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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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  • Movies recommendation engine conceptual database design

    - by Supyxy
    I am working at an movie recommendations engine and i'm facing a DB design issue. My actual database looks like this: MOVIES [ID,TITLE] KEYWORDS_TABLE [ID,KEY_ID] - where ID is Foreign Key for MOVIES.id and KEY_ID is a key for a text keywords table This is not the entire DB, but i showed here what's important for my problem. I have about 50,000 movies and about 1,3 milion keywords correlations, and basically my algorithm consists in extracting all the who have the same keywords with a given movie, then ordering them by the number of keywords correlations. For example i looked for a movie similar to 'Cast away' and it returned 'Six days and six nights' because it had the most keywords correlations (4 keywords): Island Airplane crash Stranded Pilot The algorithm is based on more factors, but this one is the most important and the most difficult for the approach. Basically what i do now is getting all the movies that have at least one keyword similar to the given movie and then ordering them by other factors which are not important for a moment. There wouldn't be any problem if there weren't so many records, a query lasts in many cases up to 10-20 seconds and some of them return even over 5000 movies. Someone already helped me on here (thanks Mark Byers) with optimizing the query but that's not enough because it takes too longer SELECT DISTINCT M.title FROM keywords_table K1 JOIN keywords_table K2 ON K2.key_id = K1.key_id JOIN movies M ON K2.id = M.id WHERE K1.id = 4 So i thought it would be better if i pre-made those lists with movies recommendations for each movie, but i'm not sure how to design the tables.. whatever is it a good idea or how would you take this approach?

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  • Shouldn't prepared statements be much faster?

    - by silversky
    $s = explode (" ", microtime()); $s = $s[0]+$s[1]; $con = mysqli_connect ('localhost', 'test', 'pass', 'db') or die('Err'); for ($i=0; $i<1000; $i++) { $stmt = $con -> prepare( " SELECT MAX(id) AS max_id , MIN(id) AS min_id FROM tb "); $stmt -> execute(); $stmt->bind_result($M,$m); $stmt->free_result(); $rand = mt_rand( $m , $M ).'<br/>'; $res = $con -> prepare( " SELECT * FROM tb WHERE id >= ? LIMIT 0,1 "); $res -> bind_param("s", $rand); $res -> execute(); $res->free_result(); } $e = explode (" ", microtime()); $e = $e[0]+$e[1]; echo number_format($e-$s, 4, '.', ''); // and: $link = mysql_connect ("localhost", "test", "pass") or die (); mysql_select_db ("db") or die ("Unable to select database".mysql_error()); for ($i=0; $i<1000; $i++) { $range_result = mysql_query( " SELECT MAX(`id`) AS max_id , MIN(`id`) AS min_id FROM tb "); $range_row = mysql_fetch_object( $range_result ); $random = mt_rand( $range_row->min_id , $range_row->max_id ); $result = mysql_query( " SELECT * FROM tb WHERE id >= $random LIMIT 0,1 "); } defenitly prepared statements are much more safer but also every where it says that they are much faster BUT in my test on the above code I have: - 2.45 sec for prepared statements - 5.05 sec for the secon example What do you think I'm doing wrong? Should I use the second solution or I should try to optimize the prep stmt?

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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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  • How to optimize my PostgreSQL DB for prefix search?

    - by asmaier
    I have a table called "nodes" with roughly 1.7 million rows in my PostgreSQL db =#\d nodes Table "public.nodes" Column | Type | Modifiers --------+------------------------+----------- id | integer | not null title | character varying(256) | score | double precision | Indexes: "nodes_pkey" PRIMARY KEY, btree (id) I want to use information from that table for autocompletion of a search field, showing the user a list of the ten titles having the highest score fitting to his input. So I used this query (here searching for all titles starting with "s") =# explain analyze select title,score from nodes where title ilike 's%' order by score desc; QUERY PLAN ----------------------------------------------------------------------------------------------------------------------- Sort (cost=64177.92..64581.38 rows=161385 width=25) (actual time=4930.334..5047.321 rows=161264 loops=1) Sort Key: score Sort Method: external merge Disk: 5712kB -> Seq Scan on nodes (cost=0.00..46630.50 rows=161385 width=25) (actual time=0.611..4464.413 rows=161264 loops=1) Filter: ((title)::text ~~* 's%'::text) Total runtime: 5260.791 ms (6 rows) This was much to slow for using it with autocomplete. With some information from Using PostgreSQL in Web 2.0 Applications I was able to improve that with a special index =# create index title_idx on nodes using btree(lower(title) text_pattern_ops); =# explain analyze select title,score from nodes where lower(title) like lower('s%') order by score desc limit 10; QUERY PLAN ------------------------------------------------------------------------------------------------------------------------------------------ Limit (cost=18122.41..18122.43 rows=10 width=25) (actual time=1324.703..1324.708 rows=10 loops=1) -> Sort (cost=18122.41..18144.60 rows=8876 width=25) (actual time=1324.700..1324.702 rows=10 loops=1) Sort Key: score Sort Method: top-N heapsort Memory: 17kB -> Bitmap Heap Scan on nodes (cost=243.53..17930.60 rows=8876 width=25) (actual time=96.124..1227.203 rows=161264 loops=1) Filter: (lower((title)::text) ~~ 's%'::text) -> Bitmap Index Scan on title_idx (cost=0.00..241.31 rows=8876 width=0) (actual time=90.059..90.059 rows=161264 loops=1) Index Cond: ((lower((title)::text) ~>=~ 's'::text) AND (lower((title)::text) ~<~ 't'::text)) Total runtime: 1325.085 ms (9 rows) So this gave me a speedup of factor 4. But can this be further improved? What if I want to use '%s%' instead of 's%'? Do I have any chance of getting a decent performance with PostgreSQL in that case, too? Or should I better try a different solution (Lucene?, Sphinx?) for implementing my autocomplete feature?

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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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  • 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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  • 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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  • 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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  • Optimizing Haskell code

    - by Masse
    I'm trying to learn Haskell and after an article in reddit about Markov text chains, I decided to implement Markov text generation first in Python and now in Haskell. However I noticed that my python implementation is way faster than the Haskell version, even Haskell is compiled to native code. I am wondering what I should do to make the Haskell code run faster and for now I believe it's so much slower because of using Data.Map instead of hashmaps, but I'm not sure I'll post the Python code and Haskell as well. With the same data, Python takes around 3 seconds and Haskell is closer to 16 seconds. It comes without saying that I'll take any constructive criticism :). import random import re import cPickle class Markov: def __init__(self, filenames): self.filenames = filenames self.cache = self.train(self.readfiles()) picklefd = open("dump", "w") cPickle.dump(self.cache, picklefd) picklefd.close() def train(self, text): splitted = re.findall(r"(\w+|[.!?',])", text) print "Total of %d splitted words" % (len(splitted)) cache = {} for i in xrange(len(splitted)-2): pair = (splitted[i], splitted[i+1]) followup = splitted[i+2] if pair in cache: if followup not in cache[pair]: cache[pair][followup] = 1 else: cache[pair][followup] += 1 else: cache[pair] = {followup: 1} return cache def readfiles(self): data = "" for filename in self.filenames: fd = open(filename) data += fd.read() fd.close() return data def concat(self, words): sentence = "" for word in words: if word in "'\",?!:;.": sentence = sentence[0:-1] + word + " " else: sentence += word + " " return sentence def pickword(self, words): temp = [(k, words[k]) for k in words] results = [] for (word, n) in temp: results.append(word) if n > 1: for i in xrange(n-1): results.append(word) return random.choice(results) def gentext(self, words): allwords = [k for k in self.cache] (first, second) = random.choice(filter(lambda (a,b): a.istitle(), [k for k in self.cache])) sentence = [first, second] while len(sentence) < words or sentence[-1] is not ".": current = (sentence[-2], sentence[-1]) if current in self.cache: followup = self.pickword(self.cache[current]) sentence.append(followup) else: print "Wasn't able to. Breaking" break print self.concat(sentence) Markov(["76.txt"]) -- module Markov ( train , fox ) where import Debug.Trace import qualified Data.Map as M import qualified System.Random as R import qualified Data.ByteString.Char8 as B type Database = M.Map (B.ByteString, B.ByteString) (M.Map B.ByteString Int) train :: [B.ByteString] -> Database train (x:y:[]) = M.empty train (x:y:z:xs) = let l = train (y:z:xs) in M.insertWith' (\new old -> M.insertWith' (+) z 1 old) (x, y) (M.singleton z 1) `seq` l main = do contents <- B.readFile "76.txt" print $ train $ B.words contents fox="The quick brown fox jumps over the brown fox who is slow jumps over the brown fox who is dead."

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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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  • Is there a way to tell JVM to optimize my code before processing?

    - by Rogach
    I have a method, which takes much time to execute first time. But after several invocations, it takes about 30 times less time. So, to make my application respond to user interaction faster, I "warm-up" this method (5 times) with some sample data on initialization of application. But this increases app start-up time. I read, that JVM's can optimize and compile my java code to native, thus speeding things up. I wanted to know - maybe there is some way to explicitly tell JVM that I want this method to be compiled on startup of application?

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  • WPF, how can I optimize lines and circles drawing ?

    - by Aurélien Ribon
    Hello ! I am developping an application where I need to draw a graph on the screen. For this purpose, I use a Canvas and I put Controls on it. An example of such a draw as shown in the app can be found here : http://free0.hiboox.com/images/1610/d82e0b7cc3521071ede601d3542c7bc5.png It works fine for simple graphs, but I also want to be able to draw very large graphs (hundreds of nodes). And when I try to draw a very large graph, it takes a LOT of time to render. My problem is that the code is not optimized at all, I just wanted it to work. Until now, I have a Canvas on the one hand, and multiple Controls on the other hands. Actually, circles and lines are listed in collections, and for each item of these collections, I use a ControlTemplate, defining a red circle, a black circle, a line, etc. Here is an example, the definition of a graph circle : <!-- STYLE : DISPLAY DATA NODE --> <Style TargetType="{x:Type flow.elements:DisplayNode}"> <Setter Property="Canvas.Left" Value="{Binding X, RelativeSource={RelativeSource Self}}" /> <Setter Property="Canvas.Top" Value="{Binding Y, RelativeSource={RelativeSource Self}}" /> <Setter Property="Template"> <Setter.Value> <ControlTemplate TargetType="{x:Type flow.elements:DisplayNode}"> <!--TEMPLATE--> <Grid x:Name="grid" Margin="-30,-30,0,0"> <Ellipse x:Name="selectionEllipse" StrokeThickness="0" Width="60" Height="60" Opacity="0" IsHitTestVisible="False"> <Ellipse.Fill> <RadialGradientBrush> <GradientStop Color="Black" Offset="0.398" /> <GradientStop Offset="1" /> </RadialGradientBrush> </Ellipse.Fill> </Ellipse> <Ellipse Stroke="Black" Width="30" Height="30" x:Name="ellipse"> <Ellipse.Fill> <LinearGradientBrush EndPoint="0,1"> <GradientStop Offset="0" Color="White" /> <GradientStop Offset="1.5" Color="LightGray" /> </LinearGradientBrush> </Ellipse.Fill> </Ellipse> <TextBlock x:Name="tblock" Text="{Binding NodeName, RelativeSource={RelativeSource Mode=TemplatedParent}}" Foreground="Black" VerticalAlignment="Center" HorizontalAlignment="Center" FontSize="10.667" /> </Grid> <!--TRIGGERS--> <ControlTemplate.Triggers> <!--DATAINPUT--> <MultiTrigger> <MultiTrigger.Conditions> <Condition Property="SkinMode" Value="NODETYPE" /> <Condition Property="NodeType" Value="DATAINPUT" /> </MultiTrigger.Conditions> <Setter TargetName="tblock" Property="Foreground" Value="White" /> <Setter TargetName="ellipse" Property="Fill"> <Setter.Value> <LinearGradientBrush EndPoint="0,1"> <GradientStop Offset="-0.5" Color="White" /> <GradientStop Offset="1" Color="Black" /> </LinearGradientBrush> </Setter.Value> </Setter> </MultiTrigger> <!--DATAOUTPUT--> <MultiTrigger> <MultiTrigger.Conditions> <Condition Property="SkinMode" Value="NODETYPE" /> <Condition Property="NodeType" Value="DATAOUTPUT" /> </MultiTrigger.Conditions> <Setter TargetName="tblock" Property="Foreground" Value="White" /> <Setter TargetName="ellipse" Property="Fill"> <Setter.Value> <LinearGradientBrush EndPoint="0,1"> <GradientStop Offset="-0.5" Color="White" /> <GradientStop Offset="1" Color="Black" /> </LinearGradientBrush> </Setter.Value> </Setter> </MultiTrigger> ....... THERE IS A TOTAL OF 7 MULTITRIGGERS ....... </ControlTemplate.Triggers> </ControlTemplate> </Setter.Value> </Setter> </Style> Also, the lines are drawn using the Line Control. <!-- STYLE : DISPLAY LINK --> <Style TargetType="{x:Type flow.elements:DisplayLink}"> <Setter Property="Template"> <Setter.Value> <ControlTemplate TargetType="{x:Type flow.elements:DisplayLink}"> <!--TEMPLATE--> <Line X1="{Binding X1, RelativeSource={RelativeSource TemplatedParent}}" X2="{Binding X2, RelativeSource={RelativeSource TemplatedParent}}" Y1="{Binding Y1, RelativeSource={RelativeSource TemplatedParent}}" Y2="{Binding Y2, RelativeSource={RelativeSource TemplatedParent}}" Stroke="Gray" StrokeThickness="2" x:Name="line" /> <!--TRIGGERS--> <ControlTemplate.Triggers> <!--BRANCH : ASSERTION--> <MultiTrigger> <MultiTrigger.Conditions> <Condition Property="SkinMode" Value="BRANCHTYPE" /> <Condition Property="BranchType" Value="ASSERTION" /> </MultiTrigger.Conditions> <Setter TargetName="line" Property="Stroke" Value="#E0E0E0" /> </MultiTrigger> </ControlTemplate.Triggers> </ControlTemplate> </Setter.Value> </Setter> </Style> So, I need your advices. How can I drastically improve the rendering performances ? Should I define each MultiTrigger circle rendering possibility in its own ControlTemplate instead ? Is there a better line drawing technique ? Should I open a DrawingContext and draw everything in one control, instead of having hundreds of controls ?

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  • When optimizing database queries, what exactly is the relationship between number of queries and siz

    - by williamjones
    To optimize application speed, everyone always advises to minimize the number of queries an application makes to the database, consolidating them into fewer queries that retrieve more wherever possible. However, this also always comes with the caution that data transferred is still data transferred, and just because you are making fewer queries doesn't make the data transferred free. I'm in a situation where I can over-include on the query in order to cut down the number of queries, and simply remove the unwanted data in the application code. Is there any type of a rule of thumb on how much of a cost there is to each query, to know when to optimize number of queries versus size of queries? I've tried to Google for objective performance analysis data, but surprisingly haven't been able to find anything like that. Clearly this relationship will change for factors such as when the database grows in size, making this somewhat individualized, but surely this is not so individualized that a broad sense of the landscape can't be drawn out? I'm looking for general answers, but for what it's worth, I'm running an application on Heroku.com, which means Ruby on Rails with a Postgres database.

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  • Why is MySQL with InnoDB doing a table scan when key exists and choosing to examine 70 times more ro

    - by andysk
    Hello, I'm troubleshooting a query performance problem. Here's an expected query plan from explain: mysql> explain select * from table1 where tdcol between '2010-04-13:00:00' and '2010-04-14 03:16'; +----+-------------+--------------------+-------+---------------+--------------+---------+------+---------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+--------------------+-------+---------------+--------------+---------+------+---------+-------------+ | 1 | SIMPLE | table1 | range | tdcol | tdcol | 8 | NULL | 5437848 | Using where | +----+-------------+--------------------+-------+---------------+--------------+---------+------+---------+-------------+ 1 row in set (0.00 sec) That makes sense, since the index named tdcol (KEY tdcol (tdcol)) is used, and about 5M rows should be selected from this query. However, if I query for just one more minute of data, we get this query plan: mysql> explain select * from table1 where tdcol between '2010-04-13 00:00' and '2010-04-14 03:17'; +----+-------------+--------------------+------+---------------+------+---------+------+-----------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+--------------------+------+---------------+------+---------+------+-----------+-------------+ | 1 | SIMPLE | table1 | ALL | tdcol | NULL | NULL | NULL | 381601300 | Using where | +----+-------------+--------------------+------+---------------+------+---------+------+-----------+-------------+ 1 row in set (0.00 sec) The optimizer believes that the scan will be better, but it's over 70x more rows to examine, so I have a hard time believing that the table scan is better. Also, the 'USE KEY tdcol' syntax does not change the query plan. Thanks in advance for any help, and I'm more than happy to provide more info/answer questions.

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  • High performance text file parsing in .net

    - by diamandiev
    Here is the situation: I am making a small prog to parse server log files. I tested it with a log file with several thousand requests (between 10000 - 20000 don't know exactly) What i have to do is to load the log text files into memory so that i can query them. This is taking the most resources. The methods that take the most cpu time are those (worst culprits first): string.split - splits the line values into a array of values string.contains - checking if the user agent contains a specific agent string. (determine browser ID) string.tolower - various purposes streamreader.readline - to read the log file line by line. string.startswith - determine if line is a column definition line or a line with values there were some others that i was able to replace. For example the dictionary getter was taking lots of resources too. Which i had not expected since its a dictionary and should have its keys indexed. I replaced it with a multidimensional array and saved some cpu time. Now i am running on a fast dual core and the total time it takes to load the file i mentioned is about 1 sec. Now this is really bad. Imagine a site that has tens of thousands of visits a day. It's going to take minutes to load the log file. So what are my alternatives? If any, cause i think this is just a .net limitation and i can't do much about it.

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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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  • 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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  • Enforcing a query in MySql to use a specific index

    - by Hossein
    Hi, I have large table. consisting of only 3 columns (id(INT),bookmarkID(INT),tagID(INT)).I have two BTREE indexes one for each bookmarkID and tagID columns.This table has about 21 Million records. I am trying to run this query: SELECT bookmarkID,COUNT(bookmarkID) AS count FROM bookmark_tag_map GROUP BY tagID,bookmarkID HAVING tagID IN (-----"tagIDList"-----) AND count >= N which takes ages to return the results.I read somewhere that if make an index in which it has tagID,bookmarkID together, i will get a much faster result. I created the index after some time. Tried the query again, but it seems that this query is not using the new index that I have made.I ran EXPLAIN and saw that it is actually true. My question now is that how I can enforce a query to use a specific index? also comments on other ways to make the query faster are welcome. Thanks

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  • What is the best algorithm for this problem?

    - by mark
    What is the most efficient algorithm to solve the following problem? Given 6 arrays, D1,D2,D3,D4,D5 and D6 each containing 6 numbers like: D1[0] = number D2[0] = number ...... D6[0] = number D1[1] = another number D2[1] = another number .... ..... .... ...... .... D1[5] = yet another number .... ...... .... Given a second array ST1, containing 1 number: ST1[0] = 6 Given a third array ans, containing 6 numbers: ans[0] = 3, ans[1] = 4, ans[2] = 5, ......ans[5] = 8 Using as index for the arrays D1,D2,D3,D4,D5 and D6, the number that goes from 0, to the number stored in ST1[0] minus one, in this example 6, so from 0 to 6-1, compare each res array against each D array My algorithm so far is: I tried to keep everything unlooped as much as possible. EML := ST1[0] //number contained in ST1[0] EML1 := 0 //start index for the arrays D While EML1 < EML if D1[ELM1] = ans[0] goto two if D2[ELM1] = ans[0] goto two if D3[ELM1] = ans[0] goto two if D4[ELM1] = ans[0] goto two if D5[ELM1] = ans[0] goto two if D6[ELM1] = ans[0] goto two ELM1 = ELM1 + 1 return 0 //bad row of numbers, if while ends two: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[1] goto two if D2[ELM1] = ans[1] goto two if D3[ELM1] = ans[1] goto two if D4[ELM1] = ans[1] goto two if D5[ELM1] = ans[1] goto two if D6[ELM1] = ans[1] goto two ELM1 = ELM1 + 1 return 0 three: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[2] goto two if D2[ELM1] = ans[2] goto two if D3[ELM1] = ans[2] goto two if D4[ELM1] = ans[2] goto two if D5[ELM1] = ans[2] goto two if D6[ELM1] = ans[2] goto two ELM1 = ELM1 + 1 return 0 four: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[3] goto two if D2[ELM1] = ans[3] goto two if D3[ELM1] = ans[3] goto two if D4[ELM1] = ans[3] goto two if D5[ELM1] = ans[3] goto two if D6[ELM1] = ans[3] goto two ELM1 = ELM1 + 1 return 0 five: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[4] goto two if D2[ELM1] = ans[4] goto two if D3[ELM1] = ans[4] goto two if D4[ELM1] = ans[4] goto two if D5[ELM1] = ans[4] goto two if D6[ELM1] = ans[4] goto two ELM1 = ELM1 + 1 return 0 six: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[0] return 1 //good row of numbers if D2[ELM1] = ans[0] return 1 if D3[ELM1] = ans[0] return 1 if D4[ELM1] = ans[0] return 1 if D5[ELM1] = ans[0] return 1 if D6[ELM1] = ans[0] return 1 ELM1 = ELM1 + 1 return 0 As language of choice, it would be pure c

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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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