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  • How to simplify my code... 2D array in Objective C...?

    - by Tattat
    self.myArray = [NSArray arrayWithObjects: [NSArray arrayWithObjects: [self d], [self generateMySecretObject],nil], [NSArray arrayWithObjects: [self generateMySecretObject], [self generateMySecretObject],nil],nil]; for (int k=0; k<[self.myArray count]; k++) { for(int s = 0; s<[[self.myArray objectAtIndex:k] count]; s++){ [[[self.myArray objectAtIndex:k] objectAtIndex:s] setAttribute:[self generateSecertAttribute]]; } } As you can see this is a simple 2*2 array, but it takes me lots of code to assign the NSArray in very first place, because I found that the NSArray can't assign the size at very beginning. Also, I want to set attribute one by one. I can't think of if my array change to 10*10. How long it could be. So, I hope you guys can give me some suggestions on shorten the code, and more readable. thz

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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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  • 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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  • 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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  • Initializing a C++ vector to random values... fast

    - by Flamewires
    Hey, id like to make this as fast as possible because it gets called A LOT in a program i'm writing, so is there any faster way to initialize a C++ vector to random values than: double range;//set to the range of a particular function i want to evaluate. std::vector<double> x(30, 0.0); for (int i=0;i<x.size();i++) { x.at(i) = (rand()/(double)RAND_MAX)*range; } EDIT:Fixed x's initializer.

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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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  • 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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  • How can I store large amount of data from a database to XML (speed problem, part three)?

    - by Andrija
    After getting some responses, the current situation is that I'm using this tip: http://www.ibm.com/developerworks/xml/library/x-tipbigdoc5.html (Listing 1. Turning ResultSets into XML), and XMLWriter for Java from http://www.megginson.com/downloads/ . Basically, it reads date from the database and writes them to a file as characters, using column names to create opening and closing tags. While doing so, I need to make two changes to the input stream, namely to the dates and numbers. // Iterate over the set while (rs.next()) { w.startElement("row"); for (int i = 0; i < count; i++) { Object ob = rs.getObject(i + 1); if (rs.wasNull()) { ob = null; } String colName = meta.getColumnLabel(i + 1); if (ob != null ) { if (ob instanceof Timestamp) { w.dataElement(colName, Util.formatDate((Timestamp)ob, dateFormat)); } else if (ob instanceof BigDecimal){ w.dataElement(colName, Util.transformToHTML(new Integer(((BigDecimal)ob).intValue()))); } else { w.dataElement(colName, ob.toString()); } } else { w.emptyElement(colName); } } w.endElement("row"); } The SQL that gets the results has the to_number command (e.g. to_number(sif.ID) ID ) and the to_date command (e.g. TO_DATE (sif.datum_do, 'DD.MM.RRRR') datum_do). The problems are that the returning date is a timestamp, meaning I don't get 14.02.2010 but rather 14.02.2010 00:00:000 so I have to format it to the dd.mm.yyyy format. The second problem are the numbers; for some reason, they are in database as varchar2 and can have leading zeroes that need to be stripped; I'm guessing I could do that in my SQL with the trim function so the Util.transformToHTML is unnecessary (for clarification, here's the method): public static String transformToHTML(Integer number) { String result = ""; try { result = number.toString(); } catch (Exception e) {} return result; } What I'd like to know is a) Can I get the date in the format I want and skip additional processing thus shortening the processing time? b) Is there a better way to do this? We're talking about XML files that are in the 50 MB - 250 MB filesize category.

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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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  • 50 million+ Rows of Data - CSV or MySQL

    - by eWizardII
    Hello, I have a CSV file which is about 1GB big and contains about 50million rows of data, I am wondering is it better to keep it as a CSV file or store it as some form of a database. I don't know a great deal about MySQL to argue for why I should use it or another database framework over just keeping it as a CSV file. I am basically doing a Breadth-First Search with this dataset, so once I get the initial "seed" set the 50million I use this as the first values in my queue. Thanks,

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  • Anything wrong with this MySQL quert? takes 10 seconds+ to load

    - by user345426
    I have a search that is taking 10 seconds+ to execute! Keep in mind it is also searching over 200,000 products in the database. I posted the explain and MySQL query here. 1 SIMPLE p ref PRIMARY,products_status,prod_prodid_status,product... products_status 1 const 9048 Using where; Using temporary; Using filesort 1 SIMPLE v ref PRIMARY,vendors_id,vendors_vendorid vendors_vendorid 4 rhinomar_rhinomartnew.p.vendors_id 1 1 SIMPLE s ref products_id products_id 4 rhinomar_rhinomartnew.p.products_id 1 1 SIMPLE pd ref PRIMARY,products,prod_desc_prodid_prodname prod_desc_prodid_prodname 4 rhinomar_rhinomartnew.p.products_id 1 1 SIMPLE p2c ref PRIMARY,ptc_catidx PRIMARY 4 rhinomar_rhinomartnew.p.products_id 1 Using where; Using index 1 SIMPLE c eq_ref PRIMARY PRIMARY 4 rhinomar_rhinomartnew.p2c.categories_id 1 Using where MySQL Query: select p.products_id, p.products_image, p.products_price, p.products_weight, p.products_unit_quantity, s.specials_new_products_price, s.status, pd.products_name, pd.products_img_alt from products p left join vendors v ON v.vendors_id = p.vendors_id left join specials s on s.products_id = p.products_id left join products_description pd on pd.products_id = p.products_id left join products_to_categories p2c on p2c.products_id = p.products_id left join categories c on c.categories_id = p2c.categories_id where ( ( pd.products_name like '%apparel%' ) or p2c.categories_id IN (773, 132, 135, 136, 119, 122, 124, 125, 126, 1749, 1753, 1747, 123, 127, 130, 131, 178, 137, 140, 164, 165, 166, 167, 168, 169, 832, 2045 ) or p.products_id = 'apparel' or p.products_model = 'apparel' or CONCAT(v.vendors_prefix, '-') = 'apparel' or CONCAT( v.vendors_prefix, '-', p.products_id ) = 'apparel' ) and p.products_status = '1' and c.categories_status = '1' group by p.products_id order by pd.products_name

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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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  • How to optimize this javascript code?

    - by Andrija
    I have a jsp which uses a lot of javascript and it's just not fast enough. I would like to optimize it so first, here's a part of the code: In the jsp I have the initialization: window.onload = function () { formCollection.pageSize.value = "<%= pagingSize%>"; elemCollection = iDom3.Table.all["spis"].XML.DOM; <% if (resultList != null) { %> elementsNumber = <%= resultList.size() %>; <%} else { %> elementsNumber = 0; <% } %> contextPath = "<%= request.getContextPath() %>"; } In my js file I have two types of js functions: // gets the first element and sets it's value to all the other; //the selectSingleNode function is used because I use XSLT transformation //to generate the table _setTehJed = function(){ var resultId = formCollection.elements["idTehJedinice_spis_1"].value; var resultText = formCollection.elements["tehnicka_spis_1"].value; if (resultId != ""){ var counter = 1; while (counter<elementsNumber){ counter++; if(formCollection.elements["idTehJedinice_spis_"+counter] != null){ formCollection.elements["idTehJedinice_spis_"+counter].value=resultId; formCollection.elements["tehnicka_spis_"+counter].value=resultText; } var node=elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'tehnicka']/title"); node.text=resultText; var node2=elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'idTehJedinice']/title"); node2.text=resultId; } } } // sets the elements checkbox to checked or unchecked _SelectCheckRokCuvanja = { all : [], Item : function (oItem, sId) { this.all["spis_"+sId] = oItem.value; if (oItem.checked) { elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "true"); }else{ elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "false"); } } } I've used these tips: http://blogs.msdn.com/b/ie/archive/2006/08/28/728654.aspx http://code.google.com/speed/articles/optimizing-javascript.html but I still think something could be done like defining the functions like this: In the jsp: window.onload = function () { iDom3.DigitalnaArhivaPrihvat.formCollection=document.forms["controller"]; iDom3.DigitalnaArhivaPrihvat.formCollection.pageSize.value = "<%= pagingSize%>"; iDom3.DigitalnaArhivaPrihvat.elemCollection = iDom3.Table.all["spis"].XML.DOM; <% if (resultList != null) { %> iDom3.DigitalnaArhivaPrihvat.elementsNumber = <%= resultList.size() %> <%} else { %> iDom3.DigitalnaArhivaPrihvat.elementsNumber = 0; <% } %> } in the js: iDom3.DigitalnaArhivaPrihvat = { formCollection:null, elemCollection:null, elementsNumber:null, _setTehJed : function(){ var resultId = this.formCollection.elements.idTehJedinice_spis_1.value; var resultText = this.formCollection.elements.tehnicka_spis_1.value; if (resultId != ""){ var counter = 1; while (counter<this.elementsNumber){ counter++; if(this.formCollection.elements["idTehJedinice_spis_"+counter] !== null){ this.formCollection.elements["idTehJedinice_spis_"+counter].value=resultId; this.formCollection.elements["tehnicka_spis_"+counter].value=resultText; } var node=this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'tehnicka']/title"); node.text=resultText; var node2=this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'idTehJedinice']/title"); node2.text=resultId; } } }, _SelectCheckRokCuvanja = { all : [], Item : function (oItem, sId) { this.all["spis_"+sId] = oItem.value; if (oItem.checked) { this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "true"); }else{ this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "false"); } } } but the problem is scoping (if I do it like this, the second function does not execute properly). Any suggestions?

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  • Common causes of slow performing jQuery and how to optimize the code?

    - by Polaris878
    Hello, This might be a bit of a vague or general question, but I figure it might be able to serve as a good resource for other jQuery-ers. I'm interested in common causes of slow running jQuery and how to optimize these cases. We have a good amount of jQuery/JavaScript performing actions on our page... and performance can really suffer with a large number off elements. What are some obvious performance pitfalls you know of with jQuery? What are some general optimizations a jQuery-er can do to squeeze every last bit of performance out of his/her scripts? One example: a developer may use a selector to access an element that is slower than some other way. Thanks

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  • Which is faster in memory, ints or chars? And file-mapping or chunk reading?

    - by Nick
    Okay, so I've written a (rather unoptimized) program before to encode images to JPEGs, however, now I am working with MPEG-2 transport streams and the H.264 encoded video within them. Before I dive into programming all of this, I am curious what the fastest way to deal with the actual file is. Currently I am file-mapping the .mts file into memory to work on it, although I am not sure if it would be faster to (for example) read 100 MB of the file into memory in chunks and deal with it that way. These files require a lot of bit-shifting and such to read flags, so I am wondering that when I reference some of the memory if it is faster to read 4 bytes at once as an integer or 1 byte as a character. I thought I read somewhere that x86 processors are optimized to a 4-byte granularity, but I'm not sure if this is true... Thanks!

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  • Inline function v. Macro in C -- What's the Overhead (Memory/Speed)?

    - by Jason R. Mick
    I searched Stack Overflow for the pros/cons of function-like macros v. inline functions. I found the following discussion: Pros and Cons of Different macro function / inline methods in C ...but it didn't answer my primary burning question. Namely, what is the overhead in c of using a macro function (with variables, possibly other function calls) v. an inline function, in terms of memory usage and execution speed? Are there any compiler-dependent differences in overhead? I have both icc and gcc at my disposal. My code snippet I'm modularizing is: double AttractiveTerm = pow(SigmaSquared/RadialDistanceSquared,3); double RepulsiveTerm = AttractiveTerm * AttractiveTerm; EnergyContribution += 4 * Epsilon * (RepulsiveTerm - AttractiveTerm); My reason for turning it into an inline function/macro is so I can drop it into a c file and then conditionally compile other similar, but slightly different functions/macros. e.g.: double AttractiveTerm = pow(SigmaSquared/RadialDistanceSquared,3); double RepulsiveTerm = pow(SigmaSquared/RadialDistanceSquared,9); EnergyContribution += 4 * Epsilon * (RepulsiveTerm - AttractiveTerm); (note the difference in the second line...) This function is a central one to my code and gets called thousands of times per step in my program and my program performs millions of steps. Thus I want to have the LEAST overhead possible, hence why I'm wasting time worrying about the overhead of inlining v. transforming the code into a macro. Based on the prior discussion I already realize other pros/cons (type independence and resulting errors from that) of macros... but what I want to know most, and don't currently know is the PERFORMANCE. I know some of you C veterans will have some great insight for me!!

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  • How to batch retrieve documents with mongoDB?

    - by edude05
    Hello everyone, I have an application that queries data from a mongoDB using the mongoDB C# driver something like this: public void main() { foreach (int i in listOfKey) { list.add(getObjectfromDB(i); } } public myObject getObjFromDb(int primaryKey) { document query = new document(); query["primKey"] = primaryKey; document result= mongo["myDatabase"]["myCollection"].findOne(query); return parseObject(result); } On my local (development) machine to get 100 object this way takes less than a second. However, I recently moved the database to a server on the internet, and this query takes about 30 seconds to execute for the same number of object. Furthermore, looking at the mongoDB log, it seems to open about 8-10 connections to the DB to perform this query. So what I'd like to do is have the query the database for an array of primaryKeys and get them all back at once, then do the parsing in a loop afterwards, using one connection if possible. How could I optimize my query to do so? Thanks, --Michael

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  • File IO with Streams - Best Memory Buffer Size

    - by AJ
    I am writing a small IO library to assist with a larger (hobby) project. A part of this library performs various functions on a file, which is read / written via the FileStream object. On each StreamReader.Read(...) pass, I fire off an event which will be used in the main app to display progress information. The processing that goes on in the loop is vaired, but is not too time consuming (it could just be a simple file copy, for example, or may involve encryption...). My main question is: What is the best memory buffer size to use? Thinking about physical disk layouts, I could pick 2k, which would cover a CD sector size and is a nice multiple of a 512 byte hard disk sector. Higher up the abstraction tree, you could go for a larger buffer which could read an entire FAT cluster at a time. I realise with today's PC's, I could go for a more memory hungry option (a couple of MiB, for example), but then I increase the time between UI updates and the user perceives a less responsive app. As an aside, I'm eventually hoping to provide a similar interface to files hosted on FTP / HTTP servers (over a local network / fastish DSL). What would be the best memory buffer size for those (again, a "best-case" tradeoff between perceived responsiveness vs. performance).

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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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  • How much faster is a database running in RAM?

    - by orokusaki
    I"m looking to run PostgreSQL in RAM for performance enhancement. The database isn't more than 1GB and shouldn't ever grow to more than 5GB. Is it worth doing? Are there any benchmarks out there? Is it buggy? My second major concern is: How easy is it to back things up when it's running purely in RAM. Is this just like using RAM as tier 1 HD, or is it much more complicated?

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