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  • How to measure the time HTTP requests spend sitting in the accept-queue?

    - by David Jones
    I am using Apache2 on Ubuntu 9.10, and I am trying to tune my configuration for a web application to reduce latency of responses to HTTP requests. During a moderately heavy load on my small server, there are 24 apache2 processes handling requests. Additional requests get queued. Using "netstat", I see 24 connections are ESTABLISHED and 125 connections are TIME_WAIT. I am trying to figure out if that is considered a reasonable backlog. Most requests get serviced in a fraction of a second, so I am assuming requests move through the accept-queue fairly quickly, probably within 1 or 2 seconds, but I would like to be more certain. Can anyone recommend an easy way to measure the time an HTTP request sits in the accept-queue? The suggestions I have come across so far seem to start the clock after the apache2 worker accepts the connection. I'm trying to quantify the accept-queue delay before that. thanks in advance, David Jones

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  • Require help in Writing Query

    - by harigm
    The following image have been uploaded to show what I am trying to do and what I wanted out of it Can any one help me write the Query to get the results what I want Please check the following SELECT * FROM KPT WHERE PROPERTY_ID IN (SELECT PROPERTY_ID FROM khata_header WHERE DIV_ID = 3 and RECORD_STATUS = 0) and CHALLAN_NO > 42646 The above is the query I have written and I have got the following result set ID CHALLAN_NO PROPERTY_ID SITE_NO TOTAL_AMOUNT ----- ------------- -------------- ------------------- --------------- 1242 42757 3103010141 296 595 1243 63743 3204190257 483 594 1244 63743 3204190257 483 594 1334 43395 3217010223 1088 576 1421 524210 3320050416 (null) (null) 1422 524210 3320050416 (null) (null) 1560 564355 3320021408 (null) (null) 1870 516292 3320040420 (null) (null) 1940 68357 3217100104 139 1153 1941 68357 3217100104 139 1153 2002 56256 3320100733 511 4430 2003 56256 3320100733 511 4430 2004 66488 3217040869 293 3094 2005 66488 3217040869 293 3094 2016 64571 3217040374 (null) (null) 2036 523122 3320020352 (null) (null) 2039 65682 3217040021 273 919 In my resultset, I am getting the PropertyId repeated, since there are multilple entries, How Can I know How many have been repeated What are those Property Id which have repeated more than 2 times. Little Back ground about the tables are PROPERTY_ID is the FK in the KPT PROPERTY_ID is the PK in KH I am writing a subquery to get the Result, so I am stuck I dont know how to get my results Please help

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  • exchanging 2 memory positions

    - by Jordi
    I am working with OpenCV and Qt, Opencv use BGR while Qt uses RGB , so I have to swap those 2 bytes for very big images. There is a better way of doing the following? I can not think of anything faster but looks so simple and lame... int width = iplImage->width; int height = iplImage->height; uchar *iplImagePtr = (uchar *) iplImage->imageData; uchar buf; int limit = height * width; for (int y = 0; y < limit; ++y) { buf = iplImagePtr[2]; iplImagePtr[2] = iplImagePtr[0]; iplImagePtr[0] = buf; iplImagePtr += 3; } QImage img((uchar *) iplImage->imageData, width, height, QImage::Format_RGB888);

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  • I need some help optimizing my database schema

    - by Steffan
    Here's a layout of my data: Heading 1: Sub heading Sub heading Sub heading Sub heading Sub heading Heading 2: Sub heading Sub heading Sub heading Sub heading Sub heading Heading 3: Sub heading Sub heading Sub heading Sub heading Sub heading Heading 4: Sub heading Sub heading Sub heading Sub heading Sub heading Heading 5: Sub heading Sub heading Sub heading Sub heading Sub heading These headings need to have a 'Completion Status' boolean value which gets linked to a user Id. Currently, this is how my table looks: id | userID | field_1 | field_2 | field_3 | field_4 | etc... ----------------------------------------------------------------------- 1 | 1 | 0 | 0 | 1 | 0 | ----------------------------------------------------------------------- 2 | 2 | 1 | 0 | 1 | 1 | Each field represents one Sub Heading. Having this many columns in my table looks awfully inefficient... How can I go about optimizing this? I can't think of any way to neaten it up :/

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  • How fast can you make linear search?

    - by Mark Probst
    I'm looking to optimize this linear search: static int linear (const int *arr, int n, int key) { int i = 0; while (i < n) { if (arr [i] >= key) break; ++i; } return i; } The array is sorted and the function is supposed to return the index of the first element that is greater or equal to the key. They array is not large (below 200 elements) and will be prepared once for a large number of searches. Array elements after the n-th can if necessary be initialized to something appropriate, if that speeds up the search. No, binary search is not allowed, only linear search.

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  • Simple MySQL Query taking 45 seconds (Gets a record and its "latest" child record)

    - by Brian Lacy
    I have a query which gets a customer and the latest transaction for that customer. Currently this query takes over 45 seconds for 1000 records. This is especially problematic because the script itself may need to be executed as frequently as once per minute! I believe using subqueries may be the answer, but I've had trouble constructing it to actually give me the results I need. SELECT customer.CustID, customer.leadid, customer.Email, customer.FirstName, customer.LastName, transaction.*, MAX(transaction.TransDate) AS LastTransDate FROM customer INNER JOIN transaction ON transaction.CustID = customer.CustID WHERE customer.Email = '".$email."' GROUP BY customer.CustID ORDER BY LastTransDate LIMIT 1000 I really need to get this figured out ASAP. Any help would be greatly appreciated!

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  • SQL-query task, decision?

    - by Sirius Lampochkin
    There is a table of currencies rates in MS SQL Server 2005: ID | CURR | RATE | DATE 1   | USD   | 30      | 01.10.2010 3   | GBP   | 45      | 07.10.2010 5   | USD   | 31      | 08.10.2010 7   | GBP   | 46      | 09.10.2010 9   | USD   | 32      | 12.10.2010 11 | GBP   | 48      | 03.10.2010 Rate are updated in real time and there are more than 1 billion rows in the table. It needs to write a SQL-query, wich will provide latest rates per each currency. My decision is: SELECT c.[id],c.[curr],c.[rate],c.[date] FROM [curr_rate] c, (SELECT curr, MAX(date) AS rate_date FROM [curr_rate] GROUP BY curr) t WHERE c.date = t.rate_date AND c.curr = t.curr ORDER BY c.[curr] ASC Is it possible to write a query without sub-queries and join's with derived tables?

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  • Cannot sort a row of size 8130, which is greater than the allowable maximum of 8094

    - by Sri Kumar
    Hello All, SELECT DISTINCT tblJobReq.JobReqId, tblJobReq.JobStatusId, tblJobClass.JobClassId, tblJobClass.Title, tblJobReq.JobClassSubTitle, tblJobAnnouncement.JobClassDesc, tblJobAnnouncement.EndDate, tblJobAnnouncement.AgencyMktgVerbage, tblJobAnnouncement.SpecInfo, tblJobAnnouncement.Benefits, tblSalary.MinRateSal, tblSalary.MaxRateSal, tblSalary.MinRateHour, tblSalary.MaxRateHour, tblJobClass.StatementEval, tblJobReq.ApprovalDate, tblJobReq.RecruiterId, tblJobReq.AgencyId FROM ((tblJobReq LEFT JOIN tblJobAnnouncement ON tblJobReq.JobReqId =tblJobAnnouncement.JobReqId) INNER JOIN tblJobClass ON tblJobReq.JobClassId = tblJobClass.JobClassId) LEFT JOIN tblSalary ON tblJobClass.SalaryCode = tblSalary.SalaryCode WHERE (tblJobReq.JobClassId in (SELECT JobClassId from tblJobClass WHERE tblJobClass.Title like '%Family Therapist%')) When i try to execute the query it results in the following error. Cannot sort a row of size 8130, which is greater than the allowable maximum of 8094 I checked and didn't find any solution. The only way is to truncate (substring())the "tblJobAnnouncement.JobClassDesc" in the query which has column size of around 8000. Do we have any work around so that i need not truncate the values. Or Can this query be optimised? Any setting in SQL Server 2000?

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  • MySQL MyISAM table performance... painfully, painfully slow

    - by Salman A
    I've got a table structure that can be summarized as follows: pagegroup * pagegroupid * name has 3600 rows page * pageid * pagegroupid * data references pagegroup; has 10000 rows; can have anything between 1-700 rows per pagegroup; the data column is of type mediumtext and the column contains 100k - 200kbytes data per row userdata * userdataid * pageid * column1 * column2 * column9 references page; has about 300,000 rows; can have about 1-50 rows per page The above structure is pretty straight forwad, the problem is that that a join from userdata to page group is terribly, terribly slow even though I have indexed all columns that should be indexed. The time needed to run a query for such a join (userdata inner_join page inner_join pagegroup) exceeds 3 minutes. This is terribly slow considering the fact that I am not selecting the data column at all. Example of the query that takes too long: SELECT userdata.column1, pagegroup.name FROM userdata INNER JOIN page USING( pageid ) INNER JOIN pagegroup USING( pagegroupid ) Please help by explaining why does it take so long and what can i do to make it faster. Edit #1 Explain returns following gibberish: id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE userdata ALL pageid 372420 1 SIMPLE page eq_ref PRIMARY,pagegroupid PRIMARY 4 topsecret.userdata.pageid 1 1 SIMPLE pagegroup eq_ref PRIMARY PRIMARY 4 topsecret.page.pagegroupid 1 Edit #2 SELECT u.field2, p.pageid FROM userdata u INNER JOIN page p ON u.pageid = p.pageid; /* 0.07 sec execution, 6.05 sec fecth */ id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE u ALL pageid 372420 1 SIMPLE p eq_ref PRIMARY PRIMARY 4 topsecret.u.pageid 1 Using index SELECT p.pageid, g.pagegroupid FROM page p INNER JOIN pagegroup g ON p.pagegroupid = g.pagegroupid; /* 9.37 sec execution, 60.0 sec fetch */ id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE g index PRIMARY PRIMARY 4 3646 Using index 1 SIMPLE p ref pagegroupid pagegroupid 5 topsecret.g.pagegroupid 3 Using where Moral of the story Keep medium/long text columns in a separate table if you run into performance problems such as this one.

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  • Representing game states in Tic Tac Toe

    - by dacman
    The goal of the assignment that I'm currently working on for my Data Structures class is to create a of Quantum Tic Tac Toe with an AI that plays to win. Currently, I'm having a bit of trouble finding the most efficient way to represent states. Overview of current Structure: AbstractGame Has and manages AbstractPlayers (game.nextPlayer() returns next player by int ID) Has and intializes AbstractBoard at the beginning of the game Has a GameTree (Complete if called in initialization, incomplete otherwise) AbstractBoard Has a State, a Dimension, and a Parent Game Is a mediator between Player and State, (Translates States from collections of rows to a Point representation Is a StateConsumer AbstractPlayer Is a State Producer Has a ConcreteEvaluationStrategy to evaluate the current board StateTransveralPool Precomputes possible transversals of "3-states". Stores them in a HashMap, where the Set contains nextStates for a given "3-state" State Contains 3 Sets -- a Set of X-Moves, O-Moves, and the Board Each Integer in the set is a Row. These Integer values can be used to get the next row-state from the StateTransversalPool SO, the principle is Each row can be represented by the binary numbers 000-111, where 0 implies an open space and 1 implies a closed space. So, for an incomplete TTT board: From the Set<Integer> board perspective: X_X R1 might be: 101 OO_ R2 might be: 110 X_X R3 might be: 101, where 1 is an open space, and 0 is a closed space From the Set<Integer> xMoves perspective: X_X R1 might be: 101 OO_ R2 might be: 000 X_X R3 might be: 101, where 1 is an X and 0 is not From the Set<Integer> oMoves perspective: X_X R1 might be: 000 OO_ R2 might be: 110 X_X R3 might be: 000, where 1 is an O and 0 is not Then we see that x{R1,R2,R3} & o{R1,R2,R3} = board{R1,R2,R3} The problem is quickly generating next states for the GameTree. If I have player Max (x) with board{R1,R2,R3}, then getting the next row-states for R1, R2, and R3 is simple.. Set<Integer> R1nextStates = StateTransversalPool.get(R1); The problem is that I have to combine each one of those states with R1 and R2. Is there a better data structure besides Set that I could use? Is there a more efficient approach in general? I've also found Point<-State mediation cumbersome. Is there another approach that I could try there? Thanks! Here is the code for my ConcretePlayer class. It might help explain how players produce new states via moves, using the StateProducer (which might need to become StateFactory or StateBuilder). public class ConcretePlayerGeneric extends AbstractPlayer { @Override public BinaryState makeMove() { // Given a move and the current state, produce a new state Point playerMove = super.strategy.evaluate(this); BinaryState currentState = super.getInGame().getBoard().getState(); return StateProducer.getState(this, playerMove, currentState); } } EDIT: I'm starting with normal TTT and moving to Quantum TTT. Given the framework, it should be as simple as creating several new Concrete classes and tweaking some things.

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  • Datatable add new column and values speed issue

    - by Cine
    I am having some speed issue with my datatables. In this particular case I am using it as holder of data, it is never used in GUI or any other scenario that actually uses any of the fancy features. In my speed trace, this particular constructor was showing up as a heavy user of time when my database is ~40k rows. The main user was set_Item of DataTable. protected myclass(DataTable dataTable, DataColumn idColumn) { this.dataTable = dataTable; IdColumn = idColumn ?? this.dataTable.Columns.Add(string.Format("SYS_{0}_SYS", Guid.NewGuid()), Type.GetType("System.Int32")); JobIdColumn = this.dataTable.Columns.Add(string.Format("SYS_{0}_SYS", Guid.NewGuid()), Type.GetType("System.Int32")); IsNewColumn = this.dataTable.Columns.Add(string.Format("SYS_{0}_SYS", Guid.NewGuid()), Type.GetType("System.Int32")); int id = 1; foreach (DataRow r in this.dataTable.Rows) { r[JobIdColumn] = id++; r[IsNewColumn] = (r[IdColumn] == null || r[IdColumn].ToString() == string.Empty) ? 1 : 0; } Digging deeper into the trace, it turns out that set_Item calls EndEdit, which brings my thoughts to the transaction support of the DataTable, for which I have no usage for in my scenario. So my solution to this was to open editing on all of the rows and never close them again. _dt.BeginLoadData(); foreach (DataRow row in _dt.Rows) row.BeginEdit(); Is there a better solution? This feels too much like a big giant hack that will eventually come and bite me. You might suggest that I dont use DataTable at all, but I have already considered that and rejected it due to the amount of effort that would be required to reimplement with a custom class. The main reason it is a datatable is that it is ancient code (.net 1.1 time) and I dont want to spend that much time changing it, and it is also because the original table comes out of a third party component.

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  • Mysql - help me optimize this query

    - by sandeepan-nath
    About the system: -The system has a total of 8 tables - Users - Tutor_Details (Tutors are a type of User,Tutor_Details table is linked to Users) - learning_packs, (stores packs created by tutors) - learning_packs_tag_relations, (holds tag relations meant for search) - tutors_tag_relations and tags and orders (containing purchase details of tutor's packs), order_details linked to orders and tutor_details. For a more clear idea about the tables involved please check the The tables section in the end. -A tags based search approach is being followed.Tag relations are created when new tutors register and when tutors create packs (this makes tutors and packs searcheable). For details please check the section How tags work in this system? below. Following is a simpler representation (not the actual) of the more complex query which I am trying to optimize:- I have used statements like explanation of parts in the query select SUM(DISTINCT( t.tag LIKE "%Dictatorship%" )) as key_1_total_matches, SUM(DISTINCT( t.tag LIKE "%democracy%" )) as key_2_total_matches, td., u., count(distinct(od.id_od)), if (lp.id_lp > 0) then some conditional logic on lp fields else 0 as tutor_popularity from Tutor_Details AS td JOIN Users as u on u.id_user = td.id_user LEFT JOIN Learning_Packs_Tag_Relations AS lptagrels ON td.id_tutor = lptagrels.id_tutor LEFT JOIN Learning_Packs AS lp ON lptagrels.id_lp = lp.id_lp LEFT JOIN `some other tables on lp.id_lp - let's call learning pack tables set (including Learning_Packs table)` LEFT JOIN Order_Details as od on td.id_tutor = od.id_author LEFT JOIN Orders as o on od.id_order = o.id_order LEFT JOIN Tutors_Tag_Relations as ttagrels ON td.id_tutor = ttagrels.id_tutor JOIN Tags as t on (t.id_tag = ttagrels.id_tag) OR (t.id_tag = lptagrels.id_tag) where some condition on Users table's fields AND CASE WHEN ((t.id_tag = lptagrels.id_tag) AND (lp.id_lp 0)) THEN `some conditions on learning pack tables set` ELSE 1 END AND CASE WHEN ((t.id_tag = wtagrels.id_tag) AND (wc.id_wc 0)) THEN `some conditions on webclasses tables set` ELSE 1 END AND CASE WHEN (od.id_od0) THEN od.id_author = td.id_tutor and some conditions on Orders table's fields ELSE 1 END AND ( t.tag LIKE "%Dictatorship%" OR t.tag LIKE "%democracy%") group by td.id_tutor HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 order by tutor_popularity desc, u.surname asc, u.name asc limit 0,20 ===================================================================== What does the above query do? Does AND logic search on the search keywords (2 in this example - "Democracy" and "Dictatorship"). Returns only those tutors for which both the keywords are present in the union of the two sets - tutors details and details of all the packs created by a tutor. To make things clear - Suppose a Tutor name "Sandeepan Nath" has created a pack "My first pack", then:- Searching "Sandeepan Nath" returns Sandeepan Nath. Searching "Sandeepan first" returns Sandeepan Nath. Searching "Sandeepan second" does not return Sandeepan Nath. ====================================================================================== The problem The results returned by the above query are correct (AND logic working as per expectation), but the time taken by the query on heavily loaded databases is like 25 seconds as against normal query timings of the order of 0.005 - 0.0002 seconds, which makes it totally unusable. It is possible that some of the delay is being caused because all the possible fields have not yet been indexed, but I would appreciate a better query as a solution, optimized as much as possible, displaying the same results ========================================================================================== How tags work in this system? When a tutor registers, tags are entered and tag relations are created with respect to tutor's details like name, surname etc. When a Tutors create packs, again tags are entered and tag relations are created with respect to pack's details like pack name, description etc. tag relations for tutors stored in tutors_tag_relations and those for packs stored in learning_packs_tag_relations. All individual tags are stored in tags table. ==================================================================== The tables Most of the following tables contain many other fields which I have omitted here. CREATE TABLE IF NOT EXISTS users ( id_user int(10) unsigned NOT NULL AUTO_INCREMENT, name varchar(100) NOT NULL DEFAULT '', surname varchar(155) NOT NULL DEFAULT '', PRIMARY KEY (id_user) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=636 ; CREATE TABLE IF NOT EXISTS tutor_details ( id_tutor int(10) NOT NULL AUTO_INCREMENT, id_user int(10) NOT NULL DEFAULT '0', PRIMARY KEY (id_tutor), KEY Users_FKIndex1 (id_user) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=51 ; CREATE TABLE IF NOT EXISTS orders ( id_order int(10) unsigned NOT NULL AUTO_INCREMENT, PRIMARY KEY (id_order), KEY Orders_FKIndex1 (id_user), ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=275 ; ALTER TABLE orders ADD CONSTRAINT Orders_ibfk_1 FOREIGN KEY (id_user) REFERENCES users (id_user) ON DELETE NO ACTION ON UPDATE NO ACTION; CREATE TABLE IF NOT EXISTS order_details ( id_od int(10) unsigned NOT NULL AUTO_INCREMENT, id_order int(10) unsigned NOT NULL DEFAULT '0', id_author int(10) NOT NULL DEFAULT '0', PRIMARY KEY (id_od), KEY Order_Details_FKIndex1 (id_order) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=284 ; ALTER TABLE order_details ADD CONSTRAINT Order_Details_ibfk_1 FOREIGN KEY (id_order) REFERENCES orders (id_order) ON DELETE NO ACTION ON UPDATE NO ACTION; CREATE TABLE IF NOT EXISTS learning_packs ( id_lp int(10) unsigned NOT NULL AUTO_INCREMENT, id_author int(10) unsigned NOT NULL DEFAULT '0', PRIMARY KEY (id_lp), KEY Learning_Packs_FKIndex2 (id_author), KEY id_lp (id_lp) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=23 ; CREATE TABLE IF NOT EXISTS tags ( id_tag int(10) unsigned NOT NULL AUTO_INCREMENT, tag varchar(255) DEFAULT NULL, PRIMARY KEY (id_tag), UNIQUE KEY tag (tag), KEY id_tag (id_tag), KEY tag_2 (tag), KEY tag_3 (tag) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=3419 ; CREATE TABLE IF NOT EXISTS tutors_tag_relations ( id_tag int(10) unsigned NOT NULL DEFAULT '0', id_tutor int(10) DEFAULT NULL, KEY Tutors_Tag_Relations (id_tag), KEY id_tutor (id_tutor), KEY id_tag (id_tag) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; ALTER TABLE tutors_tag_relations ADD CONSTRAINT Tutors_Tag_Relations_ibfk_1 FOREIGN KEY (id_tag) REFERENCES tags (id_tag) ON DELETE NO ACTION ON UPDATE NO ACTION; CREATE TABLE IF NOT EXISTS learning_packs_tag_relations ( id_tag int(10) unsigned NOT NULL DEFAULT '0', id_tutor int(10) DEFAULT NULL, id_lp int(10) unsigned DEFAULT NULL, KEY Learning_Packs_Tag_Relations_FKIndex1 (id_tag), KEY id_lp (id_lp), KEY id_tag (id_tag) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; ALTER TABLE learning_packs_tag_relations ADD CONSTRAINT Learning_Packs_Tag_Relations_ibfk_1 FOREIGN KEY (id_tag) REFERENCES tags (id_tag) ON DELETE NO ACTION ON UPDATE NO ACTION; =================================================================================== Following is the exact query (this includes classes also - tutors can create classes and search terms are matched with classes created by tutors):- select count(distinct(od.id_od)) as tutor_popularity, CASE WHEN (IF((wc.id_wc 0), ( wc.wc_api_status = 1 AND wc.wc_type = 0 AND wc.class_date '2010-06-01 22:00:56' AND wccp.status = 1 AND (wccp.country_code='IE' or wccp.country_code IN ('INT'))), 0)) THEN 1 ELSE 0 END as 'classes_published', CASE WHEN (IF((lp.id_lp 0), (lp.id_status = 1 AND lp.published = 1 AND lpcp.status = 1 AND (lpcp.country_code='IE' or lpcp.country_code IN ('INT'))),0)) THEN 1 ELSE 0 END as 'packs_published', td . * , u . * from Tutor_Details AS td JOIN Users as u on u.id_user = td.id_user LEFT JOIN Learning_Packs_Tag_Relations AS lptagrels ON td.id_tutor = lptagrels.id_tutor LEFT JOIN Learning_Packs AS lp ON lptagrels.id_lp = lp.id_lp LEFT JOIN Learning_Packs_Categories AS lpc ON lpc.id_lp_cat = lp.id_lp_cat LEFT JOIN Learning_Packs_Categories AS lpcp ON lpcp.id_lp_cat = lpc.id_parent LEFT JOIN Learning_Pack_Content as lpct on (lp.id_lp = lpct.id_lp) LEFT JOIN Webclasses_Tag_Relations AS wtagrels ON td.id_tutor = wtagrels.id_tutor LEFT JOIN WebClasses AS wc ON wtagrels.id_wc = wc.id_wc LEFT JOIN Learning_Packs_Categories AS wcc ON wcc.id_lp_cat = wc.id_wp_cat LEFT JOIN Learning_Packs_Categories AS wccp ON wccp.id_lp_cat = wcc.id_parent LEFT JOIN Order_Details as od on td.id_tutor = od.id_author LEFT JOIN Orders as o on od.id_order = o.id_order LEFT JOIN Tutors_Tag_Relations as ttagrels ON td.id_tutor = ttagrels.id_tutor JOIN Tags as t on (t.id_tag = ttagrels.id_tag) OR (t.id_tag = lptagrels.id_tag) OR (t.id_tag = wtagrels.id_tag) where (u.country='IE' or u.country IN ('INT')) AND CASE WHEN ((t.id_tag = lptagrels.id_tag) AND (lp.id_lp 0)) THEN lp.id_status = 1 AND lp.published = 1 AND lpcp.status = 1 AND (lpcp.country_code='IE' or lpcp.country_code IN ('INT')) ELSE 1 END AND CASE WHEN ((t.id_tag = wtagrels.id_tag) AND (wc.id_wc 0)) THEN wc.wc_api_status = 1 AND wc.wc_type = 0 AND wc.class_date '2010-06-01 22:00:56' AND wccp.status = 1 AND (wccp.country_code='IE' or wccp.country_code IN ('INT')) ELSE 1 END AND CASE WHEN (od.id_od0) THEN od.id_author = td.id_tutor and o.order_status = 'paid' and CASE WHEN (od.id_wc 0) THEN od.can_attend_class=1 ELSE 1 END ELSE 1 END AND 1 group by td.id_tutor order by tutor_popularity desc, u.surname asc, u.name asc limit 0,20 Please note - The provided database structure does not show all the fields and tables as in this query

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  • what webserver / mod / technique should I use to serve everything from memory?

    - by reinier
    I've lots of lookuptables from which I'll generate my webresponse. I think IIS with Asp.net enables me to keep static lookuptables in memory which I can use to serve up my responses very fast. Are there however also non .net solutions which can do the same? I've looked at fastcgi, but I think this starts X processes, of which anyone can handle Y requests. But the processes are by definition shielded from eachother. I could configure fastcgi to use just 1 process, but does this have scalability implications? anything using PHP or any other interpreted language won't fly because it is also cgi or fastcgi bound right? I understand memcache could be an option, though this would require another (local) socket connection which I'd rather avoid since everything in memory would be much faster. The solution can work under WIndows or Unix... it doesn't matter too much. The only thing which matters is that there will be a lot of requests (100/sec now and growing to 500/sec in a year), and I want to reduce the amount of webservers needed to process it. The current solution is done using PHP and memcache (and the occasional hit to the SQL server backend). Although it is fast (for php anyway), Apache has real problems when the 50/sec is passed. I've put a bounty on this question since I've not seen enough responses to make a wise choice. At the moment I'm considering either Asp.net or fastcgi with C(++).

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  • Multiple ParticleSystems in cocos2d

    - by Mattias Akerman
    I wonder about what road I should go with ParticleSystem. In this particular case I want to create 1-20 small explosions at the same time but with different positions. Right now I'm creating a new ParticleSystem for each explosion and then release it, but of course this is very punishing to the performance. My question is: Is there a way to create one ParticleSystem with multiple emitting sources. If not should I create an array of ParticleSystem in init and then use a free one when an explosion is needed? Or is there another approach I haven't thought of?

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  • Permutations of Varying Size

    - by waiwai933
    I'm trying to write a function in PHP that gets all permutations of all possible sizes. I think an example would be the best way to start off: $my_array = array(1,1,2,3); Possible permutations of varying size: 1 1 // * See Note 2 3 1,1 1,2 1,3 // And so forth, for all the sets of size 2 1,1,2 1,1,3 1,2,1 // And so forth, for all the sets of size 3 1,1,2,3 1,1,3,2 // And so forth, for all the sets of size 4 Note: I don't care if there's a duplicate or not. For the purposes of this example, all future duplicates have been omitted. What I have so far in PHP: function getPermutations($my_array){ $permutation_length = 1; $keep_going = true; while($keep_going){ while($there_are_still_permutations_with_this_length){ // Generate the next permutation and return it into an array // Of course, the actual important part of the code is what I'm having trouble with. } $permutation_length++; if($permutation_length>count($my_array)){ $keep_going = false; } else{ $keep_going = true; } } return $return_array; } The closest thing I can think of is shuffling the array, picking the first n elements, seeing if it's already in the results array, and if it's not, add it in, and then stop when there are mathematically no more possible permutations for that length. But it's ugly and resource-inefficient. Any pseudocode algorithms would be greatly appreciated. Also, for super-duper (worthless) bonus points, is there a way to get just 1 permutation with the function but make it so that it doesn't have to recalculate all previous permutations to get the next? For example, I pass it a parameter 3, which means it's already done 3 permutations, and it just generates number 4 without redoing the previous 3? (Passing it the parameter is not necessary, it could keep track in a global or static). The reason I ask this is because as the array grows, so does the number of possible combinations. Suffice it to say that one small data set with only a dozen elements grows quickly into the trillions of possible combinations and I don't want to task PHP with holding trillions of permutations in its memory at once.

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  • Is it possible to implement bitwise operators using integer arithmetic?

    - by Statement
    Hello World! I am facing a rather peculiar problem. I am working on a compiler for an architecture that doesn't support bitwise operations. However, it handles signed 16 bit integer arithmetics and I was wondering if it would be possible to implement bitwise operations using only: Addition (c = a + b) Subtraction (c = a - b) Division (c = a / b) Multiplication (c = a * b) Modulus (c = a % b) Minimum (c = min(a, b)) Maximum (c = max(a, b)) Comparisons (c = (a < b), c = (a == b), c = (a <= b), et.c.) Jumps (goto, for, et.c.) The bitwise operations I want to be able to support are: Or (c = a | b) And (c = a & b) Xor (c = a ^ b) Left Shift (c = a << b) Right Shift (c = a b) (All integers are signed so this is a problem) Signed Shift (c = a b) One's Complement (a = ~b) (Already found a solution, see below) Normally the problem is the other way around; how to achieve arithmetic optimizations using bitwise hacks. However not in this case. Writable memory is very scarce on this architecture, hence the need for bitwise operations. The bitwise functions themselves should not use a lot of temporary variables. However, constant read-only data & instruction memory is abundant. A side note here also is that jumps and branches are not expensive and all data is readily cached. Jumps cost half the cycles as arithmetic (including load/store) instructions do. On other words, all of the above supported functions cost twice the cycles of a single jump. Some thoughts that might help: I figured out that you can do one's complement (negate bits) with the following code: // Bitwise one's complement b = ~a; // Arithmetic one's complement b = -1 - a; I also remember the old shift hack when dividing with a power of two so the bitwise shift can be expressed as: // Bitwise left shift b = a << 4; // Arithmetic left shift b = a * 16; // 2^4 = 16 // Signed right shift b = a >>> 4; // Arithmetic right shift b = a / 16; For the rest of the bitwise operations I am slightly clueless. I wish the architects of this architecture would have supplied bit-operations. I would also like to know if there is a fast/easy way of computing the power of two (for shift operations) without using a memory data table. A naive solution would be to jump into a field of multiplications: b = 1; switch (a) { case 15: b = b * 2; case 14: b = b * 2; // ... exploting fallthrough (instruction memory is magnitudes larger) case 2: b = b * 2; case 1: b = b * 2; } Or a Set & Jump approach: switch (a) { case 15: b = 32768; break; case 14: b = 16384; break; // ... exploiting the fact that a jump is faster than one additional mul // at the cost of doubling the instruction memory footprint. case 2: b = 4; break; case 1: b = 2; break; }

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  • How to improve my LDAP schema?

    - by asmaier
    Hello, I have a OpenLDAP Database and it holds some project objects that look like dn: cn=Proj1,ou=Project,ou=ua,dc=org cn: Proj1 objectClass: top objectClass: posixGroup member: 001ag member: 002ag System: ABEL System: PCx Budget: ABEL:1000000:0.3 Budget: PCx:300000:0.3 One can see that the Budget attribute is a ":"-separated string, where the first part holds the name of the system the budget is for, the second part holds some budget (which may change every month) and the last entry is a conversion factor for the budget of that system. Seeing this, I thought this is bad database design, since attribute values should always be atomic. But how can I improve that in LDAP, so that I can do a direct ldapsearch or a direct ldapmodify of the budget of System "ABEL" instead of writing a script, that will have to parse and split the ":"-separated string?

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  • Does query plan optimizer works well with joined/filtered table-valued functions?

    - by smoothdeveloper
    In SQLSERVER 2005, I'm using table-valued function as a convenient way to perform arbitrary aggregation on subset data from large table (passing date range or such parameters). I'm using theses inside larger queries as joined computations and I'm wondering if the query plan optimizer work well with them in every condition or if I'm better to unnest such computation in my larger queries. Does query plan optimizer unnest table-valued functions if it make sense? If it doesn't, what do you recommend to avoid code duplication that would occur by manually unnesting them? If it does, how do you identify that from the execution plan? code sample: create table dbo.customers ( [key] uniqueidentifier , constraint pk_dbo_customers primary key ([key]) ) go /* assume large amount of data */ create table dbo.point_of_sales ( [key] uniqueidentifier , customer_key uniqueidentifier , constraint pk_dbo_point_of_sales primary key ([key]) ) go create table dbo.product_ranges ( [key] uniqueidentifier , constraint pk_dbo_product_ranges primary key ([key]) ) go create table dbo.products ( [key] uniqueidentifier , product_range_key uniqueidentifier , release_date datetime , constraint pk_dbo_products primary key ([key]) , constraint fk_dbo_products_product_range_key foreign key (product_range_key) references dbo.product_ranges ([key]) ) go . /* assume large amount of data */ create table dbo.sales_history ( [key] uniqueidentifier , product_key uniqueidentifier , point_of_sale_key uniqueidentifier , accounting_date datetime , amount money , quantity int , constraint pk_dbo_sales_history primary key ([key]) , constraint fk_dbo_sales_history_product_key foreign key (product_key) references dbo.products ([key]) , constraint fk_dbo_sales_history_point_of_sale_key foreign key (point_of_sale_key) references dbo.point_of_sales ([key]) ) go create function dbo.f_sales_history_..snip.._date_range ( @accountingdatelowerbound datetime, @accountingdateupperbound datetime ) returns table as return ( select pos.customer_key , sh.product_key , sum(sh.amount) amount , sum(sh.quantity) quantity from dbo.point_of_sales pos inner join dbo.sales_history sh on sh.point_of_sale_key = pos.[key] where sh.accounting_date between @accountingdatelowerbound and @accountingdateupperbound group by pos.customer_key , sh.product_key ) go -- TODO: insert some data -- this is a table containing a selection of product ranges declare @selectedproductranges table([key] uniqueidentifier) -- this is a table containing a selection of customers declare @selectedcustomers table([key] uniqueidentifier) declare @low datetime , @up datetime -- TODO: set top query parameters . select saleshistory.customer_key , saleshistory.product_key , saleshistory.amount , saleshistory.quantity from dbo.products p inner join @selectedproductranges productrangeselection on p.product_range_key = productrangeselection.[key] inner join @selectedcustomers customerselection on 1 = 1 inner join dbo.f_sales_history_..snip.._date_range(@low, @up) saleshistory on saleshistory.product_key = p.[key] and saleshistory.customer_key = customerselection.[key] I hope the sample makes sense. Much thanks for your help!

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  • Why does adding Crossover to my Genetic Algorithm gives me worse results?

    - by MahlerFive
    I have implemented a Genetic Algorithm to solve the Traveling Salesman Problem (TSP). When I use only mutation, I find better solutions than when I add in crossover. I know that normal crossover methods do not work for TSP, so I implemented both the Ordered Crossover and the PMX Crossover methods, and both suffer from bad results. Here are the other parameters I'm using: Mutation: Single Swap Mutation or Inverted Subsequence Mutation (as described by Tiendil here) with mutation rates tested between 1% and 25%. Selection: Roulette Wheel Selection Fitness function: 1 / distance of tour Population size: Tested 100, 200, 500, I also run the GA 5 times so that I have a variety of starting populations. Stop Condition: 2500 generations With the same dataset of 26 points, I usually get results of about 500-600 distance using purely mutation with high mutation rates. When adding crossover my results are usually in the 800 distance range. The other confusing thing is that I have also implemented a very simple Hill-Climbing algorithm to solve the problem and when I run that 1000 times (faster than running the GA 5 times) I get results around 410-450 distance, and I would expect to get better results using a GA. Any ideas as to why my GA performing worse when I add crossover? And why is it performing much worse than a simple Hill-Climb algorithm which should get stuck on local maxima as it has no way of exploring once it finds a local max?

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  • Optimize GROUP BY&ORDER BY query

    - by Jan Hancic
    I have a web page where users upload&watch videos. Last week I asked what is the best way to track video views so that I could display the most viewed videos this week (videos from all dates). Now I need some help optimizing a query with which I get the videos from the database. The relevant tables are this: video (~239371 rows) VID(int), UID(int), title(varchar), status(enum), type(varchar), is_duplicate(enum), is_adult(enum), channel_id(tinyint) signup (~115440 rows) UID(int), username(varchar) videos_views (~359202 rows after 6 days of collecting data, so this table will grow rapidly) videos_id(int), views_date(date), num_of_views(int) The table video holds the videos, signup hodls users and videos_views holds data about video views (each video can have one row per day in that table). I have this query that does the trick, but takes ~10s to execute, and I imagine this will only get worse over time as the videos_views table grows in size. SELECT v.VID, v.title, v.vkey, v.duration, v.addtime, v.UID, v.viewnumber, v.com_num, v.rate, v.THB, s.username, SUM(vvt.num_of_views) AS tmp_num FROM video v LEFT JOIN videos_views vvt ON v.VID = vvt.videos_id LEFT JOIN signup s on v.UID = s.UID WHERE v.status = 'Converted' AND v.type = 'public' AND v.is_duplicate = '0' AND v.is_adult = '0' AND v.channel_id <> 10 AND vvt.views_date >= '2001-05-11' GROUP BY vvt.videos_id ORDER BY tmp_num DESC LIMIT 8 And here is a screenshot of the EXPLAIN result: So, how can I optimize this?

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  • Date arithmetic using integer values

    - by Dave Jarvis
    Problem String concatenation is slowing down a query: date(extract(YEAR FROM m.taken)||'-1-1') d1, date(extract(YEAR FROM m.taken)||'-1-31') d2 This is realized in code as part of a string, which follows (where the p_ variables are integers): date(extract(YEAR FROM m.taken)||''-'||p_month1||'-'||p_day1||''') d1, date(extract(YEAR FROM m.taken)||''-'||p_month2||'-'||p_day2||''') d2 This part of the query runs in 3.2 seconds with the dates, and 1.5 seconds without, leading me to believe there is ample room for improvement. Question What is a better way to create the date (presumably without concatenation)? Many thanks!

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  • Any ideas on How to search a 2D array quickly?

    - by Tattat
    I jave a 2D array like this, just like a matrix: {{1, 2, 4, 5, 3, 6}, {8, 3, 4, 4, 5, 2}, {8, 3, 4, 2, 6, 2}, //code skips... ... } I want to get all the "4" position, instead of searching the array one by way, and return the position, how can I search it faster / more efficient? thz in advance.

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  • optimal memory layout for read-only/write memory segments.

    - by aaa
    hello. Suppose I have two memory segments (equal size each, approximately 1kb in size) , one is read-only (after initialization), and other is read/write. what is the best layout in memory for such segments in terms of memory performance? one allocation, contiguous segments or two allocations (in general not contiguous). my primary architecture is linux Intel 64-bit. my feeling is former (cache friendlier) case is better. is there circumstances, where second layout is preferred? Thanks

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  • Python performance improvement request for winkler

    - by Martlark
    I'm a python n00b and I'd like some suggestions on how to improve the algorithm to improve the performance of this method to compute the Jaro-Winkler distance of two names. def winklerCompareP(str1, str2): """Return approximate string comparator measure (between 0.0 and 1.0) USAGE: score = winkler(str1, str2) ARGUMENTS: str1 The first string str2 The second string DESCRIPTION: As described in 'An Application of the Fellegi-Sunter Model of Record Linkage to the 1990 U.S. Decennial Census' by William E. Winkler and Yves Thibaudeau. Based on the 'jaro' string comparator, but modifies it according to whether the first few characters are the same or not. """ # Quick check if the strings are the same - - - - - - - - - - - - - - - - - - # jaro_winkler_marker_char = chr(1) if (str1 == str2): return 1.0 len1 = len(str1) len2 = len(str2) halflen = max(len1,len2) / 2 - 1 ass1 = '' # Characters assigned in str1 ass2 = '' # Characters assigned in str2 #ass1 = '' #ass2 = '' workstr1 = str1 workstr2 = str2 common1 = 0 # Number of common characters common2 = 0 #print "'len1', str1[i], start, end, index, ass1, workstr2, common1" # Analyse the first string - - - - - - - - - - - - - - - - - - - - - - - - - # for i in range(len1): start = max(0,i-halflen) end = min(i+halflen+1,len2) index = workstr2.find(str1[i],start,end) #print 'len1', str1[i], start, end, index, ass1, workstr2, common1 if (index > -1): # Found common character common1 += 1 #ass1 += str1[i] ass1 = ass1 + str1[i] workstr2 = workstr2[:index]+jaro_winkler_marker_char+workstr2[index+1:] #print "str1 analyse result", ass1, common1 #print "str1 analyse result", ass1, common1 # Analyse the second string - - - - - - - - - - - - - - - - - - - - - - - - - # for i in range(len2): start = max(0,i-halflen) end = min(i+halflen+1,len1) index = workstr1.find(str2[i],start,end) #print 'len2', str2[i], start, end, index, ass1, workstr1, common2 if (index > -1): # Found common character common2 += 1 #ass2 += str2[i] ass2 = ass2 + str2[i] workstr1 = workstr1[:index]+jaro_winkler_marker_char+workstr1[index+1:] if (common1 != common2): print('Winkler: Wrong common values for strings "%s" and "%s"' % \ (str1, str2) + ', common1: %i, common2: %i' % (common1, common2) + \ ', common should be the same.') common1 = float(common1+common2) / 2.0 ##### This is just a fix ##### if (common1 == 0): return 0.0 # Compute number of transpositions - - - - - - - - - - - - - - - - - - - - - # transposition = 0 for i in range(len(ass1)): if (ass1[i] != ass2[i]): transposition += 1 transposition = transposition / 2.0 # Now compute how many characters are common at beginning - - - - - - - - - - # minlen = min(len1,len2) for same in range(minlen+1): if (str1[:same] != str2[:same]): break same -= 1 if (same > 4): same = 4 common1 = float(common1) w = 1./3.*(common1 / float(len1) + common1 / float(len2) + (common1-transposition) / common1) wn = w + same*0.1 * (1.0 - w) return wn

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  • Is a red-black tree my ideal data structure?

    - by Hugo van der Sanden
    I have a collection of items (big rationals) that I'll be processing. In each case, processing will consist of removing the smallest item in the collection, doing some work, and then adding 0-2 new items (which will always be larger than the removed item). The collection will be initialised with one item, and work will continue until it is empty. I'm not sure what size the collection is likely to reach, but I'd expect in the range 1M-100M items. I will not need to locate any item other than the smallest. I'm currently planning to use a red-black tree, possibly tweaked to keep a pointer to the smallest item. However I've never used one before, and I'm unsure whether my pattern of use fits its characteristics well. 1) Is there a danger the pattern of deletion from the left + random insertion will affect performance, eg by requiring a significantly higher number of rotations than random deletion would? Or will delete and insert operations still be O(log n) with this pattern of use? 2) Would some other data structure give me better performance, either because of the deletion pattern or taking advantage of the fact I only ever need to find the smallest item? Update: glad I asked, the binary heap is clearly a better solution for this case, and as promised turned out to be very easy to implement. Hugo

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