Request timeout in Rails - ruby-on-rails

Question

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

Answer 1

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.

Answer 2

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.