Skip to main content

Benefits of indirection

We shard our databases and keep the metadata information as to what shard is located in what database host in a table.  We recently had a database spike where due to thundering herd problem, lots of our clients would come and execute a very costly query concurrently.  The only solution is to avoid making this query and change the application architecture but the problem would take 1-2 months to solve. We didn't had the luxury to wait that long.  So we were looking for solutions to buy time.

Luckily to buy time we can throw more hardware, we had recently ordered a pair of mysql servers for some other purpose so we repurposed it.  Because we had desgined our application to have a layer of indirection on how to look what customer is located on what shard and what shard is located on what database host.  We were able to quickly spin off 2 slaves and connect them to the db host having load isues. As soon as replication was done we cut off the db access and wait for replication to be 100% done.

The source database  had 8 schemas and 64 shards so we dropped 4 schemas from source and 4 from target and the final picture was 32 shards on one host and 32 on the other. Then all we need to do is change the mappings of shard to host info and restart servers and we were done.

There is still a room to do this without downtime, thats my next goal but still we were able to within 2-3 hours  do this in night and the load avg on next day was under control.


Comments

Popular posts from this blog

Haproxy and tomcat JSESSIONID

One of the biggest problems I have been trying to solve at our startup is to put our tomcat nodes in HA mode. Right now if a customer comes, he lands on to a node and remains there forever. This has two major issues: 1) We have to overprovision each node with ability to handle worse case capacity. 2) If two or three high profile customers lands on to same node then we need to move them manually. 3) We need to cut over new nodes and we already have over 100+ nodes.  Its a pain managing these nodes and I waste lot of my time in chasing node specific issues. I loath when I know I have to chase this env issue. I really hate human intervention as if it were up to me I would just automate thing and just enjoy the fruits of automation and spend quality time on major issues rather than mundane task,call me lazy but thats a good quality. So Finally now I am at a stage where I can put nodes behing HAProxy in QA env. today we were testing the HA config and first problem I immediat...

Adding Jitter to cache layer

Thundering herd is an issue common to webapp that rely on heavy caching where if lots of items expire at the same time due to a server restart or temporal event, then suddenly lots of calls will go to database at same time. This can even bring down the database in extreme cases. I wont go into much detail but the app need to do two things solve this issue. 1) Add consistent hashing to cache layer : This way when a memcache server is added/removed from the pool, entire cache is not invalidated.  We use memcahe from both python and Java layer and I still have to find a consistent caching solution that is portable across both languages. hash_ring and spymemcached both use different points for server so need to read/test more. 2) Add a jitter to cache or randomise the expiry time: We expire long term cache  records every 8 hours after that key was added and short term cache expiry is 2 hours. As our customers usually comes to work in morning and access the cloud file server it ...

Spring 3.2 quartz 2.1 Jobs added with no trigger must be durable.

I am trying to enable HA on nodes and in that process I found that in a two test node setup a job that has a frequency of 10 sec was running into deadlock. So I tried upgrading from Quartz 1.8 to 2.1 by following the migration guide but I ran into an exception that says "Jobs added with no trigger must be durable.". After looking into spring and Quartz code I figured out that now Quartz is more strict and earlier the scheduler.addJob had a replace parameter which if passed to true would skip the durable check, in latest quartz this is fixed but spring hasnt caught up to this. So what do you do, well I jsut inherited the factory and set durability to true and use that public class DurableJobDetailFactoryBean extends JobDetailFactoryBean {     public DurableJobDetailFactoryBean() {         setDurability(true);     } } and used this instead of JobDetailFactoryBean in the spring bean definition     <bean i...