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  • [N]Hibernate: view-like fetching properties of associated class

    - by chiccodoro
    (Felt quite helpless in formulating an appropriate title...) In my C# app I display a list of "A" objects, along with some properties of their associated "B" objects and properties of B's associated "C" objects: A.Name B.Name B.SomeValue C.Name Foo Bar 123 HelloWorld Bar Hello 432 World ... To clarify: A has an FK to B, B has an FK to C. (Such as, e.g. BankAccount - Person - Company). I have tried two approaches to load these properties from the database (using NHibernate): A fast approach and a clean approach. My eventual question is how to do a fast & clean approach. Fast approach: Define a view in the database which joins A, B, C and provides all these fields. In the A class, define properties "BName", "BSomeValue", "CName" Define a hibernate mapping between A and the View, whereas the needed B and C properties are mapped with update="false" insert="false" and do actually stem from B and C tables, but Hibernate is not aware of that since it uses the view. This way, the listing only loads one object per "A" record, which is quite fast. If the code tries to access the actual associated property, "A.B", I issue another HQL query to get B, set the property and update the faked BName and BSomeValue properties as well. Clean approach: There is no view. Class A is mapped to table A, B to B, C to C. When loading the list of A, I do a double left-join-fetch to get B and C as well: from A a left join fetch a.B left join fetch a.B.C B.Name, B.SomeValue and C.Name are accessed through the eagerly loaded associations. The disadvantage of this approach is that it gets slower and takes more memory, since it needs to created and map 3 objects per "A" record: An A, B, and C object each. Fast and clean approach: I feel somehow uncomfortable using a database view that hides a join and treat that in NHibernate as if it was a table. So I would like to do something like: Have no views in the database. Declare properties "BName", "BSomeValue", "CName" in class "A". Define the mapping for A such that NHibernate fetches A and these properties together using a join SQL query as a database view would do. The mapping should still allow for defining lazy many-to-one associations for getting A.B.C My questions: Is this possible? Is it [un]artful? Is there a better way?

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  • Slow query with unexpected scan

    - by zerkms
    Hello I have this query: SELECT * FROM SAMPLE SAMPLE INNER JOIN TEST TEST ON SAMPLE.SAMPLE_NUMBER = TEST.SAMPLE_NUMBER INNER JOIN RESULT RESULT ON TEST.TEST_NUMBER = RESULT . TEST_NUMBER WHERE SAMPLED_DATE BETWEEN '2010-03-17 09:00' AND '2010-03-17 12:00' the biggest table here is RESULT, contains 11.1M records. The left 2 tables about 1M. this query works slowly (more than 10 minutes) and returns about 800 records. executing plan shows clustered index scan over all 11M records. RESULT.TEST_NUMBER is a clustered primary key. if I change 2010-03-17 09:00 to 2010-03-17 10:00 - i get about 40 records. it executes for 300ms. and plan shows clustered index seek if i replace * in SELECT clause to RESULT.TEST_NUMBER (covered with index) - then all become fast in first case too. this points to hdd io issues, but doesn't clarifies changing plan. so, any ideas?

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  • Custom session state provider needed for DB storage?

    - by subt13
    I know this question is related to many others, but please bear with me. I am trying an experiment to store all information in database tables instead of the ASP.NET session. In ASP.NET 4 one can create a custom provider for session. So, again should I implement a Custom Session-State Provider or should I just disable session (in Web.config)? Thanks! From the comments my question can be misunderstood. Hopefully this tidbit will help clarify: I don't want to store the session in the database. I want to store information in the database that you would typically store in the session. One reason why: I don't want to carry around a session on every page, especially if that page doesn't care about 90 percent of the information in the session

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  • Should I aim for fewer HTTP requests or more cacheable CSS files?

    - by Jonathan Hanson
    We're being told that fewer HTTP requests per page load is a Good Thing. The extreme form of that for CSS would be to have a single, unique CSS file per page, with any shared site-wide styles duplicated in each file. But there's a trade off there. If you have separate shared global CSS files, they can be cached once when the front page is loaded and then re-used on multiple pages, thereby reducing the necessary size of the page-specific CSS files. So which is better in real-world practice? Shorter CSS files through multiple discrete CSS files that are cacheable, or fewer HTTP requests through fewer-but-larger CSS files?

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  • Are there any tools to optimize the number of consumer and producer threads on a JMS queue?

    - by lindelof
    I'm working on an application that is distributed over two JBoss instances and that produces/consumes JMS messages on several JMS queues. When we configured the application we had to determine which threading model we would use, in particular the number of producing and consuming threads per queue. We have done this in a rather ad-hoc fashion but after reading the most recent columns by Herb Sutter in Dr Dobbs (in particular this one) I would like to size our threads in a more rigorous manner. Are there any methods/tools to measure the throughput of JMS queues (in particular JBoss Messaging queues) as a function of the number of producing/consuming threads?

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  • Python re module becomes 20 times slower when called on greater than 101 different regex

    - by Wiil
    My problem is about parsing log files and removing variable parts on each lines to be able to group them. For instance: s = re.sub(r'(?i)User [_0-9A-z]+ is ', r"User .. is ", s) s = re.sub(r'(?i)Message rejected because : (.*?) \(.+\)', r'Message rejected because : \1 (...)', s) I have about 120+ matching rules like those above. I have found no performances issues while searching successively on 100 different regex. But a huge slow down comes when applying 101 regex. Exact same behavior happens when replacing my rules set by for a in range(100): s = re.sub(r'(?i)caught here'+str(a)+':.+', r'( ... )', s) Got 20 times slower when putting range(101) instead. # range(100) % ./dashlog.py file.bz2 == Took 2.1 seconds. == # range(101) % ./dashlog.py file.bz2 == Took 47.6 seconds. == Why such thing is happening ? And is there any known workaround ? (Happens on Python 2.6.6/2.7.2 on Linux/Windows.)

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  • How to copy files without slowing down my app?

    - by Kevin Gebhardt
    I have a bunch of little files in my assets which need to be copied to the SD-card on the first start of my App. The copy code i got from here placed in an IntentService works like a charm. However, when I start to copy many litte files, the whole app gets increddible slow (I'm not really sure why by the way), which is a really bad experience for the user on first start. As I realised other apps running normal in that time, I tried to start a child process for the service, which didn't work, as I can't acess my assets from another process as far as I understood. Has anybody out there an idea how a) to copy the files without blocking my app b) to get through to my assets from a private process (process=":myOtherProcess" in Manifest) or c) solve the problem in a complete different way Edit: To make this clearer: The copying allready takes place in a seperate thread (started automaticaly by IntentService). The problem is not to separate the task of copying but that the copying in a dedicated thread somehow affects the rest of the app (e.g. blocking to many app-specific resources?) but not other apps (so it's not blocking the whole CPU or someting) Edit2: Problem solved, it turns out, there wasn't really a problem. See my answer below.

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  • Why does Go compile quickly?

    - by Evan Kroske
    I've Googled and poked around the Go website, but I can't seem to find an explanation for Go's extraordinary build times. Are they products of the language features (or lack thereof), a highly optimized compiler, or something else? I'm not trying to promote Go; I'm just curious.

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  • mySQL & Relational databases: How to handle sharding/splitting on application level?

    - by Industrial
    Hi everybody, I have thought a bit about sharding tables, since partitioning cannot be done with foreign keys in a mySQL table. Maybe there's an option to switch to a different relational database that features both, but I don't see that as an option right now. So, the sharding idea seems like a pretty decent thing. But, what's a good approach to do this on a application level? I am guessing that a take-off point would be to prefix tables with a max value for the primary key in each table. Something like products_4000000 , products_8000000 and products_12000000. Then the application would have to check with a simple if-statement the size of the id (PK) that will be requested is smaller then four, eight or twelve million before doing any actual database calls. So, is this a step in the right direction or are we doing something really stupid?

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  • How does CouchDB perform for a regularly updated dataset?

    - by Ritesh M Nayak
    I am planning on using CouchDB on a project. But as the querying mechanism involves writing views (which are a lot like indexes on regular RDMBMS's) I was wondering, if the document database keeps getting updated a lot ( a write heavy database) would CouchDB perform well compared to a regular RDBMS? Or do we have to compact/re-index the system occasionally to make it perform faster?

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  • Python Speeding Up Retrieving data from extremely large string

    - by Burninghelix123
    I have a list I converted to a very very long string as I am trying to edit it, as you can gather it's called tempString. It works as of now it just takes way to long to operate, probably because it is several different regex subs. They are as follow: tempString = ','.join(str(n) for n in coords) tempString = re.sub(',{2,6}', '_', tempString) tempString = re.sub("[^0-9\-\.\_]", ",", tempString) tempString = re.sub(',+', ',', tempString) clean1 = re.findall(('[-+]?[0-9]*\.?[0-9]+,[-+]?[0-9]*\.?[0-9]+,' '[-+]?[0-9]*\.?[0-9]+'), tempString) tempString = '_'.join(str(n) for n in clean1) tempString = re.sub(',', ' ', tempString) Basically it's a long string containing commas and about 1-5 million sets of 4 floats/ints (mixture of both possible),: -5.65500020981,6.88999986649,-0.454999923706,1,,,-5.65500020981,6.95499992371,-0.454999923706,1,,, The 4th number in each set I don't need/want, i'm essentially just trying to split the string into a list with 3 floats in each separated by a space. The above code works flawlessly but as you can imagine is quite time consuming on large strings. I have done a lot of research on here for a solution but they all seem geared towards words, i.e. swapping out one word for another. EDIT: Ok so this is the solution i'm currently using: def getValues(s): output = [] while s: # get the three values you want, discard the 3 commas, and the # remainder of the string v1, v2, v3, _, _, _, s = s.split(',', 6) output.append("%s %s %s" % (v1.strip(), v2.strip(), v3.strip())) return output coords = getValues(tempString) Anyone have any advice to speed this up even farther? After running some tests It still takes much longer than i'm hoping for. I've been glancing at numPy, but I honestly have absolutely no idea how to the above with it, I understand that after the above has been done and the values are cleaned up i could use them more efficiently with numPy, but not sure how NumPy could apply to the above. The above to clean through 50k sets takes around 20 minutes, I cant imagine how long it would be on my full string of 1 million sets. I'ts just surprising that the program that originally exported the data took only around 30 secs for the 1 million sets

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  • How to delete duplicate/aggregate rows faster in a file using Java (no DB)

    - by S. Singh
    I have a 2GB big text file, it has 5 columns delimited by tab. A row will be called duplicate only if 4 out of 5 columns matches. Right now, I am doing dduping by first loading each coloumn in separate List , then iterating through lists, deleting the duplicate rows as it encountered and aggregating. The problem: it is taking more than 20 hours to process one file. I have 25 such files to process. Can anyone please share their experience, how they would go about doing such dduping? This dduping will be a throw away code. So, I was looking for some quick/dirty solution, to get job done as soon as possible. Here is my pseudo code (roughly) Iterate over the rows i=current_row_no. Iterate over the row no. i+1 to last_row if(col1 matches //find duplicate && col2 matches && col3 matches && col4 matches) { col5List.set(i,get col5); //aggregate } Duplicate example A and B will be duplicate A=(1,1,1,1,1), B=(1,1,1,1,2), C=(2,1,1,1,1) and output would be A=(1,1,1,1,1+2) C=(2,1,1,1,1) [notice that B has been kicked out]

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  • percentage of memory used used by a process

    - by benjamin button
    percentage of memory used used by a process. normally prstat -J will give the memory of process image and RSS(resident set size) etc. how do i knowlist of processes with percentage of memory is used by a each process. i am working on solaris unix. addintionally ,what are the regular commands that you use for monitoring processes,performences of processes that might be very useful to all!

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  • Are Conditional subquery

    - by Tobias Schulte
    I have a table foo and a table bar, where each foo might have a bar (and a bar might belong to multiple foos). Now I need to select all foos with a bar. My sql looks like this SELECT * FROM foo f WHERE [...] AND ($param IS NULL OR (SELECT ((COUNT(*))>0) FROM bar b WHERE f.bar = b.id)) with $param being replaced at runtime. The question is: Will the subquery be executed even if param is null, or will the dbms optimize the subquery out?

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  • NetNamedPipe: varying response time when communication is idling

    - by Sven Künzler
    I have two WCF apps communicating one-way over named pipes. All is nice, except for one thing: Normally, the request/response cycle takes zero (marginal) time. However, if there was a time span of, say, half a minute without any communication, the request/response increases up to ~300-500ms. I looked around the net and I got the idea of using a heart beat/ping mechanism to keep the communication channel busy. Using trial and error I found that when doing a request each 10 seconds, the response times stay low. Starting at around 15s intervals, the "hiccup" response times begin to appear. Now I'm wondering where this phenomenon is originating from. I tried setting alle conceivable timeouts on both sides to 1 minute, but that did not help. Can anybody explain what's going on there?

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  • Windows Workflow runs very slowlyh on my DEV machine

    - by Joon
    I am developing an app using WF hosted in IIS as WCF services as a business layer. This runs quickly on any machine running Windows Server 2008 R2, but very slowly on our dev machines, running Windows XP SP3. Yesterday, the workflows were as fast on my dev machine as they are on the server for the whole day. Today, they are back to running slowly again (I rebooted overnight) Has anyone else experienced this problem with workflows running slowly on IIS in XP? What did you do to fix it?

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  • Scalable way of doing self join with many to many table

    - by johnathan
    I have a table structure like the following: user id name profile_stat id name profile_stat_value id name user_profile user_id profile_stat_id profile_stat_value_id My question is: How do I evaluate a query where I want to find all users with profile_stat_id and profile_stat_value_id for many stats? I've tried doing an inner self join, but that quickly gets crazy when searching for many stats. I've also tried doing a count on the actual user_profile table, and that's much better, but still slow. Is there some magic I'm missing? I have about 10 million rows in the user_profile table and want the query to take no longer than a few seconds. Is that possible?

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  • Quickest way to compare a bunch of array or list of values.

    - by zapping
    Can you please let me know on the quickest and efficient way to compare a large set of values. Its like there are a list of parent codes(string) and each code has a series of child values(string). The child lists have to be compared with each other and find out duplicates and count how many times they repeat. code1(code1_value1, code1_value2, code3_value3, ..., code1_valueN); code2(code2_value1, code1_value2, code2_value3, ..., code2_valueN); code3(code2_value1, code3_value2, code3_value3, ..., code3_valueN); . . . codeN(codeN_value1, codeN_value2, codeN_value3, ..., codeN_valueN); The lists are huge say like there are 100 parent codes and each has about 250 values in them. There will not be duplicates within a code list. Doing it in java and the solution i could figure out is. Store the values of first set of code in as codeMap.put(codeValue, duplicateCount). The count initialized to 0. Then compare the rest of the values with this. If its in the map then increment the count otherwise append it to the map. The downfall of this is to get the duplicates. Another iteration needs to be performed on a very large list. An alternative is to maintain another hashmap for duplicates like duplicateCodeMap.put(codeValue, duplicateCount) and change the initial hashmap to codeMap.put(codeValue, codeValue). Speed is what is requirement. Hope one of you can help me with it.

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  • Python: how to run several scripts (or functions) at the same time under windows 7 multicore processor 64bit

    - by Gianni
    sorry for this question because there are several examples in Stackoverflow. I am writing in order to clarify some of my doubts because I am quite new in Python language. i wrote a function: def clipmyfile(inFile,poly,outFile): ... # doing something with inFile and poly and return outFile Normally I do this: clipmyfile(inFile="File1.txt",poly="poly1.shp",outFile="res1.txt") clipmyfile(inFile="File2.txt",poly="poly2.shp",outFile="res2.txt") clipmyfile(inFile="File3.txt",poly="poly3.shp",outFile="res3.txt") ...... clipmyfile(inFile="File21.txt",poly="poly21.shp",outFile="res21.txt") I had read in this example Run several python programs at the same time and i can use (but probably i wrong) from multiprocessing import Pool p = Pool(21) # like in your example, running 21 separate processes to run the function in the same time and speed my analysis I am really honest to say that I didn't understand the next step. Thanks in advance for help and suggestion Gianni

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  • Reusing of a PreparedStatement between methods?

    - by MRalwasser
    We all know that we should rather reuse a JDBC PreparedStatement than creating a new instance within a loop. But how to deal with PreparedStatement reuse between different method invocations? Does the reuse-"rule" still count? Should I really consider using a field for the PreparedStatement or should I close and re-create the prepared statement in every invocation? (Of course an instance of such a class would be bound to a Connection which might be a disadvantage) I am aware that the ideal answer might be "it depends". But I am looking for a best practice for less experienced developers that they will do the right choice in most of the cases.

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  • How to profile object creation in Java?

    - by gooli
    The system I work with is creating a whole lot of objects and garbage collecting them all the time which results in a very steeply jagged graph of heap consumption. I would like to know which objects are being generated to tune the code, but I can't figure out a way to dump the heap at the moment the garbage collection starts. When I tried to initiate dumpHeap via JConsole manually at random times, I always got results after GC finished its run, and didn't get any useful data. Any notes on how to track down excessive temporary object creation are welcome.

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