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  • Does the <script> tag position in HTML affects performance of the webpage?

    - by Rahul Joshi
    If the script tag is above or below the body in a HTML page, does it matter for the performance of a website? And what if used in between like this: <body> ..blah..blah.. <script language="JavaScript" src="JS_File_100_KiloBytes"> function f1() { .. some logic reqd. for manipulating contents in a webpage } </script> ... some text here too ... </body> Or is this better?: <script language="JavaScript" src="JS_File_100_KiloBytes"> function f1() { .. some logic reqd. for manipulating contents in a webpage } </script> <body> ..blah..blah.. ..call above functions on some events like onclick,onfocus,etc.. </body> Or this one?: <body> ..blah..blah.. ..call above functions on some events like onclick,onfocus,etc.. <script language="JavaScript" src="JS_File_100_KiloBytes"> function f1() { .. some logic reqd. for manipulating contents in a webpage } </script> </body> Need not tell everything is again in the <html> tag!! How does it affect performance of webpage while loading? Does it really? Which one is the best, either out of these 3 or some other which you know? And one more thing, I googled a bit on this, from which I went here: Best Practices for Speeding Up Your Web Site and it suggests put scripts at the bottom, but traditionally many people put it in <head> tag which is above the <body> tag. I know it's NOT a rule but many prefer it that way. If you don't believe it, just view source of this page! And tell me what's the better style for best performance.

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  • Oracle Sql Query taking a day long to return results using dblink

    - by Suresh S
    Guys i have the following oracle sql query that gives me the monthwise report between the dates. Basically for nov month i want sum of values between the dates 01nov to 30 nov. The table tha is being queried is residing in another database and accesssed using dblink. The DT columns is of NUMBER type (for ex 20101201) .The execution of the query is taking a day long and not completed. kindly suggest me , if their is any optimisation that can be suggested to my DBA on the dblink, or any tuning that can be done on the query , or rewriting the same. SELECT /*+ PARALLEL (A 8) */ TO_CHAR(TRUNC(TRUNC(SYSDATE,'MM')- 1,'MM'),'MONYYYY') "MONTH", TYPE AS "TYPE", COLUMN, COUNT (DISTINCT A) AS "A_COUNT", COUNT (COLUMN) AS NO_OF_COLS, SUM (DURATION) AS "SUM_DURATION", SUM (COST) AS "COST" FROM **A@LN_PROD A** WHERE DT >=TO_NUMBER(TO_CHAR(TRUNC(TRUNC(SYSDATE,'MM')-1,'MM'),'YYYYMMDD')) AND DT < TO_NUMBER(TO_CHAR(TRUNC(TRUNC(SYSDATE,'MM'),'MM'),'YYYYMMDD')) GROUP BY TYPE, COLUMN

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  • Is SQL DATEDIFF(year, ..., ...) an Expensive Computation?

    - by rlb.usa
    I'm trying to optimize up some horrendously complicated SQL queries because it takes too long to finish. In my queries, I have dynamically created SQL statements with lots of the same functions, so I created a temporary table where each function is only called once instead of many, many times - this cut my execution time by 3/4. So my question is, can I expect to see much of a difference if say, 1,000 datediff computations are narrowed to 100?

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  • Javascriptlibrary more efficient than Rickshaw for realtime visualizations

    - by dan kutz
    I want to visualize data as time-series graphs on mobile devices(tablets) and therefore stumbled upon rickshaw, which is based on D3. First I must say I was a little bit confused when I realized that realtime in web design is defined totally different to realtime in engineering which has fixed(and often very short) timeframes. Anyway my aim is to visualize the data as fast as possible, and on older tablets visualization with rickshaw is quite slow. Can anybody recommend another library, which may be more efficient in rendering? Or is there no way out and I have to go native? regards Dan.

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  • Data Access from single table in sql server 2005 is too slow

    - by Muhammad Kashif Nadeem
    Following is the script of table. Accessing data from this table is too slow. SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO CREATE TABLE [dbo].[Emails]( [id] [int] IDENTITY(1,1) NOT NULL, [datecreated] [datetime] NULL CONSTRAINT [DF_Emails_datecreated] DEFAULT (getdate()), [UID] [nvarchar](250) COLLATE Latin1_General_CI_AS NULL, [From] [nvarchar](100) COLLATE Latin1_General_CI_AS NULL, [To] [nvarchar](100) COLLATE Latin1_General_CI_AS NULL, [Subject] [nvarchar](max) COLLATE Latin1_General_CI_AS NULL, [Body] [nvarchar](max) COLLATE Latin1_General_CI_AS NULL, [HTML] [nvarchar](max) COLLATE Latin1_General_CI_AS NULL, [AttachmentCount] [int] NULL, [Dated] [datetime] NULL ) ON [PRIMARY] Following query takes 50 seconds to fetch data. select id, datecreated, UID, [From], [To], Subject, AttachmentCount, Dated from emails If I include Body and Html in select then time is event worse. indexes are on: id unique clustered From Non unique non clustered To Non unique non clustered Tabls has currently 180000+ records. There might be 100,000 records each month so this will become more slow as time will pass. Does splitting data into two table will solve the problem? What other indexes should be there?

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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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  • What does ER_WARN_FIELD_RESOLVED mean?

    - by VolkerK
    When SHOW WARNINGS after a EXPLAIN EXTENDED shows a Note 1276 Field or reference 'test.foo.bar' of SELECT #2 was resolved in SELECT #1 what exactly does that mean and what impact does it have? In my case it prevents mysql from using what seems to be a perfectly good index. But it's not about fixing that specific query (as it is an irrelevant test). I found http://dev.mysql.com/doc/refman/5.0/en/error-messages-server.html butError: 1276 SQLSTATE: HY000 (ER_WARN_FIELD_RESOLVED) Message: Field or reference '%s%s%s%s%s' of SELECT #%d was resolved in SELECT #%d isn't much of an explaination.

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  • MySQL subqueries

    - by swamprunner7
    Can we do this query without subqueries? SELECT login, post_n, (SELECT SUM(vote) FROM votes WHERE votes.post_n=posts.post_n)AS votes, (SELECT COUNT(comments.post_n) FROM comments WHERE comments.post_n=posts.post_n)AS comments_count FROM users, posts WHERE posts.id=users.id AND (visibility=2 OR visibility=3) ORDER BY date DESC LIMIT 0, 15 tables: Users: id, login Posts: post_n, id, visibility Votes: post_n, vote id — it`s user id, Users the main table.

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  • most efficient method of turning multiple 1D arrays into columns of a 2D array

    - by Ty W
    As I was writing a for loop earlier today, I thought that there must be a neater way of doing this... so I figured I'd ask. I looked briefly for a duplicate question but didn't see anything obvious. The Problem: Given N arrays of length M, turn them into a M-row by N-column 2D array Example: $id = [1,5,2,8,6] $name = [a,b,c,d,e] $result = [[1,a], [5,b], [2,c], [8,d], [6,e]] My Solution: Pretty straight forward and probably not optimal, but it does work: <?php // $row is returned from a DB query // $row['<var>'] is a comma separated string of values $categories = array(); $ids = explode(",", $row['ids']); $names = explode(",", $row['names']); $titles = explode(",", $row['titles']); for($i = 0; $i < count($ids); $i++) { $categories[] = array("id" => $ids[$i], "name" => $names[$i], "title" => $titles[$i]); } ?> note: I didn't put the name = value bit in the spec, but it'd be awesome if there was some way to keep that as well.

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  • "Anagram solver" based on statistics rather than a dictionary/table?

    - by James M.
    My problem is conceptually similar to solving anagrams, except I can't just use a dictionary lookup. I am trying to find plausible words rather than real words. I have created an N-gram model (for now, N=2) based on the letters in a bunch of text. Now, given a random sequence of letters, I would like to permute them into the most likely sequence according to the transition probabilities. I thought I would need the Viterbi algorithm when I started this, but as I look deeper, the Viterbi algorithm optimizes a sequence of hidden random variables based on the observed output. I am trying to optimize the output sequence. Is there a well-known algorithm for this that I can read about? Or am I on the right track with Viterbi and I'm just not seeing how to apply it?

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  • Unicorn: Which number of worker processes to use?

    - by blackbird07
    I am running a Ruby on Rails app on a virtual Linux server that is capped at 1GB RAM. Currently, I am constantly hitting the limit and would like to optimize memory utilization. One option I am looking at is reducing the number of unicorn workers. So what is the best way to determine the number of unicorn workers to use? The current setting is 10 workers, but the maximum number of requests per second I have seen on Google Analytics Real-Time is 3 (only scored once at a peak time; in 99% of the time not going above 1 request per second). So is it a save assumption that I can - for now - go with 4 workers, leaving room for unexpected amounts of requests? What are the metrics I should have a look at for determining the number of workers and what are the tools I can use for that on my Ubuntu machine?

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  • Long-running Database Query

    - by JamesMLV
    I have a long-running SQL Server 2005 query that I have been hoping to optimize. When I look at the actual execution plan, it says a Clustered Index Seek has 66% of the cost. Execuation Plan Snippit: <RelOp AvgRowSize="31" EstimateCPU="0.0113754" EstimateIO="0.0609028" EstimateRebinds="0" EstimateRewinds="0" EstimateRows="10198.5" LogicalOp="Clustered Index Seek" NodeId="16" Parallel="false" PhysicalOp="Clustered Index Seek" EstimatedTotalSubtreeCost="0.0722782"> <OutputList> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="quoteDate" /> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="price" /> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </OutputList> <RunTimeInformation> <RunTimeCountersPerThread Thread="0" ActualRows="1067" ActualEndOfScans="1" ActualExecutions="1" /> </RunTimeInformation> <IndexScan Ordered="true" ScanDirection="FORWARD" ForcedIndex="false" NoExpandHint="false"> <DefinedValues> <DefinedValue> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="quoteDate" /> </DefinedValue> <DefinedValue> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="price" /> </DefinedValue> <DefinedValue> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </DefinedValue> </DefinedValues> <Object Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Index="[_dta_index_Indices_14_320720195__K5_K2_K1_3]" Alias="[I]" /> <SeekPredicates> <SeekPredicate> <Prefix ScanType="EQ"> <RangeColumns> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="HedgeProduct" ComputedColumn="true" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="(1)"> <Const ConstValue="(1)" /> </ScalarOperator> </RangeExpressions> </Prefix> <StartRange ScanType="GE"> <RangeColumns> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="[@StartMonth]"> <Identifier> <ColumnReference Column="@StartMonth" /> </Identifier> </ScalarOperator> </RangeExpressions> </StartRange> <EndRange ScanType="LE"> <RangeColumns> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="[@EndMonth]"> <Identifier> <ColumnReference Column="@EndMonth" /> </Identifier> </ScalarOperator> </RangeExpressions> </EndRange> </SeekPredicate> </SeekPredicates> </IndexScan> </RelOp> From this, does anyone see an obvious problem that would be causing this to take so long? Here is the query: (SELECT quotedate, tenure, price, ActualVolume, HedgePortfolioValue, Price AS UnhedgedPrice, ((ActualVolume*Price - HedgePortfolioValue)/ActualVolume) AS HedgedPrice FROM ( SELECT [quoteDate] ,[price] , tenure ,isnull(wf_1.[Risks].[HedgePortValueAsOfDate2](1,tenureMonth,quotedate,price),0) as HedgePortfolioValue ,[TotalOperatingGasVolume] as ActualVolume FROM [wf_1].[dbo].[Indices] I inner join ( SELECT DISTINCT tenureMonth FROM [wf_1].[Risks].[KnowRiskTrades] WHERE HedgeProduct = 1 AND portfolio <> 'Natural Gas Hedge Transactions' ) B ON I.tenure=B.tenureMonth inner join ( SELECT [Month],[TotalOperatingGasVolume] FROM [wf_1].[Risks].[ActualGasVolumes] ) C ON C.[Month]=B.tenureMonth WHERE HedgeProduct = 1 AND quoteDate>=dateadd(day, -3*365, tenureMonth) AND quoteDate<=dateadd(day,-3,tenureMonth) )A )

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  • When compiling programs to run inside a VM, what should march and mtune be set to?

    - by Russ
    With VMs being slave to whatever the host machine is providing, what compiler flags should be provided to gcc? I would normally think that -march=native would be what you would use when compiling for a dedicated box, but the fine detail that -march=native is going to as indicated in this article makes me extremely wary of using it. So... what to set -march and -mtune to inside a VM? For a specific example... My specific case right now is compiling python (and more) in a linux guest inside a KVM-based "cloud" host that I have no real control over the host hardware (aside from 'simple' stuff like CPU GHz m CPU count, and available RAM). Currently, cpuinfo tells me I've got an "AMD Opteron(tm) Processor 6176" but I honestly don't know (yet) if that is reliable and whether the guest can get moved around to different architectures on me to meet the host's infrastructure shuffling needs (sounds hairy/unlikely). All I can really guarantee is my OS, which is a 64-bit linux kernel where uname -m yields x86_64.

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  • Mysql - help me optimize this query (improved question)

    - by sandeepan-nath
    About the system: - There are tutors who create classes and packs - 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 the concerned query SELECT SUM(DISTINCT( t.tag LIKE "%Dictatorship%" )) AS key_1_total_matches, SUM(DISTINCT( t.tag LIKE "%democracy%" )) AS key_2_total_matches, 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_od 0 ) 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 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 The problem The results returned by the above query are correct (AND logic working as per expectation), but the time taken by the query rises alarmingly for heavier data and for the current data I have it 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. The tag field of tags table is indexed. Is there something faulty with the query? What can be the reason behind 20+ seconds of execution time? 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 explain query output:- Please see this screenshot - http://www.test.examvillage.com/Explain_query.jpg

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  • Does the order of columns in a query matter?

    - by James Simpson
    When selecting columns from a MySQL table, is performance affected by the order that you select the columns as compared to their order in the table (not considering indexes that may cover the columns)? For example, you have a table with rows uid, name, bday, and you have the following query. SELECT uid, name, bday FROM table Does MySQL see the following query any differently and thus cause any sort of performance hit? SELECT uid, bday, name FROM table

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  • Hierarchical Hibernate, how many queries are executed?

    - by ghost1
    So I've been dealing with a home brew DB framework that has some seriously flaws, the justification for use being that not using an ORM will save on the number of queries executed. If I'm selecting all possibile records from the top level of a joinable object hierarchy, how many separate calls to the DB will be made when using an ORM (such as Hibernate)? I feel like calling bullshit on this, as joinable entities should be brought down in one query , right? Am I missing something here? note: lazy initialization doesn't matter in this scenario as all records will be used.

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  • Optimizing an embedded SELECT query in mySQL

    - by Crazy Serb
    Ok, here's a query that I am running right now on a table that has 45,000 records and is 65MB in size... and is just about to get bigger and bigger (so I gotta think of the future performance as well here): SELECT count(payment_id) as signup_count, sum(amount) as signup_amount FROM payments p WHERE tm_completed BETWEEN '2009-05-01' AND '2009-05-30' AND completed > 0 AND tm_completed IS NOT NULL AND member_id NOT IN (SELECT p2.member_id FROM payments p2 WHERE p2.completed=1 AND p2.tm_completed < '2009-05-01' AND p2.tm_completed IS NOT NULL GROUP BY p2.member_id) And as you might or might not imagine - it chokes the mysql server to a standstill... What it does is - it simply pulls the number of new users who signed up, have at least one "completed" payment, tm_completed is not empty (as it is only populated for completed payments), and (the embedded Select) that member has never had a "completed" payment before - meaning he's a new member (just because the system does rebills and whatnot, and this is the only way to sort of differentiate between an existing member who just got rebilled and a new member who got billed for the first time). Now, is there any possible way to optimize this query to use less resources or something, and to stop taking my mysql resources down on their knees...? Am I missing any info to clarify this any further? Let me know... EDIT: Here are the indexes already on that table: PRIMARY PRIMARY 46757 payment_id member_id INDEX 23378 member_id payer_id INDEX 11689 payer_id coupon_id INDEX 1 coupon_id tm_added INDEX 46757 tm_added, product_id tm_completed INDEX 46757 tm_completed, product_id

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  • How to store static content across branches in a single location in version control

    - by Shravan
    [Just a random thought] I have a pdf doc that is downloaded when the user clicks on 'help' on my website. Now, this is a pretty huge document and is saved in version control (SVN) and is thus copied for all branches that exist in SVN. This is static content and something that developers are not working on, and does not change often. Is there a more efficient way to store it (that would not hamper local deployments) that would make SVN checkouts and updates relatively faster. I know the benefit we get is not huge, this is something that came to my head none the less.

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  • Nginx , Apache , Mysql , Memcache with server 4G ram. How optimize to enoigh of memory?

    - by TomSawyer
    i have 1 dedicated server with Nginx proxy for Apache. Memcache, mysql, 4G Ram. These day, my visitor on my site wasn't increased, but my server get overload always in some specified time. (9AM - 15PM) Ram in use is increased second by second to full. that's moment, my server will get overload. i have to kill all apache , mysql service and reboot it to get free memory. and it'll full again. that's the terrible circle. here is my ram in use at the moment 160(nginx) 220(apache) 512(memcache) 924(mysql) here's process number 4(nginx) 14(apache) 5(memcache) 20(mysql) and here's my my.cnf config. someone can help me to optimize it? [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql skip-locking skip-networking skip-name-resolve # enable log-slow-queries log-slow-queries = /var/log/mysql-slow-queries.log long_query_time=3 max_connections=200 wait_timeout=64 connect_timeout = 10 interactive_timeout = 25 thread_stack = 512K max_allowed_packet=16M table_cache=1500 read_buffer_size=4M join_buffer_size=4M sort_buffer_size=4M read_rnd_buffer_size = 4M max_heap_table_size=256M tmp_table_size=256M thread_cache=256 query_cache_type=1 query_cache_limit=4M query_cache_size=16M thread_concurrency=8 myisam_sort_buffer_size=128M # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqldump] quick max_allowed_packet=16M [mysql] no-auto-rehash [isamchk] key_buffer=256M sort_buffer=256M read_buffer=64M write_buffer=64M [myisamchk] key_buffer=256M sort_buffer=256M read_buffer=64M write_buffer=64M [mysqlhotcopy] interactive-timeout [mysql.server] user=mysql basedir=/var/lib [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid

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  • Why is doing a top(1) on an indexed column in SQL Server slow?

    - by reinier
    I'm puzzled by the following. I have a DB with around 10 million rows, and (among other indices) on 1 column (campaignid_int) is an index. Now I have 700k rows where the campaignid is indeed 3835 For all these rows, the connectionid is the same. I just want to find out this connectionid. use messaging_db; SELECT TOP (1) connectionid FROM outgoing_messages WITH (NOLOCK) WHERE (campaignid_int = 3835) Now this query takes approx 30 seconds to perform! I (with my small db knowledge) would expect that it would take any of the rows, and return me that connectionid If I test this same query for a campaign which only has 1 entry, it goes really fast. So the index works. How would I tackle this and why does this not work? edit: estimated execution plan: select (0%) - top (0%) - clustered index scan (100%)

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  • In PHP is faster to get a value from an if statement or from an array?

    - by Vittorio Vittori
    Maybe this is a stupid question but what is faster? <?php function getCss1 ($id = 0) { if ($id == 1) { return 'red'; } else if ($id == 2) { return 'yellow'; } else if ($id == 3) { return 'green'; } else if ($id == 4) { return 'blue'; } else if ($id == 5) { return 'orange'; } else { return 'grey'; } } function getCss2 ($id = 0) { $css[] = 'grey'; $css[] = 'red'; $css[] = 'yellow'; $css[] = 'green'; $css[] = 'blue'; $css[] = 'orange'; return $css[$id]; } echo getCss1(3); echo getCss2(3); ?> I suspect is faster the if statement but I prefere to ask!

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  • MySQL won't use index for query?

    - by Jack Sleight
    I have this table: CREATE TABLE `point` ( `id` INT(11) NOT NULL AUTO_INCREMENT, `siteid` INT(11) NOT NULL, `lft` INT(11) DEFAULT NULL, `rgt` INT(11) DEFAULT NULL, `level` SMALLINT(6) DEFAULT NULL, PRIMARY KEY (`id`), KEY `point_siteid_site_id` (`siteid`), CONSTRAINT `point_siteid_site_id` FOREIGN KEY (`siteid`) REFERENCES `site` (`id`) ON DELETE CASCADE ) ENGINE=INNODB AUTO_INCREMENT=35 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci And this query: SELECT * FROM `point` WHERE siteid = 1; Which results in this EXPLAIN information: +----+-------------+-------+------+----------------------+------+---------+------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+------+----------------------+------+---------+------+------+-------------+ | 1 | SIMPLE | point | ALL | point_siteid_site_id | NULL | NULL | NULL | 6 | Using where | +----+-------------+-------+------+----------------------+------+---------+------+------+-------------+ Question is, why isn't the query using the point_siteid_site_id index?

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  • Script Speed vs Memory Usage

    - by Doug Neiner
    I am working on an image generation script in PHP and have gotten it working two ways. One way is slow but uses a limited amount of memory, the second is much faster, but uses 6x the memory . There is no leakage in either script (as far as I can tell). In a limited benchmark, here is how they performed: -------------------------------------------- METHOD | TOTAL TIME | PEAK MEMORY | IMAGES -------------------------------------------- One | 65.626 | 540,036 | 200 Two | 20.207 | 3,269,600 | 200 -------------------------------------------- And here is the average of the previous numbers (if you don't want to do your own math): -------------------------------------------- METHOD | TOTAL TIME | PEAK MEMORY | IMAGES -------------------------------------------- One | 0.328 | 540,036 | 1 Two | 0.101 | 3,269,600 | 1 -------------------------------------------- Which method should I use and why? I anticipate this being used by a high volume of users, with each user making 10-20 requests to this script during a normal visit. I am leaning toward the faster method because though it uses more memory, it is for a 1/3 of the time and would reduce the number of concurrent requests.

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