProperties of any type. A Bucket saves and gets the actual values of these BucketProperties... now my question is, how to deal with the storage of these values, and what is the penalty of using a typecasting when retrieving them? I currently use an array of BucketEntries that save the property values as simple objects. Is there any better way of saving and returning these values? Beneath is a simpliefied version: public class BucketProperty<T> : BucketPropertyBase { } public class Bucket { private BucketEntry[] _bucketEntries; public void SaveValue<T>(BucketProperty<T> property, T value) { SaveBucketEntry(property.GlobalIndex, value) } public T GetValue<T>(BucketProperty<T> property) { return (T)FindBucketEntry(property.GlobalIndex).Value; } } public class BucketEntry { private object _value; private uint _index; public BucketEntry(uint globalIndex, object value) { ... } }

    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 | 49 50 51 52 53 54 55 56 57 58 59 60  | Next Page >