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  • microsoft access query speed...

    - by V.S.
    Hello everyone! I am now writing a report about MS Access and I can't find any information about its performance speed in comparison to other alternatives such as Micorsoft SQL Server, MySQL, Oracle, etc... It's obvious that MS Access is going to be the slowest among the rest, but there is no solid documents confirming this other than forums threads, and I don't have the time and resources to do the research myself :( Hoping for your help, V.S.

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  • C# - Fast and simple multi dimensional data structures?

    - by Jeremy Rudd
    I need to store multi-dimensional data consisting of numbers in a manner thats easy to work with. I'm capturing data in real time, and once processed I would destroy and GC older data. This data structure must be fast so it won't hit my overall app performance. The faster the better. What are my choices in terms of platform supported data structures? I'm using VS 2010. and .NET 4.

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  • Is mono fast enough for Mac OS X?

    - by prosseek
    I have to use .NET/C# for the next company project. As I've developed my project on Mac, I looked into the mono for development environment/tool. Is the mono for Mac OS X is fast enough? I mean, what about the performance in running the assembly compared to running the same code on .NET under windows machine? Do I have to buy PC laptop for developing C#/.NET in practical sense?

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  • Mod_rewrite on all website images

    - by Esteve Camps
    I'm designing an image repository. I want to uncouple the filename from the image html link. For instance: image in filesystem is called images/items/12543.jpg HTML is <img src="images/car.jpg" /> Does anyone strongly discourages me to rewrite all image requests using PHP so when retrieving images/car.jpg, Apache really replies content from images/items/12543.jpg? I don't know if I may get performance problems.

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  • What's the fastest lookup algorithm for a key, pair data structure (i.e, a map)?

    - by truncheon
    In the following example a std::map structure is filled with 26 values from A - Z (for key) and 0 – 26 for value. The time taken (on my system) to lookup the last entry (10000000 times) is roughly 250 ms for the vector, and 125 ms for the map. (I compiled using release mode, with O3 option turned on for g++ 4.4) But if for some odd reason I wanted better performance than the std::map, what data structures and functions would I need to consider using? I apologize if the answer seems obvious to you, but I haven't had much experience in the performance critical aspects of C++ programming. #include <ctime> #include <map> #include <vector> #include <iostream> struct mystruct { char key; int value; mystruct(char k = 0, int v = 0) : key(k), value(v) { } }; int find(const std::vector<mystruct>& ref, char key) { for (std::vector<mystruct>::const_iterator i = ref.begin(); i != ref.end(); ++i) if (i->key == key) return i->value; return -1; } int main() { std::map<char, int> mymap; std::vector<mystruct> myvec; for (int i = 'a'; i < 'a' + 26; ++i) { mymap[i] = i - 'a'; myvec.push_back(mystruct(i, i - 'a')); } int pre = clock(); for (int i = 0; i < 10000000; ++i) { find(myvec, 'z'); } std::cout << "linear scan: milli " << clock() - pre << "\n"; pre = clock(); for (int i = 0; i < 10000000; ++i) { mymap['z']; } std::cout << "map scan: milli " << clock() - pre << "\n"; return 0; }

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  • Maximum capabilities of MySQL

    - by cdated
    How do I know when a project is just to big for MySQL and I should use something with a better reputation for scalability? Is there a max database size for MySQL before degradation of performance occurs? What factors contribute to MySQL not being a viable option compared to a commercial DBMS like Oracle or SQL Server?

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  • What does "performant" software actually mean?

    - by Roddy
    I see it used a lot, but haven't seen a definition that makes complete sense. Wiktionary says "characterized by an adequate or excellent level of performance or efficiency", which isn't much help. Initially I though performant just meant "fast", but others seem to think it's also about stability, code quality, memory use/footprint, or some combination of all those. I think this is a "real" question - but if enough people reckon this is a subjective question, that's an answer in itself.

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  • What would be better, (1 database + 4 tables) or (2 databases + 2 tables each) ?

    - by griseldas
    Hi there, I would like to be advised on what would be better (in regards to performance) A) 1 DATABASE with 4 tables or B) 2 DATABASES (same server), each with 2 tables. The tables size and usage are more or less similar, so the 2 tables on Database 1 would be similar usage/size to the 2 tables on database 2 The tables could have +500,000 records and the 2 tables on each database are not related (no join queries etc between them) Thanks in advance for your comments

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  • Regex vs. string:find() for simple word boundary

    - by user576267
    Say I only need to find out whether a line read from a file contains a word from a finite set of words. One way of doing this is to use a regex like this: .*\y(good|better|best)\y.* Another way of accomplishing this is using a pseudo code like this: if ( (readLine.find("good") != string::npos) || (readLine.find("better") != string::npos) || (readLine.find("best") != string::npos) ) { // line contains a word from a finite set of words. } Which way will have better performance? (i.e. speed and CPU utilization)

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  • Improving performance for WRITE operation on Oracle DB in Java

    - by Lucky
    I've a typical scenario & need to understand best possible way to handle this, so here it goes - I'm developing a solution that will retrieve data from a remote SOAP based web service & will then push this data to an Oracle database on network. Also, this will be a scheduled task that will execute every 15 minutes. I've event queues on remote service that contains the INSERT/UPDATE/DELETE operations that have been done since last retrieval, & once I retrieve the events for last 15 minutes, it again add events for next retrieval. Now, its just pushing data to Oracle so all my interactions are INSERT & UPDATE statements. There are around 60 tables on Oracle with some of them having 100+ columns. Moreover, for every 15 minutes cycle there would be around 60-70 Inserts, 100+ Updates & 10-20 Deletes. This will be an executable jar file that will terminate after operation & will again start on next 15 minutes cycle. So, I need to understand how should I handle WRITE operations (best practices) to improve performance for this application as whole ? Current Test Code (on every cycle) - Connects to remote service to get events. Creates a connection with DB (single connection object). Identifies the type of operation (INSERT/UPDATE/DELETE) & table on which it is done. After above, calls the respective method based on type of operation & table. Uses Preparedstatement with positional parameters, & retrieves each column value from remote service & assigns that to statement parameters. Commits the statement & returns to get event class to process next event. Above is repeated till all the retrieved events are processed after which program closes & then starts on next cycle & everything repeats again. Thanks for help !

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  • How much slower is a try/catch block? [closed]

    - by Euclid
    Possible Duplicate: What is the real overhead of try/catch in C#? how much slower is a try catch block than a conditional? eg try { v = someArray[10]; } catch { v = defaultValue; } or if (null != someArray) { v = someArray[10]; } else { v = defaultValue; } is there much in it or isn't there a definative performance differance?

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  • Improving the performance of XSL

    - by Rachel
    In the below XSL for the variable "insert-data", I have an input param with the structure, <insert-data> <data compareIndex="4" nodeName="d1e1"> <a/> </data> <data compareIndex="5" nodeName="d1e1"> <b/> </data> <data compareIndex="7" nodeName="d1e2"> <a/> </data> <data compareIndex="9" nodeName="d1e2"> <b/> </data> </insert-data> where "nodeName" is the id of a node and "compareIndex" is the position of the text content relative to the node having id "$nodeName". I am using the below XSL to select all the text nodes(generate-id) that satisfy the above condition and construct a data xml. The below implementation works perfectly but the time taken for the execution is in min. Is there a better way of implementing or is there any in-efficient operation being used. From my observation the code where the preceding text length is calculated consumes the major time. Please share your thoughts to improve the performance of the XSL. I am using Java SAXON XSL transformer. <xsl:variable name="insert-data" as="element()*"> <xsl:for-each select="$insert-file/insert-data/data"> <xsl:sort select="xsd:integer(@index)"/> <xsl:variable name="compareIndex" select="xsd:integer(@compareIndex)" /> <xsl:variable name="nodeName" select="@nodeName" /> <xsl:variable name="nodeContent" as="node()"> <xsl:copy-of select="node()"/> </xsl:variable> <xsl:for-each select="$main-root/*//text()[ancestor::*[@id = $nodeName]]"> <xsl:variable name="preTextLength" as="xsd:integer" select="sum((preceding::text())[. ancestor::*[@id = $nodeName]]/string-length(.))" /> <xsl:variable name="currentTextLength" as="xsd:integer" select="string-length(.)" /> <xsl:variable name="sum" select="$preTextLength + $currentTextLength" as="xsd:integer"></xsl:variable> <xsl:variable name="split-index" select="$compareIndex - $preTextLength" as="xsd:integer"></xsl:variable> <xsl:if test="($sum ge $compareIndex) and ($compareIndex gt $preTextLength)"> <data split-index="{$split-index}" text-id="{generate-id(.)}"> <xsl:copy-of select="$nodeContent"/> </data> </xsl:if> </xsl:for-each> </xsl:for-each> </xsl:variable>

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  • HttpClient multithread performance

    - by pepper
    I have an application which downloads more than 4500 html pages from 62 target hosts using HttpClient (4.1.3 or 4.2-beta). It runs on Windows 7 64-bit. Processor - Core i7 2600K. Network bandwidth - 54 Mb/s. At this moment it uses such parameters: DefaultHttpClient and PoolingClientConnectionManager; Also it hasIdleConnectionMonitorThread from http://hc.apache.org/httpcomponents-client-ga/tutorial/html/connmgmt.html; Maximum total connections = 80; Default maximum connections per route = 5; For thread management it uses ForkJoinPool with the parallelism level = 5 (Do I understand correctly that it is a number of working threads?) In this case my network usage (in Windows task manager) does not rise above 2.5%. To download 4500 pages it takes 70 minutes. And in HttpClient logs I have such things: DEBUG ForkJoinPool-2-worker-1 [org.apache.http.impl.conn.PoolingClientConnectionManager]: Connection released: [id: 209][route: {}-http://stackoverflow.com][total kept alive: 6; route allocated: 1 of 5; total allocated: 10 of 80] Total allocated connections do not raise above 10-12, in spite of that I've set it up to 80 connections. If I'll try to rise parallelism level to 20 or 80, network usage remains the same but a lot connection time-outs will be generated. I've read tutorials on hc.apache.org (HttpClient Performance Optimization Guide and HttpClient Threading Guide) but they does not help. Task's code looks like this: public class ContentDownloader extends RecursiveAction { private final HttpClient httpClient; private final HttpContext context; private List<Entry> entries; public ContentDownloader(HttpClient httpClient, List<Entry> entries){ this.httpClient = httpClient; context = new BasicHttpContext(); this.entries = entries; } private void computeDirectly(Entry entry){ final HttpGet get = new HttpGet(entry.getLink()); try { HttpResponse response = httpClient.execute(get, context); int statusCode = response.getStatusLine().getStatusCode(); if ( (statusCode >= 400) && (statusCode <= 600) ) { logger.error("Couldn't get content from " + get.getURI().toString() + "\n" + response.toString()); } else { HttpEntity entity = response.getEntity(); if (entity != null) { String htmlContent = EntityUtils.toString(entity).trim(); entry.setHtml(htmlContent); EntityUtils.consumeQuietly(entity); } } } catch (Exception e) { } finally { get.releaseConnection(); } } @Override protected void compute() { if (entries.size() <= 1){ computeDirectly(entries.get(0)); return; } int split = entries.size() / 2; invokeAll(new ContentDownloader(httpClient, entries.subList(0, split)), new ContentDownloader(httpClient, entries.subList(split, entries.size()))); } } And the question is - what is the best practice to use multi threaded HttpClient, may be there is a some rules for setting up ConnectionManager and HttpClient? How can I use all of 80 connections and raise network usage? If necessary, I will provide more code.

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  • ListView slow performance

    - by Mohamed Hemdan
    I've created a list of recipes using Listview/customcursoradapter. A custom layout includes a photo for the recipe , Now I've some problems with the performance of viewing and scrolling the Listview although it has only 10 records (Target is 150). sometimes i get this error java.lang.OutOfMemoryError: bitmap size exceeds VM budget , I've tried to implement the Async task but i failed to do it. Is there any way i can overcome this problem? Your help is highly appreciated !! Here is my GetView method public View getView(int position, View convertView, ViewGroup parent) { View row = super.getView(position, convertView, parent); Cursor cursbbn = getCursor(); if (row == null) { LayoutInflater inflater = (LayoutInflater) localContext.getSystemService(Context.LAYOUT_INFLATER_SERVICE); row = inflater.inflate(R.layout.listtype, null); } String Title = cursbbn.getString(2); String SandID=cursbbn.getString(1); String Readyin = cursbbn.getString(4); String Faovoites=cursbbn.getString(8); TextView titler=(TextView)row.findViewById(R.id.listmaintitle); TextView readyinr=(TextView)row.findViewById(R.id.listreadyin); int colorPos = position % colors.length; row.setBackgroundColor(colors[colorPos]); titler.setText(Title); readyinr.setText(Readyin); ImageView picture = (ImageView) row.findViewById(R.id.imageView1); Bitmap bitImg1 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0001); Bitmap bitImg2 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0002); Bitmap bitImg3 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0003); Bitmap bitImg4 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0004); Bitmap bitImg5 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0005); Bitmap bitImg6 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0006); Bitmap bitImg7 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0007); Bitmap bitImg8 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0008); Bitmap bitImg9 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0009); Bitmap bitImg10 = BitmapFactory.decodeResource(localContext.getResources(), R.drawable.rec0010); if(SandID.contentEquals("0001")) picture.setImageBitmap(getRoundedCornerImage(bitImg1)); if(SandID.contentEquals("0002")) picture.setImageBitmap(getRoundedCornerImage(bitImg2)); if(SandID.contentEquals("0003")) picture.setImageBitmap(getRoundedCornerImage(bitImg3)); if(SandID.contentEquals("0004")) picture.setImageBitmap(getRoundedCornerImage(bitImg4)); if(SandID.contentEquals("0005")) picture.setImageBitmap(getRoundedCornerImage(bitImg5)); if(SandID.contentEquals("0006")) picture.setImageBitmap(getRoundedCornerImage(bitImg6)); if(SandID.contentEquals("0007")) picture.setImageBitmap(getRoundedCornerImage(bitImg7)); if(SandID.contentEquals("0008")) picture.setImageBitmap(getRoundedCornerImage(bitImg8)); if(SandID.contentEquals("0009")) picture.setImageBitmap(getRoundedCornerImage(bitImg9)); if(SandID.contentEquals("0010")) picture.setImageBitmap(getRoundedCornerImage(bitImg10)); return row; } And This is the error : 05-02 03:11:55.898: E/AndroidRuntime(376): FATAL EXCEPTION: main 05-02 03:11:55.898: E/AndroidRuntime(376): java.lang.OutOfMemoryError: bitmap size exceeds VM budget 05-02 03:11:55.898: E/AndroidRuntime(376): at android.graphics.BitmapFactory.nativeDecodeAsset(Native Method) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.graphics.BitmapFactory.decodeStream(BitmapFactory.java:460) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.graphics.BitmapFactory.decodeResourceStream(BitmapFactory.java:336) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.graphics.BitmapFactory.decodeResource(BitmapFactory.java:359) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.graphics.BitmapFactory.decodeResource(BitmapFactory.java:385) 05-02 03:11:55.898: E/AndroidRuntime(376): at master.chef.mediamaster.AlternateRowCursorAdapter.getView(AlternateRowCursorAdapter.java:83) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.AbsListView.obtainView(AbsListView.java:1409) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.ListView.makeAndAddView(ListView.java:1745) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.ListView.fillUp(ListView.java:700) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.ListView.fillGap(ListView.java:646) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.AbsListView.trackMotionScroll(AbsListView.java:3399) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.AbsListView.onTouchEvent(AbsListView.java:2233) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.widget.ListView.onTouchEvent(ListView.java:3446) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.View.dispatchTouchEvent(View.java:3885) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:903) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewGroup.dispatchTouchEvent(ViewGroup.java:942) 05-02 03:11:55.898: E/AndroidRuntime(376): at com.android.internal.policy.impl.PhoneWindow$DecorView.superDispatchTouchEvent(PhoneWindow.java:1691) 05-02 03:11:55.898: E/AndroidRuntime(376): at com.android.internal.policy.impl.PhoneWindow.superDispatchTouchEvent(PhoneWindow.java:1125) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.app.Activity.dispatchTouchEvent(Activity.java:2096) 05-02 03:11:55.898: E/AndroidRuntime(376): at com.android.internal.policy.impl.PhoneWindow$DecorView.dispatchTouchEvent(PhoneWindow.java:1675) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewRoot.deliverPointerEvent(ViewRoot.java:2194) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.view.ViewRoot.handleMessage(ViewRoot.java:1878) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.os.Handler.dispatchMessage(Handler.java:99) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.os.Looper.loop(Looper.java:123) 05-02 03:11:55.898: E/AndroidRuntime(376): at android.app.ActivityThread.main(ActivityThread.java:3683) 05-02 03:11:55.898: E/AndroidRuntime(376): at java.lang.reflect.Method.invokeNative(Native Method) 05-02 03:11:55.898: E/AndroidRuntime(376): at java.lang.reflect.Method.invoke(Method.java:507) 05-02 03:11:55.898: E/AndroidRuntime(376): at com.android.internal.os.ZygoteInit$MethodAndArgsCaller.run(ZygoteInit.java:839) 05-02 03:11:55.898: E/AndroidRuntime(376): at com.android.internal.os.ZygoteInit.main(ZygoteInit.java:597) 05-02 03:11:55.898: E/AndroidRuntime(376): at dalvik.system.NativeStart.main(Native Method)

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  • Optimizing python code performance when importing zipped csv to a mongo collection

    - by mark
    I need to import a zipped csv into a mongo collection, but there is a catch - every record contains a timestamp in Pacific Time, which must be converted to the local time corresponding to the (longitude,latitude) pair found in the same record. The code looks like so: def read_csv_zip(path, timezones): with ZipFile(path) as z, z.open(z.namelist()[0]) as input: csv_rows = csv.reader(input) header = csv_rows.next() check,converters = get_aux_stuff(header) for csv_row in csv_rows: if check(csv_row): row = { converter[0]:converter[1](value) for converter, value in zip(converters, csv_row) if allow_field(converter) } ts = row['ts'] lng, lat = row['loc'] found_tz_entry = timezones.find_one(SON({'loc': {'$within': {'$box': [[lng-tz_lookup_radius, lat-tz_lookup_radius],[lng+tz_lookup_radius, lat+tz_lookup_radius]]}}})) if found_tz_entry: tz_name = found_tz_entry['tz'] local_ts = ts.astimezone(timezone(tz_name)).replace(tzinfo=None) row['tz'] = tz_name else: local_ts = (ts.astimezone(utc) + timedelta(hours = int(lng/15))).replace(tzinfo = None) row['local_ts'] = local_ts yield row def insert_documents(collection, source, batch_size): while True: items = list(itertools.islice(source, batch_size)) if len(items) == 0: break; try: collection.insert(items) except: for item in items: try: collection.insert(item) except Exception as exc: print("Failed to insert record {0} - {1}".format(item['_id'], exc)) def main(zip_path): with Connection() as connection: data = connection.mydb.data timezones = connection.timezones.data insert_documents(data, read_csv_zip(zip_path, timezones), 1000) The code proceeds as follows: Every record read from the csv is checked and converted to a dictionary, where some fields may be skipped, some titles be renamed (from those appearing in the csv header), some values may be converted (to datetime, to integers, to floats. etc ...) For each record read from the csv, a lookup is made into the timezones collection to map the record location to the respective time zone. If the mapping is successful - that timezone is used to convert the record timestamp (pacific time) to the respective local timestamp. If no mapping is found - a rough approximation is calculated. The timezones collection is appropriately indexed, of course - calling explain() confirms it. The process is slow. Naturally, having to query the timezones collection for every record kills the performance. I am looking for advises on how to improve it. Thanks. EDIT The timezones collection contains 8176040 records, each containing four values: > db.data.findOne() { "_id" : 3038814, "loc" : [ 1.48333, 42.5 ], "tz" : "Europe/Andorra" } EDIT2 OK, I have compiled a release build of http://toblerity.github.com/rtree/ and configured the rtree package. Then I have created an rtree dat/idx pair of files corresponding to my timezones collection. So, instead of calling collection.find_one I call index.intersection. Surprisingly, not only there is no improvement, but it works even more slowly now! May be rtree could be fine tuned to load the entire dat/idx pair into RAM (704M), but I do not know how to do it. Until then, it is not an alternative. In general, I think the solution should involve parallelization of the task. EDIT3 Profile output when using collection.find_one: >>> p.sort_stats('cumulative').print_stats(10) Tue Apr 10 14:28:39 2012 ImportDataIntoMongo.profile 64549590 function calls (64549180 primitive calls) in 1231.257 seconds Ordered by: cumulative time List reduced from 730 to 10 due to restriction <10> ncalls tottime percall cumtime percall filename:lineno(function) 1 0.012 0.012 1231.257 1231.257 ImportDataIntoMongo.py:1(<module>) 1 0.001 0.001 1230.959 1230.959 ImportDataIntoMongo.py:187(main) 1 853.558 853.558 853.558 853.558 {raw_input} 1 0.598 0.598 370.510 370.510 ImportDataIntoMongo.py:165(insert_documents) 343407 9.965 0.000 359.034 0.001 ImportDataIntoMongo.py:137(read_csv_zip) 343408 2.927 0.000 287.035 0.001 c:\python27\lib\site-packages\pymongo\collection.py:489(find_one) 343408 1.842 0.000 274.803 0.001 c:\python27\lib\site-packages\pymongo\cursor.py:699(next) 343408 2.542 0.000 271.212 0.001 c:\python27\lib\site-packages\pymongo\cursor.py:644(_refresh) 343408 4.512 0.000 253.673 0.001 c:\python27\lib\site-packages\pymongo\cursor.py:605(__send_message) 343408 0.971 0.000 242.078 0.001 c:\python27\lib\site-packages\pymongo\connection.py:871(_send_message_with_response) Profile output when using index.intersection: >>> p.sort_stats('cumulative').print_stats(10) Wed Apr 11 16:21:31 2012 ImportDataIntoMongo.profile 41542960 function calls (41542536 primitive calls) in 2889.164 seconds Ordered by: cumulative time List reduced from 778 to 10 due to restriction <10> ncalls tottime percall cumtime percall filename:lineno(function) 1 0.028 0.028 2889.164 2889.164 ImportDataIntoMongo.py:1(<module>) 1 0.017 0.017 2888.679 2888.679 ImportDataIntoMongo.py:202(main) 1 2365.526 2365.526 2365.526 2365.526 {raw_input} 1 0.766 0.766 502.817 502.817 ImportDataIntoMongo.py:180(insert_documents) 343407 9.147 0.000 491.433 0.001 ImportDataIntoMongo.py:152(read_csv_zip) 343406 0.571 0.000 391.394 0.001 c:\python27\lib\site-packages\rtree-0.7.0-py2.7.egg\rtree\index.py:384(intersection) 343406 379.957 0.001 390.824 0.001 c:\python27\lib\site-packages\rtree-0.7.0-py2.7.egg\rtree\index.py:435(_intersection_obj) 686513 22.616 0.000 38.705 0.000 c:\python27\lib\site-packages\rtree-0.7.0-py2.7.egg\rtree\index.py:451(_get_objects) 343406 6.134 0.000 33.326 0.000 ImportDataIntoMongo.py:162(<dictcomp>) 346 0.396 0.001 30.665 0.089 c:\python27\lib\site-packages\pymongo\collection.py:240(insert) EDIT4 I have parallelized the code, but the results are still not very encouraging. I am convinced it could be done better. See my own answer to this question for details.

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  • How optimize code with introspection + heavy alloc on iPhone

    - by mamcx
    I have a problem. I try to display a UITable that could have 2000-20000 records (typicall numbers.) I have a SQLite database similar to the Apple contacts application. I do all the tricks I know to get a smoth scroll, but I have a problem. I load the data in 50 recods blocks. Then, when the user scroll, request next 50 until finish the list. However, load that 50 records cause a notable "pause" in loading and scrolling. Everything else works fine. I cache the data, have opaque cells, draw it by code, etc... I swap the code loading the same data in dicts and have a performance boost but wonder if I could keep my object oriented aproach and improve the actual code. This is the code I think have the performance problem: -(NSArray *) loadAndFill: (NSString *)sql theClass: (Class)cls { [self openDb]; NSMutableArray *list = [NSMutableArray array]; NSAutoreleasePool *pool = [[NSAutoreleasePool alloc] init]; DbObject *ds; Class myClass = NSClassFromString([DbObject getTableName:cls]); FMResultSet *rs = [self load:sql]; while ([rs next]) { ds = [[myClass alloc] init]; NSDictionary *props = [ds properties]; NSString *fieldType = nil; id fieldValue; for (NSString *fieldName in [props allKeys]) { fieldType = [props objectForKey: fieldName]; fieldValue = [self ValueForField:rs Name:fieldName Type:fieldType]; [ds setValue:fieldValue forKey:fieldName]; } [list addObject :ds]; [ds release]; } [rs close]; [pool drain]; return list; } And I think the main culprit is: -(id) ValueForField: (FMResultSet *)rs Name:(NSString *)fieldName Type:(NSString *)fieldType { id fieldValue = nil; if ([fieldType isEqualToString:@"i"] || // int [fieldType isEqualToString:@"I"] || // unsigned int [fieldType isEqualToString:@"s"] || // short [fieldType isEqualToString:@"S"] || // unsigned short [fieldType isEqualToString:@"f"] || // float [fieldType isEqualToString:@"d"] ) // double { fieldValue = [NSNumber numberWithInt: [rs longForColumn:fieldName]]; } else if ([fieldType isEqualToString:@"B"]) // bool or _Bool { fieldValue = [NSNumber numberWithBool: [rs boolForColumn:fieldName]]; } else if ([fieldType isEqualToString:@"l"] || // long [fieldType isEqualToString:@"L"] || // usigned long [fieldType isEqualToString:@"q"] || // long long [fieldType isEqualToString:@"Q"] ) // unsigned long long { fieldValue = [NSNumber numberWithLong: [rs longForColumn:fieldName]]; } else if ([fieldType isEqualToString:@"c"] || // char [fieldType isEqualToString:@"C"] ) // unsigned char { fieldValue = [rs stringForColumn:fieldName]; //Is really a boolean? if ([fieldValue isEqualToString:@"0"] || [fieldValue isEqualToString:@"1"]) { fieldValue = [NSNumber numberWithInt: [fieldValue intValue]]; } } else if ([fieldType hasPrefix:@"@"] ) // Object { NSString *className = [fieldType substringWithRange:NSMakeRange(2, [fieldType length]-3)]; if ([className isEqualToString:@"NSString"]) { fieldValue = [rs stringForColumn:fieldName]; } else if ([className isEqualToString:@"NSDate"]) { NSDateFormatter* dateFormatter = [[NSDateFormatter alloc] init]; [dateFormatter setDateFormat:@"yyyy-MM-dd'T'HH:mm:ss"]; NSString *theDate = [rs stringForColumn:fieldName]; if (theDate) { fieldValue = [dateFormatter dateFromString: theDate]; } else { fieldValue = nil; } [dateFormatter release]; } else if ([className isEqualToString:@"NSInteger"]) { fieldValue = [NSNumber numberWithInt: [rs intForColumn :fieldName]]; } else if ([className isEqualToString:@"NSDecimalNumber"]) { fieldValue = [rs stringForColumn :fieldName]; if (fieldValue) { fieldValue = [NSDecimalNumber decimalNumberWithString:[rs stringForColumn :fieldName]]; } } else if ([className isEqualToString:@"NSNumber"]) { fieldValue = [NSNumber numberWithDouble: [rs doubleForColumn:fieldName]]; } else { //Is a relationship one-to-one? if (![fieldType hasPrefix:@"NS"]) { id rel = class_createInstance(NSClassFromString(className), sizeof(unsigned)); Class theClass = [rel class]; if ([rel isKindOfClass:[DbObject class]]) { fieldValue = [rel init]; //Load the record... NSInteger Id = [rs intForColumn:[theClass relationName]]; if (Id>0) { [fieldValue release]; Db *db = [Db currentDb]; fieldValue = [db loadById: theClass theId:Id]; } } } else { NSString *error = [NSString stringWithFormat:@"Err Can't get value for field %@ of type %@", fieldName, fieldType]; NSLog(error); NSException *e = [NSException exceptionWithName:@"DBError" reason:error userInfo:nil]; @throw e; } } } return fieldValue; }

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  • Using UUIDs for cheap equals() and hashCode()

    - by Tom McIntyre
    I have an immutable class, TokenList, which consists of a list of Token objects, which are also immutable: @Immutable public final class TokenList { private final List<Token> tokens; public TokenList(List<Token> tokens) { this.tokens = Collections.unmodifiableList(new ArrayList(tokens)); } public List<Token> getTokens() { return tokens; } } I do several operations on these TokenLists that take multiple TokenLists as inputs and return a single TokenList as the output. There can be arbitrarily many TokenLists going in, and each can have arbitrarily many Tokens. These operations are expensive, and there is a good chance that the same operation (ie the same inputs) will be performed multiple times, so I would like to cache the outputs. However, performance is critical, and I am worried about the expense of performing hashCode() and equals() on these objects that may contain arbitrarily many elements (as they are immutable then hashCode could be cached, but equals will still be expensive). This led me to wondering whether I could use a UUID to provide equals() and hashCode() simply and cheaply by making the following updates to TokenList: @Immutable public final class TokenList { private final List<Token> tokens; private final UUID uuid; public TokenList(List<Token> tokens) { this.tokens = Collections.unmodifiableList(new ArrayList(tokens)); this.uuid = UUID.randomUUID(); } public List<Token> getTokens() { return tokens; } public UUID getUuid() { return uuid; } } And something like this to act as a cache key: @Immutable public final class TopicListCacheKey { private final UUID[] uuids; public TopicListCacheKey(TopicList... topicLists) { uuids = new UUID[topicLists.length]; for (int i = 0; i < uuids.length; i++) { uuids[i] = topicLists[i].getUuid(); } } @Override public int hashCode() { return Arrays.hashCode(uuids); } @Override public boolean equals(Object other) { if (other == this) return true; if (other instanceof TopicListCacheKey) return Arrays.equals(uuids, ((TopicListCacheKey) other).uuids); return false; } } I figure that there are 2^128 different UUIDs and I will probably have at most around 1,000,000 TokenList objects active in the application at any time. Given this, and the fact that the UUIDs are used combinatorially in cache keys, it seems that the chances of this producing the wrong result are vanishingly small. Nevertheless, I feel uneasy about going ahead with it as it just feels 'dirty'. Are there any reasons I should not use this system? Will the performance costs of the SecureRandom used by UUID.randomUUID() outweigh the gains (especially since I expect multiple threads to be doing this at the same time)? Are collisions going to be more likely than I think? Basically, is there anything wrong with doing it this way?? Thanks.

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  • Make c# matrix code faster

    - by Wam
    Hi all, Working on some matrix code, I'm concerned of performance issues. here's how it works : I've a IMatrix abstract class (with all matrices operations etc), implemented by a ColumnMatrix class. abstract class IMatrix { public int Rows {get;set;} public int Columns {get;set;} public abstract float At(int row, int column); } class ColumnMatrix : IMatrix { private data[]; public override float At(int row, int column) { return data[row + columns * this.Rows]; } } This class is used a lot across my application, but I'm concerned with performance issues. Testing only read for a 2000000x15 matrix against a jagged array of the same size, I get 1359ms for array access agains 9234ms for matrix access : public void TestAccess() { int iterations = 10; int rows = 2000000; int columns = 15; ColumnMatrix matrix = new ColumnMatrix(rows, columns); for (int i = 0; i < rows; i++) for (int j = 0; j < columns; j++) matrix[i, j] = i + j; float[][] equivalentArray = matrix.ToRowsArray(); TimeSpan totalMatrix = new TimeSpan(0); TimeSpan totalArray = new TimeSpan(0); float total = 0f; for (int iteration = 0; iteration < iterations; iteration++) { total = 0f; DateTime start = DateTime.Now; for (int i = 0; i < rows; i++) for (int j = 0; j < columns; j++) total = matrix.At(i, j); totalMatrix += (DateTime.Now - start); total += 1f; //Ensure total is read at least once. total = total > 0 ? 0f : 0f; start = DateTime.Now; for (int i = 0; i < rows; i++) for (int j = 0; j < columns; j++) total = equivalentArray[i][j]; totalArray += (DateTime.Now - start); } if (total < 0f) logger.Info("Nothing here, just make sure we read total at least once."); logger.InfoFormat("Average time for a {0}x{1} access, matrix : {2}ms", rows, columns, totalMatrix.TotalMilliseconds); logger.InfoFormat("Average time for a {0}x{1} access, array : {2}ms", rows, columns, totalArray.TotalMilliseconds); Assert.IsTrue(true); } So my question : how can I make this thing faster ? Is there any way I can make my ColumnMatrix.At faster ? Cheers !

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