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  • Optimize SELECT DISTINCT CONCAT query in MySQL

    - by L. Cosio
    Hello! I'm running this query: SELECT DISTINCT CONCAT(ALFA_CLAVE, FECHA_NACI) FROM listado GROUP BY ALFA_CLAVE HAVING count(CONCAT(ALFA_CLAVE, FECHA_NACI)) > 1 Is there any way to optimize it? Queries are taking 2-3 hours on a table with 850,000 rows. Adding an index to ALFA_CLAVE and FECHA_NACI would work? Thanks in advanced

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  • Optimize SQL databases by adding index columns

    - by Viktor Sehr
    This might be implementation specific so the question regards how SQL databases is generally implemented. Say I have a database looking like this; Product with columns [ProductName] [Price] [Misc] [Etc] Order with columns [OrderID] [ProductName] [Quantity] [Misc] [Etc] ProductName is primary key of Product, of some string type and unique. OrderID is primary key and of some integer type, and ProductName being a foreign key. Say I change the primary key of Product to a new column of integer type ie [ProductID] Would this reduce the database size and optimize lookups joining these two tables (and likewise operations), or are these optimizations performed automatically by (most/general/main) SQL database implementations?

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  • MS SQL Server: how to optimize "like" queries?

    - by duke84
    I have a query that searches for clients using "like" with wildcard. For example: SELECT TOP (10) [t0].[CLIENTNUMBER], [t0].[FIRSTNAME], [t0].[LASTNAME], [t0].[MI], [t0].[MDOCNUMBER] FROM [dbo].[CLIENT] AS [t0] WHERE (LTRIM(RTRIM([t0].[DOCREVNO])) = '0') AND ([t0].[FIRSTNAME] LIKE '%John%') AND ([t0].[LASTNAME] LIKE '%Smith%') AND ([t0].[SSN] LIKE '%123%') AND ([t0].[CLIENTNUMBER] LIKE '%123%') AND ([t0].[MDOCNUMBER] LIKE '%123%') AND ([t0].[CLIENTINDICATOR] = 'ON') It can also use less parameters in "where" clause, for example: SELECT TOP (10) [t0].[CLIENTNUMBER], [t0].[FIRSTNAME], [t0].[LASTNAME], [t0].[MI], [t0].[MDOCNUMBER] FROM [dbo].[CLIENT] AS [t0] WHERE (LTRIM(RTRIM([t0].[DOCREVNO])) = '0') AND ([t0].[FIRSTNAME] LIKE '%John%') AND ([t0].[CLIENTINDICATOR] = 'ON') Can anybody tell what is the best way to optimize performance of such query? Maybe I need to create an index? This table can have up to 1000K records in production.

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  • SQL Server: how to optimize "like" queries?

    - by duke84
    I have a query that searches for clients using "like" with wildcard. For example: SELECT TOP (10) [t0].[CLIENTNUMBER], [t0].[FIRSTNAME], [t0].[LASTNAME], [t0].[MI], [t0].[MDOCNUMBER] FROM [dbo].[CLIENT] AS [t0] WHERE (LTRIM(RTRIM([t0].[DOCREVNO])) = '0') AND ([t0].[FIRSTNAME] LIKE '%John%') AND ([t0].[LASTNAME] LIKE '%Smith%') AND ([t0].[SSN] LIKE '%123%') AND ([t0].[CLIENTNUMBER] LIKE '%123%') AND ([t0].[MDOCNUMBER] LIKE '%123%') AND ([t0].[CLIENTINDICATOR] = 'ON') It can also use less parameters in "where" clause, for example: SELECT TOP (10) [t0].[CLIENTNUMBER], [t0].[FIRSTNAME], [t0].[LASTNAME], [t0].[MI], [t0].[MDOCNUMBER] FROM [dbo].[CLIENT] AS [t0] WHERE (LTRIM(RTRIM([t0].[DOCREVNO])) = '0') AND ([t0].[FIRSTNAME] LIKE '%John%') AND ([t0].[CLIENTINDICATOR] = 'ON') Can anybody tell what is the best way to optimize performance of such query? Maybe I need to create an index? This table can have up to 1000K records in production.

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  • Optimize grep, awk and sed shell stuff

    - by kockiren
    I try to sum the traffic of diffrent ports in the logfiles from "IPCop" so i write and command for my shell, but i think its possible to optimize the command. First a Line from my Logfile: 01/00:03:16 kernel INPUT IN=eth1 OUT= MAC=xxx SRC=xxx DST=xxx LEN=40 TOS=0x00 PREC=0x00 TTL=98 ID=256 PROTO=TCP SPT=47438 DPT=1433 WINDOW=16384 RES=0x00 SYN URGP=0 Now i grep with following Command the sum of all lengths who contains port 1433 grep 1433 log.dat|awk '{for(i=1;i<=10;i++)if($i ~ /LEN/)print $i};'|sed 's/LEN=//g;'|awk '{sum+=$1}END{print sum}' The for loop i need because the LEN-col is not on same position at all time. Any suggestion for optimizing this command? Regards Rene

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  • How to optimize erasing from multimap

    - by Dominating
    I have two multimaps defined so multimap phoneNums; and multimap numPhones; they are some kind of phone registry - phoneNums contains Key name, and second argument phonenumber, numPhones contain Key phonenumber and second is name. I want to optimize erase from both of them when i want to delete string Key form phoneNums, which is also second element in numPhones. When i enter data it is entered in both multimaps so they are actually the same but with swapped first and second when i put it on tests it says that erasing is too slow - N*N and must be only N cin>>stringToErase; phoneNums.erase(stringToErase); multimap<string, string>::iterator it; multimap<string, string>::iterator tmpr; for(it = numPhones.begin(); it != numPhones.end();it++) { if(it->second == tringToErase) { tmpr = it; numPhones.erase(it,tmpr); } }

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  • Optimize conditional operators branching in C#

    - by abatishchev
    Hello. I have next code: return this.AllowChooseAny.Value ? radioSpecific.Checked ? UserManager.CurrentUser.IsClient ? txtSubject.Text : subjectDropDownList.SelectedItem.Text : String.Empty : UserManager.CurrentUser.IsClient ? txtSubject.Text : subjectDropDownList.SelectedItem.Text; or in less complex form: return any ? specified ? isClient ? textbox : dropdown : empty : isClient ? textbox : dropdown; or in schematic form: | any / \ specified isClient / \ / \ isClient empty textbox dropdown / \ textbox dropdown Evidently I have a duplicated block on two different levels. Is it possible to optimize this code to probably split them to one? Or something like that..

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  • How to optimize this Linq query

    - by Luke101
    I am trying to optimize this query. It is not slow for now but I am expecting a spike to hit this query in the near future. Is there anything else i can do to make this query faster? var posts = from p in context.post where p.post_isdeleted == false && p.post_parentid == null select new { p.post_date, p.post_id, p.post_titleslug, p.post_title, p.post_descriptionrender, p.userinfo.user_username, p.userinfo.user_userid, p.userinfo.user_GravatarHash, p.userinfo.user_points, p.category.catid, p.category.name, p.post_answercount, p.post_hasbestanswer, p.post_hits, p.post_isanonymous, p.post_votecount, FavoriteCount = context.favorites.Where(x => x.post.post_id == p.post_id).Count(), tags = from tg in context.posttag where tg.posttag_postid == p.post_id select new { tg.tag.tag_id, tg.tag.tag_title } };

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  • How to optimize an database suggestion engine

    - by Dimitar Vouldjeff
    Hi, I`m making an online engine for item-to-item recommending movies. I have made some researches and I think that the best way to implement that is using pearson correlation and make a table with item1, item2 and correlation fields, but the problem is that after each rate of item I have to regenerate the correlation for in the worst case N records (where N is the number of items). Another think that I read is the following article, but I haven`t thought a way to implement it. So what is your suggestion to optimize this process? Or any other suggestions? Thanks.

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  • How to optimize an SQL query with many thousands of WHERE clauses

    - by bugaboo
    I have a series of queries against a very mega large database, and I have hundreds-of-thousands of ORs in WHERE clauses. What is the best and easiest way to optimize such SQL queries? I found some articles about creating temporary tables and using joins, but I am unsure. I'm new to serious SQL, and have been cutting and pasting results from one into the next. SELECT doc_id, language, author, title FROM doc_text WHERE language='fr' OR language='es' SELECT doc_id, ref_id FROM doc_ref WHERE doc_id=1234567 OR doc_id=1234570 OR doc_id=1234572 OR doc_id=1234596 OR OR OR ... SELECT ref_id, location_id FROM ref_master WHERE ref_id=098765 OR ref_id=987654 OR ref_id=876543 OR OR OR ... SELECT location_id, location_display_name FROM location SELECT doc_id, index_code, FROM doc_index WHERE doc_id=1234567 OR doc_id=1234570 OR doc_id=1234572 OR doc_id=1234596 OR OR OR x100,000 These unoptimized query can take over 24 hours each. Cheers.

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  • Optimize Binary Search Algorithm

    - by Ganesh M
    In a binary search, we have two comparisons one for greater than and other for less than, otherwise its the mid value. How would you optimize so that we need to check only once? bool binSearch(int array[], int key, int left, int right) { mid = left + (right-left)/2; if (key < array[mid]) return binSearch(array, key, left, mid-1); else if (key > array[mid]) return binSearch(array, key, mid+1, right); else if (key == array[mid]) return TRUE; // Found return FALSE; // Not Found }

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  • Rewriting .each() loop as for loop to optimize, how to replicate $(this).attr()

    - by John B
    I running into some performance issues with a jquery script i wrote when running in ie so I'm going through it trying to optimize any way possible. Apparently using for loops is way faster than using the jQuery .each method. This has led me to a question regarding the equivalent of $(this) inside a for loop. I'm simplifying what I'm doing in my loop down to just using an attr() function as it gets across my main underlying question. Im doing this with each(simplified) var existing = $('#existing'); existing.each(function(){ console.log($(this).attr('id')); }); And I've tried rewriting it as a for loop as such: var existing = $('#existing'); for(var i = 0;i < existing.length;i++) { console.log(existing[i].attr('id')); } Its throwing an error saying: Uncaught TypeError: Object #<HTMLDivElement> has no method 'attr' Thanks.

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  • How to optimize indexing of large number of DB records using Zend_Lucene and Zend_Paginator

    - by jdichev
    So I have this cron script that is deployed and ran using Cron on a host and indexes all the records in a database table - the index is later used both for the front end of the site and the backed operations as well. After the operation, the index is about 3-4 MB. The problem is it takes a lot of resources (CPU: 30+ and a good chunk of memory) and slows the machine down. My question is about how to optimize the operation described below: First there is a select query built using the Zend Framework API, this query is then passed to a Paginator factory that returns a paginator which I am using to balance the current number of items being indexed and not iterate over too much items. The script is iterating over the current items in the paginator object using a foreach loop until reaching the end and then it starts from the beginning after getting items for the next page. I am suspecting this overhead is caused by the Zend_Lucene but no idea how this could be improved.

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  • How to optimize this script

    - by marks34
    I have written the following script. It opens a file, reads each line from it splitting by new line character and deleting first character in line. If line exists it's being added to array. Next each element of array is splitted by whitespace, sorted alphabetically and joined again. Every line is printed because script is fired from console and writes everything to file using standard output. I'd like to optimize this code to be more pythonic. Any ideas ? import sys def main(): filename = sys.argv[1] file = open(filename) arr = [] for line in file: line = line[1:].replace("\n", "") if line: arr.append(line) for line in arr: lines = line.split(" ") lines.sort(key=str.lower) line = ''.join(lines) print line if __name__ == '__main__': main()

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  • How can I optimize this code?

    - by loop0
    Hi, I'm developing a logger daemon to squid to grab the logs on a mongodb database. But I'm experiencing too much cpu utilization. How can I optimize this code? from sys import stdin from pymongo import Connection connection = Connection() db = connection.squid logs = db.logs buffer = [] a = 'timestamp' b = 'resp_time' c = 'src_ip' d = 'cache_status' e = 'reply_size' f = 'req_method' g = 'req_url' h = 'username' i = 'dst_ip' j = 'mime_type' L = 'L' while True: l = stdin.readline() if l[0] == L: l = l[1:].split() buffer.append({ a: float(l[0]), b: int(l[1]), c: l[2], d: l[3], e: int(l[4]), f: l[5], g: l[6], h: l[7], i: l[8], j: l[9] } ) if len(buffer) == 1000: logs.insert(buffer) buffer = [] if not l: break connection.disconnect()

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  • SQL: Optimize insensive SELECTs on DateTime fields

    - by Fedyashev Nikita
    I have an application for scheduling certain events. And all these events must be reviewed after each scheduled time. So basically we have 3 tables: items(id, name) scheduled_items(id, item_id, execute_at - datetime) - item_id column has an index option. reviewed_items(id, item_id, created_at - datetime) - item_id column has an index option. So core function of the application is "give me any items(which are not yet reviewed) for the actual moment". How can I optimize this solution for speed(because it is very core business feature and not micro optimization)? I suppose that adding index to the datetime fields doesn't make any sense because the cardinality or uniqueness on that fields are very high and index won't give any(?) speed-up. Is it correct? What would you recommend? Should I try no-SQL? -- mysql -V 5.075 I use caching where it makes sence.

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  • MySQL is killing the server IO.

    - by OneOfOne
    I manage a fairly large/busy vBulletin forums (~2-3k requests per second, running on gigenet cloud), the database is ~ 10 GB (~9 milion posts, ~60 queries per second), lately MySQL have been grinding the disk like there's no tomorrow according to iotop and slowing the site. The last idea I can think of is using replication, but I'm not sure how much that would help and worried about database sync. I'm out of ideas, any tips on how to improve the situation would be highly appreciated. Specs : Debian Lenny 64bit ~12Ghz (6 cores) CPU, 7520gb RAM, 160gb disk. Kernel : 2.6.32-4-amd64 mysqld Ver 5.1.54-0.dotdeb.0 for debian-linux-gnu on x86_64 ((Debian)) Other software: vBulletin 3.8.4 memcached 1.2.2 PHP 5.3.5-0.dotdeb.0 (fpm-fcgi) (built: Jan 7 2011 00:07:27) lighttpd/1.4.28 (ssl) - a light and fast webserver PHP and vBulletin are configured to use memcached. MySQL Settings : [mysqld] key_buffer = 128M max_allowed_packet = 16M thread_cache_size = 8 myisam-recover = BACKUP max_connections = 1024 query_cache_limit = 2M query_cache_size = 128M expire_logs_days = 10 max_binlog_size = 100M key_buffer_size = 128M join_buffer_size = 8M tmp_table_size = 16M max_heap_table_size = 16M table_cache = 96

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  • MySQL is killing the server IO.

    - by OneOfOne
    I manage a fairly large/busy vBulletin forums (running on gigenet cloud), the database is ~ 10 GB (~9 milion posts, ~60 queries per second), lately MySQL have been grinding the disk like there's no tomorrow according to iotop and slowing the site. The last idea I can think of is using replication, but I'm not sure how much that would help and worried about database sync. I'm out of ideas, any tips on how to improve the situation would be highly appreciated. Specs : Debian Lenny 64bit ~12Ghz (6x2GHz) CPU, 7520gb RAM, 160gb disk. Kernel : 2.6.32-4-amd64 mysqld Ver 5.1.54-0.dotdeb.0 for debian-linux-gnu on x86_64 ((Debian)) Other software: vBulletin 3.8.4 memcached 1.2.2 PHP 5.3.5-0.dotdeb.0 (fpm-fcgi) (built: Jan 7 2011 00:07:27) lighttpd/1.4.28 (ssl) - a light and fast webserver PHP and vBulletin are configured to use memcached. MySQL Settings : [mysqld] key_buffer = 128M max_allowed_packet = 16M thread_cache_size = 8 myisam-recover = BACKUP max_connections = 1024 query_cache_limit = 2M query_cache_size = 128M expire_logs_days = 10 max_binlog_size = 100M key_buffer_size = 128M join_buffer_size = 8M tmp_table_size = 16M max_heap_table_size = 16M table_cache = 96 Other : From the cloud's IO chart, we're averaging 100mb/s read. > vmstat procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu---- r b swpd free buff cache si so bi bo in cs us sy id wa 9 0 73140 36336 8968 1859160 0 0 42 15 3 2 6 1 89 5 > /etc/init.d/mysql status Threads: 49 Questions: 252139 Slow queries: 164 Opens: 53573 Flush tables: 1 Open tables: 337 Queries per second avg: 61.302. moved from superuser

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  • MySQL is killing the server IO.

    - by OneOfOne
    I manage a fairly large/busy vBulletin forums (running on gigenet cloud), the database is ~ 10 GB (~9 milion posts, ~60 queries per second), lately MySQL have been grinding the disk like there's no tomorrow according to iotop and slowing the site. The last idea I can think of is using replication, but I'm not sure how much that would help and worried about database sync. I'm out of ideas, any tips on how to improve the situation would be highly appreciated. Specs : Debian Lenny 64bit ~12Ghz (6 cores) CPU, 7520gb RAM, 160gb disk. Kernel : 2.6.32-4-amd64 mysqld Ver 5.1.54-0.dotdeb.0 for debian-linux-gnu on x86_64 ((Debian)) Other software: vBulletin 3.8.4 memcached 1.2.2 PHP 5.3.5-0.dotdeb.0 (fpm-fcgi) (built: Jan 7 2011 00:07:27) lighttpd/1.4.28 (ssl) - a light and fast webserver PHP and vBulletin are configured to use memcached. MySQL Settings : [mysqld] key_buffer = 128M max_allowed_packet = 16M thread_cache_size = 8 myisam-recover = BACKUP max_connections = 1024 query_cache_limit = 2M query_cache_size = 128M expire_logs_days = 10 max_binlog_size = 100M key_buffer_size = 128M join_buffer_size = 8M tmp_table_size = 16M max_heap_table_size = 16M table_cache = 96 Other : > vmstat procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu---- r b swpd free buff cache si so bi bo in cs us sy id wa 9 0 73140 36336 8968 1859160 0 0 42 15 3 2 6 1 89 5 > /etc/init.d/mysql status Threads: 49 Questions: 252139 Slow queries: 164 Opens: 53573 Flush tables: 1 Open tables: 337 Queries per second avg: 61.302. Edit Additional info.

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  • Code Trivia: optimize the code for multiple nested loops

    - by CodeToGlory
    I came across this code today and wondering what are some of the ways we can optimize it. Obviously the model is hard to change as it is legacy, but interested in getting opinions. Changed some names around and blurred out some core logic to protect. private static Payment FindPayment(Order order, Customer customer, int paymentId) { Payment payment = Order.Payments.FindById(paymentId); if (payment != null) { if (payment.RefundPayment == null) { return payment; } if (String.Compare(payment.RefundPayment, "refund", true) != 0 ) { return payment; } } Payment finalPayment = null; foreach (Payment testpayment in Order.payments) { if (testPayment.Customer.Name != customer.Name){continue;} if (testPayment.Cancelled) { continue; } if (testPayment.RefundPayment != null) { if (String.Compare(testPayment.RefundPayment, "refund", true) == 0 ) { continue; } } if (finalPayment == null) { finalPayment = testPayment; } else { if (testPayment.Value > finalPayment.Value) { finalPayment = testPayment; } } } if (finalPayment == null) { return payment; } return finalPayment; } Making this a wiki so code enthusiasts can answer without worrying about points.

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  • How to optimize this algorithm?

    - by Bakhtiyor
    I have two sets of arrays like this for example. $Arr1['uid'][]='user 1'; $Arr1['weight'][]=1; $Arr1['uid'][]='user 2'; $Arr1['weight'][]=10; $Arr1['uid'][]='user 3'; $Arr1['weight'][]=5; $Arr2['uid'][]='user 1'; $Arr2['weight'][]=3; $Arr2['uid'][]='user 4'; $Arr2['weight'][]=20; $Arr2['uid'][]='user 5'; $Arr2['weight'][]=15; $Arr2['uid'][]='user 2'; $Arr2['weight'][]=2; The size of two arrays could be different of course. $Arr1 has coefficient of 0.7 and $Arr2 has coefficient of 0.3. I need to calculate following formula $result=$Arr1['weight'][$index]*$Arr1Coeff+$Arr2['weight'][$index]*$Arr2Coeff; where $Arr1['uid']=$Arr2['uid']. So when $Arr1['uid'] doesn't exists in $Arr2 then we need to omit $Arr2 and vice versa. And, here is an algorithm I am using now. foreach($Arr1['uid'] as $index=>$arr1_uid){ $pos=array_search($arr1_uid, $Arr2['uid']); if ($pos===false){ $result=$Arr1['weight'][$index]*$Arr1Coeff; echo "<br>$arr1_uid has not found and RES=".$result; }else{ $result=$Arr1['weight'][$index]*$Arr1Coeff+$Arr2['weight'][$pos]*$Arr2Coeff; echo "<br>$arr1_uid has found on $pos and RES=".$result; } } foreach($Arr2['uid'] as $index=>$arr2_uid){ if (!in_array($arr2_uid, $Arr1['uid'])){ $result=$Arr2['weight'][$index]*$Arr2Coeff; echo "<br>$arr2_uid has not found and RES=".$result; }else{ echo "<br>$arr2_uid has found somewhere"; } } The question is how can I optimize this algorithm? Can you offer other better solution for this problem? Thank you.

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