Showing posts with label jconsole. Show all posts
Showing posts with label jconsole. Show all posts

Thursday, January 16, 2014

force sstable compaction through jconsole

Happy new year everyone, this is my first article for 2014 and as a start, it is going to be short and sweet one. :-)

I was working on this project where I have deleted the column and I remember the definition of tombstone is that, you need to run compact so that the tombstone is removed. When I run nodetool compact, this message appear below.
INFO 19:15:09,170 Nothing to compact in index1.  Use forceUserDefinedCompaction if you wish to force compaction of single sstables (e.g. for tombstone collection)

So what is this means is that, you need to have jconsole running because forceUserDefinedCompaction can only invoke through jconsole. When jconsole is connected to your cassandra daemon process, you need to navigate to the compactionmanager mbean.

Then you need to provide two value to this method as this method expected two parameters. That is the keyspace and the sstables where you wish to compact. You can see in this attachment on how I did it.



So if you ls the data directory where the sstable are store, a new sstable should be generated. Once the operation is complete, you can navigate to the data directory where the sstable is stored.

$ ls data/lucene1/
index1-hc-3-Data.db index1-hc-3-Digest.sha1 index1-hc-3-Filter.db index1-hc-3-Index.db index1-hc-3-Statistics.db snapshots

We have production machine which a single sstable size is more than 25GB. When the soft limit compaction is met (default min 4 and max 32) , in this situation, I think it will load the server if it takes place, probably best is, we forceUserDefinedCompaction on this single large sstable.

Tuesday, December 31, 2013

Cassandra cluster jmx metrics inspection to decide if cluster expansion is justifiable

One of the important decision during managing the clusters is to determine when cluster capacity should expand. To maintain a cluster in optimal performance will give the applications working nicely and most importantly, it give confidence to the people.

So, to answer question like, how do I determine if my cluster is at bottleneck? To answer this type of question, you will need to have the measuring tools ready and measure over time. Meaning that you need to display statistics in graphical form and with the history, it should give an indication of the cluster performance.

Because the topic will grow huge, hence, we will focus on a specific metric. This article gonna inspect the metric exposed by the jmx beans. In order to inspect the jmx metrics, you will need a jmx client. There is a gui jmx client that comes with the jdk, that is jconsole. Because nature of this article, I would suggest you go for cli jmx client, for example jmxterm. You can read introduction of jmxterm here.

There are many metrics exposed by cassandra jmx beans. But we will focus on bean org.apache.cassandra.db:type=CompactionManager.

If you are using jmxterm, you can read the output below:
$ cat test.script 
open localhost:7199
bean org.apache.cassandra.db:type=CompactionManager
get PendingTasks
$ java -jar jmxterm-1.0-alpha-4-uber.jar -i test.script
Welcome to JMX terminal. Type "help" for available commands.
#Connection to localhost:7199 is opened
#bean is set to org.apache.cassandra.db:type=CompactionManager
#mbean = org.apache.cassandra.db:type=CompactionManager:
PendingTasks = 0;

So if you plot PendingTasks in a graph over time with a periodic interval, it should give insight to your cluster performance. You can also plot the statistics output from nodetool tpstats. I would suggest also, you plot Message type dropped as those metrics indicate over time that the performance is impacted. If you have a stock cassandra settings, you will probably want to fine tune to your node at this point after this investigation and analysis on the graph.

There is no best strategies, as mentioned earlier, you need experience and there are many other metrics measuring tools, example sar , iostats, top, your application measurement. So it take some times to even master all of these but it is crucial if you managed a production cluster.