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  • Fastest way to do a weighted tag search in SQL Server

    - by Hasan Khan
    My table is as follows ObjectID bigint Tag nvarchar(50) Weight float Type tinyint I want to get search for all objects that has tags 'big' or 'large' I want the objectid in order of sum of weights (so objects having both the tags will be on top) select objectid, row_number() over (order by sum(weight) desc) as rowid from tags where tag in ('big', 'large') and type=0 group by objectid the reason for row_number() is that i want paging over results. The query in its current form is very slow, takes a minute to execute over 16 million tags. What should I do to make it faster? I have a non clustered index (objectid, tag, type) Any suggestions?

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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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  • Limit CPU usage of a process

    - by jb
    I have a service running which periodically checks a folder for a file and then processes it. (Reads it, extracts the data, stores it in sql) So I ran it on a test box and it took a little longer thaan expected. The file had 1.6 million rows, and it was still running after 6 hours (then I went home). The problem is the box it is running on is now absolutely crippled - remote desktop was timing out so I cant even get on it to stop the process, or attach a debugger to see how far through etc. It's solidly using 90%+ CPU, and all other running services or apps are suffering. The code is (from memory, may not compile): List<ItemDTO> items = new List<ItemDTO>(); using (StreamReader sr = fileInfo.OpenText()) { while (!sr.EndOfFile) { string line = sr.ReadLine() try { string s = line.Substring(0,8); double y = Double.Parse(line.Substring(8,7)); //If the item isnt already in the collection, add it. if (items.Find(delegate(ItemDTO i) { return (i.Item == s); }) == null) items.Add(new ItemDTO(s,y)); } catch { /*Crash*/ } } return items; } - So I am working on improving the code (any tips appreciated). But it still could be a slow affair, which is fine, I've no problems with it taking a long time as long as its not killing my server. So what I want from you fine people is: 1) Is my code hideously un-optimized? 2) Can I limit the amount of CPU my code block may use? Cheers all

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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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  • STL vectors with uninitialized storage?

    - by Jim Hunziker
    I'm writing an inner loop that needs to place structs in contiguous storage. I don't know how many of these structs there will be ahead of time. My problem is that STL's vector initializes its values to 0, so no matter what I do, I incur the cost of the initialization plus the cost of setting the struct's members to their values. Is there any way to prevent the initialization, or is there an STL-like container out there with resizeable contiguous storage and uninitialized elements? (I'm certain that this part of the code needs to be optimized, and I'm certain that the initialization is a significant cost.) Also, see my comments below for a clarification about when the initialization occurs. SOME CODE: void GetsCalledALot(int* data1, int* data2, int count) { int mvSize = memberVector.size() memberVector.resize(mvSize + count); // causes 0-initialization for (int i = 0; i < count; ++i) { memberVector[mvSize + i].d1 = data1[i]; memberVector[mvSize + i].d2 = data2[i]; } }

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  • MySQL Prepared Statements vs Stored Procedures Performance

    - by amardilo
    Hi there, I have an old MySQL 4.1 database with a table that has a few millions rows and an old Java application that connects to this database and returns several thousand rows from this this table on a frequent basis via a simple SQL query (i.e. SELECT * FROM people WHERE first_name = 'Bob'. I think the Java application uses client side prepared statements but was looking at switching this to the server, and in the example mentioned the value for first_name will vary depending on what the user enters). I would like to speed up performance on the select query and was wondering if I should switch to Prepared Statements or Stored Procedures. Is there a general rule of thumb of what is quicker/less resource intensive (or if a combination of both is better)

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  • Where does the compiler store methods for C++ classes?

    - by Mashmagar
    This is more a curiosity than anything else... Suppose I have a C++ class Kitty as follows: class Kitty { void Meow() { //Do stuff } } Does the compiler place the code for Meow() in every instance of Kitty? Obviously repeating the same code everywhere requires more memory. But on the other hand, branching to a relative location in nearby memory requires fewer assembly instructions than branching to an absolute location in memory on modern processors, so this is potentially faster. I suppose this is an implementation detail, so different compilers may perform differently. Keep in mind, I'm not considering static or virtual methods here.

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  • PHP what is faster to use

    - by user1631500
    What is faster / better to use? To put html into variables and print them later, or to just html print / echo print the content based on condition? EXAMPLE 1:(html into variables) if(!isset($_SESSION['daddy'])) { $var = "<span class='something'>Go here:<a href='#'>Click</a></span> <span class='something'>Go here:<a href='#'>Click</a></span>" } else { $one=$_SESSION["one"]; $two=$_SESSION["two"]; $three=$_SESSION["three"]; $var = You are cool enough to view the content; } echo $var; EXAMPLE 2:(print based on condition) if(!isset($_SESSION['daddy'])) { $var = 1; } else { $one=$_SESSION["one"]; $two=$_SESSION["two"]; $three=$_SESSION["three"]; $var = 0; } if ($var==1) { ?> <span class='something'>Go here:<a href='#'>Click</a></span> <span class='something'>Go here:<a href='#'>Click</a></span <?php } else { ?> You are cool enough to view the content. <?php } ?>

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  • How can I get a COUNT(col) ... GROUP BY to use an index?

    - by thecoop
    I've got a table (col1, col2, ...) with an index on (col1, col2, ...). The table has got millions of rows in it, and I want to run a query: SELECT col1, COUNT(col2) WHERE col1 NOT IN (<couple of exclusions>) GROUP BY col1 Unfortunately, this is resulting in a full table scan of the table, which takes upwards of a minute. Is there any way of getting oracle to use the index on the columns to return the results much faster?

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  • Java: how to read BufferedReader faster

    - by Cata
    Hello, I want to optimize this code: InputStream is = rp.getEntity().getContent(); BufferedReader reader = new BufferedReader(new InputStreamReader(is)); String text = ""; String aux = ""; while ((aux = reader.readLine()) != null) { text += aux; } The thing is that i don't know how to read the content of the bufferedreader and copy it in a String faster than what I have above. I need to spend as little time as possible. Thank you

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  • .net Compiler Optimizations

    - by Dested
    I am writing an application that I need to run at incredibly low speeds. The application creates and destroys memory in creative ways throughout its run, and it works just fine. I am wondering what compiler optimizations occur so I can try to build to that. One trick off hand is that the CLR handles arrays much faster than lists, so if you need to handle a ton of elements in a List, you may be better off calling ToArray() and handling it rather than calling ElementAt() again and again. I am wondering if there is any sort of comprehensive list for this kind of thing, or maybe the SO community can create one :-)

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  • [Python] Tips for making a fraction calculator code more optimized (faster and using less memory)

    - by Logic Named Joe
    Hello Everyone, Basicly, what I need for the program to do is to act a as simple fraction calculator (for addition, subtraction, multiplication and division) for the a single line of input, for example: -input: 1/7 + 3/5 -output: 26/35 My initial code: import sys def euclid(numA, numB): while numB != 0: numRem = numA % numB numA = numB numB = numRem return numA for wejscie in sys.stdin: wyjscie = wejscie.split(' ') a, b = [int(x) for x in wyjscie[0].split("/")] c, d = [int(x) for x in wyjscie[2].split("/")] if wyjscie[1] == '+': licz = a * d + b * c mian= b * d nwd = euclid(licz, mian) konA = licz/nwd konB = mian/nwd wynik = str(konA) + '/' + str(konB) print(wynik) elif wyjscie[1] == '-': licz= a * d - b * c mian= b * d nwd = euclid(licz, mian) konA = licz/nwd konB = mian/nwd wynik = str(konA) + '/' + str(konB) print(wynik) elif wyjscie[1] == '*': licz= a * c mian= b * d nwd = euclid(licz, mian) konA = licz/nwd konB = mian/nwd wynik = str(konA) + '/' + str(konB) print(wynik) else: licz= a * d mian= b * c nwd = euclid(licz, mian) konA = licz/nwd konB = mian/nwd wynik = str(konA) + '/' + str(konB) print(wynik) Which I reduced to: import sys def euclid(numA, numB): while numB != 0: numRem = numA % numB numA = numB numB = numRem return numA for wejscie in sys.stdin: wyjscie = wejscie.split(' ') a, b = [int(x) for x in wyjscie[0].split("/")] c, d = [int(x) for x in wyjscie[2].split("/")] if wyjscie[1] == '+': print("/".join([str((a * d + b * c)/euclid(a * d + b * c, b * d)),str((b * d)/euclid(a * d + b * c, b * d))])) elif wyjscie[1] == '-': print("/".join([str((a * d - b * c)/euclid(a * d - b * c, b * d)),str((b * d)/euclid(a * d - b * c, b * d))])) elif wyjscie[1] == '*': print("/".join([str((a * c)/euclid(a * c, b * d)),str((b * d)/euclid(a * c, b * d))])) else: print("/".join([str((a * d)/euclid(a * d, b * c)),str((b * c)/euclid(a * d, b * c))])) Any advice on how to improve this futher is welcome. Edit: one more thing that I forgot to mention - the code can not make use of any libraries apart from sys.

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  • Efficiently select top row for each category in the set

    - by VladV
    I need to select a top row for each category from a known set (somewhat similar to this question). The problem is, how to make this query efficient on the large number of rows. For example, let's create a table that stores temperature recording in several places. CREATE TABLE #t ( placeId int, ts datetime, temp int, PRIMARY KEY (ts, placeId) ) -- insert some sample data SET NOCOUNT ON DECLARE @n int, @ts datetime SELECT @n = 1000, @ts = '2000-01-01' WHILE (@n>0) BEGIN INSERT INTO #t VALUES (@n % 10, @ts, @n % 37) IF (@n % 10 = 0) SET @ts = DATEADD(hour, 1, @ts) SET @n = @n - 1 END Now I need to get the latest recording for each of the places 1, 2, 3. This way is efficient, but doesn't scale well (and looks dirty). SELECT * FROM ( SELECT TOP 1 placeId, temp FROM #t WHERE placeId = 1 ORDER BY ts DESC ) t1 UNION ALL SELECT * FROM ( SELECT TOP 1 placeId, temp FROM #t WHERE placeId = 2 ORDER BY ts DESC ) t2 UNION ALL SELECT * FROM ( SELECT TOP 1 placeId, temp FROM #t WHERE placeId = 3 ORDER BY ts DESC ) t3 The following looks better but works much less efficiently (30% vs 70% according to the optimizer). SELECT placeId, ts, temp FROM ( SELECT placeId, ts, temp, ROW_NUMBER() OVER (PARTITION BY placeId ORDER BY ts DESC) rownum FROM #t WHERE placeId IN (1, 2, 3) ) t WHERE rownum = 1 The problem is, during the latter query execution plan a clustered index scan is performed on #t and 300 rows are retrieved, sorted, numbered, and then filtered, leaving only 3 rows. For the former query three times one row is fetched. Is there a way to perform the query efficiently without lots of unions?

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  • Compiler reordering around mutex boundaries?

    - by shojtsy
    Suppose I have my own non-inline functions LockMutex and UnlockMutex, which are using some proper mutex - such as boost - inside. How will the compiler know not to reorder other operations with regard to calls to the LockMutex and UnlockMutex? It can not possibly know how will I implement these functions in some other compilation unit. void SomeClass::store(int i) { LockMutex(_m); _field = i; // could the compiler move this around? UnlockMutex(_m); } ps: One is supposed to use instances of classes for holding locks to guarantee unlocking. I have left this out to simplify the example.

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  • I'm doing a lot of lists and dictionary sorting...and this is causing memory errors in Python websit

    - by alex
    I retrieved data from the log table in my database. Then I started finding unique users, comparing/sorting lists, etc. In the end I got down to this. stats = {'2010-03-19': {'date': '2010-03-19', 'unique_users': 312, 'queries': 1465}, '2010-03-18': {'date': '2010-03-18', 'unique_users': 329, 'queries': 1659}, '2010-03-17': {'date': '2010-03-17', 'unique_users': 379, 'queries': 1845}, '2010-03-16': {'date': '2010-03-16', 'unique_users': 434, 'queries': 2336}, '2010-03-15': {'date': '2010-03-15', 'unique_users': 390, 'queries': 2138}, '2010-03-14': {'date': '2010-03-14', 'unique_users': 460, 'queries': 2221}, '2010-03-13': {'date': '2010-03-13', 'unique_users': 507, 'queries': 2242}, '2010-03-12': {'date': '2010-03-12', 'unique_users': 629, 'queries': 3523}, '2010-03-11': {'date': '2010-03-11', 'unique_users': 811, 'queries': 4274}, '2010-03-10': {'date': '2010-03-10', 'unique_users': 171, 'queries': 1297}, '2010-03-26': {'date': '2010-03-26', 'unique_users': 299, 'queries': 1617}, '2010-03-27': {'date': '2010-03-27', 'unique_users': 323, 'queries': 1310}, '2010-03-24': {'date': '2010-03-24', 'unique_users': 352, 'queries': 2112}, '2010-03-25': {'date': '2010-03-25', 'unique_users': 330, 'queries': 1290}, '2010-03-22': {'date': '2010-03-22', 'unique_users': 329, 'queries': 1798}, '2010-03-23': {'date': '2010-03-23', 'unique_users': 329, 'queries': 1857}, '2010-03-20': {'date': '2010-03-20', 'unique_users': 368, 'queries': 1693}, '2010-03-21': {'date': '2010-03-21', 'unique_users': 329, 'queries': 1511}, '2010-03-29': {'date': '2010-03-29', 'unique_users': 325, 'queries': 1718}, '2010-03-28': {'date': '2010-03-28', 'unique_users': 340, 'queries': 1815}, '2010-03-30': {'date': '2010-03-30', 'unique_users': 329, 'queries': 1891}} It's not a big dictionary. But when I try to do one last thing...it craps out on me. for k, v in stats: mylist.append(v) too many values to unpack What the heck does that mean??? TOO MANY VALUES TO UNPACK.

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  • Fastest way to find the rotation of a vector

    - by kriss
    I have two 2D vectors, say u and v, defined by cartesian coordinates. Imagine that vectors are needles of a clock. I'm looking for the fastest way to find out, using python, if v is after or before u (or in other words find out in wich half plane is v, regarding to position of u). For the purpose of the problem if vectors are aligned answer should be before. It seems easy using some trigonometry, but I believe there should be a faster way using coordinates only. My test case: def after(u, v): """code here""" after((4,2), (6, 1)) : True after((4,2), (3, 3)) : False after((4,2), (2, 1)) : False after((4,2), (3, -3)) : True after((4,2), (-2, -5)) : True after((4,2), (-4, -2)) : False

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  • PHP error handling : my code is not optimized

    - by Tristan
    Hello, I must warn you, this code will heart your eyes, so please don't judge me, i'm trying to improve the way I handle errors all my tests are like this : if ($something < 27) { $error_IP= '<div class="error_message">something bad</div> '; }else{ $erreur_IP=''; } and here's the ugliest thing : if( !isset($_POST) || ($erreur_captcha !='') || ($erreur_email !='') || ($erreur_hebergeurVide != '') || ($erreur_paysVide != '') || ($erreur_slotVide != '') || ($erreur_rconVide != '') || ($erreur_tick != '') + a lot more :d ) What do you suggest to me to optimize my errors handling ? Thank you

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  • Is count(*) really expensive ?

    - by Anil Namde
    I have a page where I have 4 tabs displaying 4 different reports based off different tables. I obtain the row count of each table using a select count(*) from <table> query and display number of rows available in each table on the tabs. As a result, each page postback causes 5 count(*) queries to be executed (4 to get counts and 1 for pagination) and 1 query for getting the report content. Now my question is: are count(*) queries really expensive -- should I keep the row counts (at least those that are displayed on the tab) in the view state of page instead of querying multiple times? How expensive are COUNT(*) queries ?

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  • How computer multiplies 2 numbers?

    - by ckv
    How does a computer perform a multiplication on 2 numbers say 100 * 55. My guess was that the computer did repeated addition to achieve multiplication. Of course this could be the case for integer numbers. However for floating point numbers there must be some other logic. Note: This was asked in an interview.

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