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  • Which field is explain telling me to index?

    - by shady
    I don't understand what this explain statement is saying. Which field needs an index?. The first line to me is confusing because ref is null. Here's the query I'm using: SELECT pp.property_id AS 'good_prop_id', pr.site_number AS 'pr.site_number', CONCAT(pr.site_street_name, ' ', pr.site_street_type) AS 'pr.partial_addr', pr.county FROM realval_newdb.preforeclosures AS pr INNER JOIN realval_newdb.properties_preforeclosures AS pp USE INDEX (mee_id) ON (pr.mee_id = pp.mee_id) INNER JOIN listings_copy AS lc ON (pr.site_number = lc.site_number) AND (lc.site_street_name = CONCAT(pr.site_street_name, ' ', pr.site_street_type)) WHERE lc.site_county = pr.county LIMIT 1; Can anyone help me optimize this query?

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  • Database indexes - what should they be

    - by WebweaverD
    Most of my database tables have a clear unique index through which lookups are done 90% of the time but I am a bit unsure on this one - I have a table which keeps track of user rating totals for items in my database, I now want to add another table, to track individual ratings with an ip address column to make sure no one can rate something twice. Since I can see this becoming a big, high use table it is important to optimize it correctly. (MYSQL table) This table will have the following fields: rating_id(always - unique), item_id (always - not unique), user_id (optional - not unique), ip_address (always - not unique), rating_value(always - not unique), has_review(bool) Now I envisions 90% the queries going something like this: When a user rates something - select where item_id = x and ip_address = y, (if rows = 0) insert rating When in user account pages - select where ip_address = x or username = y Now none of the fields searched on are unique, can I still use them as indexes (for example item _id and ip_address), can I have two indexes and will this still improve performance over a non indexed table?

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  • prevent using functions before initialization, constructors-like in C

    - by Hernán Eche
    This is the way I get to prevent funA,funB,funC, etc.. for being used before init #define INIT_KEY 0xC0DE //any number except 0, is ok static int initialized=0; int Init() { //many init task initialized=INIT_KEY; } int funA() { if (initialized!=INIT_KEY) return 1 //.. } int funB() { if (initialized!=INIT_KEY) return 1 //.. } int funC() { if (initialized!=INIT_KEY) return 1 //.. } The problem with this approach is that if some of those function is called within a loop so "if (initialized!=INIT_KEY)" is called again, and again, although it's not necessary. It's a good example of why constructors are useful haha, If it were an object I would be sure that when was created initialization was called, but in C, I don't know how to do it. Any other ideas are welcome!

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  • How to increase query speed without using full-text search?

    - by andre matos
    This is my simple query; By searching selectnothing I'm sure I'll have no hits. SELECT nome_t FROM myTable WHERE nome_t ILIKE '%selectnothing%'; This is the EXPLAIN ANALYZE VERBOSE Seq Scan on myTable (cost=0.00..15259.04 rows=37 width=29) (actual time=2153.061..2153.061 rows=0 loops=1) Output: nome_t Filter: (nome_t ~~* '%selectnothing%'::text) Total runtime: 2153.116 ms myTable has around 350k rows and the table definition is something like: CREATE TABLE myTable ( nome_t text NOT NULL, ) I have an index on nome_t as stated below: CREATE INDEX idx_m_nome_t ON myTable USING btree (nome_t); Although this is clearly a good candidate for Fulltext search I would like to rule that option out for now. This query is meant to be run from a web application and currently it's taking around 2 seconds which is obviously too much; Is there anything I can do, like using other index methods, to improve the speed of this query?

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  • Feedback on Optimizing C# NET Code Block

    - by Brett Powell
    I just spent quite a few hours reading up on TCP servers and my desired protocol I was trying to implement, and finally got everything working great. I noticed the code looks like absolute bollocks (is the the correct usage? Im not a brit) and would like some feedback on optimizing it, mostly for reuse and readability. The packet formats are always int, int, int, string, string. try { BinaryReader reader = new BinaryReader(clientStream); int packetsize = reader.ReadInt32(); int requestid = reader.ReadInt32(); int serverdata = reader.ReadInt32(); Console.WriteLine("Packet Size: {0} RequestID: {1} ServerData: {2}", packetsize, requestid, serverdata); List<byte> str = new List<byte>(); byte nextByte = reader.ReadByte(); while (nextByte != 0) { str.Add(nextByte); nextByte = reader.ReadByte(); } // Password Sent to be Authenticated string string1 = Encoding.UTF8.GetString(str.ToArray()); str.Clear(); nextByte = reader.ReadByte(); while (nextByte != 0) { str.Add(nextByte); nextByte = reader.ReadByte(); } // NULL string string string2 = Encoding.UTF8.GetString(str.ToArray()); Console.WriteLine("String1: {0} String2: {1}", string1, string2); // Reply to Authentication Request MemoryStream stream = new MemoryStream(); BinaryWriter writer = new BinaryWriter(stream); writer.Write((int)(1)); // Packet Size writer.Write((int)(requestid)); // Mirror RequestID if Authenticated, -1 if Failed byte[] buffer = stream.ToArray(); clientStream.Write(buffer, 0, buffer.Length); clientStream.Flush(); } I am going to be dealing with other packet types as well that are formatted the same (int/int/int/str/str), but different values. I could probably create a packet class, but this is a bit outside my scope of knowledge for how to apply it to this scenario. If it makes any difference, this is the Protocol I am implementing. http://developer.valvesoftware.com/wiki/Source_RCON_Protocol

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  • In SQL Server what is most efficient way to compare records to other records for duplicates with in

    - by Glenn
    We have an SQL Server that gets daily imports of data files from clients. This data is interrelated and we are always scrubbing it and having to look for suspect duplicate records between these files. Finding and tagging suspect records can get pretty complicated. We use logic that requires some field values to be the same, allows some field values to differ, and allows a range to be specified for how different certain field values can be. The only way we've found to do it is by using a cursor based process, and it places a heavy burden on the database. So I wanted to ask if there's a more efficient way to do this. I've heard it said that there's almost always a more efficient way to replace cursors with clever JOINS. But I have to admit I'm having a lot of trouble with this one. For a concrete example suppose we have 1 table, an "orders" table, with the following 6 fields. order_id, customer_id product_id, quantity, sale_date, price We want to look through the records to find suspect duplicates on the following example criteria. These get increasingly harder. 1. Records that have the same product_id, sale_date, and quantity but different customer_id's should be marked as suspect duplicates for review. 2. Records that have the same customer_id, product_id, quantity and have sale_dates within five days of each other should be marked as suspect duplicates for review 3. Records that have the same customer_id, product_id, but different quantities within 20 units, and sales dates within five days of each other should be considered suspect. Is it possible to satisfy each one of these criteria with a single SQL Query that uses JOINS? Is this the most efficient way to do this?

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  • Where is the bottleneck in this code?

    - by Mikhail
    I have the following tight loop that makes up the serial bottle neck of my code. Ideally I would parallelize the function that calls this but that is not possible. //n is about 60 for (int k = 0;k < n;k++) { double fone = z[k*n+i+1]; double fzer = z[k*n+i]; z[k*n+i+1]= s*fzer+c*fone; z[k*n+i] = c*fzer-s*fone; } Are there any optimizations that can be made such as vectorization or some evil inline that can help this code? I am looking into finding eigen solutions of tridiagonal matrices. http://www.cimat.mx/~posada/OptDoglegGraph/DocLogisticDogleg/projects/adjustedrecipes/tqli.cpp.html

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  • online CSS optimizer?

    - by Dand
    Is there an online CSS optimizer equivalent to Googles JavaScript Closure Optimizer. I've found plenty of CSS compressors online, but I'm looking for a CSS optimizer ... where it actually removes redundant/conflicting attributes

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  • Resize an image and maintain quality?

    - by JasonS
    Hi, I have a problem with resizing images. What happens is that if you upload a file larger than the stated parameters, the image is cropped, then saved at 100% quality. So if I upload a large jpeg which is 272Kb. The image is cropped by 100 odd pixels. The file size then goes up to 1.2Mb. We are saving images at a 100% quality. I assume that this is what is causing the problem. The image is exported from Photoshop at 30% quality which reduces the file size. Resaving the image at 100% quality creates the same image but I assume with a lot of redundant file data. Has anyone encountered this before? Does anyone have a solution? This is what we are using. $source_im = imagecreatefromjpeg ($file); $dest_im = imagecreatetruecolor ($newsize_x, $newsize_y); imagecopyresampled ( $dest_im, $source_im, 0, 0, $offset_x, $offset_y, $newsize_x, $newsize_y, $sourceWidth, $sourceHeight ); imagedestroy ($source_im); if ($greyscale) { $dest_im = $this->imageconvertgreyscale ($dest_im); } imagejpeg($dest_im, $save_to_file, $quality); break;

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  • PHP Increasing writing to page speed.

    - by Frederico
    I'm currently writing out xml and have done the following: header ("content-type: text/xml"); header ("content-length: ".strlen($xml)); $xml being the xml to be written out. I'm near about 1.8 megs of text (which I found via firebug), it seems as the writing is taking more time than the script to run.. is there a way to increase this write speed? Thank you in advance.

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  • Cleaner way of using modulus for columns

    - by WmasterJ
    I currently have a list (<ul>) of people that I have divided up into two columns. But after finishing the code for it I keept wondering if there is a more effective or clean way to do the same thing. echo "<table class='area_list'><tr>"; // Loop users within areas, divided up in 2 columns $count = count($areaArray); for($i=0 ; $i<$count ; $i++) { $uid = $areaArray[$i]; // get the modulus value + ceil for uneven numbers $rowCalc = ($i+1) % ceil($count/2); if ($rowCalc == 1) echo "<td><ul>"; // OUTPUT the actual list item echo "<li>{$users[$uid]->profile_lastname}</li>"; if ($rowCalc == 0 && $i!=0) echo "</ul></td>"; } echo "</tr></table>"; Any ideas of how to make this cleaner or do it in another way?

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  • Does anybody have any suggestions on which of these two approaches is better for large delete?

    - by RPS
    Approach #1: DECLARE @count int SET @count = 2000 DECLARE @rowcount int SET @rowcount = @count WHILE @rowcount = @count BEGIN DELETE TOP (@count) FROM ProductOrderInfo WHERE ProductId = @product_id AND bCopied = 1 AND FileNameCRC = @localNameCrc SELECT @rowcount = @@ROWCOUNT WAITFOR DELAY '000:00:00.400' Approach #2: DECLARE @count int SET @count = 2000 DECLARE @rowcount int SET @rowcount = @count WHILE @rowcount = @count BEGIN DELETE FROM ProductOrderInfo WHERE ProductId = @product_id AND FileNameCRC IN ( SELECT TOP(@count) FileNameCRC FROM ProductOrderInfo WITH (NOLOCK) WHERE bCopied = 1 AND FileNameCRC = @localNameCrc ) SELECT @rowcount = @@ROWCOUNT WAITFOR DELAY '000:00:00.400' END

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  • Which is quicker? Memcache or file query? (using maxmind geoip.dat file)

    - by tomcritchlow
    Hi, I'm using Python on Appengine and am looking up the geolocation of an IP address like this: import pygeoip gi = pygeoip.GeoIP('GeoIP.dat') Location = gi.country_code_by_addr(self.request.remote_addr) (pygeoip can be found here: http://code.google.com/p/pygeoip/) I want to geolocate each page of my app for a user so currently I lookup the IP address once then store it in memcache. My question - which is quicker? Looking up the IP address each time from the .dat file or fetching it from memcache? Are there any other pros/cons I need to be aware of? For general queries like this, is there a good guide to teach me how to optimise my code and run speed tests myself? I'm new to python and coding in general so apologies if this is a basic concept. Thanks! Tom

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  • How to handle large table in MySQL ?

    - by Frantz Miccoli
    I've a database used to store items and properties about these items. The number of properties is extensible, thus there is a join table to store each property associated to an item value. CREATE TABLE `item_property` ( `property_id` int(11) NOT NULL, `item_id` int(11) NOT NULL, `value` double NOT NULL, PRIMARY KEY (`property_id`,`item_id`), KEY `item_id` (`item_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci; This database has two goals : storing (which has first priority and has to be very quick, I would like to perform many inserts (hundreds) in few seconds), retrieving data (selects using item_id and property_id) (this is a second priority, it can be slower but not too much because this would ruin my usage of the DB). Currently this table hosts 1.6 billions entries and a simple count can take up to 2 minutes... Inserting isn't fast enough to be usable. I'm using Zend_Db to access my data and would really be happy if you don't suggest me to develop any php side part. Thanks for your advices !

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  • optimized grid for rectangular items

    - by peterchen
    I have N rectangular items with an aspect ratio Aitem (X:Y). I have a rectangular display area with an aspect ratio Aview The items should be arranged in a table-like layout (i.e. r rows, c columns). what is the ideal grid rows x columns, so that individual items are largest? (rows * colums = N, of course - i.e. there may be "unused" grid places). A simple algorithm could iterate over rows = 1..N, calculate the required number of columns, and keep the row/column pair with the largest items. I wonder if there's a non-iterative algorithm, though (e.g. for Aitem = Aview = 1, rows / cols can be approximated by sqrt(N)).

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  • Is a program compiled with -g gcc flag slower than the same program compiled without -g?

    - by e271p314
    I'm compiling a program with -O3 for performance and -g for debug symbols (in case of crash I can use the core dump). One thing bothers me a lot, does the -g option results in a performance penalty? When I look on the output of the compilation with and without -g, I see that the output without -g is 80% smaller than the output of the compilation with -g. If the extra space goes for the debug symbols, I don't care about it (I guess) since this part is not used during runtime. But if for each instruction in the compilation output without -g I need to do 4 more instructions in the compilation output with -g than I certainly prefer to stop using -g option even at the cost of not being able to process core dumps. How to know the size of the debug symbols section inside the program and in general does compilation with -g creates a program which runs slower than the same code compiled without -g?

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  • How to optimize a postgreSQL server for a "write once, read many"-type infrastructure ?

    - by mhu
    Greetings, I am working on a piece of software that logs entries (and related tagging) in a PostgreSQL database for storage and retrieval. We never update any data once it has been inserted; we might remove it when the entry gets too old, but this is done at most once a day. Stored entries can be retrieved by users. The insertion of new entries can happen rather fast and regularly, thus the database will commonly hold several millions elements. The tables used are pretty simple : one table for ids, raw content and insertion date; and one table storing tags and their values associated to an id. User search mostly concern tags values, so SELECTs usually consist of JOIN queries on ids on the two tables. To sum it up : 2 tables Lots of INSERT no UPDATE some DELETE, once a day at most some user-generated SELECT with JOIN huge data set What would an optimal server configuration (software and hardware, I assume for example that RAID10 could help) be for my PostgreSQL server, given these requirements ? By optimal, I mean one that allows SELECT queries taking a reasonably little amount of time. I can provide more information about the current setup (like tables, indexes ...) if needed.

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  • optimize python code

    - by user283405
    i have code that uses BeautifulSoup library for parsing. But it is very slow. The code is written in such a way that threads cannot be used. Can anyone help me about this? I am using beautifulsoup library for parsing and than save in DB. if i comment the save statement, than still it takes time so there is no problem with database. def parse(self,text): soup = BeautifulSoup(text) arr = soup.findAll('tbody') for i in range(0,len(arr)-1): data=Data() soup2 = BeautifulSoup(str(arr[i])) arr2 = soup2.findAll('td') c=0 for j in arr2: if str(j).find("<a href=") > 0: data.sourceURL = self.getAttributeValue(str(j),'<a href="') else: if c == 2: data.Hits=j.renderContents() #and few others... #... c = c+1 data.save() Any suggestions? Note: I already ask this question here but that was closed due to incomplete information.

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  • Eliminate full table scan due to BETWEEN (and GROUP BY)

    - by Dave Jarvis
    Description According to the explain command, there is a range that is causing a query to perform a full table scan (160k rows). How do I keep the range condition and reduce the scanning? I expect the culprit to be: Y.YEAR BETWEEN 1900 AND 2009 AND Code Here is the code that has the range condition (the STATION_DISTRICT is likely superfluous). SELECT COUNT(1) as MEASUREMENTS, AVG(D.AMOUNT) as AMOUNT, Y.YEAR as YEAR, MAKEDATE(Y.YEAR,1) as AMOUNT_DATE FROM CITY C, STATION S, STATION_DISTRICT SD, YEAR_REF Y FORCE INDEX(YEAR_IDX), MONTH_REF M, DAILY D WHERE -- For a specific city ... -- C.ID = 10663 AND -- Find all the stations within a specific unit radius ... -- 6371.009 * SQRT( POW(RADIANS(C.LATITUDE_DECIMAL - S.LATITUDE_DECIMAL), 2) + (COS(RADIANS(C.LATITUDE_DECIMAL + S.LATITUDE_DECIMAL) / 2) * POW(RADIANS(C.LONGITUDE_DECIMAL - S.LONGITUDE_DECIMAL), 2)) ) <= 50 AND -- Get the station district identification for the matching station. -- S.STATION_DISTRICT_ID = SD.ID AND -- Gather all known years for that station ... -- Y.STATION_DISTRICT_ID = SD.ID AND -- The data before 1900 is shaky; insufficient after 2009. -- Y.YEAR BETWEEN 1900 AND 2009 AND -- Filtered by all known months ... -- M.YEAR_REF_ID = Y.ID AND -- Whittled down by category ... -- M.CATEGORY_ID = '003' AND -- Into the valid daily climate data. -- M.ID = D.MONTH_REF_ID AND D.DAILY_FLAG_ID <> 'M' GROUP BY Y.YEAR Update The SQL is performing a full table scan, which results in MySQL performing a "copy to tmp table", as shown here: +----+-------------+-------+--------+-----------------------------------+--------------+---------+-------------------------------+--------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+-----------------------------------+--------------+---------+-------------------------------+--------+-------------+ | 1 | SIMPLE | C | const | PRIMARY | PRIMARY | 4 | const | 1 | | | 1 | SIMPLE | Y | range | YEAR_IDX | YEAR_IDX | 4 | NULL | 160422 | Using where | | 1 | SIMPLE | SD | eq_ref | PRIMARY | PRIMARY | 4 | climate.Y.STATION_DISTRICT_ID | 1 | Using index | | 1 | SIMPLE | S | eq_ref | PRIMARY | PRIMARY | 4 | climate.SD.ID | 1 | Using where | | 1 | SIMPLE | M | ref | PRIMARY,YEAR_REF_IDX,CATEGORY_IDX | YEAR_REF_IDX | 8 | climate.Y.ID | 54 | Using where | | 1 | SIMPLE | D | ref | INDEX | INDEX | 8 | climate.M.ID | 11 | Using where | +----+-------------+-------+--------+-----------------------------------+--------------+---------+-------------------------------+--------+-------------+ Related http://dev.mysql.com/doc/refman/5.0/en/how-to-avoid-table-scan.html http://dev.mysql.com/doc/refman/5.0/en/where-optimizations.html http://stackoverflow.com/questions/557425/optimize-sql-that-uses-between-clause Thank you!

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