Skip to main content

Mysql Sharding at our company- Part2 (picking least used shard)

in Mysql sharding at my company part1 I covered that when a customer registers we assign him next free shard. Now this problem seems simple at first but it has its own twists. You could have different strategies to determine next free shard id
  1. Based on no of rows in shard
  2. Based on no of customers in shard
After lots of thinking I use the first approach. When a customer registers I pick up the next free shard by looking up information schema and query least used 8 shards and then randomly pick one of those.  Picking shards based on no of customers was rejected because we use a nagios monitor to test registration and that causes lots of dummy registrations and also QA team does registrations and some times people will register a trial use for 15 days and wont convert as they are either spammers or just want to use us for sharing large files for <15 days.

The reason to not always pick the first least used shard is that 6 months down the line if we add 2 more shards to cluster then every new registration would pick those two shards only.  The way our customers use the system is that they register and play with the system for a while during the 15 day trial period and if they like the solution (which they do) then they upload their real dataset.  During the trial period the customer would upload may be 100-1000 files/folders but when they upload the real dataset then they would upload 1-2 million files. So always picking the least used shard would cause hotspots. That's  why we pick the least 8 used shards and randomly pick one of those shards.

This gives us uniform distribution here is a screenshot of 5 random shards from our Graphite dashboard.

As you can see the rows are evenly distributed, you could get many small customers on 1 shard and 1 big customer can take up 1 shard.  As we use memcache many small customers on 1 shard will not cause issues for reads. Its usually the bigger customers with 3-5 M files that cause issues.

One key thing to note is that information schema can be slow when you run select query on it. If the statistics on table are obsolete, then  select query on information schema can cause mysql to scan the table and calculate statistics, which can be bad for registration. So I wrote a quartz job that every hour find the 8 least used shard per cluster and populates in memcache  and registration process just uses that. If for some reason the data is not in cache cache then registration process queries and populates it.

Part1 of series

Part2 of series

Part3 of series

Part4 of series 


Popular posts from this blog

RabbitMQ java clients for beginners

Here is a sample of a consumer and producer example for RabbitMQ. The steps are
Download ErlangDownload Rabbit MQ ServerDownload Rabbit MQ Java client jarsCompile and run the below two class and you are done.
This sample create a Durable Exchange, Queue and a Message. You will have to start the consumer first before you start the for the first time.

For more information on AMQP, Exchanges, Queues, read this excellent tutorial
import com.rabbitmq.client.Connection; import com.rabbitmq.client.Channel; import com.rabbitmq.client.*; public class RabbitMQProducer { public static void main(String []args) throws Exception { ConnectionFactory factory = new ConnectionFactory(); factory.setUsername("guest"); factory.setPassword("guest"); factory.setVirtualHost("/"); factory.setHost(""); factory.setPort(5672); Conne…

Logging to Graphite monitoring tool from java

We use Graphite as a tool for monitoring some stats and watch trends. A requirement is to monitor impact of new releases as build is deployed to app nodes to see if things like
1) Has the memcache usage increased.
2) Has the no of Java exceptions went up.
3) Is the app using more tomcat threads.
Here is a screenshot

We changed the installer to log a deploy event when a new build is deployed. I wrote a simple spring bean to log graphite events using java. Logging to graphite is easy, all you need to do is open a socket and send lines of events.
import org.slf4j.Logger;import org.slf4j.LoggerFactory; import; import; import; import java.util.HashMap; import java.util.Map; public class GraphiteLogger { private static final Logger logger = LoggerFactory.getLogger(GraphiteLogger.class); private String graphiteHost; private int graphitePort; public String getGraphiteHost() { return graphiteHost; } public void setGraphite…

What a rocky start to labor day weekend

Woke up by earthquake at 7:00 AM in morning and then couldn't get to sleep. I took a bath, made my tea and started checking emails and saw that after last night deployment three storage node out of 100s of nodes were running into Full GC. What was special about the 3 nodes was that each one was in a different Data centre but it was named same app02.  This got me curious I asked the node to be taken out of rotation and take a heap dump.  Yesterday night a new release has happened and I had upgraded spymemcached library version as new relic now natively supports instrumentation on it so it was a suspect. And the hunch was a bullseye, the heap dump clearly showed it taking 1.3G and full GCs were taking 6 sec but not claiming anything.

I have a quartz job in each jvm that takes a thread dump every 5 minutes and saves last 300 of them, checking few of them quickly showed a common thread among all 3 data centres. It seems there was a long running job that was trying to replicate pending…