I have a simple rails app that scrapes JSON from a remote URL for each instance of a model (let's call it A). The app then creates a new data-point under an associated model of the 1st. Let's call this middle model B and the data point model C. There's also a front end that let's users browse this data graphically/visually.
Thus the hierarchy is A has many -> B which has many -> C. I scrape a URL for each A which returns a few instances of B with new Cs that have data for the respective B.
While attempting to test/scale this app I have encountered a problem where rails will stop processing, hang for a while, and finally throw a "ActiveRecord::ConnectionTimeoutError could not obtain a database connection within 5.000 seconds" Obviously the 5 is just the default.
I can't understand why this is happening when 1) there are no DB calls being made explicitly, 2) the log doesn't show any under the hood DB calls happening when it does work 3) it works sometimes and not others.
What's going on with rails 4 AR and the connection pool?!
A couple of notes:
The general algorithm is to spawn a thread for each model A, scrape the data, create in memory new instances of model C, save all the C's in one transaction at the end.
Sometimes this works, other times it doesn't, i can't figure out what causes it to fail. However, once it fails it seems to fail more and more.
I eager load all the model A's and B's to begin with.
I use a transaction at the end to insert all the newly created C instances.
I currently use resque and resque scheduler to do this work but I highly doubt they are the source of the problem as it persists even if I just do "rails runner Class.do_work"
Any suggestions and or thoughts greatly appreciated!
I believe I have found the cause of this problem. When you loop through an association via
model.association.each do |a|
#work here
end
Rails does some behind the scenes work that "uses" a DB connection. I put uses in quotes because in my case I think the result is actually returned from memory. I eager loaded the association and thus the DB is never actually hit.
Preliminary testing of wrapping my block in a
ActiveRecord::Base.connection_pool.with_connection do
#something me doing?
end
seems to have resolved the issue.
I uncovered this by adding a backtrace to my thread's error message that was printing out.
-----For those using resque----
I also had to add a bit in my resque.rake file to get this fully working as intended.
task 'resque:setup' => :environment do
Resque.after_fork do |job|
ActiveRecord::Base.establish_connection
end
end
If you are you using
ActiveRecord::Base.transaction do
... code
end
to accomplish faster transactions in a thread, note that this locks the database. I had an app that did this for a hugely expensive process, in a thread, and it would lock the DB for over 5 seconds. It is faster, though it will lock your database
Related
I'm working on a Rails 7 app with some pretty tight response time SLAs. I am well within SLA during normal runtime. Where I fall painfully short is first request. I've added an initializer that will load up ActiveRecord and make sure all of my DB models are loaded. It hydrates some various memory caches, etc. This took me pretty far. My first response time was reduced about 60%. However, I've been trying to figure out a couple things are are still slowing down first response time.
First API request does a check to see if I need to do a rails migration. I've not figured out how to move this check to init.
First API request appears to be be using a fresh DB Pool.. not the one that was used in init phase. I've tried fully hydrating the pool to spare the API from creating them when Rails kicks on, but I've not figured it out.
In an initializer I can do something like this:
connections = []
ActiveRecord::Base.connection.pool.size.times do
connections << ActiveRecord::Base.connection.pool.checkout
end
connections.each { ActiveRecord::Base.connection.pool.checkin(_1) }
According to my PG logs, this opens up the connections and Rails does all of this typing queries, setting session properties, etc. However, when I go to fire off my first API call, my pool is empty.
In the end what ended up being the general issue was I needed to be hydrating the pool with the correct connections. on_worker_boot is because this is running behind puma.
on_worker_boot do
ActiveRecord::Base.connected_to(role: :reading) do
# spin up db connections
connections = []
(ActiveRecord::Base.connection.pool.size - 1).times do
connections << ActiveRecord::Base.connection.pool.checkout
end
connections.each { |x| ActiveRecord::Base.connection.pool.checkin(x) }
end
end
We are working on a data visualization problem right now. Our customer wants us to show the last 6 months data for a honeybee hive on a graph.
Clearly it's gonna be a huge dataset. Adding indexes we overcame the database slowness problem in loading data though we still have problem in visualizing data on a graph.
Here is the related code:
def self.prepare_single_hive_messages_for_datatable_dygraph(messages, us_metric_enabled)
data = []
messages.each do |message|
record = []
record << message.occurance_time.to_s(:dygraph_format)
record << weight_according_to_metric(message.weight, us_metric_enabled)
record << temperature_according_to_metric(message.temperature, us_metric_enabled)
record << (message.humidity.nil? ? nil : message.humidity.to_f)
data << record
end
return data
end
The problem is that messages.each is very slow and takes more than 30 seconds. Is there any solution to overcome this?
Project Specification:
Rails Version: 4.1.9
Graph Library: Dygraph
Database: Postgres
There are two ways to attack a performance problem like this.
Find and correct the performance bottle neck
Break it into smaller pieces
Finding Performance issues
First, get a dataset large enough to reproduce the problem setup on your dev system. Then look at the logs so you can see how long the transaction is taking. You should be looking for a line like this:
Completed 200 OK in 432.1ms (Views: 367.7ms | ActiveRecord: 61.4ms)
Rerun the task a couple times since caching can cause variations. Write down your different times. Then remove everything in the loop and run it with just the loop. Do the numbers go back to looking reasonable? If that is the case then you know the problem is the work you are doing inside the loop. Next, add each line in the loop back on its own (or one at a time if they depend on each other). Figure out which line causes those numbers to jump the most.
This is the point where you should try to performance tune your code. Check for queries that could be smarter. Make sure you aren't querying the same data over and over. If you have a function in a model that computes something and you call it multiple times to get the same answer then use this to only compute once:
def something
return #savedvalue if #savedvalue
#savedvalue = really complex calculation
end
The goal is to find the worse offender so you can make changes that have the biggest impact. However, if you are working with a LOT of data this may only get you so far. It may be impossible to performance tune enough for all the data. In that case there is option 2.
Break it into smaller pieces
Write a second rails action who's only job is to render a single record on a graph. It will do the inner part of your loop but only on the message who's id was passed to it.
Call your original function to setup the view and pass the list of messages to the view. In the view loop through the list of messages to setup jquery ajax code to call the above action once for each message. Have this run in on document ready.
Then, the page will load with an empty graph... but as soon as it is up the individual processed records will be fed to it and appear one at a time on the page. It will still take just ask long (or even a little longer because of overhead) to complete the graph... but it will no longer time out. Each ajax call will be its own quick hit to the server instead of one big long hit.
I just used this very technique to load a rather long report on a site I work on. Ideally we'd like to fix any underlying performance issues... but what we really wanted was to have a report working right away and then fix the performance issues as we had time.
Ok you said every person sees the same set of data, which is great, means we can cache without worrying about who's logged in, first here's your method, with tiny improvements
def self.prepare_single_hive_messages_for_datatable_dygraph(messages, us_metric_enabled)
messages.inject([]) do |records, message|
records << [].tap do |record|
record << message.occurance_time.to_s(:dygraph_format)
record << weight_according_to_metric(message.weight, us_metric_enabled)
record << temperature_according_to_metric(message.temperature, us_metric_enabled)
record << (message.humidity.nil? ? nil : message.humidity.to_f)
end
end
end
Then create a caching function, that runs this method and caches it
# some class constants
CACHE_KEY = 'some_cache_key'
EXPIRY_TIME = 15.minutes
# the methods
def self.write_single_hive_messages_to_cache(messages, us_metric_enabled)
Rails.cache.write CACHE_KEY,
self.class.prepare_single_hive_messages_for_datatable_dygraph(messages, us_metric_enabled),
expires_in: EXPIRY_TIME
end
And a simple cache reading method
self.read_single_hive_messages_from_cache
Rails.cache.read CACHE_KEY
end
Then create a rake task that just fetches these messages and call the caching method, and rails will write the cache.
Create a cron job that calls this rake task, set the cron job to 5 minutes or so, the expiry time is longer just in case for some reason the cron job didn't run, the data will still be available for the next run.
This way your processing is run in the background, every 5 ( or whatever time you choose ) minutes, the page load should happen normally with no delay at all, since the array data will be loaded from the pre-calculated cache.
In case the cron stops working, the data will expire in the 15 minutes I've set, and then the read cache method will return nil, you could avoid this and set the data to never expire, but then the data will become stale and the old data will keep getting returned.
Another way to handle this is to tell the cache reading method how to generate the cache it self, so if it finds the cache empty it generates one and caches it itself before returning the data, the method would look like this
def self.read_single_hive_messages_from_cache(messages, us_metric_enabled)
Rails.cache.fetch CACHE_KEY, expires_in: EXPIRY_TIME do
self.class.write_single_hive_messages_to_cache(messages, us_metric_enabled)
end
end
But then make sure that messages is an ActiveRecord::Relation and not a processed array, because you don't want to query for 1+ million records and then find the cache already ready, if it's an ActiveRecord::Relation it will not touch the database until the array is started ( inside the caching block ), if the cache exists it will be returned before you enter the block and thus the data won't get fetched, saving you that huge query.
I know the answer got long, if you need more help tell me.
When I executing query
Mymodel.all.each do |model|
# ..do something
end
It uses allot of memory and amount of used memory increases at all the time and at the and it crashes. I found out that to fix it I need to disable identity_map but when I adding to my mongoid.yml file identity_map_enabled: false I am getting error
Invalid configuration option: identity_map_enabled.
Summary:
A invalid configuration option was provided in your mongoid.yml, or a typo is potentially present. The valid configuration options are: :include_root_in_json, :include_type_for_serialization, :preload_models, :raise_not_found_error, :scope_overwrite_exception, :duplicate_fields_exception, :use_activesupport_time_zone, :use_utc.
Resolution:
Remove the invalid option or fix the typo. If you were expecting the option to be there, please consult the following page with repect to Mongoid's configuration:
I am using Rails 4 and Mongoid 4, Mymodel.all.count => 3202400
How can I fix it or maybe some one know other way to reduce amount of memory used during executing query .all.each ..?
Thank you very much for the help!!!!
I started with something just like you by doing loop through millions of record and the memory just keep increasing.
Original code:
#portal.listings.each do |listing|
listing.do_something
end
I've gone through many forum answers and I tried them out.
1st attempt: I try to use the combination of WeakRef and GC.start but no luck, I fail.
2nd attempt: Adding listing = nil to the first attempt, and still fail.
Success Attempt:
#start_date = 10.years.ago
#end_date = 1.day.ago
while #start_date < #end_date
#portal.listings.where(created_at: #start_date..#start_date.next_month).each do |listing|
listing.do_something
end
#start_date = #start_date.next_month
end
Conclusion
All the memory allocated for the record will never be released during
the query request. Therefore, trying with small number of record every
request does the job, and memory is in good condition since it will be
released after each request.
Your problem isn't the identity map, I don't think Mongoid4 even has an identity map built in, hence the configuration error when you try to turn it off. Your problem is that you're using all. When you do this:
Mymodel.all.each
Mongoid will attempt to instantiate every single document in the db.mymodels collection as a Mymodel instance before it starts iterating. You say that you have about 3.2 million documents in the collection, that means that Mongoid will try to create 3.2 million model instances before it tries to iterate. Presumably you don't have enough memory to handle that many objects.
Your Mymodel.all.count works fine because that just sends a simple count call into the database and returns a number, it won't instantiate any models at all.
The solution is to not use all (and preferably forget that it exists). Depending on what "do something" does, you could:
Page through all the models so that you're only working with a reasonable number of them at a time.
Push the logic into the database using mapReduce or the aggregation framework.
Whenever you're working with real data (i.e. something other than a trivially small database), you should push as much work as possible into the database because databases are built to manage and manipulate big piles of data.
I have a background operation I would like to occur every 20 seconds in Rails given that some condition is true. It kicked off when a certain controller route is hit, and it looks like this
def startProcess
argId = self.id
t = Thread.new do
while (Argument.isRunning(argId)) do
Argument.update(argId)
Argument.markVotes(argId)
puts "Thread ran"
sleep 20
end
end
end
However, this code does absolutely nothing to my database unless I call "t.join" in which case my whole server is blocked for a long time (but it works).
Why can't the read commit ActiveRecords without being joined to the main thread?
The thread calls methods that look something like
def sample
model = Model.new()
model.save()
end
but the models are not saved to the DB unless the thread is joined to the main thread. Why is this? I have been banging my head about this for hours.
EDIT:
The answer marked correct is technically correct, however this edit is to outline the solution I eventually used. The issues is that Ruby does not have true threading, so even once I got my DB connection working the Thread couldn't get processor time unless there was little traffic to the server.
Solution: start a new Heroku worker instance, point it at the same database, and make it execute a rake task that has the same functionality as the thread. Now everything works great.
You need to re-establish the database connection:
ActiveRecord::Base.establish_connection Rails.env
I'm using rufus-scheduler to run a number of frequent jobs that do some various tasks with ActiveRecord objects. If there is any sort of network or postgresql hiccup, even after recovery, all the threads will throw the following error until the process is restarted:
ActiveRecord::ConnectionTimeoutError (could not obtain a database connection within 5 seconds (waited 5.000122687 seconds). The max pool size is currently 5; consider increasing it.
The error can easily be reproduced by restarting postgres. I've tried playing (up to 15) with the pool size, but no luck there.
That leads me to believe the connections are just in a stale state, which I thought would be fixed with the call to clear_stale_cached_connections!.
Is there a more reliable pattern to do this?
The block that is passed is a simple select and update active record call, and happens to matter what the AR object is.
The rufus job:
scheduler.every '5s' do
db do
DataFeed.update #standard AR select/update
end
end
wrapper:
def db(&block)
begin
ActiveRecord::Base.connection_pool.clear_stale_cached_connections!
#ActiveRecord::Base.establish_connection # this didn't help either way
yield block
rescue Exception => e
raise e
ensure
ActiveRecord::Base.connection.close if ActiveRecord::Base.connection
ActiveRecord::Base.clear_active_connections!
end
end
Rufus scheduler starts a new thread for every job.
ActiveRecord on the other hand cannot share connections between threads, so it needs to assign a connection to a specific thread.
When your thread doesn't have a connection yet, it will get one from the pool.
(If all connections in the pool are in use, it will wait untill one is returned from another thread. Eventually timing out and throwing ConnectionTimeoutError)
It is your responsibility to return it back to the pool when you are done with it, in a Rails app, this is done automatically. But if you are managing your own threads (as rufus does), you have to do this yourself.
Lucklily, there is an api for this:
If you put your code inside a with_connection block, it will get a connection form the pool, and release it when it is done
ActiveRecord::Base.connection_pool.with_connection do
#your code here
end
In your case:
def db
ActiveRecord::Base.connection_pool.with_connection do
yield
end
end
Should do the trick....
http://api.rubyonrails.org/classes/ActiveRecord/ConnectionAdapters/ConnectionPool.html#method-i-with_connection
The reason can be that you have many threads which are using all connections, if DataFeed.update method takes more than 5 seconds, than your block can be overlapped.
try
scheduler.every("5s", :allow_overlapping => false) do
#...
end
Also try release connection instead of closing it.
ActiveRecord::Base.connection_pool.release_connection
I don't really know about rufus-scheduler, but I got some ideas.
The first problem could be a bug on rufus-scheduler that does not checkout database connection properly. If it's the case the only solution is to clear stale connections manually as you already do and to inform the author of rufus-scheduler about your issue.
Another problem that could happen is that your DataFeed operation takes a really long time and because it is performed every 5 secondes Rails is running out of database connections, but it's rather unlikely.