Initial study to docker

Docker making so much fuss lately and today we are going to look into Docker. Let's start something basic, what actually is a docker? According to the definition from official site,

Docker is an open platform for developers and sysadmins to build, ship, and run distributed applications. Consisting of Docker Engine, a portable, lightweight runtime and packaging tool, and Docker Hub, a cloud service for sharing applications and automating workflows, Docker enables apps to be quickly assembled from components and eliminates the friction between development, QA, and production environments. As a result, IT can ship faster and run the same app, unchanged, on laptops, data center VMs, and any cloud.

and explanation from wikipedia

Docker is an open-source project that automates the deployment of applications inside software containers, by providing an additional layer of abstraction and automation of operating system–level virtualization on Linux.[2] Docker uses resource isolation features of the Linux kernel such as cgroups and kernel namespaces to allow independent "containers" to run within a single Linux instance, avoiding the overhead of starting virtual machines.[3]

Okay, that's the theory. If you want to quickly get an idea how docker work, you can try it here!

For people who has run virtual machine environment before, it may seem, hey isn't this very similar to the current virtual machine? But they are not the same really. See the software stack below virtual machines versus docker.



Next, we will install docker locally and the below illustration is using debian sid. If you run other linux distribution, you should read this page. First we will install and then start bash in the ubuntu container. Note that when pulling ubuntu image down, may take sometime which depending on your internet speed.

root@localhost:~# apt-get install docker.io
Reading package lists... Done
Building dependency tree       
Reading state information... Done
The following extra packages will be installed:
  aufs-tools cgroupfs-mount libnih-dbus1 libnih1 makedev mountall plymouth
Suggested packages:
  btrfs-tools debootstrap lxc rinse plymouth-themes
The following NEW packages will be installed:
  aufs-tools cgroupfs-mount docker.io libnih-dbus1 libnih1 makedev mountall plymouth
0 upgraded, 8 newly installed, 0 to remove and 557 not upgraded.
Need to get 4,360 kB of archives.
After this operation, 21.6 MB of additional disk space will be used.
Do you want to continue? [Y/n] Y
Get:1 http://cdn.debian.net/debian/ unstable/main makedev all 2.3.1-93 [42.6 kB]
Get:2 http://cdn.debian.net/debian/ unstable/main plymouth amd64 0.9.0-9 [189 kB]
Get:3 http://cdn.debian.net/debian/ unstable/main libnih1 amd64 1.0.3-4.3 [127 kB]
Get:4 http://cdn.debian.net/debian/ unstable/main libnih-dbus1 amd64 1.0.3-4.3 [97.1 kB]
Get:5 http://cdn.debian.net/debian/ unstable/main mountall amd64 2.54 [68.3 kB]
Get:6 http://cdn.debian.net/debian/ unstable/main aufs-tools amd64 1:3.2+20130722-1.1 [92.9 kB]
Get:7 http://cdn.debian.net/debian/ unstable/main cgroupfs-mount all 1.1 [4,572 B]
Get:8 http://cdn.debian.net/debian/ unstable/main docker.io amd64 1.3.3~dfsg1-2 [3,739 kB]
Fetched 4,360 kB in 44s (97.8 kB/s)
Selecting previously unselected package makedev.
(Reading database ... 324961 files and directories currently installed.)
Preparing to unpack .../makedev_2.3.1-93_all.deb ...
Unpacking makedev (2.3.1-93) ...
Selecting previously unselected package plymouth.
Preparing to unpack .../plymouth_0.9.0-9_amd64.deb ...
Unpacking plymouth (0.9.0-9) ...
Selecting previously unselected package libnih1.
Preparing to unpack .../libnih1_1.0.3-4.3_amd64.deb ...
Unpacking libnih1 (1.0.3-4.3) ...
Selecting previously unselected package libnih-dbus1.
Preparing to unpack .../libnih-dbus1_1.0.3-4.3_amd64.deb ...
Unpacking libnih-dbus1 (1.0.3-4.3) ...
Selecting previously unselected package mountall.
Preparing to unpack .../mountall_2.54_amd64.deb ...
Unpacking mountall (2.54) ...
Selecting previously unselected package aufs-tools.
Preparing to unpack .../aufs-tools_1%3a3.2+20130722-1.1_amd64.deb ...
Unpacking aufs-tools (1:3.2+20130722-1.1) ...
Selecting previously unselected package cgroupfs-mount.
Preparing to unpack .../cgroupfs-mount_1.1_all.deb ...
Unpacking cgroupfs-mount (1.1) ...
Selecting previously unselected package docker.io.
Preparing to unpack .../docker.io_1.3.3~dfsg1-2_amd64.deb ...
Unpacking docker.io (1.3.3~dfsg1-2) ...
Processing triggers for man-db (2.7.0.2-5) ...
Processing triggers for dbus (1.8.12-3) ...
Setting up makedev (2.3.1-93) ...
/run/udev or .udevdb or .udev presence implies active udev.  Aborting MAKEDEV invocation.
/run/udev or .udevdb or .udev presence implies active udev.  Aborting MAKEDEV invocation.
/run/udev or .udevdb or .udev presence implies active udev.  Aborting MAKEDEV invocation.
Setting up plymouth (0.9.0-9) ...
update-initramfs: deferring update (trigger activated)
update-rc.d: warning: start and stop actions are no longer supported; falling back to defaults
update-rc.d: warning: start and stop actions are no longer supported; falling back to defaults
Setting up libnih1 (1.0.3-4.3) ...
Setting up libnih-dbus1 (1.0.3-4.3) ...
Setting up mountall (2.54) ...
Setting up aufs-tools (1:3.2+20130722-1.1) ...
Setting up docker.io (1.3.3~dfsg1-2) ...
Adding group `docker' (GID 139) ...
Done.
Processing triggers for dbus (1.8.12-3) ...
Setting up cgroupfs-mount (1.1) ...
Processing triggers for initramfs-tools (0.117) ...
update-initramfs: Generating /boot/initrd.img-3.9-1-amd64
W: mdadm: /etc/mdadm/mdadm.conf defines no arrays.
W: mdadm: no arrays defined in configuration file.
Processing triggers for libc-bin (2.19-13) ...
root@localhost:~#

jason@localhost:~$ docker run -i -t ubuntu /bin/bash
2015/01/08 16:27:07 Post http:///var/run/docker.sock/v1.15/containers/create: dial unix /var/run/docker.sock: permission denied
jason@localhost:~$ sudo docker run -i -t ubuntu /bin/bash
Unable to find image 'ubuntu' locally
Pulling repository ubuntu
8eaa4ff06b53: Download complete 
511136ea3c5a: Download complete 
3b363fd9d7da: Download complete 
607c5d1cca71: Download complete 
f62feddc05dc: Download complete 
Status: Downloaded newer image for ubuntu:latest
root@bedef9a17ac3:/# cat /etc/issue
Ubuntu 14.04.1 LTS \n \l

root@bedef9a17ac3:/# exit
jason@localhost:~$ sudo docker run ubuntu /bin/echo "hello world"
hello world

One would ask, why should I replace virtualbox to docker? There are four main points as outline in this article :

• Faster delivery of your applications


• Deploy and scale more easily


• Get higher density and run more workloads


• Faster deployment makes for easier management

If you think the above points are attracting, perhaps you should consider it and I leave these additional materials for your further exploration.

docker 101 video presentation.
remember to sign up
get the image from docker hub.
last but not least, documentation.

how to improve apache cassandra 1.0.8 read speed

This article is for improve reading speed for apache cassandra 1.0.8. Because the reading improvement determined by many factors, we will investigate all possible areas so the gain will be improve collectively. So you may experience these factors and alter according to suit your node environment to achieve the best result. As the cassandra 1.0 released, the official cited that the read performance has increased up to 400%!

First and foremost, there are numerous articles which I use as a reference has cited copyright, I take no ownership nor credit of their hardwork as that is rightfully belong to them entirely. I only reference their work to improve my knowledge and to help people (like me) who need help and came to read what I share in my article.

Let's split these improvements into two parts, the hardware and the software.

hardware

ssd

ssd disk is way faster than hdd disk in term of reading in multiple magnitude, please read cassandra-benchmark for the benchmark. Although the cassandra using was version 0.8.10, but when cassandra 1.0 was released, read gained tremendous improvement. Then these two improvemetns will be linear gain too. Also, it is recommend to read the aforementioned article as it explain why is the random speed will hurt the read performance for hdd disk.

multiple disks

disks allocation to the commit log should be different than the data directory. Because during data write, data is repeating appending to the commit log. If the data directory is located on different drive, read performance gain should be visible.

 

software

memtable
If write behaviour has a lot of updates, it is good to look into memtable settings. There are two settings which you can start with

• memtable_total_space_in_mb


• commitlog_total_space_in_mb

more memory to this settings means the frequent write (update) will be absorded by the memory and thus, reading will be fast too as read start from memtable first before going into sstable. But because this impact system wide, you might want to gradually start to increase it and measure them. Read below for more information on what these two settings are and how to tune them
http://www.datastax.com/docs/1.0/operations/tuning#memtable-sizing
http://www.datastax.com/docs/1.0/configuration/node_configuration#memtable-total-space-in-mb
http://www.slideshare.net/driftx/cassandra-summit-2010-performance-tuning slide 14 and slide 26
http://wiki.apache.org/cassandra/MemtableThresholds

WP-DataStax-Cassandra page 16
Specifically, for read performance, Cassandra 1.0 optimizes queries by using a lighter-weight data structure for representing a row fragment from a read, than for a row fragment in a memtable into which updates accumulates. Also, with named reads, Cassandra 1.0 includes enhancements for deserializing the most recent versions of requested columns. Combined with the other optimizations, this makes reads in Cassandra as fast as writes for many workloads.

data compression

Previously I have done a study on the compression affect improvement read, read here, here, here and here. Please read the links as it provide comprehensive explanation than I could describe here.

compaction

compaction can improve (or impact) the read speed. Citation fromWP-DataStax-Cassandra,

The above process produces exceptionally fast write operations; however it also can lead to data fragmentation across the disk. Read requests may have to combine data from many SStables as well as Memtables to satisfy end user requests for data, and this can increase query response times.

To reduce data fragmentation and reclaim space taken by obsolete data, Cassandra performs "compactions" that merge the most recent data from many different SStables on disk into a new one.

So with my experience, if you trigger compaction (major) through nodetool, during compaction, the read latency will increase, thus impact but when the compaction is done, the read performance is improved.

In this documentation,  it explain different compaction strategy to use for read or write workload. So identify how's your environment write and read pattern and always measure it so you know what and when it could went wrong. Choose compaction strategy to suit your data model. For instance, if cassandra is not strong at a point, choose other big data technology. Read here for bad experience encountered.

sstables counts

Keep the sstables counts as low as possible for a column family. Excerpt from FULLTEXT02 page 39.

If a read operation is performed, initially the data are read from the memtable. If data are not in the memtable, then data get read from SSTable. Multiple SSTables may be looked up to find the data. Reading directly from SSTable decreases the performance because there are many SSTable that might need to be looked at hence requires an I/O operation means it requires touching the disk. Compared to SSTable, reading directly from memtable is fast because there is no I/O involved. The more the I/O operations are involved, the more performance will be degraded. Performance can also be increased by increasing the size of memtable [7].

Cassandra uses Bloom filter to judge quickly whether the key exists in the SSTable or not before touching the disk. Bloom filter is a efficient data structure that checks whether element is a member of a set by dividing the memory into buckets. Check each bucket to see if a key is present and if any bucket is empty then key was never inserted before. If there are many SSTables, then lots of I/O operations would be needed to read the data which can definitely decrease the performance. This is because of the fact that I/O operations are expensive and therefore compaction is used to improve read performance. Compaction merge two SSTables and sort to become one SSTable, which eventually decreases the number of SSTables and number of I/O operations, hence increasing the performance [7].

key / row cache

key cache should be enable to reduce the search from touching the disk, especially spinning disk. Excerpt from FULLTEXT02 page 47.

By default key cache is enabled and Cassandra caches 20,000 keys per Column Family (CF). The key cache decreases the Input/Output (I/O) operations because if key cache is not enabled then I/O operation is required in order to figure out the exact location of the row. Key cache holds the exact location of the data belonging to that key.

 

Row cache holds the entire content of the row in cache. By default, row cache is disabled. The overhead of enabling or increasing the row cache is that it may require more Java Virtual Machine (JVM) heap of Cassandra. By if jna lib is available, then storing row cache off heap is a good option. This article has diagram on how read is perform.

concurrent_read

Excerpt from FULLTEXT02 page 48.

Read performance can also be increased by tuning the concurrent reads. The rule is span 4 threads per Central Processing Units (CPU) core in the cluster. The higher the number of threads spanned for read, the higher performance can be achieved if the machines have got faster I/O.

A word of cautious, I tried increase concurrent_read from 32 to 64 and see some unpredictable behaviour, so it is better you do this in test environment.

decreasing read consistency level

If your business requirement can tolerate of eventual consistency, then decrease from quorum to one will improve read speed as only one node acknowledgement is sufficient to fulfill the read request compare to a certain amount of nodes in quorum.

turn off swap space

When the node start to swap due to shortage of memory, the response of node be it write or read will be visible. Hence it is best to turn off swap, and let the operating system kill or jvm kill itself to oom than the page swap start to happen.

java heap

Citation from OS-8.1.3-Cassandra Installation and Configuration Guide page 33

HEAP_NEWSIZE : Size of young generation. Larger value leads to longer GC pause times while smaller value will typically lead to more expensive GC. Set in conjunction with MAX_HEAP_SIZE.

So tune it carefully since this is pretty low level. Read this article as it mentioned a few garbage collector settings for cassandra and memory footprint.

upgrade

Each release of software improve or fix the previous defect, so is cassandra. If upgrade is viable, you should consider. For instance, to quote Aaron Morton

1.0 has key and row caches defined per CF, 1.1 has global ones which are better utilised and easier to manage. 1.2 moves bloom filters and compression meta off heap which reduces GC, which will help.  Things normally get faster.

This is also true.

monitoring

Because data load increase and/or decrease will impact the read response time, it is vital if there is monitoring services running. As cited from this paper, p1724_tilmannrabl_vldb2012 Page 1,

In modern enterprise systems it is not uncommon to have thousands of different metrics that are reported from a single host machine.

So monitor crucial metrics by cassandra, example, cpu, java heap and io should give some indicator if your speed has been reduced.

Whilst these are collected knowledge are from public and free will sharing. Any mistake and errors in this article is mine alone and does not reflect to them. Thank you and I hope you learned something.

Investigate into Apache Cassandra Memtable updateLiveRatio logging output

Today, we are going to study apache cassandra 1.0.8 on memtable logging its statistics in the cassandra system.log. Example below

WARN [MemoryMeter:1] 2014-10-17 07:38:15,346 Memtable.java (line 176) setting live ratio to minimum of 1.0 instead of 0.16714977001091136
INFO [MemoryMeter:1] 2014-10-17 07:38:15,346 Memtable.java (line 186) CFS(Keyspace='OpsCenter', ColumnFamily='pdps') liveRatio is 1.6474114033116056 (just-counted was 1.0).  calculation took 3ms for 595 columns

What does the above logging output means? Is cassandra instance operating normally since logging level is warn? Before we dive into the code to understand its meaning, let first read and understand what is memtable in cassandra context.

Excerpts from datastax documentation

Cassandra is optimized for write throughput. Cassandra writes are first written to a commit log (for durability), and then to an in-memory table structure called a memtable. A write is successful once it is written to the commit log and memory, so there is very minimal disk I/O at the time of write. Writes are batched in memory and periodically written to disk to a persistent table structure called an SSTable (sorted string table). Memtables and SSTables are maintained per column family. Memtables are organized in sorted order by row key and flushed to SSTables sequentially (no random seeking as in relational databases).

Whenever method updateRatio() from class Memtable is called, the following codes applies.

public void updateLiveRatio()
{
        if (!MemoryMeter.isInitialized())
        {
            // hack for openjdk.  we log a warning about this in the startup script too.
            logger.warn("MemoryMeter uninitialized (jamm not specified as java agent); assuming liveRatio of 10.0.  Usually this means cassandra-env.sh disabled jamm because you are using a buggy JRE; upgrade to the Sun JRE instead");
            cfs.liveRatio = 10.0;
            return;
        }

        Runnable runnable = new Runnable()
        {
            public void run()
            {
                activelyMeasuring = Memtable.this;

                long start = System.currentTimeMillis();
                // ConcurrentSkipListMap has cycles, so measureDeep will have to track a reference to EACH object it visits.
                // So to reduce the memory overhead of doing a measurement, we break it up to row-at-a-time.
                long deepSize = meter.measure(columnFamilies);
                int objects = 0;
                for (Map.Entry<DecoratedKey, ColumnFamily> entry : columnFamilies.entrySet())
                {
                    deepSize += meter.measureDeep(entry.getKey()) + meter.measureDeep(entry.getValue());
                    objects += entry.getValue().getColumnCount();
                }
                double newRatio = (double) deepSize / currentThroughput.get();

                if (newRatio < MIN_SANE_LIVE_RATIO)
                {
                    logger.warn("setting live ratio to minimum of 1.0 instead of {}", newRatio);
                    newRatio = MIN_SANE_LIVE_RATIO;
                }
                if (newRatio > MAX_SANE_LIVE_RATIO)
                {
                    logger.warn("setting live ratio to maximum of 64 instead of {}", newRatio);
                    newRatio = MAX_SANE_LIVE_RATIO;
                }
                cfs.liveRatio = Math.max(cfs.liveRatio, newRatio);

                logger.info("{} liveRatio is {} (just-counted was {}).  calculation took {}ms for {} columns",
                            new Object[]{ cfs, cfs.liveRatio, newRatio, System.currentTimeMillis() - start, objects });
                activelyMeasuring = null;
            }
        };

        try
        {
            meterExecutor.submit(runnable);
        }
        catch (RejectedExecutionException e)
        {
            logger.debug("Meter thread is busy; skipping liveRatio update for {}", cfs);
        }
}

There is a new thread which will be execute by the executor meterExecutor. This executor if it is not busy, will start to measure this column family associated with this memtable. There are two essential metrics that is involve in the arithmetic, key size plus value size and the column count. deepSize is the summation of the column family , its key and its value. A new variable newRatio is calculated with the deepSize divided by the currentThroughput.

Valid newRatio range is between 1.0 to 64.0 inclusive. When calculated newRatio is less than 1.0, first line of log such as above will started to appear in cassandra system log and newRatio will be reset to 1.0. The same check when newRatio exceed 64.0, it will be logged and value for newRatio reset to maximum valid value of 64.0. Then column family live ratio is updated with whichever which is higher, the current or the new calculated newRatio.

So technically, this is nothing to really concern about. It's a measurement of the number of operations has increased as compare to the previous. Also, given the next throughput, as estimated of size of the memtable can be calculated based on the newRatio. As a side note, this method updateRatio() is called after a mutation has been applied to the memtable but before a flush is requested.

That's it for today, I hope you learned something.

operate casandra using jmx in terminal including changing pool size, compacting sstables and key cache

If you operate apache cassandra cluster and if load per node goes huge (like nodetool info show 800GB), compactions become a problem. It's a big problem for apache cassandra 1.0.8 if you have load per node average hover around 600GB to 1TB. The read performance suffers and at times system uptime load goes high. In some instance, I noticed when repair is running, system load goes more than 20. It's not a concern if this is operating well, but the more often you see this, something has gone wrong. Today, I will share my experience on how to operate cassandra when node load is huge and cassandra instance is still running. Often times, there are nice method that is exposed via jmx but to operate remotely, jmx gui client such as jmxconsole is not ideal. Instead, we will using a jmxterm for these operation in apache cassandra 1.0.8. So let's get started.

Changing pool size

So, it is pretty simple, launch it and set to the bean, and then set the CorePoolSize. The steps will be illustrate below.

$ java -jar jmxterm-1.0-alpha-4-uber.jar
$>open localhost:7199   
#Connection to localhost:7199 is opened
$>bean org.apache.cassandra.request:type=ReplicateOnWriteStage
#bean is set to org.apache.cassandra.request:type=ReplicateOnWriteStage
$>get CorePoolSize
#mbean = org.apache.cassandra.request:type=ReplicateOnWriteStage:
CorePoolSize = 32;
$>info
#mbean = org.apache.cassandra.request:type=ReplicateOnWriteStage
#class name = org.apache.cassandra.concurrent.JMXConfigurableThreadPoolExecutor
# attributes
  %0   - ActiveCount (int, r)
  %1   - CompletedTasks (long, r)
  %2   - CorePoolSize (int, rw)
  %3   - CurrentlyBlockedTasks (int, r)
  %4   - PendingTasks (long, r)
  %5   - TotalBlockedTasks (int, r)
#there's no operations
#there's no notifications
$>set CorePoolSize 64
$>get CorePoolSize
#mbean = org.apache.cassandra.request:type=ReplicateOnWriteStage:
CorePoolSize = 64;

Alter key cache

Often times, when there is heap pressure in the jvm, the safety valve kicks in.  You can restart the cassandra instance or you can reset the key cache back to the initial value. Assuming your column family name FooBar and keyspace just4fun, then the following are steps to illustrate how is this done.

$>bean org.apache.cassandra.db:cache=FooBarKeyCache,keyspace=just4fun,type=Caches
#bean is set to org.apache.cassandra.db:cache=FooBarKeyCache,keyspace=just4fun,type=Caches
$>info
#mbean = org.apache.cassandra.db:cache=FooBarKeyCache,keyspace=just4fun,type=Caches
#class name = org.apache.cassandra.cache.AutoSavingKeyCache
# attributes
  %0   - Capacity (int, rw)
  %1   - Hits (long, r)
  %2   - RecentHitRate (double, r)
  %3   - Requests (long, r)
  %4   - Size (int, r)
#there's no operations
#there's no notifications
$>
$>get Size
#mbean = org.apache.cassandra.db:cache=FooBarKeyCache,keyspace=just4fun,type=Caches:
Size = 122307;

$>set Capacity 250000
#Value of attribute Capacity is set to 250000
$>get Capacity;      
#mbean = org.apache.cassandra.db:cache=FooBarKeyCache,keyspace=just4fun,type=Caches:
$>get Capacity 
#mbean = org.apache.cassandra.db:cache=FooBarKeyCache,keyspace=just4fun,type=Caches:
Capacity = 250000;

Compact sstable

Lastly, to compact sstables. It's amazing we have a sstable that as huge as 84GB! So trigger major compaction is not an option here, often time when load per node goes beyond 600GB, compaction took forever, as GC kick in and cpu keep on recollecting heap, making system load goes high. So here, we will select one sstable that is huge and compact that only. You can also select a few sstable and compact them and separate using comma.

$>bean org.apache.cassandra.db:type=CompactionManager
#bean is set to org.apache.cassandra.db:type=CompactionManager
$>run forceUserDefinedCompaction just4fun FooBar-hc-5-Index.db
#calling operation forceUserDefinedCompaction of mbean org.apache.cassandra.db:type=CompactionManager
#RuntimeMBeanException: java.lang.IllegalArgumentException: FooBar-hc-5-Index.db does not appear to be a data file
$>run forceUserDefinedCompaction just4fun FooBar-hc-401-Data.db 
#calling operation forceUserDefinedCompaction of mbean org.apache.cassandra.db:type=CompactionManager
#operation returns: 
null

The compaction should be started, you can check in cassandra system log or the nodetool compaction. So that's it, I hope you learned something.

Embed video into debian mediawiki

Today, this article is a bit special and a short one, we will configured
something interesting. We will embed video into mediawiki in debian. It's
actually a request from friend and so we will take a look at how to do it.
Let's see the screenshot below and if you want to do something like this, then
read on.



 

Before we get started, you will require root access in debian and already install
and configured mediawiki already.

1. change directory to

# cd /usr/share/mediawiki-extensions

2. pull from mediawiki embedvideo source from github.

# git pull https://github.com/Alexia/mediawiki-embedvideo.git

3. enable this extension.

# cd /etc/mediawiki-extensions/extensions-available
# ln -s /usr/share/mediawiki-extensions/mediawiki-embedvideo/EmbedVideo.php
# cd ../extensions-enabled
# ln -s ../extensions-available/EmbedVideo.php

Easy! Three easy steps. Now, let's edit a wiki page and an example below.

[https://www.youtube.com/watch?v=xmmYEtS13BQ Al Gromer Khan & Klaus Wiese - The Alchemy of Happiness]
{{#ev:youtube|xmmYEtS13BQ}}

[https://www.youtube.com/watch?v=ls7NMH_O5Ck&list=RDVpxBTgbeMsw&index=10 RELAXING MUSIC Relax Mind Body, Sleep Music, Meditation music, Relaxation Music Stress Relief]
{{#ev:youtube|ls7NMH_O5Ck}}

Save the page and that's it!

apache cassandra 1.0.8 IncompatibleClassChangeError vtable stub and AssertionError Added column does not sort as the last column

Today we will spend sometime to look into two errors and see if it is really something to concern about. The erros are thrown when apache cassandra version 1.0.8 is running. Okay, let's to the first error.

ERROR [ReadStage:1559] 2012-10-16 20:38:25,336 AbstractCassandraDaemon.java (line 139) Fatal exception in thread Thread[ReadStage:1559,5,main]
java.lang.IncompatibleClassChangeError: vtable stub
        at org.apache.cassandra.db.AbstractColumnContainer.getColumn(AbstractColumnContainer.java:134)
        at org.apache.cassandra.db.Memtable$6.computeNext(Memtable.java:402)
        at org.apache.cassandra.db.Memtable$6.computeNext(Memtable.java:384)
        at com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:140)
        at com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:135)
        at org.apache.cassandra.db.CollationController.collectTimeOrderedData(CollationController.java:93)
        at org.apache.cassandra.db.CollationController.getTopLevelColumns(CollationController.java:62)
        at org.apache.cassandra.db.ColumnFamilyStore.getTopLevelColumns(ColumnFamilyStore.java:1298)
        at org.apache.cassandra.db.ColumnFamilyStore.getColumnFamily(ColumnFamilyStore.java:1184)
        at org.apache.cassandra.db.ColumnFamilyStore.getColumnFamily(ColumnFamilyStore.java:1151)
        at org.apache.cassandra.db.Table.getRow(Table.java:375)
        at org.apache.cassandra.db.SliceByNamesReadCommand.getRow(SliceByNamesReadCommand.java:58)
        at org.apache.cassandra.service.StorageProxy$LocalReadRunnable.runMayThrow(StorageProxy.java:765)
        at org.apache.cassandra.service.StorageProxy$DroppableRunnable.run(StorageProxy.java:1224)
        at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
        at java.lang.Thread.run(Thread.java:662)

I guess this is really some fatal errors encountered. Let's check out what is IncompatibleClassChangeError means. From IncompatibleClassChangeError javadoc

Thrown when an incompatible class change has occurred to some class definition. The definition of some class, on which the currently executing method depends, has since changed.

Honestly, this is really odd, this error thrown out of no where and the jvm stopped. I guess nobody change the compiled apache cassandra code during the node instance is running. It certainly sounds odd but I guess when the data hold per node is huge, then strange thing start to happened. Now, let's get into stack trace and follow stack trace path.

Bottom three stack traces are pretty obvious, a new thread was started and execute by the thread pool executor. Then we have class StorageProxy. Within this class, there is a static class LocalReadRunnable which implement the abstract method LocalReadRunnable. It seem like it is trying to read a local node table row. The table eventually make calls to the column family to retrieve column. Tracing even deeper, at line 134 of class AbstractColumnContainer,  reveal that no exception is thrown from here. This is like a mystery! :) The stack trace analysis and observed jvm stopped shown something is wrong. Though I am not sure what went wrong but if you have any idea, please discuss it as a comment below.

Next we look to another error.

ERROR [CompactionExecutor:4] 2014-10-22 06:13:00,884 AbstractCassandraDaemon.java (line 139) Fatal exception in thread Thread[CompactionExecutor:4,1,main]
java.lang.AssertionError: Added column does not sort as the last column
        at org.apache.cassandra.db.ArrayBackedSortedColumns.addColumn(ArrayBackedSortedColumns.java:126)
        at org.apache.cassandra.db.AbstractColumnContainer.addColumn(AbstractColumnContainer.java:129)
        at org.apache.cassandra.db.AbstractColumnContainer.addColumn(AbstractColumnContainer.java:124)
        at org.apache.cassandra.db.ColumnFamilySerializer.deserializeColumns(ColumnFamilySerializer.java:148)
        at org.apache.cassandra.io.sstable.SSTableIdentityIterator.getColumnFamilyWithColumns(SSTableIdentityIterator.java:232)
        at org.apache.cassandra.db.compaction.PrecompactedRow.merge(PrecompactedRow.java:110)
        at org.apache.cassandra.db.compaction.PrecompactedRow.<init>(PrecompactedRow.java:97)
        at org.apache.cassandra.db.compaction.CompactionController.getCompactedRow(CompactionController.java:137)
        at org.apache.cassandra.db.compaction.CompactionIterable$Reducer.getReduced(CompactionIterable.java:102)
        at org.apache.cassandra.db.compaction.CompactionIterable$Reducer.getReduced(CompactionIterable.java:87)
        at org.apache.cassandra.utils.MergeIterator$ManyToOne.consume(MergeIterator.java:118)
        at org.apache.cassandra.utils.MergeIterator$ManyToOne.computeNext(MergeIterator.java:101)
        at com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:140)
        at com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:135)
        at com.google.common.collect.Iterators$7.computeNext(Iterators.java:614)
        at com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:140)
        at com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:135)
        at org.apache.cassandra.db.compaction.CompactionTask.execute(CompactionTask.java:173)
        at org.apache.cassandra.db.compaction.CompactionManager$1.call(CompactionManager.java:135)
        at org.apache.cassandra.db.compaction.CompactionManager$1.call(CompactionManager.java:115)
        at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:303)
        at java.util.concurrent.FutureTask.run(FutureTask.java:138)
        at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
        at java.lang.Thread.run(Thread.java:662)

Again, this error pop out of nowhere, during node operation, this exception just thrown. So now, we will look into what happened using the stack trace given. Similar to the above, bottom three stack traces are pretty obvious, a new thread was started and execute by the thread pool executor. It is a compaction thread and when compacting sstable, things break. Then row get reduced and columns get deserialized. When columns are re-formation, it throw an exception as the column does not sort. This is another strange phenomenon. It should have been sort before anyway but it is not. The javdoc for this method addColumn

AddColumn throws an exception if the column added does not sort after the last column in the map. The reasoning is that this implementation can get slower if too much insertions are done in unsorted order and right now we only use it when *all* insertion (with this method) are done in sorted order. The assertion throwing is thus a protection against performance regression without knowing about (we can revisit that decision later if we have use cases where most insert are in sorted order but a few are not).

It seem that this is probably reproducible during development environment as a few are not.. I guess this is not as fatal as previous error. That's it for this analysis, please give your inputs or comments if you have workaround.

---

 

UPDATE:

It seem that the second error is fix in https://issues.apache.org/jira/browse/CASSANDRA-5856

Android first application hello world

First Off, Happy New Year Everybody!

Perhaps there are ten or even hundreds of first application develop using android if you google. Well today, I will share mine too, hey, start of year, a hello world would be nice too. :) If you have programming skill in java and using eclipse IDE, then you come to this right place. In this article, I will use eclipse IDE and develop a hello world android application. I figured it was a painless few steps setup but it took me several days to get everything going due to my hectic life and problems encountered during this learning journey. I hope with these explain, you will have better and easier learning experience than I did.

This article assume you have read and had setup the Android Developer Toolkit plugin into eclipse IDE and Speed up android emulator startup in eclipse. If you have not, please refer to this link and this link respectively. Okay, let's get started as I will show project creation in steps with screenshots. I will document and describe my learning experience below but if you want to read further on certain topics, you can refer on the official documentation, then please refer to this link.

1. create a new android application project. If it is not listed in the tab File, try Other... ;)





2. Click Next button, it is a window to configure the new android application project. Here fill in the information which as such for this introduction course.



3. Click Next button, yet another window to configure the project. The default settings will work mostly fine for this introductory course.



4. Click next button, this is a setting for the application icons. I'm not a color person but this colors design works like a charm for me. :-) if you want to take the challenge, try change the default icon.



5. Click next button, the default Black Activity just fine to display the text hello world later.



6. Click next button, again, the default configuration work just fine. This is the last configuration.



7. Click finish button and now check your workspace, it should have created all the necessary files.

I remembered the first time I have setup, the tutorial never mentioned about installing android support libraries, so once Finish button was click, the project created with errors. This is a big of learning curve for something who is new to android. Let alone to say if you are new to java or even IDE. See screenshot below.



For your information, this project require a support library which is available in Android SDK manager. Okay, now, let's install android support library. On eclipse tab, click on Window and then Android SDK Manager. Find out where is the android support library and install it. See the screenshots below, it should give you sufficient of information to get this done.



 

 By now, eclipse will request you to restart, hence, restart your eclipse. Once restarted, you should see a new project known as appcompat_v7 exists in the Package Explorer window. If you project is still contain error, check if your project is build automatically. You can click on eclipse menu tab, Project then Build Automatically... is checked. The project should contain no error and if there is still error, in the eclipse, click on Problems tab and identify what is the error. Because error is dependent on your platform and version of eclipse and/or android sdk, hence, if you have problem, google and fix them. This is left for your exercises. If everything is okay, your project should be as similar as mine such as below.



Okay, now check the project properties make sure everything is okay.



As you can notice above, I have also install Android 4.4W.2 sdk for my learning journey, but I have enabled Android 5.0 for this project. The reference project appcompat_v7 is valid and exists. Both of android projects are free from any errors. So far so good.

Note, there is a directory known as gen and educated guess said it is automatic generated files. As such, you should not modify directory to the file within this gen package but leave it automatically generated. Please note, R.java must autogenerated for this project to compiled successfully for our next journey and if you do not see this file, then you should be worry and find out where and what is the problem why R.java never get generated. Hint, don't try to add into an invalid R.java from somewhere but fix the root cause here.

Just before we launch the application in android emulator, let's see some android files here.



So all looking good, it should be ready now to launch this hello world android application in android emulator. Just like launching a simple java app, the sequence is pretty much the same for android. Right click on the project, then click on Run As / Debug As. Since this is the first android application, you might have not configured Android Virtual Device (avd), you should by now configure one. If you have done the previous article, Speed up android emulator startup in eclipse. It should be a breeze here and just select this avd. If not, you can follow the procedures using the screenshots below.



Because the startup emulator is slow, I would suggest to leave the emulator running as long as you are learning to develop the application. Because starting the emulator in my workstation took minutes. As seen in the output below, I have configured two different avd and the output of one screenshot shown My First App is shown in the android menu. Cool!



Try click on My First App through the emulator, it should hello world. :-) That's it for this learning experience and I hope you learn something and if you want to contribute back, you can do so by donating back.

Thank you.