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• how much more memcache memory do i need to get 95% hit ratio? [on hold]

  - by OneSolitaryNoob

  I have a memcache instance running that has a 90% hit ratio. How can I estimate how much more memory it needs to get to a 95% hit ratio? edit: This question was blocked, but I do not think this is impossible to answer. After all, anyone that's used a caching system HAS answered this question, most likely with trial&error&luck. I can look at my usage patterns. I can increase or decrease memory and see how hit rate changes. Both of these provide data that informs an estimate. But what's a good/better/best way to do this?

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• How do I tell memcache to ignore the django admin page?

  - by Chris

  I'm running memcache infront of django without any explicit configuration in my code. I.e. nothing more than MIDDLEWARE_CLASSES = ( 'django.middleware.cache.UpdateCacheMiddleware', ... 'django.middleware.cache.FetchFromCacheMiddleware', ) and CACHE_BACKEND = 'memcached://127.0.0.1:11211/' in my settings.py. This works great, in fact so great that it's caching my admin page leaving me no way to moderate live actions on the site until the cache refetches the data. Is there a regex I can throw somewhere to let memcached know to leave my admin page alone? (I'm also using nginx and gunicorn)

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• High-concurrency counters without sharding

  - by dound

  This question concerns two implementations of counters which are intended to scale without sharding (with a tradeoff that they might under-count in some situations): http://appengine-cookbook.appspot.com/recipe/high-concurrency-counters-without-sharding/ (the code in the comments) http://blog.notdot.net/2010/04/High-concurrency-counters-without-sharding My questions: With respect to #1: Running memcache.decr() in a deferred, transactional task seems like overkill. If memcache.decr() is done outside the transaction, I think the worst-case is the transaction fails and we miss counting whatever we decremented. Am I overlooking some other problem that could occur by doing this? What are the significiant tradeoffs between the two implementations? Here are the tradeoffs I see: #2 does not require datastore transactions. To get the counter's value, #2 requires a datastore fetch while with #1 typically only needs to do a memcache.get() and memcache.add(). When incrementing a counter, both call memcache.incr(). Periodically, #2 adds a task to the task queue while #1 transactionally performs a datastore get and put. #1 also always performs memcache.add() (to test whether it is time to persist the counter to the datastore). Conclusions (without actually running any performance tests): #1 should typically be faster at retrieving a counter (#1 memcache vs #2 datastore). Though #1 has to perform an extra memcache.add() too. However, #2 should be faster when updating counters (#1 datastore get+put vs #2 enqueue a task). On the other hand, with #1 you have to be a bit more careful with the update interval since the task queue quota is almost 100x smaller than either the datastore or memcahce APIs.

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• How do I reconnect to Memcache when forking in rails?

  - by Daniel Huckstep

  I have a rails 3 application, and a script called by rails runner. This script forks and does some stuff in other processes. I do the proper thing with ActiveRecord before forking, where I disconnect-fork-reconnect and all that jazz. My question is I also use memcache for the Rails.cache but should I be disconnecting-reconnecting that too for my forks? If so, how would I go about that in the rails way.

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• Is it possible to store a resource in memcache?

  - by Chad Johnson

  I have not tried yet, as I would rather not spend time setting up memcached if this is not going to work... I am using Ruby. Is is possible to store a resource, such as an FTP connection, in memcache?

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• Rails.cache throws "marshal dump" error when changed from memory store to memcached store

  - by gsmendoza

  If I set this in my environment config.action_controller.cache_store = :mem_cache_store ActionController::Base.cache_store will use a memcached store but Rails.cache will use a memory store instead: $ ./script/console >> ActionController::Base.cache_store => #<ActiveSupport::Cache::MemCacheStore:0xb6eb4bbc @data=<MemCache: 1 servers, ns: nil, ro: false>> >> Rails.cache => #<ActiveSupport::Cache::MemoryStore:0xb78b5e54 @data={}> In my app, I use Rails.cache.fetch(key){ object } to cache objects inside my helpers. All this time, I assumed that Rails.cache uses the memcached store so I'm surprised that it uses memory store. If I change the cache_store setting in my environment to config.cache_store = :mem_cache_store both ActionController::Base.cache_store and Rails.cache will now use the same memory store, which is what I expect: $ ./script/console >> ActionController::Base.cache_store => #<ActiveSupport::Cache::MemCacheStore:0xb7b8e928 @data=<MemCache: 1 servers, ns: nil, ro: false>, @middleware=#<Class:0xb7b73d44>, @thread_local_key=:active_support_cache_mem_cache_store_local_cache> >> Rails.cache => #<ActiveSupport::Cache::MemCacheStore:0xb7b8e928 @data=<MemCache: 1 servers, ns: nil, ro: false>, @middleware=#<Class:0xb7b73d44>, @thread_local_key=:active_support_cache_mem_cache_store_local_cache> However, when I run the app, I get a "marshal dump" error in the line where I call Rails.cache.fetch(key){ object } no marshal_dump is defined for class Proc Extracted source (around line #1): 1: Rails.cache.fetch(fragment_cache_key(...), :expires_in => 15.minutes) { ... } vendor/gems/memcache-client-1.8.1/lib/memcache.rb:359:in 'dump' vendor/gems/memcache-client-1.8.1/lib/memcache.rb:359:in 'set_without_newrelic_trace' What gives? Is Rails.cache meant to be a memory store? Should I call controller.cache_store.fetch in the places where I call Rails.cache.fetch?

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• Rails - difference between config.cache_store and config.action_controller.cache_store?

  - by gsmendoza

  If I set this in my environment config.action_controller.cache_store = :mem_cache_store ActionController::Base.cache_store will use a memcached store but Rails.cache will use a memory store instead: $ ./script/console >> ActionController::Base.cache_store => #<ActiveSupport::Cache::MemCacheStore:0xb6eb4bbc @data=<MemCache: 1 servers, ns: nil, ro: false>> >> Rails.cache => #<ActiveSupport::Cache::MemoryStore:0xb78b5e54 @data={}> In my app, I use Rails.cache.fetch(key){ object } to cache objects inside my helpers. All this time, I assumed that Rails.cache uses the memcached store so I'm surprised that it uses memory store. If I change the cache_store setting in my environment to config.cache_store = :mem_cache_store both ActionController::Base.cache_store and Rails.cache will now use the same memory store, which is what I expect: $ ./script/console >> ActionController::Base.cache_store => #<ActiveSupport::Cache::MemCacheStore:0xb7b8e928 @data=<MemCache: 1 servers, ns: nil, ro: false>, @middleware=#<Class:0xb7b73d44>, @thread_local_key=:active_support_cache_mem_cache_store_local_cache> >> Rails.cache => #<ActiveSupport::Cache::MemCacheStore:0xb7b8e928 @data=<MemCache: 1 servers, ns: nil, ro: false>, @middleware=#<Class:0xb7b73d44>, @thread_local_key=:active_support_cache_mem_cache_store_local_cache> However, when I run the app, I get a "marshal dump" error in the line where I call Rails.cache.fetch(key){ object } no marshal_dump is defined for class Proc Extracted source (around line #1): 1: Rails.cache.fetch(fragment_cache_key(...), :expires_in => 15.minutes) { ... } vendor/gems/memcache-client-1.8.1/lib/memcache.rb:359:in 'dump' vendor/gems/memcache-client-1.8.1/lib/memcache.rb:359:in 'set_without_newrelic_trace' What gives? Is Rails.cache meant to be a memory store? Should I call controller.cache_store.fetch in the places where I call Rails.cache.fetch?

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• Efficiently Serving Dynamic Content in Google App Engine

  - by awegawef

  My app on google app engine returns content items (just text) and comments on them. It works like this (pseudo-ish code): query: get keys of latest content #query to datastore for each item in content if item_dict in memcache: use item_dict else: build_item_dict(item) #by fetching from datastore store item_dict in memcache send all item_dicts to template Sorry if the code isn't understandable. I get all of the content dictionaries and send them to the template, which uses them to create the webpage. My problem is that if the memcache has expired, for each item I want to display, I have to (1) lookup item in memcache, (2) since no memcache exists I must fetch item from the datastore, and (3) store the item in memcache. These calls build up quickly. I don't set an expire time for the entries to the memcache, so this really only happens once in the morning, but the webpage takes long enough to load (~1 sec) that the browser reports it as not existing. Regularly, my webpages take about 50ms to load. This approach works decently for frequent visits, but it has its flaws as shown above. How can I remedy this? The entries are dynamic enough that I don't think it would be in my best interest to cache my initial request. Thanks in advance

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• Memcache Error? "Could not find specified socket in poll list."

  - by Benno

  For some reason recently I've been getting this error in my apache error log on my server. We have a single instance of memcached running on our Mac OSX 10.7 server. (20014)Internal error: Unknown memcached error while writing: Could not find specified socket in poll list. I can't find anything about this error message online :. Does anyone have any idea what could cause it or how I can try debugging it? There's a memcached-tools(?) function on linux, but it doesn't seem to be on the Mac...

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• Slow Memcached: Average 10ms memcached `get`

  - by Chris W.

  We're using Newrelic to measure our Python/Django application performance. Newrelic is reporting that across our system "Memcached" is taking an average of 12ms to respond to commands. Drilling down into the top dozen or so web views (by # of requests) I can see that some Memcache get take up to 30ms; I can't find a single use of Memcache get that returns in less than 10ms. More details on the system architecture: Currently we have four application servers each of which has a memcached member. All four memcached members participate in a memcache cluster. We're running on a cloud hosting provider and all traffic is running across the "internal" network (via "internal" IPs) When I ping from one application server to another the responses are in ~0.5ms Isn't 10ms a slow response time for Memcached? As far as I understand if you think "Memcache is too slow" then "you're doing it wrong". So am I doing it wrong? Here's the output of the memcache-top command: memcache-top v0.7 (default port: 11211, color: on, refresh: 3 seconds) INSTANCE USAGE HIT % CONN TIME EVICT/s GETS/s SETS/s READ/s WRITE/s cache1:11211 37.1% 62.7% 10 5.3ms 0.0 73 9 3958 84.6K cache2:11211 42.4% 60.8% 11 4.4ms 0.0 46 12 3848 62.2K cache3:11211 37.5% 66.5% 12 4.2ms 0.0 75 17 6056 170.4K AVERAGE: 39.0% 63.3% 11 4.6ms 0.0 64 13 4620 105.7K TOTAL: 0.1GB/ 0.4GB 33 13.9ms 0.0 193 38 13.5K 317.2K (ctrl-c to quit.) ** Here is the output of the top command on one machine: ** (Roughly the same on all cluster machines. As you can see there is very low CPU utilization, because these machines only run memcache.) top - 21:48:56 up 1 day, 4:56, 1 user, load average: 0.01, 0.06, 0.05 Tasks: 70 total, 1 running, 69 sleeping, 0 stopped, 0 zombie Cpu(s): 0.0%us, 0.0%sy, 0.0%ni, 99.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.3%st Mem: 501392k total, 424940k used, 76452k free, 66416k buffers Swap: 499996k total, 13064k used, 486932k free, 181168k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 6519 nobody 20 0 384m 74m 880 S 1.0 15.3 18:22.97 memcached 3 root 20 0 0 0 0 S 0.3 0.0 0:38.03 ksoftirqd/0 1 root 20 0 24332 1552 776 S 0.0 0.3 0:00.56 init 2 root 20 0 0 0 0 S 0.0 0.0 0:00.00 kthreadd 4 root 20 0 0 0 0 S 0.0 0.0 0:00.00 kworker/0:0 5 root 20 0 0 0 0 S 0.0 0.0 0:00.02 kworker/u:0 6 root RT 0 0 0 0 S 0.0 0.0 0:00.00 migration/0 7 root RT 0 0 0 0 S 0.0 0.0 0:00.62 watchdog/0 8 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 cpuset 9 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 khelper ...output truncated...

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• Multiple memcached servers question.

  - by Andre

  hypothetically - if I have multiple memcached servers like this: //PHP $MEMCACHE_SERVERS = array( "10.1.1.1", //web1 "10.1.1.2", //web2 "10.1.1.3", //web3 ); $memcache = new Memcache(); foreach($MEMCACHE_SERVERS as $server){ $memcache->addServer ( $server ); } And then I set data like this: $huge_data_for_frong_page = 'some data blah blah blah'; $memcache->set("huge_data_for_frong_page", $huge_data_for_frong_page); And then I retrieve data like this: $huge_data_for_frong_page = $memcache->get("huge_data_for_frong_page"); When i would to retrieve this data from memcached servers - how would php memcached client know which server to query for this data? Or is memcached client going to query all memcached servers?

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• What is the best way to create a running integer id on the AppEngine data storage?

  - by Freed

  For various reasons, I need a unique running integer id for my entities stored on the Google AppEngine. The automatically generated key sort of has this behaviour, but it doesn't start from 1 (or 0) and doesn't guarantee that the generated integer part will come from a continuous sequence. What would be the best way to efficiently implement this on AppEngine? Is there any support from the storage system? To add to the complexity, I might need to do this over entities from different entity groups, meaning I can't just get the highest id right now and save an entity with the next id in a transaction. Might memcache be the way to go..? Edit: I havn't yet implemented this, but to clarify on the memcache idea. I know memcache is unreliable, but in practice it probably won't lose data "too often" to hurt performance. Basically, I would have a memcache entry for the last used id, update it (somehow atomically) whenever I create a new entity and use that id. In the case of memcache not having a value for this entry, I'd get the highest id so far by doing a query on my entities sorted by the id and update memcache (unless someone else had already done so). The only problem I can see with this right now would be atomicity of the operation as a whole if the save of my new entity was also part of a transaction. Thoughts..?

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• Loading datasets from datastore and merge into single dictionary. Resource problem.

  - by fredrik

  Hi, I have a productdatabase that contains products, parts and labels for each part based on langcodes. The problem I'm having and haven't got around is a huge amount of resource used to get the different datasets and merging them into a dict to suit my needs. The products in the database are based on a number of parts that is of a certain type (ie. color, size). And each part has a label for each language. I created 4 different models for this. Products, ProductParts, ProductPartTypes and ProductPartLabels. I've narrowed it down to about 10 lines of code that seams to generate the problem. As of currently I have 3 Products, 3 Types, 3 parts for each type, and 2 languages. And the request takes a wooping 5500ms to generate. for product in productData: productDict = {} typeDict = {} productDict['productName'] = product.name cache_key = 'productparts_%s' % (slugify(product.key())) partData = memcache.get(cache_key) if not partData: for type in typeData: typeDict[type.typeId] = { 'default' : '', 'optional' : [] } ## Start of problem lines ## for defaultPart in product.defaultPartsData: for label in labelsForLangCode: if label.key() in defaultPart.partLabelList: typeDict[defaultPart.type.typeId]['default'] = label.partLangLabel for optionalPart in product.optionalPartsData: for label in labelsForLangCode: if label.key() in optionalPart.partLabelList: typeDict[optionalPart.type.typeId]['optional'].append(label.partLangLabel) ## end problem lines ## memcache.add(cache_key, typeDict, 500) partData = memcache.get(cache_key) productDict['parts'] = partData productList.append(productDict) I guess the problem lies in the number of for loops is too many and have to iterate over the same data over and over again. labelForLangCode get all labels from ProductPartLabels that match the current langCode. All parts for a product is stored in a db.ListProperty(db.key). The same goes for all labels for a part. The reason I need the some what complex dict is that I want to display all data for a product with it's default parts and show a selector for the optional one. The defaultPartsData and optionaPartsData are properties in the Product Model that looks like this: @property def defaultPartsData(self): return ProductParts.gql('WHERE __key__ IN :key', key = self.defaultParts) @property def optionalPartsData(self): return ProductParts.gql('WHERE __key__ IN :key', key = self.optionalParts) When the completed dict is in the memcache it works smoothly, but isn't the memcache reset if the application goes in to hibernation? Also I would like to show the page for first time user(memcache empty) with out the enormous delay. Also as I said above, this is only a small amount of parts/product. What will the result be when it's 30 products with 100 parts. Is one solution to create a scheduled task to cache it in the memcache every hour? It this efficient? I know this is alot to take in, but I'm stuck. I've been at this for about 12 hours straight. And can't figure out a solution. ..fredrik

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• php info not effect when edit value in php.ini on nginx webserver

  - by khoanhd

  I've already installed php, fcgi, nginx, the system running as no problem, but the problem happen when: I update memory_limit in php.ini, then restart php-cgi, nginx, but when use phpinfo, theo memory_limit is not effected. I install 2 new extensions: curl and memcache, add 2 lines: extension=curl.so and extension=memcache.so, restart php-cgi and nginx, phpinfo also not show up the value curl and memcache in phpinfo. So, how should i do?Please help me.

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• memcached and PHP ... massive lag with sessions

  - by Ben Dauphinee

  I'm working on a new server built with Unbuntu 10.04, running php-fastcgi, nginx, and memcached. phpinfo() script loads and works great, same as a test memcached script. For any script using sessions, page load time rockets through the roof. --- memcached.ini --- extension=memcached.so memcache.hash_strategy = "consistent" memcache.max_failover_attempts = 100 memcache.allow_failover = 1 session.save_handler = memcached session.save_path = "tcp://127.0.0.1:11211?persistent=1&weight=1&timeout=1&retry_interval=15" Let me know if you need to see any other configs.

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• php_memcache.dll for PHP 5.3

  - by whobutsb

  Hello all, I recently setup a server using the latest version of XAMPP for Windows. With it came PHP 5.3. I'm now looking for a memcache.dll file that works with PHP 5.3 I've used some of the previous .dll files and recieved an error message: "PHP Startup: memcache: Unable t initialize module. Module compiled with module API=20060613 PHP compiled with module api=20090626 These options need to match" Any links to a PHP 5.3 memcache.dll file would be greatly appreciated. Thanks for the help!

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• Failed to save data at the server from memcached program

  - by zahir hussain

  hi i want to know why i cant store multi dimensional(array size is more than 1000) $memcache = new Memcache; $memcache->connect('localhost', 11211) or die ("Could not connect"); the above s working correctly... the below one have error... $memcache->set('key', $sear, false, 60) or die ("Failed to save data at the server"); if the $sear is string or object array then no problem for store data at the server.. but i store multi dimensional array in memcached,,i will get the error is Failed to save data at the server thanks and advance

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• AppEngine: how do cursors work?

  - by victor a.k.a. python for ever

  hello, i have the following code def get(self): date = datetime.date.today() loc_query = Location.all() last_cursor = memcache.get('location_cursor') if last_cursor: loc_query.with_cursor(last_cursor) loc_result = loc_query.fetch(1) for loc in loc_result: self.record(loc, date) taskqueue.add( url='/task/query/simplegeo', params={'date':date, 'locid':loc.key().id()} ) if len(loc_result): memcache.add('location_cursor', loc_query.cursor()) taskqueue.add(url='/task/count/', method='GET') else: memcache.add('location_cursor', None) i don't know what i'm doing wrong, but i am getting the same cursor which is not the effect i wanted. why isn't the cursor moving?

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• memcached: which is faster, doing an add (and checking result), or doing a get (and set when returni

  - by Mike Sherov

  The title of this question isn't so clear, but the code and question is straightforward. Let's say I want to show my users an ad once per day. To accomplish this, every time they visit a page on my site, I check to see if a certain memcache key has any data stored on it. If so, don't show an ad. If not, store the value '1' in that key with an expiration of 86400. I can do this 2 ways: //version a $key='OPD_'.date('Ymd').'_'.$type.'_'.$user; if($memcache->get($key)===false){ $memcache->set($key,'1',false,$expire); //show ad } //version b $key='OPD_'.date('Ymd').'_'.$type.'_'.$user; if($memcache->add($key,'1',false,$expire)){ //show ad } Now, it might seem obvious that b is better, it always makes 1 memcache call. However, what is the overhead of "add" vs. "get"? These aren't the real comparisons... and I just made up these numbers, but let's say 1 add ~= 1 set ~= 5 get in terms of effort, and the average user views 5 pages a day: a: (5 get * 1 effort) + (1 set * 5 effort) = 10 units of effort b: (5 add * 5 effort) = 25 units of effort Would it make sense to always do the add call? Is this an unnecessary micro-optimization?

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• session management: verifying a user's log-in state

  - by good_computer

  I am storing sessions in my database. Everytime a user logs in, I create a new row corresponding to the new session, generate a new session id and send it as a cookie to the browser. My session data looks something like this: { 'user_id': 1234 'user_name': 'Sam' ... } When a request comes, I check whether a cookie with a session id is sent. If it is, I fetch session data from my database (or memcache) corresponding to that session id. When the user logs out, I remove the session data from my database (and memcache), and delete the cookie from the user's browser too. Notice that in my session data, I don't have something like logged_in: true. This is because if I find a session record in the database (or memcache) I deduce that the user is logged in, and if there is no session record found, the user is not logged in. My question is: is this the right approach? Should I have a logged_in key in my session data? Is there any possibility that a session record may be present on the server where the corresponding user is actually NOT logged in? Are there any security implications in having or not having such a key?

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• Simple App Engine Sessions Implementation

  - by raz0r

  Here is a very basic class for handling sessions on App Engine: """Lightweight implementation of cookie-based sessions for Google App Engine. Classes: Session """ import os import random import Cookie from google.appengine.api import memcache _COOKIE_NAME = 'app-sid' _COOKIE_PATH = '/' _SESSION_EXPIRE_TIME = 180 * 60 class Session(object): """Cookie-based session implementation using Memcached.""" def __init__(self): self.sid = None self.key = None self.session = None cookie_str = os.environ.get('HTTP_COOKIE', '') self.cookie = Cookie.SimpleCookie() self.cookie.load(cookie_str) if self.cookie.get(_COOKIE_NAME): self.sid = self.cookie[_COOKIE_NAME].value self.key = 'session-' + self.sid self.session = memcache.get(self.key) if self.session: self._update_memcache() else: self.sid = str(random.random())[5:] + str(random.random())[5:] self.key = 'session-' + self.sid self.session = dict() memcache.add(self.key, self.session, _SESSION_EXPIRE_TIME) self.cookie[_COOKIE_NAME] = self.sid self.cookie[_COOKIE_NAME]['path'] = _COOKIE_PATH print self.cookie def __len__(self): return len(self.session) def __getitem__(self, key): if key in self.session: return self.session[key] raise KeyError(str(key)) def __setitem__(self, key, value): self.session[key] = value self._update_memcache() def __delitem__(self, key): if key in self.session: del self.session[key] self._update_memcache() return None raise KeyError(str(key)) def __contains__(self, item): try: i = self.__getitem__(item) except KeyError: return False return True def _update_memcache(self): memcache.replace(self.key, self.session, _SESSION_EXPIRE_TIME) I would like some advices on how to improve the code for better security. Note: In the production version it will also save a copy of the session in the datastore. Note': I know there are much more complete implementations available online though I would like to learn more about this subject so please don't answer the question with "use that" or "use the other" library.

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• Whats wrong with this task queue setup?

  - by Peter Farmer

  I've setup this task queue implementation on a site I host for a customer, it has a cron job which runs each morning at 2am "/admin/tasks/queue", this queues up emails to be sent out, "/admin/tasks/email", and uses cursors so as to do the queuing in small chunks. For some reason last night /admin/tasks/queue kept getting run by this code and so sent out my whole quota of emails :/. Have I done something wrong with this code? class QueueUpEmail(webapp.RequestHandler): def post(self): subscribers = Subscriber.all() subscribers.filter("verified =", True) last_cursor = memcache.get('daily_email_cursor') if last_cursor: subscribers.with_cursor(last_cursor) subs = subscribers.fetch(10) logging.debug("POST - subs count = %i" % len(subs)) if len(subs) < 10: logging.debug("POST - Less than 10 subscribers in subs") # Subscribers left is less than 10, don't reschedule the task for sub in subs: task = taskqueue.Task(url='/admin/tasks/email', params={'email': sub.emailaddress, 'day': sub.day_no}) task.add("email") memcache.delete('daily_email_cursor') else: logging.debug("POST - Greater than 10 subscibers left in subs - reschedule") # Subscribers is 10 or greater, reschedule for sub in subs: task = taskqueue.Task(url='/admin/tasks/email', params={'email': sub.emailaddress, 'day': sub.day_no}) task.add("email") cursor = subscribers.cursor() memcache.set('daily_email_cursor', cursor) task = taskqueue.Task(url="/admin/tasks/queue", params={}) task.add("queueup")

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• Google App Engine - Dealing with concurrency issues of storing an object

  - by Spines

  My User object that I want to create and store in the datastore has an email, and a username. How do I make sure when creating my User object that another User object doesn't also have either the same email or the same username? If I just do a query to see if any other users have already used the username or the email, then there could be a race condition. UPDATE: The solution I'm currently considering is to use the MemCache to implement a locking mechanism. I would acquire 2 locks before trying to store the User object in the datastore. First a lock that locks based on email, then another that locks based on username. Since creating new User objects only happens at user registration time, and it's even rarer that two people try to use either the same username or the same email, I think it's okay to take the performance hit of locking. I'm thinking of using the MemCache locking code that is here: http://appengine-cookbook.appspot.com/recipe/mutex-using-memcache-api/ What do you guys think?

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• ?????QCon Tokyo 2010 ??????????!

  - by rika.tokumichi

  ??????OTN????????? 2010?4?19??20??????????·??????????QCon Tokyo 2010?????????? ??????????????????????????????????????????! ??????????????????????????????????^^ ???????????! >QCon Tokyo 2010 ????? ?????????? ????????????????? -------------------------------------------- ???:?? ?? (???? ????) ?????????????? - ????????CoE - ?????????? BI/SOA????????????? ???:?? ?? (???? ?????) ?????????? - ????????? - ??????????? -------------------------------------------- ??????????????????????????????????QCon Tokyo 2010?????????? QCon????????????????????????????InfoQ???????????????????????????????????????·?????????? ????????????4???????????????????????????????·?????????? InfoQ????????????????????????????????????????????????? ?1??? ??????????????Twitter????Nick Kallen??????????? ??????Data Architecture at Twitter Scale?? ?????????????????????????????????????????????????????????????????120????????????????????????????????????????? ??????????????????????????????????????????????????????????????????Twitter????????????????????????????????????????????????? ?????????????????????????????????????????????????????????????????????????????? ????????Oracle Coherence????????????Patrick Peralta??? ?Connected Clouds: A Platform for Globally Distributed Service? ??????????????? Coherence????????KVS??????????????????????????????????????Oracle Coherence?????????????????????????????????? ??????????????????????????????????????????Coherence?Push Replication Pattern?????????????????????????????????????????????????????????????????????????????????????????? ??????????????????????????? ?????????????????????????????????? ?????? ??????????????????????????2???3??????????? ???????????????????????????????! ??????????????????????????????? ?2??? 2??????????????Facebook?Marc Kwiatkowski?????????? ??????Scaling Memcache at Facebook?? 4??????????Facebook???????memcache??????????????????????????????????????? ?????????memchace????????????????????????????????memcache???????????????????????????????????????????????????????????????????????????? ????????????? Java7???????????????????????????????????? Ruby??????????????????????????????Ruby????????? ??????????????????????????? ???????????????! --------------------------------------- ?????????????????????????!! ???????????! ???????2?????????? ??????????????????????????? >QCon Tokyo 2010 ????? ?????????&??????? ?????????????Patrick Peralta?????????? >?????Connected Clouds: A Platform for Globally Distributed Service?(??) by Patrick Peralta ?Oracle Coherence????? ???? ?????? ???????????? Oracle Coherence?????(??????????) OTN????????????????????????????? ??????????????????? >???????????????????1(?????? ???) >???????????????????2(???????) ???????????????????????????????????????????????????!

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• "Unable to initialize module" fileinfo php-pecl-Fileinfo.x86_64

  - by Myers Network

  I have a brand new server server that I am trying to get setup up. This is a 64 bit machine that I can not install "fileinfo" or "memcache". I have uninstalled these and reinstalled them using yum and pecl with no luck. Yum install fine "no error" but then get error when running php. pecl from what I can tell is only installing 32bit. Does not put anything in the lib64 directory. Here is my output from php -v: PHP Warning: PHP Startup: fileinfo: Unable to initialize module Module compiled with module API=20050922, debug=0, thread-safety=0 PHP compiled with module API=20060613, debug=0, thread-safety=0 These options need to match in Unknown on line 0 PHP Warning: PHP Startup: memcache: Unable to initialize module Module compiled with module API=20050922, debug=0, thread-safety=0 PHP compiled with module API=20060613, debug=0, thread-safety=0 These options need to match in Unknown on line 0 PHP 5.2.14 (cli) (built: Aug 12 2010 16:03:48) Copyright (c) 1997-2010 The PHP Group Zend Engine v2.2.0, Copyright (c) 1998-2010 Zend Technologies Here is some other system info incase you need it uname: Linux server.actham.us 2.6.18-194.26.1.el5 #1 SMP Tue Nov 9 12:54:20 EST 2010 x86_64 x86_64 x86_64 GNU/Linux php -m: PHP Warning: PHP Startup: fileinfo: Unable to initialize module Module compiled with module API=20050922, debug=0, thread-safety=0 PHP compiled with module API=20060613, debug=0, thread-safety=0 These options need to match in Unknown on line 0 PHP Warning: PHP Startup: memcache: Unable to initialize module Module compiled with module API=20050922, debug=0, thread-safety=0 PHP compiled with module API=20060613, debug=0, thread-safety=0 These options need to match in Unknown on line 0 [PHP Modules] bz2 calendar ctype curl date dbase dom exif filter ftp gd gettext gmp hash iconv imap json ldap libxml mbstring mcrypt mysql mysqli openssl pcntl pcre PDO pdo_mysql pdo_sqlite readline Reflection session shmop SimpleXML sockets SPL standard tokenizer wddx xml xmlreader xmlrpc xmlwriter xsl zip zlib [Zend Modules] Any help would be greatly appreciated, thanks....

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