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  • webservice method is not accessible from jquery ajax

    - by Abhisheks.net
    Hello everyone.. i am using jqery ajax to calling a web service method but is is not doing and genrating error.. the code is here for jquery ajax in asp page var indexNo = 13; //pass the value $(document).ready(function() { $("#a1").click(function() { $.ajax({ type: "POST", url: "myWebService.asmx/GetNewDownline", data: "{'indexNo':user_id}", contentType: "application/json; charset=utf-8", dataType: "json", success: function(msg) { $("#divResult").text(msg.d); } }); }); }); and this is the is web service method using System; using System.Collections; using System.Linq; using System.Web; using System.Web.Services; using System.Web.Services.Protocols; using System.Xml.Linq; using System.Data; using System.Web.Script.Serialization; using TC.MLM.DAL; using TC.MLM.BLL.AS; /// /// Summary description for myWebService /// [WebService(Namespace = "http://tempuri.org/")] [WebServiceBinding(ConformsTo = WsiProfiles.BasicProfile1_1)] // To allow this Web Service to be called from script, using ASP.NET AJAX, uncomment the following line. [System.Web.Script.Services.ScriptService] public class myWebService : System.Web.Services.WebService { public myWebService() { //Uncomment the following line if using designed components //InitializeComponent(); } [WebMethod] public string HelloWorld() { return "Hello World"; } [WebMethod] public string GetNewDownline(string indexNo) { IndexDetails indexDtls = new IndexDetails(); indexDtls.IndexNo = "13"; DataSet ds = new DataSet(); ds = TC.MLM.BLL.AS.Index.getIndexDownLineByIndex(indexDtls); indexNoDownline[] newDownline = new indexNoDownline[ds.Tables[0].Rows.Count]; for (int count = 0; count <= ds.Tables[0].Rows.Count - 1; count++) { newDownline[count] = new indexNoDownline(); newDownline[count].adjustedid = ds.Tables[0].Rows[count]["AdjustedID"].ToString(); newDownline[count].name = ds.Tables[0].Rows[count]["name"].ToString(); newDownline[count].structPostion = ds.Tables[0].Rows[count]["Struct_Position"].ToString(); newDownline[count].indexNo = ds.Tables[0].Rows[count]["IndexNo"].ToString(); newDownline[count].promoterId = ds.Tables[0].Rows[count]["PromotorID"].ToString(); newDownline[count].formNo = ds.Tables[0].Rows[count]["FormNo"].ToString(); } JavaScriptSerializer serializer = new JavaScriptSerializer(); JavaScriptSerializer js = new JavaScriptSerializer(); string resultedDownLine = js.Serialize(newDownline); return resultedDownLine; } public class indexNoDownline { public string adjustedid; public string name; public string indexNo; public string structPostion; public string promoterId; public string formNo; } } please help me something.

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  • Report generation in PHP (formats required pdf,xls,doc,csv)

    - by Ish Kumar
    I need to generate reports in my PHP website (in zend framework) Formats required: PDF (with tables & images) // presently using Zend_Pdf XLS (with tables & images) DOC (with tables & images) CSV (only tables) Please recommend robust and fast solution for generating reports in PHP. Platform: Zend Framework on LAMP I know there are some tricky solutions for creating such reports, i wonder is there any open source report generation utility that can be used with LAMP environment

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  • Table clusters in SQLServer

    - by Bruno Martinez
    In Oracle, a table cluster is a group of tables that share common columns and store related data in the same blocks. When tables are clustered, a single data block can contain rows from multiple tables. For example, a block can store rows from both the employees and departments tables rather than from only a single table: http://download.oracle.com/docs/cd/E11882_01/server.112/e10713/tablecls.htm#i25478 Can this be done in SQLServer?

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  • Dynamic sizing of SSRS Report....

    - by Mike
    Hello....I have a report with 12 Tablixes on it. The user can pcik and choose which one of these Tables and their associated data shows when the Report is generated. However, when chosing a subset of the 12 tables, the report shows blank space where I hide the non-selected tablse. Is there any way to make the report resize/fit the size of the selected tables...truncating the white space where the invisible tables are? Thanks

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  • removing null valued columns from dataset in asp .net

    - by N.Sai Harish
    I have a table which stores data with null valued columns for some entries .I want to retrieve only Not null data to the detail view. I tried the following foreach(string strTableField in (objDataSet.Tables[0].Columns[i])) { if(objDataSet.Tables[0].Columns[i].Equals(null)) { objDataSet.Tables[0].Columns.Remove(strTableField); objDataSet.Tables[0].AcceptChanges(); } i++; } but it is giving error .. Pls help me reg this ...

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  • one or more Entity models for one database for entity framework?

    - by KentZhou
    When use entity framework for DAL tier, VS 2010 can create edmx for each database. Question: If I have a database with many tables, should I create only one edmx for all tables or mutiple edmx files? for example, maybe all security tables for one edmx file, other tables for another edmx file. If there is more than one, then in other tiers, there will have more then on ObjectContext in code for business logic. Which one it the best solution for this case?

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  • how to organize country data?

    - by fayer
    how do i organize country data (countries, states and cities etc) in mysql? cause every country has 3 tables: countries, states and cities. should i have each country in separate set of tables or should i have them all in these 3 tables? if i have all of them in same tables, im afraid that the amount of rows will be huge cause i tend to have a lot of countries! what is best practice for this?

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  • Best methods for Lazy Initialization with properties

    - by Stuart Pegg
    I'm currently altering a widely used class to move as much of the expensive initialization from the class constructor into Lazy Initialized properties. Below is an example (in c#): Before: public class ClassA { public readonly ClassB B; public void ClassA() { B = new ClassB(); } } After: public class ClassA { private ClassB _b; public ClassB B { get { if (_b == null) { _b = new ClassB(); } return _b; } } } There are a fair few more of these properties in the class I'm altering, and some are not used in certain contexts (hence the Laziness), but if they are used they're likely to be called repeatedly. Unfortunately, the properties are often also used inside the class. This means there is a potential for the private variable (_b) to be used directly by a method without it being initialized. Is there a way to make only the public property (B) available inside the class, or even an alternative method with the same initialized-when-needed?

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  • CPU Utilization LAMP stack

    - by Max
    We've got an ec2 m2.4xlarge running Magento (centos 5.6, httpd 2.2, php 5.2.17 with eaccelerator 0.9.5.3, mysql 5.1.52). Right now we're getting a large traffic spike, and our top looks like this: top - 09:41:29 up 31 days, 1:12, 1 user, load average: 120.01, 129.03, 113.23 Tasks: 1190 total, 18 running, 1172 sleeping, 0 stopped, 0 zombie Cpu(s): 97.3%us, 1.8%sy, 0.0%ni, 0.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.4%st Mem: 71687720k total, 36898928k used, 34788792k free, 49692k buffers Swap: 880737784k total, 0k used, 880737784k free, 1586524k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 2433 mysql 15 0 23.6g 4.5g 7112 S 564.7 6.6 33607:34 mysqld 24046 apache 16 0 411m 65m 28m S 26.4 0.1 0:09.05 httpd 24360 apache 15 0 410m 60m 25m S 26.4 0.1 0:03.65 httpd 24993 apache 16 0 410m 57m 21m S 26.1 0.1 0:01.41 httpd 24838 apache 16 0 428m 74m 20m S 24.8 0.1 0:02.37 httpd 24359 apache 16 0 411m 62m 26m R 22.3 0.1 0:08.12 httpd 23850 apache 15 0 411m 64m 27m S 16.8 0.1 0:14.54 httpd 25229 apache 16 0 404m 46m 17m R 10.2 0.1 0:00.71 httpd 14594 apache 15 0 404m 63m 34m S 8.4 0.1 1:10.26 httpd 24955 apache 16 0 404m 50m 21m R 8.4 0.1 0:01.66 httpd 24313 apache 16 0 399m 46m 22m R 8.1 0.1 0:02.30 httpd 25119 apache 16 0 411m 59m 23m S 6.8 0.1 0:01.45 httpd Questions: Would giving msyqld more memory help it cache queries and react faster? If so, how? Other than splitting mysql and php to separate servers (which we're about to do) is there anything else we could/should be doing? Thanks! UPDATE: Here's our my.cnf along with the output of mysqltuner. It looks like a cache problem. Thanks again! # cat /etc/my.cnf [client] port = **** socket = /var/lib/mysql/mysql.sock [mysqld] datadir=/mnt/persistent/mysql port=**** socket=/var/lib/mysql/mysql.sock key_buffer = 512M max_allowed_packet = 64M table_cache = 1024 sort_buffer_size = 8M read_buffer_size = 4M read_rnd_buffer_size = 2M myisam_sort_buffer_size = 64M thread_cache_size = 128M tmp_table_size = 128M join_buffer_size = 1M query_cache_limit = 2M query_cache_size= 64M query_cache_type = 1 max_connections = 1000 thread_stack = 128K thread_concurrency = 48 log-bin=mysql-bin server-id = 1 wait_timeout = 300 innodb_data_home_dir = /mnt/persistent/mysql/ innodb_data_file_path = ibdata1:10M:autoextend innodb_buffer_pool_size = 20G innodb_additional_mem_pool_size = 20M innodb_log_file_size = 64M innodb_log_buffer_size = 8M innodb_flush_log_at_trx_commit = 1 innodb_lock_wait_timeout = 50 innodb_thread_concurrency = 48 ft_min_word_len=3 [myisamchk] ft_min_word_len=3 key_buffer = 128M sort_buffer_size = 128M read_buffer = 2M write_buffer = 2M # ./mysqltuner.pl >> MySQLTuner 1.2.0 - Major Hayden <[email protected]> >> Bug reports, feature requests, and downloads at http://mysqltuner.com/ >> Run with '--help' for additional options and output filtering -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.52-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB +Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 2G (Tables: 26) [--] Data in InnoDB tables: 749M (Tables: 250) [!!] Total fragmented tables: 262 -------- Security Recommendations ------------------------------------------- -------- Performance Metrics ------------------------------------------------- [--] Up for: 31d 2h 30m 38s (680M q [253.371 qps], 2M conn, TX: 4825B, RX: 236B) [--] Reads / Writes: 89% / 11% [--] Total buffers: 20.6G global + 15.1M per thread (1000 max threads) [OK] Maximum possible memory usage: 35.4G (51% of installed RAM) [OK] Slow queries: 0% (35K/680M) [OK] Highest usage of available connections: 53% (537/1000) [OK] Key buffer size / total MyISAM indexes: 512.0M/457.2M [OK] Key buffer hit rate: 100.0% (9B cached / 264K reads) [OK] Query cache efficiency: 42.3% (260M cached / 615M selects) [!!] Query cache prunes per day: 4384652 [OK] Sorts requiring temporary tables: 0% (1K temp sorts / 38M sorts) [!!] Joins performed without indexes: 100404 [OK] Temporary tables created on disk: 17% (7M on disk / 45M total) [OK] Thread cache hit rate: 99% (537 created / 2M connections) [!!] Table cache hit rate: 0% (1K open / 946K opened) [OK] Open file limit used: 9% (453/5K) [OK] Table locks acquired immediately: 99% (758M immediate / 758M locks) [OK] InnoDB data size / buffer pool: 749.3M/20.0G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Variables to adjust: query_cache_size (> 64M) join_buffer_size (> 1.0M, or always use indexes with joins) table_cache (> 1024)

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  • Building a jQuery Plug-in to make an HTML Table scrollable

    - by Rick Strahl
    Today I got a call from a customer and we were looking over an older application that uses a lot of tables to display financial and other assorted data. The application is mostly meta-data driven with lots of layout formatting automatically driven through meta data rather than through explicit hand coded HTML layouts. One of the problems in this apps are tables that display a non-fixed amount of data. The users of this app don't want to use paging to see more data, but instead want to display overflow data using a scrollbar. Many of the forms are very densely populated, often with multiple data tables that display a few rows of data in the UI at the most. This sort of layout does not lend itself well to paging, but works much better with scrollable data. Unfortunately scrollable tables are not easily created. HTML Tables are mangy beasts as anybody who's done any sort of Web development knows. Tables are finicky when it comes to styling and layout, and they have many funky quirks, especially when it comes to scrolling both of the table rows themselves or even the child columns. There's no built-in way to make tables scroll and to lock headers while you do, and while you can embed a table (or anything really) into a scrolling div with something like this: <div style="position:relative; overflow: hidden; overflow-y: scroll; height: 200px; width: 400px;"> <table id="table" style="width: 100%" class="blackborder" > <thead> <tr class="gridheader"> <th>Column 1</th> <th>Column 2</th> <th>Column 3</th> <th >Column 4</th> </tr> </thead> <tbody> <tr> <td>Column 1 Content</td> <td>Column 2 Content</td> <td>Column 3 Content</td> <td>Column 4 Content</td> </tr> <tr> <td>Column 1 Content</td> <td>Column 2 Content</td> <td>Column 3 Content</td> <td>Column 4 Content</td> </tr> … </tbody> </table> </div> </div> that won't give a very satisfying visual experience: Both the header and body scroll which looks odd. You lose context as soon as the header scrolls off the top and when you reach the bottom of the list the bottom outline of the table shows which also looks off. The the side bar shows all the way down the length of the table yet another visual miscue. In a pinch this will work, but it's ugly. What's out there? Before we go further here you should know that there are a few capable grid plug-ins out there already. Among them: Flexigrid (can work of any table as well as with AJAX data) jQuery Scrollable Table Plug-in (feature similar to what I need but not quite) jqGrid (mostly an Ajax Grid which is very powerful and works very well) But in the end none of them fit the bill of what I needed in this situation. All of these require custom CSS and some of them are fairly complex to restyle. Others are AJAX only or work better with AJAX loaded data. However, I need to actually try (as much as possible) to maintain the original styling of the tables without requiring extensive re-styling. Building the makeTableScrollable() Plug-in To make a table scrollable requires rearranging the table a bit. In the plug-in I built I create two <div> tags and split the table into two: one for the table header and one for the table body. The bottom <div> tag then contains only the table's row data and can be scrolled while the header stays fixed. Using jQuery the basic idea is pretty simple: You create the divs, copy the original table into the bottom, then clone the table, clear all content append the <thead> section, into new table and then copy that table into the second header <div>. Easy as pie, right? Unfortunately it's a bit more complicated than that as it's tricky to get the width of the table right to account for the scrollbar (by adding a small column) and making sure the borders properly line up for the two tables. A lot of style settings have to be made to ensure the table is a fixed size, to remove and reattach borders, to add extra space to allow for the scrollbar and so forth. The end result of my plug-in is a table with a scrollbar. Using the same table I used earlier the result looks like this: To create it, I use the following jQuery plug-in logic to select my table and run the makeTableScrollable() plug-in against the selector: $("#table").makeTableScrollable( { cssClass:"blackborder"} ); Without much further ado, here's the short code for the plug-in: (function ($) { $.fn.makeTableScrollable = function (options) { return this.each(function () { var $table = $(this); var opt = { // height of the table height: "250px", // right padding added to support the scrollbar rightPadding: "10px", // cssclass used for the wrapper div cssClass: "" } $.extend(opt, options); var $thead = $table.find("thead"); var $ths = $thead.find("th"); var id = $table.attr("id"); var cssClass = $table.attr("class"); if (!id) id = "_table_" + new Date().getMilliseconds().ToString(); $table.width("+=" + opt.rightPadding); $table.css("border-width", 0); // add a column to all rows of the table var first = true; $table.find("tr").each(function () { var row = $(this); if (first) { row.append($("<th>").width(opt.rightPadding)); first = false; } else row.append($("<td>").width(opt.rightPadding)); }); // force full sizing on each of the th elemnts $ths.each(function () { var $th = $(this); $th.css("width", $th.width()); }); // Create the table wrapper div var $tblDiv = $("<div>").css({ position: "relative", overflow: "hidden", overflowY: "scroll" }) .addClass(opt.cssClass); var width = $table.width(); $tblDiv.width(width).height(opt.height) .attr("id", id + "_wrapper") .css("border-top", "none"); // Insert before $tblDiv $tblDiv.insertBefore($table); // then move the table into it $table.appendTo($tblDiv); // Clone the div for header var $hdDiv = $tblDiv.clone(); $hdDiv.empty(); var width = $table.width(); $hdDiv.attr("style", "") .css("border-bottom", "none") .width(width) .attr("id", id + "_wrapper_header"); // create a copy of the table and remove all children var $newTable = $($table).clone(); $newTable.empty() .attr("id", $table.attr("id") + "_header"); $thead.appendTo($newTable); $hdDiv.insertBefore($tblDiv); $newTable.appendTo($hdDiv); $table.css("border-width", 0); }); } })(jQuery); Oh sweet spaghetti code :-) The code starts out by dealing the parameters that can be passed in the options object map: height The height of the full table/structure. The height of the outside wrapper container. Defaults to 200px. rightPadding The padding that is added to the right of the table to account for the scrollbar. Creates a column of this width and injects it into the table. If too small the rightmost column might get truncated. if too large the empty column might show. cssClass The CSS class of the wrapping container that appears to wrap the table. If you want a border around your table this class should probably provide it since the plug-in removes the table border. The rest of the code is obtuse, but pretty straight forward. It starts by creating a new column in the table to accommodate the width of the scrollbar and avoid clipping of text in the rightmost column. The width of the columns is explicitly set in the header elements to force the size of the table to be fixed and to provide the same sizing when the THEAD section is moved to a new copied table later. The table wrapper div is created, formatted and the table is moved into it. The new wrapper div is cloned for the header wrapper and configured. Finally the actual table is cloned and cleared of all elements. The original table's THEAD section is then moved into the new table. At last the new table is added to the header <div>, and the header <div> is inserted before the table wrapper <div>. I'm always amazed how easy jQuery makes it to do this sort of re-arranging, and given of what's happening the amount of code is rather small. Disclaimer: Your mileage may vary A word of warning: I make no guarantees about the code above. It's a first cut and I provided this here mainly to demonstrate the concepts of decomposing and reassembling an HTML layout :-) which jQuery makes so nice and easy. I tested this component against the typical scenarios we plan on using it for which are tables that use a few well known styles (or no styling at all). I suspect if you have complex styling on your <table> tag that things might not go so well. If you plan on using this plug-in you might want to minimize your styling of the table tag and defer any border formatting using the class passed in via the cssClass parameter, which ends up on the two wrapper div's that wrap the header and body rows. There's also no explicit support for footers. I rarely if ever use footers (when not using paging that is), so I didn't feel the need to add footer support. However, if you need that it's not difficult to add - the logic is the same as adding the header. The plug-in relies on a well-formatted table that has THEAD and TBODY sections along with TH tags in the header. Note that ASP.NET WebForm DataGrids and GridViews by default do not generate well-formatted table HTML. You can look at my Adding proper THEAD sections to a GridView post for more info on how to get a GridView to render properly. The plug-in has no dependencies other than jQuery. Even with the limitations in mind I hope this might be useful to some of you. I know I've already identified a number of places in my own existing applications where I will be plugging this in almost immediately. Resources Download Sample and Plug-in code Latest version in the West Wind Web & AJAX Toolkit Repository © Rick Strahl, West Wind Technologies, 2005-2011Posted in jQuery  HTML  ASP.NET  

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  • Building Queries Systematically

    - by Jeremy Smyth
    The SQL language is a bit like a toolkit for data. It consists of lots of little fiddly bits of syntax that, taken together, allow you to build complex edifices and return powerful results. For the uninitiated, the many tools can be quite confusing, and it's sometimes difficult to decide how to go about the process of building non-trivial queries, that is, queries that are more than a simple SELECT a, b FROM c; A System for Building Queries When you're building queries, you could use a system like the following:  Decide which fields contain the values you want to use in our output, and how you wish to alias those fields Values you want to see in your output Values you want to use in calculations . For example, to calculate margin on a product, you could calculate price - cost and give it the alias margin. Values you want to filter with. For example, you might only want to see products that weigh more than 2Kg or that are blue. The weight or colour columns could contain that information. Values you want to order by. For example you might want the most expensive products first, and the least last. You could use the price column in descending order to achieve that. Assuming the fields you've picked in point 1 are in multiple tables, find the connections between those tables Look for relationships between tables and identify the columns that implement those relationships. For example, The Orders table could have a CustomerID field referencing the same column in the Customers table. Sometimes the problem doesn't use relationships but rests on a different field; sometimes the query is looking for a coincidence of fact rather than a foreign key constraint. For example you might have sales representatives who live in the same state as a customer; this information is normally not used in relationships, but if your query is for organizing events where sales representatives meet customers, it's useful in that query. In such a case you would record the names of columns at either end of such a connection. Sometimes relationships require a bridge, a junction table that wasn't identified in point 1 above but is needed to connect tables you need; these are used in "many-to-many relationships". In these cases you need to record the columns in each table that connect to similar columns in other tables. Construct a join or series of joins using the fields and tables identified in point 2 above. This becomes your FROM clause. Filter using some of the fields in point 1 above. This becomes your WHERE clause. Construct an ORDER BY clause using values from point 1 above that are relevant to the desired order of the output rows. Project the result using the remainder of the fields in point 1 above. This becomes your SELECT clause. A Worked Example   Let's say you want to query the world database to find a list of countries (with their capitals) and the change in GNP, using the difference between the GNP and GNPOld columns, and that you only want to see results for countries with a population greater than 100,000,000. Using the system described above, we could do the following:  The Country.Name and City.Name columns contain the name of the country and city respectively.  The change in GNP comes from the calculation GNP - GNPOld. Both those columns are in the Country table. This calculation is also used to order the output, in descending order To see only countries with a population greater than 100,000,000, you need the Population field of the Country table. There is also a Population field in the City table, so you'll need to specify the table name to disambiguate. You can also represent a number like 100 million as 100e6 instead of 100000000 to make it easier to read. Because the fields come from the Country and City tables, you'll need to join them. There are two relationships between these tables: Each city is hosted within a country, and the city's CountryCode column identifies that country. Also, each country has a capital city, whose ID is contained within the country's Capital column. This latter relationship is the one to use, so the relevant columns and the condition that uses them is represented by the following FROM clause:  FROM Country JOIN City ON Country.Capital = City.ID The statement should only return countries with a population greater than 100,000,000. Country.Population is the relevant column, so the WHERE clause becomes:  WHERE Country.Population > 100e6  To sort the result set in reverse order of difference in GNP, you could use either the calculation, or the position in the output (it's the third column): ORDER BY GNP - GNPOld or ORDER BY 3 Finally, project the columns you wish to see by constructing the SELECT clause: SELECT Country.Name AS Country, City.Name AS Capital,        GNP - GNPOld AS `Difference in GNP`  The whole statement ends up looking like this:  mysql> SELECT Country.Name AS Country, City.Name AS Capital, -> GNP - GNPOld AS `Difference in GNP` -> FROM Country JOIN City ON Country.Capital = City.ID -> WHERE Country.Population > 100e6 -> ORDER BY 3 DESC; +--------------------+------------+-------------------+ | Country            | Capital    | Difference in GNP | +--------------------+------------+-------------------+ | United States | Washington | 399800.00 | | China | Peking | 64549.00 | | India | New Delhi | 16542.00 | | Nigeria | Abuja | 7084.00 | | Pakistan | Islamabad | 2740.00 | | Bangladesh | Dhaka | 886.00 | | Brazil | Brasília | -27369.00 | | Indonesia | Jakarta | -130020.00 | | Russian Federation | Moscow | -166381.00 | | Japan | Tokyo | -405596.00 | +--------------------+------------+-------------------+ 10 rows in set (0.00 sec) Queries with Aggregates and GROUP BY While this system might work well for many queries, it doesn't cater for situations where you have complex summaries and aggregation. For aggregation, you'd start with choosing which columns to view in the output, but this time you'd construct them as aggregate expressions. For example, you could look at the average population, or the count of distinct regions.You could also perform more complex aggregations, such as the average of GNP per head of population calculated as AVG(GNP/Population). Having chosen the values to appear in the output, you must choose how to aggregate those values. A useful way to think about this is that every aggregate query is of the form X, Y per Z. The SELECT clause contains the expressions for X and Y, as already described, and Z becomes your GROUP BY clause. Ordinarily you would also include Z in the query so you see how you are grouping, so the output becomes Z, X, Y per Z.  As an example, consider the following, which shows a count of  countries and the average population per continent:  mysql> SELECT Continent, COUNT(Name), AVG(Population)     -> FROM Country     -> GROUP BY Continent; +---------------+-------------+-----------------+ | Continent     | COUNT(Name) | AVG(Population) | +---------------+-------------+-----------------+ | Asia          |          51 |   72647562.7451 | | Europe        |          46 |   15871186.9565 | | North America |          37 |   13053864.8649 | | Africa        |          58 |   13525431.0345 | | Oceania       |          28 |    1085755.3571 | | Antarctica    |           5 |          0.0000 | | South America |          14 |   24698571.4286 | +---------------+-------------+-----------------+ 7 rows in set (0.00 sec) In this case, X is the number of countries, Y is the average population, and Z is the continent. Of course, you could have more fields in the SELECT clause, and  more fields in the GROUP BY clause as you require. You would also normally alias columns to make the output more suited to your requirements. More Complex Queries  Queries can get considerably more interesting than this. You could also add joins and other expressions to your aggregate query, as in the earlier part of this post. You could have more complex conditions in the WHERE clause. Similarly, you could use queries such as these in subqueries of yet more complex super-queries. Each technique becomes another tool in your toolbox, until before you know it you're writing queries across 15 tables that take two pages to write out. But that's for another day...

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  • SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

    - by pinaldave
    Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Resolving data redundancy up front

    - by okeofs
    Introduction As all of us do when confronted with a problem, the resource of choice is to ‘Google it’. This is where the plot thickens. Recently I was asked to stage data from numerous databases which were to be loaded into a data warehouse. To make a long story short, I was looking for a manner in which to obtain the table names from each database, to ascertain potential overlap.   As the source data comes from a SQL database created from dumps of a third party product,  one could say that there were +/- 95 tables for each database.   Yes I know that first instinct is to use the system stored procedure “exec sp_msforeachdb 'select "?" AS db, * from [?].sys.tables'”. However, if one stops to think about this, it would be nice to have all the results in a temporary or disc based  table; which in itself , implies additional labour. This said,  I decided to ‘re-invent’ the wheel. The full code sample may be found at the bottom of this article.   Define a few temporary tables and variables   declare @SQL varchar(max); declare @databasename varchar(75) /* drop table ##rawdata3 drop table #rawdata1 drop table #rawdata11 */ -- A temp table to hold the names of my databases CREATE TABLE #rawdata1 (    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) )     --A temp table with the same database names as above, HOWEVER using an --Identity number (recNO) as a loop variable. --You will note below that I loop through until I reach 25 (see below) as at --that point the system databases, the reporting server database etc begin. --1- 24 are user databases. These are really what I was looking for. --Whilst NOT the best solution,it works and the code was meant as a quick --and dirty. CREATE TABLE #rawdata11 (    recNo int identity(1,1),    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) )   --My output table showing the database name and table name CREATE TABLE ##rawdata3 (    database_name varchar(75) ,    table_name varchar(75), )   Insert the database names into a temporary table I pull the database names using the system stored procedure sp_databases   INSERT INTO #rawdata1 EXEC sp_databases Go   Insert the results from #rawdata1 into a table containing a record number  #rawdata11 so that I can LOOP through the extract   INSERT into #rawdata11 select * from  #rawdata1   We now declare 3 more variables:  @kounter is used to keep track of our position within the loop. @databasename is used to keep track of the’ current ‘ database name being used in the current pass of the loop;  as inorder to obtain the tables for that database we  need to issue a ‘USE’ statement, an insert command and other related code parts. This is the challenging part. @sql is a varchar(max) variable used to contain the ‘USE’ statement PLUS the’ insert ‘ code statements. We now initalize @kounter to 1 .   declare @kounter int; declare @databasename varchar(75); declare @sql varchar(max); set @kounter = 1   The Loop The astute reader will remember that the temporary table #rawdata11 contains our  database names  and each ‘database row’ has a record number (recNo). I am only interested in record numbers under 25. I now set the value of the temporary variable @DatabaseName (see below) .Note that I used the row number as a part of the predicate. Now, knowing the database name, I can create dynamic T-SQL to be executed using the sp_sqlexec stored procedure (see the code in red below). Finally, after all the tables for that given database have been placed in temporary table ##rawdata3, I increment the counter and continue on. Note that I used a global temporary table to ensure that the result set persists after the termination of the run. At some stage, I plan to redo this part of the code, as global temporary tables are not really an ideal solution.    WHILE (@kounter < 25)  BEGIN  select @DatabaseName = database_name from #rawdata11 where recNo = @kounter  set @SQL = 'Use ' + @DatabaseName + ' Insert into ##rawdata3 ' + + ' SELECT table_catalog,Table_name FROM information_schema.tables' exec sp_sqlexec  @Sql  SET @kounter  = @kounter + 1  END   The full code extract   Here is the full code sample.   declare @SQL varchar(max); declare @databasename varchar(75) /* drop table ##rawdata3 drop table #rawdata1 drop table #rawdata11 */ CREATE TABLE #rawdata1 (    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) ) CREATE TABLE #rawdata11 (    recNo int identity(1,1),    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) ) CREATE TABLE ##rawdata3 (    database_name varchar(75) ,    table_name varchar(75), )   INSERT INTO #rawdata1 EXEC sp_databases go INSERT into #rawdata11 select * from  #rawdata1 declare @kounter int; declare @databasename varchar(75); declare @sql varchar(max); set @kounter = 1 WHILE (@kounter < 25)  BEGIN  select @databasename = database_name from #rawdata11 where recNo = @kounter  set @SQL = 'Use ' + @DatabaseName + ' Insert into ##rawdata3 ' + + ' SELECT table_catalog,Table_name FROM information_schema.tables' exec sp_sqlexec  @Sql  SET @kounter  = @kounter + 1  END    select * from ##rawdata3  where table_name like '%SalesOrderHeader%'

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  • Joins in single-table queries

    - by Rob Farley
    Tables are only metadata. They don’t store data. I’ve written something about this before, but I want to take a viewpoint of this idea around the topic of joins, especially since it’s the topic for T-SQL Tuesday this month. Hosted this time by Sebastian Meine (@sqlity), who has a whole series on joins this month. Good for him – it’s a great topic. In that last post I discussed the fact that we write queries against tables, but that the engine turns it into a plan against indexes. My point wasn’t simply that a table is actually just a Clustered Index (or heap, which I consider just a special type of index), but that data access always happens against indexes – never tables – and we should be thinking about the indexes (specifically the non-clustered ones) when we write our queries. I described the scenario of looking up phone numbers, and how it never really occurs to us that there is a master list of phone numbers, because we think in terms of the useful non-clustered indexes that the phone companies provide us, but anyway – that’s not the point of this post. So a table is metadata. It stores information about the names of columns and their data types. Nullability, default values, constraints, triggers – these are all things that define the table, but the data isn’t stored in the table. The data that a table describes is stored in a heap or clustered index, but it goes further than this. All the useful data is going to live in non-clustered indexes. Remember this. It’s important. Stop thinking about tables, and start thinking about indexes. So let’s think about tables as indexes. This applies even in a world created by someone else, who doesn’t have the best indexes in mind for you. I’m sure you don’t need me to explain Covering Index bit – the fact that if you don’t have sufficient columns “included” in your index, your query plan will either have to do a Lookup, or else it’ll give up using your index and use one that does have everything it needs (even if that means scanning it). If you haven’t seen that before, drop me a line and I’ll run through it with you. Or go and read a post I did a long while ago about the maths involved in that decision. So – what I’m going to tell you is that a Lookup is a join. When I run SELECT CustomerID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 285; against the AdventureWorks2012 get the following plan: I’m sure you can see the join. Don’t look in the query, it’s not there. But you should be able to see the join in the plan. It’s an Inner Join, implemented by a Nested Loop. It’s pulling data in from the Index Seek, and joining that to the results of a Key Lookup. It clearly is – the QO wouldn’t call it that if it wasn’t really one. It behaves exactly like any other Nested Loop (Inner Join) operator, pulling rows from one side and putting a request in from the other. You wouldn’t have a problem accepting it as a join if the query were slightly different, such as SELECT sod.OrderQty FROM Sales.SalesOrderHeader AS soh JOIN Sales.SalesOrderDetail as sod on sod.SalesOrderID = soh.SalesOrderID WHERE soh.SalesPersonID = 285; Amazingly similar, of course. This one is an explicit join, the first example was just as much a join, even thought you didn’t actually ask for one. You need to consider this when you’re thinking about your queries. But it gets more interesting. Consider this query: SELECT SalesOrderID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 276 AND CustomerID = 29522; It doesn’t look like there’s a join here either, but look at the plan. That’s not some Lookup in action – that’s a proper Merge Join. The Query Optimizer has worked out that it can get the data it needs by looking in two separate indexes and then doing a Merge Join on the data that it gets. Both indexes used are ordered by the column that’s indexed (one on SalesPersonID, one on CustomerID), and then by the CIX key SalesOrderID. Just like when you seek in the phone book to Farley, the Farleys you have are ordered by FirstName, these seek operations return the data ordered by the next field. This order is SalesOrderID, even though you didn’t explicitly put that column in the index definition. The result is two datasets that are ordered by SalesOrderID, making them very mergeable. Another example is the simple query SELECT CustomerID FROM Sales.SalesOrderHeader WHERE SalesPersonID = 276; This one prefers a Hash Match to a standard lookup even! This isn’t just ordinary index intersection, this is something else again! Just like before, we could imagine it better with two whole tables, but we shouldn’t try to distinguish between joining two tables and joining two indexes. The Query Optimizer can see (using basic maths) that it’s worth doing these particular operations using these two less-than-ideal indexes (because of course, the best indexese would be on both columns – a composite such as (SalesPersonID, CustomerID – and it would have the SalesOrderID column as part of it as the CIX key still). You need to think like this too. Not in terms of excusing single-column indexes like the ones in AdventureWorks2012, but in terms of having a picture about how you’d like your queries to run. If you start to think about what data you need, where it’s coming from, and how it’s going to be used, then you will almost certainly write better queries. …and yes, this would include when you’re dealing with regular joins across multiples, not just against joins within single table queries.

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  • MSSQL: Copying data from one database to another

    - by DigiMortal
    I have database that has data imported from another server using import and export wizard of SQL Server Management Studio. There is also empty database with same tables but it also has primary keys, foreign keys and indexes. How to get data from first database to another? Here is the description of my crusade. And believe me – it is not nice one. Bugs in import and export wizard There is some awful bugs in import and export wizard that makes data imports and exports possible only on very limited manner: wizard is not able to analyze foreign keys, wizard wants to create tables always, whatever you say in settings. The result is faulty and useless package. Now let’s go step by step and make things work in our scenario. Database There are two databases. Let’s name them like this: PLAIN – contains data imported from remote server (no indexes, no keys, no nothing, just plain dumb data) CORRECT – empty database with same structure as remote database (indexes, keys and everything else but no data) Our goal is to get data from PLAIN to CORRECT. 1. Create import and export package In this point we will create faulty SSIS package using SQL Server Management Studio. Run import and export wizard and let it create SSIS package that reads data from CORRECT and writes it to, let’s say, CORRECT-2. Make sure you enable identity insert. Make sure there are no views selected. Make sure you don’t let package to create tables (you can miss this step because it wants to create tables anyway). Save package to SSIS. 2. Modify import and export package Now let’s clean up the package and remove all faulty crap. Connect SQL Server Management Studio to SSIS instance. Select the package you just saved and export it to your hard disc. Run Business Intelligence Studio. Create new SSIS project (DON’T MISS THIS STEP). Add package from disc as existing item to project and open it. Move to Control Flow page do one of following: Remove all preparation SQL-tasks and connect Data Flow tasks. Modify all preparation SQL-tasks so the existence of tables is checked before table is created (yes, you have to do it manually). Add new Execute-SQL task as first task in control flow: Open task properties. Assign destination connection as connection to use. Insert the following SQL as command:   EXEC sp_MSForEachTable 'ALTER TABLE ? NOCHECK CONSTRAINT ALL' GO   EXEC sp_MSForEachTable 'DELETE FROM ?' GO   Save task. Add new Execute-SQL task as last task in control flow: Open task properties. Assign destination connection as connection to use. Insert the following SQL as command:   EXEC sp_MSForEachTable 'ALTER TABLE ? CHECK CONSTRAINT ALL' GO   Save task Now connect first Execute-SQL task with first Data Flow task and last Data Flow task with second Execute-SQL task. Now move to Package Explorer tab and change connections under Connection Managers folder. Make source connection to use database PLAIN. Make destination connection to use database CORRECT. Save package and rebuilt the project. Update package using SQL Server Management Studio. Some hints: Make sure you take the package from solution folder because it is saved there now. Don’t overwrite existing package. Use numeric suffix and let Management Studio to create a new version of package. Now you are done with your package. Run it to test it and clean out all the errors you find. TRUNCATE vs DELETE You can see that I used DELETE FROM instead of TRUNCATE. Why? Because TRUNCATE has some nasty limits (taken from MSDN): “You cannot use TRUNCATE TABLE on a table referenced by a FOREIGN KEY constraint; instead, use DELETE statement without a WHERE clause. Because TRUNCATE TABLE is not logged, it cannot activate a trigger. TRUNCATE TABLE may not be used on tables participating in an indexed view.” As I am not sure what tables you have and how they are used I provided here the solution that should work for all scenarios. If you need better performance then in some cases you can use TRUNCATE table instead of DELETE. Conclusion My conclusion is bitter this time although I am very positive guy. It is A.D. 2010 and still we have to write stupid hacks for simple things. Simple tools that existed before are long gone and we have to live mysterious bloatware that is our only choice when using default tools. If you take a look at the length of this posting and the count of steps I had to do for one easy thing you should treat it as a signal that something has went wrong in last years. Although I got my job done I would be still more happy if out of box tools are more intelligent one day. References T-SQL Trick for Deleting All Data in Your Database (Mauro Cardarelli) TRUNCATE TABLE (MSDN Library) Error Handling in SQL 2000 – a Background (Erland Sommarskog) Disable/Enable Foreign Key and Check constraints in SQL Server (Decipher)

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  • LinqDataSource wizard table list is not refreshing after updating LinqToSql classes

    - by dotnet_learner
    I have changed my dbml file like this. I have deleted all the tables and stored procs. I added new tables and stored procs from a new database. In the code-behind, I can access the new tables and stored procs. However, in the LinqDataSource using the same dbContext when I'm trying to configure the LinqDataSource. I can see all the old tables in the wizard drop-down. How to refresh the the wizard drop-down so that I can select the newly added tables? Deleting the old LinqDataSourceand adding a new one is not working.

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  • Combine 2 apps into one DB?

    - by coffeeaddict
    I'm debating whether to use the same DB for both my blog and my wiki. Since both are open source, and both install the required tables which is a very small number of tables for both apps, I'm thinking about just using one database to represent both sets of tables. Is this common and safe to do? I am hesitant because I always create a new DB for every application I create or use. But in this case, I don't want to spend another $10 a month from my shared hosting just to get another SQL 2008 DB to host a wiki..it's small and I'm the only one using the wiki. I just want to point the wiki to my existing blog DB that's already running and have the wiki wizard auto gen the tables to that DB and just hold both sets of tables there.

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  • Design Pattern for Complex Data Modeling

    - by Aaron Hayman
    I'm developing a program that has a SQL database as a backing store. As a very broad description, the program itself allows a user to generate records in any number of user-defined tables and make connections between them. As for specs: Any record generated must be able to be connected to any other record in any other user table (excluding itself...the record, not the table). These "connections" are directional, and the list of connections a record has is user ordered. Moreover, a record must "know" of connections made from it to others as well as connections made to it from others. The connections are kind of the point of this program, so there is a strong possibility that the number of connections made is very high, especially if the user is using the software as intended. A record's field can also include aggregate information from it's connections (like obtaining average, sum, etc) that must be updated on change from another record it's connected to. To conserve memory, only relevant information must be loaded at any one time (can't load the entire database in memory at load and go from there). I cannot assume the backing store is local. Right now it is, but eventually this program will include syncing to a remote db. Neither the user tables, connections or records are known at design time as they are user generated. I've spent a lot of time trying to figure out how to design the backing store and the object model to best fit these specs. In my first design attempt on this, I had one object managing all a table's records and connections. I attempted this first because it kept the memory footprint smaller (records and connections were simple dicts), but maintaining aggregate and link information between tables became....onerous (ie...a huge spaghettified mess). Tracing dependencies using this method almost became impossible. Instead, I've settled on a distributed graph model where each record and connection is 'aware' of what's around it by managing it own data and connections to other records. Doing this increases my memory footprint but also let me create a faulting system so connections/records aren't loaded into memory until they're needed. It's also much easier to code: trace dependencies, eliminate cycling recursive updates, etc. My biggest problem is storing/loading the connections. I'm not happy with any of my current solutions/ideas so I wanted to ask and see if anybody else has any ideas of how this should be structured. Connections are fairly simple. They contain: fromRecordID, fromTableID, fromRecordOrder, toRecordID, toTableID, toRecordOrder. Here's what I've come up with so far: Store all the connections in one big table. If I do this, either I load all connections at once (one big db call) or make a call every time a user table is loaded. The big issue here: the size of the connections table has the potential to be huge, and I'm afraid it would slow things down. Store in separate tables all the outgoing connections for each user table. This is probably the worst idea I've had. Now my connections are 'spread out' over multiple tables (one for each user table), which means I have to make a separate DB called to each table (or make a huge join) just to find all the incoming connections for a particular user table. I've avoided making "one big ass table", but I'm not sure the cost is worth it. Store in separate tables all outgoing AND incoming connections for each user table (using a flag to distinguish between incoming vs outgoing). This is the idea I'm leaning towards, but it will essentially double the total DB storage for all the connections (as each connection will be stored in two tables). It also means I have to make sure connection information is kept in sync in both places. This is obviously not ideal but it does mean that when I load a user table, I only need to load one 'connection' table and have all the information I need. This also presents a separate problem, that of connection object creation. Since each user table has a list of all connections, there are two opportunities for a connection object to be made. However, connections objects (designed to facilitate communication between records) should only be created once. This means I'll have to devise a common caching/factory object to make sure only one connection object is made per connection. Does anybody have any ideas of a better way to do this? Once I've committed to a particular design pattern I'm pretty much stuck with it, so I want to make sure I've come up with the best one possible.

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  • How to convert an HTML table to an array in python

    - by user345660
    I have an html document, and I want to pull the tables out of this document and return them as arrays. I'm picturing 2 functions, one that finds all the html tables in a document, and a second one that turns html tables into 2-dimensional arrays. Something like this: htmltables = get_tables(htmldocument) for table in htmltables: array=make_array(table) There's 2 catches: 1. The number tables varies day to day 2. The tables have all kinds of weird extra formatting, like bold and blink tags, randomly thrown in. Thanks!

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  • Oracle - Is there any effects of not having a primary key on a table ?

    - by Sathya
    We use sequence numbers for primary keys on the tables. There are some tables where we dont really use the primary key for any querying purpose. But, we have Indexes on other columns. These are non-unique indexes. The queries use these non-primary key columns in the WHERE conditions. So, I dont really see any benefit of having a primary key on such tables. My experience with SQL 2000 was that, it used to replicate tables which had some primary key. Otherwise it would not. I am using Oracle 10gR2. I would like to know if there are any such side-effects of having tables that dont have primary key.

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  • custom DB logging using enterprise library 4.1

    - by Rohit
    We have to create a historical log of all the changed entities. we have defined our custom tables for this purpose. I have to incorporate this tables in Enterprise library logging block and do logging in these tables. I need to write a SP to insert values to these tables. Till now,what i have got from google is that i have to create a listener inheriting from CustomTraceListener and give my implementation of WriteMessage. What i need to know is,how will i plug my tables and SP in Enterprise library logging block.

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  • Best performance approach to history mechanism?

    - by Royi Namir
    We are going to create History Mechanism for our changes in DB (DART in pic) via Triggers. we have 600 tables. Each record that will be changed - the trigger will insert the deleted one into XXX. regarding to the XXX : option 1 : clone each table in "Dart" DB and each table now will have a "sister table" e.g. : Table1 will have Table1_History problems : we will have 1200 tables programmer can do mistakes by working on wrong tables... option 2 : make a new DB (DART_2005 in pic) and the history tables will be there option 3 : use linked server which stores the Db which will contain the history tables. question : 1) which option gives the best performance ( I guess 3 is not - but is it 1 or 2 or same ?) 2) Does option 2 is acting like "linked server" ( in queries we will need to select from both DB's...) 3) What is the best practice approach ?

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  • SQLITE (C/C++interface) - How to commit a transaction

    - by AJ
    I am using sqlite c/c++ interface. Now here is my scenario - I have 3 tables (related tables) say A, B, C. Now, there is a function called Set, which get some inputs and based on the inputs inserts rows into these three tables. (sometimes it can be an update in one of the tables) Now I need two things. One, i dont want autocommit feature. Basically I would like to commit after every 1000 calls to Set function Secondly, within the set function itself, if i find that after inserting into two tables, the third insert fails, then i have to revert, those particular changes in that Set function call. Now i dont see any sqlite3_commit function exposed. I only see a function called sqlite3_commit_hook() which is slightly diff in documentation. Are there any function exposed for this purpose? or What is the way to achieve this behaviour? Can you help me with the best approach of doing this. Regards, Arjun

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