Skip to main content

Java Garbage Collection

This week we got a plenty of out of heap memory exceptions in Java. So I started looking on Java Garbage Collection, a revision of System Software Internals theory again.  Java has its heap divided into new gen and old generation. Java's garbage collection tries to take advantage of the fact that new object will be deleted sooner(objects will have smaller life time).
So Java's heap is divided into
1)Young Generation(smaller in size)
2)Old Generation (larger chunk)

Young Generation:
Young Generation is smaller in size. Traditional Recursive Garbage collection will be faster if the size to be collected is smaller. New Objects are created in Eden part of the Heap. Garbage Collector runs frequently in this space and marks objects that are referenced.  Objects that are not not referenced are removed in the second pass and the live objects are moved to Survivor Space.
Survivor Space has two regions Survivor 0 and Survivor 1 which uses an algorithm similar to Copying Garbage Collector. So Garbage Collector runs on Survivor(0/1) depending on live region and moves the live objects to the other region and the former region will have only death objects that will be freed. Objects that survive more than two/three rounds of garbage collection will be moved to Old Generation.
Old Generation:
Old Generation has objects which are alive for longer time. Since Java's garbage collection is based on the fact that objects tend to die sooner. Old Generation is collected very rarely and it is very huge in size. The old generation runs two algorithms
1)CMS-Concurrent Mark Sweep
This marks all objects that are not alive and flushes them but there will be defragmentation across the heap
2)Stop the World Collector
Stop the world collector kicks in when heap is almost full, it compacts the live objects. This will cause the java process to hang for few seconds and cause performance impact especially when dealing with heap space as high as 20/30 GB as in our case. 
Java 7 has come up with G1 collector which optimizes by combining CMS and STW collector. 

To see the garbage collection live, there is a good tool jstat
jstat -gc <pid> <interval to monitor>

Comments

Popular posts from this blog

Lessons from Memory

Started debugging an issue where Linux started calling OOM reaper despite tons of memory is used as Linux cached pages. My assumption was if there is a memory pressure, cache should shrink and leave way for the application to use. This is the documented and expected behavior. OOM reaper is called when few number of times page allocation has failed consequently. If for example mysql wants to grow its buffer and it asks for a page allocation and if the page allocation fails repeatedly, kernel invokes oom reaper. OOM reaper won't move out pages, it sleeps for some time and sees if kswapd or a program has freed up caches/application pages. If not it will start doing the dirty job of killing applications and freeing up memory. In our mysql setup, mysql is the application using most of the Used Memory, so no other application can free up memory for mysql to use. Cached pages are stored as 2 lists in Linux kernel viz active and inactive.
More details here
https://www.kernel.org/doc/gorman…

Walking down the Memory Lane!!!

This post is going to be an account of  few trouble-shootings I did recently to combat various I/O sluggishness.
Slow system during problems with backup
We have a NFS mount where we push backups of our database daily. Due to some update to the NFS infra, we started seeing throughput of NFS server drastically affected. During this time we saw general sluggishness in the system during backups. Even ssh logins appeared slower. Some boxes had to be rebooted due to this sluggishness as they were too slow to operate on them. First question we wanted to answer, does NFS keep writing if the server is slow? The slow server applied back pressure by sending small advertised window(TCP) to clients. So clients can't push huge writes if server is affected. Client writes to its page cache. The data from page cache is pushed to server when there is a memory pressure or file close is called. If server is slow, client can easily reach upto dirty_background_ratio set for page cache in sysctl. This di…

How we have systematically improved the roads our packets travel to help data imports and exports flourish

This blog post is an account of how we have toiled over the years to improve the throughput of our interDC tunnels. I joined this company around 2012. We were scaling aggressively then. We quickly expanded to 4 DCs with a mixture of AWS and colocation. Our primary DC is connected to all these new DCs via IPSEC tunnels established from SRX. The SRX model we had, had an IPSEC throughput of 350Mbps. Around December 2015 we saturated the SRX. Buying SRX was an option on the table. Buying one with 2Gbps throughput would have cut the story short. The tech team didn't see it happening.

I don't have an answer to the question, "Is it worth spending time in solving a problem if a solution is already available out of box?" This project helped us in improving our critical thinking and in experiencing the theoretical network fundamentals on live traffic, but also caused us quite a bit of fatigue due to management overhead. Cutting short the philosophy, lets jump to the story.

De…