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  • Best in-memory cache of DB objects for Silverlight [closed]

    - by Jon
    Hi, I'd like to set up a cache of database objects (i.e. rows in a table) in memory in silverlight, which I'll do using WCF and linq-to-sql. Once I have the objects in memory, I'm planning on using MSMQ to receive new objects whenever they have been modified. It's a somewhat complex approach but the goal is to reduce trips to the database and allow instant data communication between Silverlight applications that are connected to the MSMQ. My Silverlight applications are meant to be long-running and the amount of data to be cached will not be large. I'm planning on saving the in-memory cache using local storage. Anyway, in order to process the updated objects that come in, I'd like to know if the user has changed the existing object. Could I use some event relating to data-binding to set a flag indicating that the object has changes? Maybe there's a better way to do the cache entirely? Thanks!

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  • Complex knowledge management system with CRM..written internally

    - by JonH
    We've all heard of salesforce and sugarcrm and the likes of systems like this. Unfortunately at my workplace we have been asked to write a similiar system (rather then license or purchase). Basically the database is fairly large. Think of modules such as: Corporate groups, customers, programs, projects, sub projects, and issue management. In simple terms a corporate group has one to many customers. A program has one or more projects. A project has one or more sub projects. And an issue can be created on many sub projects. Of course the system is a bit more complex but instead of listing every single module I think its best to keep it simple. In any event, the system in its current state has only two resources to be working on it (basically we have to do it all: CSS, database, jquery, asp.net and C#). We've started off well by defining the UI master and footer pages that way we can reuse those across all of our pages. Now comes the hard part. The system will have about 4k end users with say 5-10% being concurrent users. We are wondering if it makes sense to cache our database data (For say 5-10 minutes) rather then continously hit our database. The reason being is some of these pages may have 5-10 search filters associated with the page. Imagine every time a selection is made from a search box how many database hits. Also some of these search fields cascade so selecting for instance an initial drop down may cascade several drop down boxes under them. Is it wrong to cache because I am not finding too many articles on whether it is a good idea or not. Remember the system is similiar to say a CRM system where we manage our various customers, projects, sub projects, issues, etc.

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  • Changing frontend cache

    - by Utsav
    Our architecture consists of a front-end cache that most read only users obtain their data from directly. The front-end cache sits in front of a farm of webservers that serve pages written in PHP. We need to be able to detect certain conditions at the front-end cache level and pass those values through to the back-end via HTTP headers. For example we would like to manually tag the carrier network based on the IP address. So, for incoming traffic if the user is say coming from an IP address in the range of "41.202.192.0"/19 we would tag them as being a Orange Cameroon user by setting the appropriate HTTP request header, e.g., X-Carrier = "Orange Cameroon". Based on the setting of this header we would like to vary the cache and serve a different banner to the end user. How would you go about doing this? Keep in mind that we don't want to pollute the cache and we also don't want to create too many small cache segments. Assumptions: You can assume that the X-Carrier has already been detected in our cache. So, for the purposes of your test you can just set this value manually in your example script.

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  • Writing low latency Java

    - by user997112
    Are there any Java-specific techniques (things which wouldnt apply to C++) for writing low latency code, in Java? I often see Java low latency roles and they ask for experience writing low latency Java- which sometimes seems a little bit of an oxymoron. The only think I could think of is experience with JNI, outsourcing I/O calls to native code. Also possibly using the disruptor pattern, but thats not an actual technology. Are there any Java specific tips for writing low latency code? I am aware there is a Real Time Java Spec, but I have been warned real-time is not the same as low latency....

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  • Interesting links week #9

    - by erwin21
    Below a list of interesting links that I found this week: Frontend: Subway Map Visualization jQuery Plugin Internet Explorer 9 Guide for Developers Development: Html Agility Pack Cache Integration - Building and Using Custom OutputCache Providers in ASP.NET Marketing: A/B testing applications Other: Top 10 Reasons Web Developers Should Avoid Flash Interested in more interesting links follow me at twitter http://twitter.com/erwingriekspoor

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  • Intel programming "performance" books? [closed]

    - by user997112
    I vaguely remember seeing that Intel have produced a few good books, especially with regards to low latency programming, but I cannot remember the titles. Could people suggest the titles of Intel books (or ones relating to Intel products)? Examples include books on: -Intel Compiler -Intel Assembler -Any low level programming on Intel assembler -The Intel CPU architecture -Intel threading blocks library

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  • What reasons are there to reduce the max-age of a logo to just 8 days? [closed]

    - by callum
    Most websites set max-age=31536000 (1 year) on the Cache-control headers of static assets such as logo images. Examples: YouTube Yahoo Twitter BBC But there is a notable exception: Google's logo has max-age=691200 (8 days). I've checked the headers on the Google logo in the past, and it definitely used to be 1 year. (Also, it used to be part of a sprite, and now it is a standalone logo image, but that's probably another question...) What could be valid technical reasons why they would want to reduce its cache lifetime to just 8 days? Google's homepage is one of the most carefully optimised pages in the world, so I imagine there's a good reason. Edit: Please make sure you understand these points before answering: Nobody uses short max-age lifetimes to allow modifying a static asset in future. When you modify it, you just serve it at a different URL. So no, it's nothing to do with Google doodles. Think about it: even if Google didn't understand this basic trick of HTTP, 8 days still wouldn't be appropriate, as only those users who don't have the original logo cached would see the doodle on doodle-day – and then that group of users would go on seeing the doodle for the following 8 days after Google changed it back :) Web servers do not worry about "filling up" the caches of clients (or proxies). The client manages this by itself – when it hits its own storage limit, it just starts dropping the lowest priority items to make space for new items. The priority score is based on the question "How likely am I to benefit from having cached this URL?", which is nothing to do with what max-age value the server sent when the URL was originally requested; it's a heuristic based on the "frecency" of requests for that URL. The max-age simply lets the server set a cut-off point – the time at which the client is supposed to discard the item regardless of how often it's being re-used. It would be very nice and trusting of a downstream client/proxy to rely on all origin servers "holding back" from filling up their caches, but I don't think we live in that world ;)

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  • Android application Database Framework

    - by Marek Sebera
    When creating mobile (specially Android) application, I usually come to touch with similar pattern of working with data. Usually I need to fetch some remote data (covered by authorization process) to local cache. And on next request: Check networking Check presence of cache file Check version of cache file (if networking) Get new version and save cache (if networking and file not in cache, or outdated) Data store is no-SQL JSON Document-Based (and yes, I know about CouchDB Android version, but it doesn't fit my needs yet.) Process of authorizing to data source and code for check version of local cache is adapted to application. But the other code (handling network, saving cache, handling exceptions,...) is always the same. Is there any Data Store helper I can use, which provides functions I described above?

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  • How can I best implement 'cache until further notice' with memcache in multiple tiers?

    - by ajreal
    the term "client" used here is not referring to client's browser, but client server Before cache workflow 1. client make a HTTP request --> 2. server process --> 3. store parsed results into memcache for next use (cache indefinitely) --> 4. return results to client --> 5. client get the result, store into client's local memcache with TTL After cache workflow 1. another client make a HTTP request --> 2. memcache found return memcache results to client --> 3. client get the result, store into client's local memcache with TTL TTL = time to live Is possible for me to know when the data was updated, and to expire relevant memcache(s) accordingly. However, the pitfalls on client site cache TTL Any data update before the TTL is not pick-up by client memcache. In reverse manner, where there is no update, client memcache still expire after the TTL First request (or concurrent requests) after cache TTL will get throttle as it need to repeat the "Before cache workflow" In the event where client require several HTTP requests on a single web page, it could be very bad in performance. Ideal solution should be client to cache indefinitely until further notice. Here are the three proposals about futher notice Proposal 1 : Make use on HTTP header (current implementation) 1. client sent HTTP request last modified time header 2. server check if last data modified time=last cache time return status 304 3. client based on header to decide further processing GOOD? ---- - save some parsing for client - lesser data transfer BAD? ---- - fire a HTTP request is still slow - server end still need to process lots of requests Proposal 2 : Consistently issue a HTTP request to check all data group last modified time 1. client fire a HTTP request 2. server to return last modified time for all data group 3. client compare local last cache time with the result 4. if data group last cache time < server last modified time then request again for that data group only GOOD? ---- - only fetch what is no up-to-date - less requests for server BAD? ---- - every web page require a HTTP request Proposal 3 : Tell client when new data is available (Push) 1. when server end notice there is a change on a data group 2. notify clients on the changes 3. help clients to fetch again data 4. then reset client local memcache after data is parsed GOOD? ---- - let the cache act/behave like a true cache BAD? ---- - encourage race condition My preference is on proposal 3, and something like Gearman could be ideal Where there is a change, Gearman server to sent the task to multiple clients (workers). Am I crazy? (I know my first question is a bit crazy)

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  • Why is facebook cache buggy?

    - by IAdapter
    I just started using facebook and I see that many times when I add something to my profile and visit it later its not there. I bet the reason is that the page is cached and not updated very often. Is this on purpose or is it a bug? P.S. For example I added the music I like and later I see that I did not add it, but next day when I visit again its there. I saw it in two web-browsers, so its a facebook bug. Does it has something to do with scalability?

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  • Are HTTP requests cached? [closed]

    - by nischayn22
    Many HTTP requests are sent repeatedly by browsers on almost every page load, such as requesting the jQuery .js file etc. Since these are already used on too many sites doesn't modern browsers keep a cache for this? I am thinking of a system where the browser has a cached copy of the .js file used very very frequently. On a new request for the .js file, it sends the server a request for a hash of the .js file (provided the server can reply to that) and compares the returned hash with the cached copy's hash... rest is intuitive.

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  • Distributed cache and improvement

    - by philipl
    Have this question from interview: Web Service function given x static HashMap map (singleton created) if (!map.containsKey(x)) { perform some function to retrieve result y map.put(x, y); } return y; The interviewer asked general question such as what is wrong with this distributed cache implementation. Then asked how to improve on it, due to distributed servers will have different cached key pairs in the map. There are simple mistakes to be pointed out about synchronization and key object, but what really startled me was that this guy thinks that moving to database implementation solves the problem that different servers will have different map content, i.e., the situation when value x is not on server A but on server B, therefore redundant data has to be retrieved in server A. Does his thinking make any sense? (As I understand this is the basic cons for distributed cache against database model, seems he does not understand it at all) What is the typical solution for the cache growth issue (weak reference?) and sync issue (do not know which server has the key already cached - use load balancing)? Thanks

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  • Is the UX affected negatively by fully cacheable pages?

    - by ChocoDeveloper
    I want to have fully cacheable pages in my websites, but one cannot do that if they contain user-specific data, like the userbar or things in the UI that can change depending on the permissions the user has. So I was thinking whether it was possible to pull everything that is user-specific via ajax, and update the UI accordingly. But I'm worried that this might be annoying for the user, and also it might be difficult to develop. What do you think? Is there a pattern or something I can follow to deal with this?

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  • Random Cache Expiry

    - by mahemoff
    I've been experimenting with random cache expiry times to avoid situations where an individual request forces multiple things to update at once. For example, a web page might include five different components. If each is set to time out in 30 minutes, the user will have a long wait time every 30 minutes. So instead, you set them all to a random time between 15 and 45 minutes to make it likely at most only one component will reload for any given page load. I'm trying to find any research or guidelines on this topic, e.g. optimal variance parameters. I do recall seeing one article about how Google (?) uses this technique, but can't locate it, and there doesn't seem to be much written about the topic.

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  • Django: making raw SQL query, passing multiple/repeated params?

    - by AP257
    Hopefully this should be a fairly straightforward question, I just don't know enough about Python and Django to answer it. I've got a raw SQL query in Django that takes six different parameters, the first two of which (centreLat and centreLng) are each repeated: query = "SELECT units, (SQRT(((lat-%s)*(lat-%s)) + ((lng-%s)*(lng-%s)))) AS distance FROM places WHERE lat<%s AND lat>%s AND lon<%s AND lon>%s ORDER BY distance;" params = [centreLat,centreLng,swLat,neLat,swLng,neLng] places = Place.objects.raw(query, params) How do I structure the params object and the query string so they know which parameters to repeat and where?

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  • In Django, can you add a method to querysets?

    - by Paul D. Waite
    In Django, if I have a model class, e.g. from django.db import models class Transaction(models.Model): ... then if I want to add methods to the model, to store reasonably complex filters, I can add a custom model manager, e.g. class TransactionManager(models.Manager): def reasonable_complex_filter(self): return self.get_query_set().filter(...) class Transaction(models.Model): objects = TransactionManager() And then I can do: >>> Transaction.objects.reasonably_complex_filter() Is there any way I can add a custom method that can be chained to the end of a query set from the model? I.e. add the custom method in such a way that I can do this: >>> Transaction.objects.filter(...).reasonably_complex_filter()

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  • Django custom SQL returning single row of results when query returns 2?

    - by Alvin
    I have a custom SQL call that is returning different results to the template than I get when I run the same query against the database directly, 1 row vs 2 Query - copied from Django Debug Toolbar: SELECT ((Sum(new_recruit_interviews) / Sum(opportunities_offered)) * 100) as avg_recruit, ((Sum(inspections) / Sum(presentations)) * 100) as avg_inspect, ((Sum(contracts_signed) / Sum(roof_approvals)) * 100) as avg_contracts, ((Sum(adjusters) / Sum(contracts_signed)) * 100) as avg_adjusters, ((Sum(roof_approvals) / Sum(adjusters)) *100) as roof_approval_avg, ((Sum(roof_turned_in) / Sum(adjusters)) * 100) as roof_jobs_avg, Sum(roof_turned_in) as roof_jobs_total, ((Sum(siding_approvals) / Sum(adjusters)) *100) as siding_approval_avg, ((Sum(siding_turned_in) / Sum(adjusters)) * 100) as siding_jobs_avg, Sum(siding_turned_in) as siding_jobs_total, ((Sum(gutter_approvals) / Sum(adjusters)) *100) as gutter_approval_avg, ((Sum(gutter_turned_in) / Sum(adjusters)) * 100) as gutter_jobs_avg, Sum(gutter_turned_in) as gutter_jobs_total, ((Sum(window_approvals) / Sum(adjusters)) *100) as window_approval_avg, ((Sum(window_turned_in) / Sum(adjusters)) * 100) as window_jobs_avg, Sum(window_turned_in) as window_jobs_total, (Sum(roof_turned_in) + Sum(siding_turned_in) + Sum(gutter_turned_in) + Sum(window_turned_in)) as total_jobs, (((Sum(collections_jobs_new) + Sum(collections_jobs_previous)) / (Sum(roof_turned_in) + Sum(siding_turned_in) + Sum(gutter_turned_in) + Sum(window_turned_in))) * 100) as total_collections, sales_report_salesmen.location_id as detail_id, business_unit_location.title as title FROM sales_report_salesmen Inner Join auth_user ON sales_report_salesmen.user_id = auth_user.id Inner Join business_unit_location ON sales_report_salesmen.location_id = business_unit_location.id GROUP BY location_id Results from direct query running the above query: INSERT INTO `` (`avg_recruit`, `avg_inspect`, `avg_contracts`, `avg_adjusters`, `roof_approval_avg`, `roof_jobs_avg`, `roof_jobs_total`, `siding_approval_avg`, `siding_jobs_avg`, `siding_jobs_total`, `gutter_approval_avg`, `gutter_jobs_avg`, `gutter_jobs_total`, `window_approval_avg`, `window_jobs_avg`, `window_jobs_total`, `total_jobs`, `total_collections`, `detail_id`, `title`) VALUES (95.3968, 92.8178, 106.9622, 90.2928, 103.5420, 103.5670, 4152, 100.2494, 106.8845, 4285, 120.1297, 86.2559, 3458, 92.9658, 106.1611, 4256, 16151, 4.281469, 12, 'St Paul, MN'); VALUES (90.2982, 73.3723, 97.8474, 104.5433, 97.7585, 86.1848, 1884, 109.9268, 109.3321, 2390, 81.0156, 96.4318, 2108, 91.7200, 123.8792, 2708, 9090, 4.531573, 13, 'Denver, CO'); Results from template: {'roof_jobs_total': Decimal('4152'), 'gutter_jobs_total': Decimal('3458'), 'avg_adjusters': Decimal('90.2928'), 'title': u'St Paul, MN', 'window_approval_avg': Decimal('92.9658'), 'total_collections': Decimal('4.281469'), 'gutter_approval_avg': Decimal('120.1297'), 'avg_recruit': Decimal('95.3968'), 'siding_approval_avg': Decimal('100.2494'), 'window_jobs_total': Decimal('4256'), 'detail_id': 12L, 'siding_jobs_avg': Decimal('106.8845'), 'avg_inspect': Decimal('92.8178'), 'roof_approval_avg': Decimal('103.5420'), 'roof_jobs_avg': Decimal('103.5670'), 'total_jobs': Decimal('16151'), 'window_jobs_avg': Decimal('106.1611'), 'avg_contracts': Decimal('106.9622'), 'gutter_jobs_avg': Decimal('86.2559'), 'siding_jobs_total': Decimal('4285')} Tried tweaking it a few ways and running the results through various for loops, keep getting the same result where my results are a single row through the Django template and the expected results (through console) have 2 rows The row that is coming back is the same as the first row returned through the console query so I'm thinking that it is running correctly just a matter of passing the results through... for good measure this is the code I'm using to generate the query (yes it's a bit ugly, been playing with it) def sql_grouped(table, fields, group_by=False, where=False): from django.db import connection query = 'SELECT %s FROM %s' % (fields, table) if where: query = query + ' WHERE %s' % (where) if group_by: query = query + ' GROUP BY %s' % (group_by) cursor = connection.cursor() cursor.execute(query) desc = cursor.description data = [dict(zip([col[0] for col in desc], row)) for row in cursor.fetchall()] return data[0] any feedback is greatly appreciated - been tinkering with this since I realized I could skip a few steps by generating my averages directly within the SQL rather than post-process

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  • How to create a custom admin configuration panel in Django?

    - by Matteo
    Hi, I would like to create a configuration panel for the homepage of the web-app I'm designing with Django. This configuration panel should let me choose some basic options like highlighting some news, setting a showcase banner, and so on. Basically I don't need an app with different rows, but just a panel page with some configuration options. The automatically generated administration area created by Django doesn't seem to handle this feature as far as I can see, so I'm asking you for some directions. Any hint is highly appreciated. Thank you in advance. Matteo

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  • How do I perform a batch insert in Django?

    - by Thierry Lam
    In mysql, you can insert multiple rows to a table in one query for n 0: INSERT INTO tbl_name (a,b,c) VALUES(1,2,3),(4,5,6),(7,8,9), ..., (n-2, n-1, n); Is there a way to achieve the above with Django queryset methods? Here's an example: values = [(1, 2, 3), (4, 5, 6), ...] for value in values: SomeModel.objects.create(first=value[0], second=value[1], third=value[2]) I believe the above is calling an insert query for each iteration of the for loop. I'm looking for a single query, is that possible in Django?

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  • How do I do this Database Model in Django?

    - by alex
    Django currently does not support the "Point" datatype in MySQL. That's why I created my own. class PointField(models.Field): def db_type(self): return 'Point' class Tag(models.Model): user = models.ForeignKey(User) utm = PointField() As you can see, this works, and syncdb creates the model fine. However, my current code calculates a length between two Points using raw SQL. cursor.execute("SELECT user_id FROM life_tag WHERE\ (GLength(LineStringFromWKB(LineString(asbinary(utm), asbinary(PointFromWKB(point(%s, %s)))))) < 55)... This says: Select where the length between the given point and the table point is less than 55. How can I do this with Django instead of RAW SQL? I don't want to do cursors and SELECT statements anymore. How can I modify the models.py in order to do this?

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  • When I run Django on Dreamhost using SQLite, why do I get an OperationalError telling me that a tabl

    - by Paul D. Waite
    I had a Django site running on Dreamhost. Although I used SQLite when developing locally, I initially used MySQL on Dreamhost, because that’s what the wiki page said to do, and because if I’m using an ORM, I might as well take advantage of it by running against a different database. After a while, I switched the settings on the server to use SQLite, to make it easier to keep my development database in sync with the server one. python manage.py syncdb worked on the server, but when I tried to access the site, I got an OperationalError. The Django error page said that one of my tables didn’t exist. I checked the database using sqlite on the command line on the server, and using python manage.py shell, and both worked fine.

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  • In Django : How to serialize dict object to json ?

    - by Rohit
    I have this very basic problem, >>> serializers.serialize("json", {'a':1}) Traceback (most recent call last): File "<console>", line 1, in <module> File "/usr/lib/pymodules/python2.6/django/core/serializers/__init__.py", line 87, in serialize s.serialize(queryset, **options) File "/usr/lib/pymodules/python2.6/django/core/serializers/base.py", line 40, in serialize for field in obj._meta.local_fields: AttributeError: 'str' object has no attribute '_meta' >>> How can this be done ? Thanks in advance !

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  • Django with custom authentication backends, is Csrf middleware really required ?

    - by Hellnar
    Hello, Under Django 1.1.1, I am using several authentication backends such as social-registration for facebook connect and django-emailauth for email based authentication instead of user names. I am curious if the Csrf middleware is an essential security measure as it seems like it sometimes generates problems, especially with facebook connect. My project is rather simple. Each user have a profile which they can fill and a purchase page where they fill the payment for to do purchases. Either of these pages are protected via @login_required.

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  • [Django] How to find out whether a model's column is a foreign key?

    - by codethief
    I'm dynamically storing information in the database depending on the request: // table, id and column are provided by the request table_obj = getattr(models, table) record = table_obj.objects.get(pk=id) setattr(record, column, request.POST['value']) The problem is that request.POST['value'] sometimes contains a foreign record's primary key (i.e. an integer) whereas Django expects the column's value to be an object of type ForeignModel: Cannot assign "u'122'": "ModelA.b" must be a "ModelB" instance. Now, is there an elegant way to dynamically check whether b is a column containing foreign keys and what model these keys are linked to? (So that I can load the foreign record by it's primary key and assign it to ModelA?) Or doesn't Django provide information like this to the programmer so I really have to get my hands dirty and use isinstance() on the foreign-key column?

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