A very good read on scalability and high-performance data management.
Over the last 10 years I’ve used all but Mongo and Redis to solve these very same issues, and had the same Findings.
A couple of the surprising lessons to me was how bad Cassandra was, and how good Solr is.
I hope you find this as interesting as I did:
<< Previous: Cassandra – Going into Production – Part 2.
With an empty cluster running, the next step I’m going to take is to install and configure OpsCenter from DataStax. This is a fantastic tool for monitoring the health and performance of your cluster.
The first order of business is to create a directory to store the Ops Center code on the server. I opted to do this within the user account used for Cassandra, as the directory datastax
:~$ mkdir datastax :~$
Next, download and extract the OpsCenter package:
:~/datastax$ wget http://downloads.datastax.com/community/opscenter-1.4-free.tar.gz --2012-03-26 08:25:30-- http://downloads.datastax.com/community/opscenter-1.4-free.tar.gz Resolving downloads.datastax.com... 173.203.57.192 Connecting to downloads.datastax.com|173.203.57.192|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 21539843 (21M) [application/octet-stream] Saving to: `opscenter-1.4-free.tar.gz' 100%[=======================================================================>] 21,539,843 3.72M/s in 7.5s 2012-03-26 08:25:38 (2.74 MB/s) - `opscenter-1.4-free.tar.gz' saved [21539843/21539843] :~/datastax$ tar -xvzf opscenter-1.4-free.tar.gz opscenter-1.4/ opscenter-1.4/log/ opscenter-1.4/bin/ opscenter-1.4/bin/create-keystore.bat opscenter-1.4/bin/create-key-pair.bat [...] opscenter-1.4/conf/event-plugins/email.conf opscenter-1.4/conf/ssl.conf opscenter-1.4/conf/opscenterd.conf :~/datastax$
Next is the setup for OpsCenter. Setup is done via a Python script, located in the BIN directory. Have your listening IP ready and know which port you want to use for the Ops Center web portal. I’m going to use the default of port 8888. Make sure you have the port open on your machine. (click here to jump to the my section on ports).
:~/datastax$ ls opscenter-1.4 opscenter-1.4-free.tar.gz :~/datastax$ cd opscenter-1.4 :~/datastax/opscenter-1.4$ bin/setup.py Generating a 1024 bit RSA private key .........++++++ ...++++++ writing new private key to 'ssl/opscenter.key' ----- MAC verified OK Certificate was added to keystore :~/datastax/opscenter-1.4$
Configure the Ops Center deamon. Set the listening IP to an IP available on the system. I’m going to node’s interal IP address (10.1.0.23). The values I’ve changed are in bold.
:~/datastax/opscenter-1.4$ vi conf/opscenterd.conf [...] [jmx] # The default jmx port for Cassandra >= 0.8.0 is 7199. If you are using # Cassandra 0.7.*, the default is 8080, and you should change this to # reflect that. port = 8001 [...] [webserver] port = 8888 interface = 10.1.0.23 staticdir = ./content log_path = ./log/http.log [...] [cassandra] # a comma-separated list of places to try for a connection to your Cassandra # cluster: seed_hosts = 10.1.0.23,10.1.0.26 [...]
Each node in the cluster must have a running Ops Center agent. The installation package for this was generated by the Ops Center setup process, and saves a compressed file. This file then needs to be copied and extracted on each node you plan to monitor with the Ops Center.
:~/datastax$ mkdir opscenter-agent :~/datastax$ cp opscenter-1.4/agent.tar.gz opscenter-agent/ :~/datastax$ cd opscenter-agent/ :~/datastax/opscenter-agent$ tar -xvzf agent.tar.gz agent/opscenter-agent-2.5-standalone.jar agent/conf/log4j.properties agent/bin/setup.bat [...] agent/bin/ssl/agentKeyStore.p12 agent/bin/ssl/opscenter.key agent/doc/LICENSE :~/datastax/opscenter-agent$
Now run the agent’s setup, assigning it’s IP and the Ops Center’s IP. 10.1.0.26 is this node’s IP address. 10.1.0.23 is the location of the Ops Center install (this may or may not be on the same system or even the same IP address):
:~/datastax/opscenter-agent$ agent/bin/setup 10.1.0.26 10.1.0.23
Make sure you copy the agent file to ALL your other nodes and follow the same setup procedure (this is an example of how I copied the file, your system, ports etc. may be different), and repeat the steps above, with the appropriate IPs.
:~/datastax/opscenter-agent$ scp -P41718 agent.tar.gz bigdata@10.1.0.26:. RSA key fingerprint is 2b:5b:26:03:87:a4:b1:ea:90:b5:4e:42:60:88:cd:d1. bigdata@10.1.0.26's password: agent.tar.gz 100% 10MB 10.3MB/s 00:01 :~/datastax/opscenter-agent$
On the Ops Center machine, move back to it’s installed directory and start the process.
:~/datastax$ cd opscenter-1.4 ~/datastax/opscenter-1.4$ bin/opscenter &
Now connect to the IP address and port and you should see a base Ops Center instance. This is what you would typically see before starting up your agents:
The last step is to start up the Agent deamons so that the OpsCenter knows the status of each node.
:~/datastax/opscenter-1.4$ cd ../opscenter-agent/ :~/datastax/opscenter-agent$ agent/bin/opscenter-agent & :~/datastax/opscenter-agent$ INFO [main] 2012-03-26 09:12:40,465 Loading conf files: conf/address.yaml INFO [main] 2012-03-26 09:12:40,505 Java vendor/version: Java HotSpot(TM) 64-Bit Server VM/1.7.0_03 INFO [main] 2012-03-26 09:12:40,505 Waiting for the config from OpsCenter INFO [main] 2012-03-26 09:12:40,637 SSL communication is enabled INFO [main] 2012-03-26 09:12:40,637 Creating stomp connection to 10.1.0.23:61620
With the Agents fired up, you will see a nice dashboard, showing the current status of the cluster, and some metrics on performance.
This basically concludes the fast deployment steps required to download, install, configure and start up Cassandra, along with the DataStax Ops Center.
Total time required to deploy was under 4 hours.
It’s been almost a month since I started the Apache Cassandra investigation, and now it’s time to move into a production stance. Some of these steps will differ from the original steps documented here in my blog. Later this week I will go back and amend those posts to point at this post as the more recent information. Those old links are already being referenced by multiple sites, so deleting them would not be a kind thing to do. Thus.. onward we move!
Originally, the OpenJDK was being used for this introduction and research into Cassandra. Being a proponent of Open Source, I was going to avoid the use of Oracle’s potentially proprietary JDK/JRE in this environment. I have since seen first had, that the JDK DOES IN FACT MATTER, and the one that supports the latest tools is the one from Oracle.
That is located here:
Downloading the JRE/JDK from Oracle has enabled the reliable use of DataStax’s OpsCenter management tool (more on that later).
These are the recommended minimums for Cassandra and OpsCenter from DataStax, a respected partner of the Apache Cassandra project.
Sun Java Runtime Environment 1.6.0_19 or later
Python 2.5, 2.6, or 2.7
OpenSSL version listed in Configuring SSL unless you disable SSL
I ended up selecting the JDK (linked here) and deposited it in the following location on my system as user root (create the directory path if you don’t already have it):
/opt/java/64/jdk-7u3-linux-x64.tar.gz
Extract the file:
:/opt/java/64# tar -xvzf jdk-7u3-linux-x64.tar.gz jdk1.7.0_03/ jdk1.7.0_03/include/ jdk1.7.0_03/include/jvmti.h jdk1.7.0_03/include/jawt.h [...] jdk1.7.0_03/jre/plugin/desktop/sun_java.desktop jdk1.7.0_03/jre/COPYRIGHT jdk1.7.0_03/LICENSE jdk1.7.0_03/COPYRIGHT :/opt/java/64#
The Cassandra Build I decided to use is this one: apache-cassandra-1.1.0-beta1. I downloaded the file to the user I created for this using wget:
:~$ wget http://apache.deathculture.net/cassandra/1.1.0/apache-cassandra-1.1.0-beta1-bin.tar.gz --2012-03-25 22:52:27-- http://apache.deathculture.net/cassandra/1.1.0/apache-cassandra-1.1.0-beta1-bin.tar.gz Resolving apache.deathculture.net... 173.236.158.254 Connecting to apache.deathculture.net|173.236.158.254|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 12505037 (12M) [application/x-gzip] Saving to: `apache-cassandra-1.1.0-beta1-bin.tar.gz' 100%[=======================================================================>] 12,505,037 8.84M/s in 1.3s 2012-03-25 22:52:29 (8.84 MB/s) - `apache-cassandra-1.1.0-beta1-bin.tar.gz' saved [12505037/12505037]
Next the file is extracted, moved to a shorter directory name:
:~$ tar -xvzf apache-cassandra-1.1.0-beta1-bin.tar.gz :~$ mv apache-cassandra-1.1.0-beta1 cass-beta1
Now the configuration is edited to define the node ring. The first file to edit is the cassandra.yaml file.
This initially will be only a 2 node cluster, but the tokens must still be calculated. Here are the node tokens I generated using a PERL script I wrote (see: Cassandra and Big Data – building a single-node “cluster” – Extra Credit for the code):
:~/cass-beta1$ ./token.pl 2 Calculate tokens for 2 nodes factor = 170141183460469231731687303715884105728 node 0 token: 0 node 1 token: 85070591730234615865843651857942052864 :~/cass-beta1$
Edit the cluster name. I’m not testing, so I changed the name to one descriptive of the data I was storing. ‘ip’. In the example below, I’m showing configs for the 2nd of the two nodes. Note: The first node would have a different IP address and also a different initial token, in this case ‘0’, as calculated by the tool.
:~$ cd cass-beta1/
:~/cass-beta1$ vi conf/cassandra.yaml
[...]
# The name of the cluster. This is mainly used to prevent machines in
# one logical cluster from joining another.
cluster_name: 'ip'
[...]
If blank, Cassandra will request a token bisecting the range of
# the heaviest-loaded existing node. If there is no load information
# available, such as is the case with a new cluster, it will pick
# a random token, which will lead to hot spots.
initial_token: 85070591730234615865843651857942052864
[...]
# directories where Cassandra should store data on disk.
data_file_directories:
- /home/bigdata/data/
[...]
# commit log
commitlog_directory: /home/bigdata/commitlog/
[...]
# saved caches
saved_caches_directory: /home/bigdata/saved_caches/
[...]
# seeds is actually a comma-delimited list of addresses.
# Ex: ",,"
- seeds: "10.1.100.101,10.1.100.102"
[...]
# Setting this to 0.0.0.0 is always wrong.
listen_address: 10.1.1.101
[...]
rpc_address: 10.1.1.101
[...]
# Time to wait for a reply from other nodes before failing the command (this was done to increase timeout to 30 seconds, sometimes the search I need to run is pretty nasty)
rpc_timeout_in_ms: 30000
Following that, the shell file needs to be modified to designate the JMX listening port:
:~/cass-beta1$ vi conf/cassandra-env.sh [...] # Specifies the default port over which Cassandra will be available for # JMX connections. JMX_PORT="8001" [...]
Make sure your logfile is in the desired location. I decided to keep it within the account itself for now:
vi cassA-1.0.8/conf/log4j-server.properties [...] log4j.appender.R.File=/home/bigdata/log/cassA.log [...]
Next I set the paths in the .bash configuration file for the account, using the following 3 environment variables (ANT_HOME is used by the ANT compiler, if you are not writing code, your JAVA_HOME will point at the JRE, not the JDK, and you won’t need the ANT_HOME path at all):
vi ~/.bash_profile export JAVA_HOME=/opt/java/64/jdk1.7.0_03 export ANT_HOME=/usr/lib/ant/ export CASS_BIN=$HOME/cass-beta1/bin export PATH=$PATH:$ANT_HOME/bin:$CASS_BIN
Make sure there is a location for the cassandra server to write it’s log files. You’ll need your SysAdmin, or root privs, to do this. I set the ownership to root and the user under which I’m currently running cassandra (bigdata):
root:/data/feed/indata# cd /var/log root:/var/log# mkdir cassandra root:/var/log# chown root:bigdata cassandra root:/var/log# chmod 775 cassandra
The following ports need to be opened up, if you are running a firewall on each system (you ARE, right!?!), to allow Cassandra nodes to communicate with each other. This is a snippet from my rules-based firewall control file.
## Cassandra ACCEPT loc $FW tcp 9160,8001,7000,7001 ## OpsCenter ACCEPT loc $FW tcp 8888,61620
This is where the truth is told. The rubber meets the road. The money is placed where your mouth is. Light ’em up!
:~$ cassandra :~$ INFO 23:52:54,232 Logging initialized INFO 23:52:54,236 JVM vendor/version: Java HotSpot(TM) 64-Bit Server VM/1.7.0_03 INFO 23:52:54,237 Heap size: 6291456000/6291456000 [...] INFO 23:52:55,162 Node /10.1.0.23 state jump to normal INFO 23:52:55,163 Bootstrap/Replace/Move completed! Now serving reads.
IT LIVES!! Now start your other node(s), and check to verify you have a complete ring, properly configured. You should see something like this in subsequent nodes, I’ve highlighted the references to the other member node:
[...] INFO 23:54:16,042 Node /10.1.0.23 has restarted, now UP INFO 23:54:16,043 InetAddress /10.1.0.23 is now UP INFO 23:54:16,043 Node /10.1.0.23 state jump to normal INFO 23:54:16,088 Compacted to [/home/bigdata/data/system/LocationInfo/system-LocationInfo-hc-6-Data.db,]. 544 to 413 (~75% of original) bytes for 4 keys at 0.003425MB/s. Time: 115ms. INFO 23:54:16,109 Completed flushing /home/bigdata/data/system/LocationInfo/system-LocationInfo-hc-5-Data.db (163 bytes) INFO 23:54:16,110 Node /10.1.0.26 state jump to normal INFO 23:54:16,111 Bootstrap/Replace/Move completed! Now serving reads.
Run nodetool:
:~$ nodetool -h10.1.0.23 -p 8001 ring
Address DC Rack Status State Load Owns Token
85070591730234615865843651857942052864
10.1.0.23 datacenter1 rack1 Up Normal 17.77 KB 50.00% 0
10.1.0.26 datacenter1 rack1 Up Normal 17.66 KB 50.00% 85070591730234615865843651857942052864
WE HAVE A RING!
NEXT: SETTING UP OPS CENTER
Rubber meeting the road. Time to insert some column families, then some data and finally pull it back off the stack.
First off, the keyspace was already defined, so I’m going to simply list it’s structure:
[default@unknown] describe ip_store;
Keyspace: ip_store:
Replication Strategy: org.apache.cassandra.locator.SimpleStrategy
Durable Writes: true
Options: [replication_factor:2]
With a keyspace ready for some column families, those are created next. Here I’m establishing that there will be 4 families in this single keyspace. This is contrary to suggestions in the High Performance Cassandra Handbook, but follows all other documentation I’ve seen. Considering that this is NOT a production implementation, I’m going to go with a more conventional strategy of organizing related data in the same keyspace.
The first action is to assume the desired keyspace, then add the desired column families:
[default@unknown] use ip_store; Authenticated to keyspace: ip_store [default@ip_store] create column family warehouse with comparator = UTF8Type; 595945d0-71ce-11e1-0000-13393ec611bf Waiting for schema agreement... ... schemas agree across the cluster [default@ip_store] create column family hourly with comparator = UTF8Type; 65ea2170-71ce-11e1-0000-13393ec611bf Waiting for schema agreement... ... schemas agree across the cluster [default@ip_store] create column family daily with comparator = UTF8Type; 6aaeae60-71ce-11e1-0000-13393ec611bf Waiting for schema agreement... ... schemas agree across the cluster [default@ip_store] create column family 30day with comparator = UTF8Type; 7b85bf30-71ce-11e1-0000-13393ec611bf Waiting for schema agreement... ... schemas agree across the cluster
OK, a basic schema has been established. Now.. to load the data. I’ll post the relevant sections of the loader code at a later date. At this point you only need to consider that the loader DOES work and it’s loading data. We’ll look at the extraction of the data following loading a very small set.
time host=10.1.0.23 port=9160 ks=ip_store cf=warehouse ttl=0 datafile=5.ips ant -DclassToRun=loader.bulkIpLoader run
Buildfile: cBuild/build.xml
init:
compile:
[javac] Compiling 1 source file to cBuild/build/classes
dist:
[jar] Building jar: cBuild/dist/lib/cass.jar
run:
[java] ks ip_store
[java] cf warehouse
[java] ttl 0
[java] datafile 5.ips
BUILD SUCCESSFUL
Total time: 1 second
Of the set, there are three unique IPs and 2 are duplicates of other data (IMPORTANT NOTE: The IP’s have been changed to protect the innocent and clueless):
2016468288 1011 suspicious 2012-03-13 18:40:01 2016468288 1011 suspicious 2012-03-13 18:40:02 3149138705 1011 suspicious 2012-03-13 18:40:00 3149138705 1011 suspicious 2012-03-13 18:40:01 2179293112 1011 suspicious 2012-03-13 18:39:59
Having loaded these, I re-launch the command line interface, authenticate to the desired keyspace, and then a VERY important command to set an assumption about how we’re going to reference the keys. If you get a strange error like this “cannot parse ‘187.180.11.17’ as hex bytes“, that means you likely forgot to issue the assumes command. Commands I issued are in bold.
cass Connected to: "ak-ip" on 10.1.0.23/9160 Welcome to Cassandra CLI version 1.0.8 [default@unknown] use ip_store [default@ip_store] assume warehouse keys as utf8; Assumption for column family 'warehouse' added successfully. [default@ip_store] get warehouse['3149138705']; => (column=2012-03-13 18:40:00, value=7b227265706f72746564223a22323031322d30332d31332031383a34383a3031222c22617474726962757465223a22737573706963696f7573222c2270726f705f6964223a2231303131222c2270726f7065727479223a22426f74204375747761696c222c226465746563746564223a22323031322d30332d31332031383a34303a3030222c226d65746164617461223a22222c226970223a223139302e3137342e3235312e313435227d, timestamp=1332168862658) => (column=2012-03-13 18:40:01, value=7b227265706f72746564223a22323031322d30332d31332031383a34383a3031222c22617474726962757465223a22737573706963696f7573222c2270726f705f6964223a2231303131222c2270726f7065727479223a22426f74204375747761696c222c226465746563746564223a22323031322d30332d31332031383a34303a3031222c226d65746164617461223a22222c226970223a223139302e3137342e3235312e313435227d, timestamp=1331689681) Returned 2 results. Elapsed time: 39 msec(s).
There we go. A single key row ip_store[‘warehouse’][‘3149138705’] containing to column records, each with a JSON blob within it. Now.. the next step, to set the assumption of utf8 when recalling the records and get output mere mortals such as yourselves can understand.
[default@ip_store] assume warehouse validator as ascii;
Assumption for column family 'warehouse' added successfully.
[default@ip_store] t warehouse['3149138705'];
=> (column=2012-03-13 18:40:00,
value={
"reported":"2012-03-13 18:48:01",
"attribute":"suspicious",
"prop_id":"1011",
"detected":"2012-03-13 18:40:00",
"ip":"187.180.11.17"
}, timestamp=1331689680)
=> (column=2012-03-13 18:40:01,
value={
"reported":"2012-03-13 18:48:01",
"attribute":"suspicious",
"prop_id":"1011",
"detected":"2012-03-13 18:40:01",
"ip":"187.180.11.17"
}, timestamp=1331689681)
Returned 2 results.
Elapsed time: 2 msec(s).
There is it! Data written, data read. Now, it’s up to you to think about how you might use this simple, flexible and powerful storage engine to solve your business needs.
Dropping a an entire keyspace using the cassandra-cli is exceptionally simple.
First, access your cluster using the cli. I have an alias in my .bash_profile so I only need to type ‘cass’ to access the clid. In an attempt to be helpful though, I shall show the full command syntax for my environment. Your host and port may vary.
alias cass='cassandra-cli -h 10.1.0.26'
In this example, I am going to drop the keyspace I was loading with test data in previous posts, ks33.
hpcass: ~$ cass Connected to: "Test1" on 10.1.0.23/9160 Welcome to Cassandra CLI version 1.0.8 Type 'help;' or '?' for help. Type 'quit;' or 'exit;' to quit. DROP keyspace ks33; 07ad5e00-7120-11e1-0000-13393ec611bd Waiting for schema agreement... ... schemas agree across the cluster [default@unknown]
That’s all there was to it. Keyspace destroyed.
PREV: Re-Configuring an Empty Cassandra Cluster
Time for the rubber to meet the road. Get some data loaded and validate the theoretical concepts garnered from the documentation consumed.
This is an record example (IP’s have been changed to protect the clueless):
ip_key: 1598595809
ip: 10.2.162.225
prop_id: 1033
property: Bad Stuff
threat: 1
attribute: suspicious
meta: 10.25.112.7
detected: 2012-01-05 15:17:14
detected_sec: 1325805434
reported: 2012-01-06 01:44:02
reported_sec: 1325843042
Preliminary model concept centers around the IP, however with over 60,000,000 records there are overlaps, so a single IP is not going to survive as the primary key. Trying to get a distribution out of MySQL takes some time. Here are some distributions by key. Thousands of of events per IP, and this is just a short 1 month window:
+------------+--------+ | ip_dec | events | +------------+--------+ | 3158358206 | 2705 | | 652542280 | 2506 | | 3495573656 | 2089 | | 3232235778 | 2015 | | 1072721396 | 1528 | | 652542281 | 1432 | | 3232235876 | 1427 | | 3448822506 | 1232 | | 1280052209 | 1106 | | 3232235779 | 1086 | +------------+--------+
Now, Cassandra will support MILLIONS of column items on a single row, thus, this actually might work, and scale without using Super Column Families (SCFs). Using the detected time seconds as the column name with an attribute suffix, then enclosing the data in a JSON blob could provide the required results. Using the datekey as a secondary index across the columns, or using them as a time progression. Concepts that need to be tested, which precisely the task at hand.
Considering that a good detected time is not always available, and the data is processed in batches, there could be a heavy grouping of timestamps. If there are a variety of issues detected on a specific IP, at the same obfuscated time, loss of data will occur. This is certainly NOT the desired result. Given this, the datastamp is not unique enough for a hash structure datastore such as Cassandra, without using SCFs.
A structure such as this could deliver the required granularity:
ipstore[$ipkey][$timekey][$propkey] = JSON:{}, JSON:{}, JSON{}... ;
To get started with loading data, wrote a quick test program in Java, compliled it and ran it:
test1.java – source code
public class test1 {
public static void main (String [] args) {
System.out.println("Cassandra Calling!");
}
}
compiling….
java/src/loader1$ javac test1.java -d ../../class/.
executing…
/java/class$ java test1 Cassandra Calling!
Environment confirmed for compiling loader code. With a model in mind…
ipstore[$ipkey][$popkey][$timestamp] = JSON:{}
..and IP data to load,
ipp < get_a_million.sql > a_million_ips.dta cass:~$ ls -l 126180075 2012-03-13 13:06 a_million_ips.dta cass:~$ wc -l a_million_ips.dta 1000001 a_million_ips.dta
...next it's designing the schema builder and loader.
REFERENCE: Setting up a Java build env to prepare for Cassandra development
With the environment confirmed, and a test file (test1.java) written, execute and verify function:
cass:~$ ant -DclassToRun=test1 run
Buildfile: ./build.xml
[...]
run:
[java] This is Java.... drink up!
VERIFIED.
To get moving forward, I created a Utilities class and a DB connector Class. You can look at the source code for those at these two links:
Cassandra DB Connector Source Code
With the code done, need to perform a couple of house keeping tasks to get it prepared for loading.
Adding the ks33 keyspace
[default@unknown] create keyspace ks33: c7944700-6e2e-11e1-0000-13393ec611bd Waiting for schema agreement... ... schemas agree across the cluster [default@unknown] use ks33; Authenticated to keyspace: ks33
Adding the cf33 ColumnFamily to ks33 Keyspace:
[default@ks33] create column family cf33 with comparator = UTF8Type; 2501f8b0-6e2f-11e1-0000-13393ec611bd Waiting for schema agreement... ... schemas agree across the cluster
Next, to load 100 trial rows. Here is a link to the source code:
Source for useMultiGet (tba)
hpcass@feed0:~/cassIP/java/cBuild$ host=10.1.0.123 port=9160 inserts=100 ks=ks33 cf=cf33 ant -DclassToRun=c01.useMultiGet run
Buildfile: /home/hpcass/cassIP/java/cBuild/build.xml
init:
compile:
[javac] Compiling 1 source file to /home/hpcass/cassIP/java/cBuild/build/classes
dist:
[jar] Building jar: /home/hpcass/cassIP/java/cBuild/dist/lib/cassIP.jar
run:
[java] get time 89062577
[java] mget time 494039096
BUILD SUCCESSFUL
Here are some results from multi-get tests. It's actually the inverse of my hope, the multi-get seems to rapidly lose it's benefit.
5 Item Slices (1000 item dataset)
=========================================================
run: RUN 1 RUN 2 RUN 3
[java] get time 339041199 436440551 358115310
[java] mget time 172484370 174690508 182833140
10 Item Slices (1000 item dataset)
=========================================================
run: RUN 1 RUN 2 RUN 3
[java] get time 346512511 332820479 314136351
[java] mget time 394049160 251152592 234719383
25 Item Slices (1000 item dataset)
=========================================================
run: RUN 1 RUN 2 RUN 3
[java] get time 335286775 293802010 295948562
[java] mget time 464933443 324505741 312226035
What I didn't expect to see, based on the information in the 'High Performance
Cookbook, was rapid fall-off in performance, and in face in all cases in the
slices of size 25 inverted the performance, showing that it became worse.
2 Item Slices (1000 item dataset)
=========================================================
run: RUN 1 RUN 2 RUN 3
[java] get time 285509637 331970814 317512021
[java] mget time 104567639 96477512 124040195
One thing I didn't think of testing was doing a slice of size 1, and see if maybe part of the perceived performance in the lower slices is really cache hits. AH! Look at this, it looks like the *test* is highly suspect at best. I think this shows some evidence the performance 'benefit' of the multi-get is really a cache hit artifact from extracting the exact same data a second time:
host=10.1.0.123 port=9160 inserts=1000 ks=ks33 cf=cf33 slice=1 ant -DclassToRun=c01.useMultiGet run
Buildfile: /home/hpcass/cassIP/java/cBuild/build.xml
1 Item Slices (1000 item dataset)
=========================================================
run: RUN 1 RUN 2 RUN 3
[java] get time 295158535 298466321 283438099
[java] mget time 109982545 103658894 98260286
This demonstrator failure to perform, is not a failure in and of itself. It's provided useful information regarding some concepts recommended in some documentation, but may not really be a true best practice. I long ago developed a healthy skepticism of expert advice in lieu of verification.
PREV: Setting up a Java build env to prepare for Cassandra development
After doing more research, I decided the Ordered Partitioning was not going to buy me anything but a lop-sided distribution. Looking at this (it’s a case of IP distributions, not hostnames as originally envisioned, that will be a later evaluation).
I’d have 3 very heavy nodes and 3 very light nodes. This is a distribution of real world data.
Node: Range: Dist: ====== ================================== ====== node00 0.0.0.0 to 42.170.170.171 6 % node01 42.170.170.172 to 85.85.85.87 32 % node02 85.85.85.88 to 128.0.0.3 34 % node03 128.0.0.4 to 170.170.170.175 2 % node04 170.170.170.176 to 213.85.85.91 21 % node05 213.85.85.92 to 255.255.255.255 3 %
Goofing around with pseudo random key naming to get a better balance only does one thing, make the keys I wanted to use (IPs) basically worthless, so the ordering is wrecked regardless. Random partitioning is the default configuration for Cassandra, so, that’s what I plan to use. Problem is, I’d built out this specific node set with this setting first:
– ByteOrderedPartitioner orders rows lexically by key bytes. BOP allows scanning rows in key order, but the ordering can generate hot spots for sequential insertion workloads.
I re-set the configurations to use the default instead:
– RandomPartitioner distributes rows across the cluster evenly by md5. When in doubt, this is the best option.
After changing the configuration from ByteOrderedPartitioner to RandomPartitioner and restarting the first node.. I am greeted with this happy message:
ERROR 13:03:36,113 Fatal exception in thread Thread[SSTableBatchOpen:3,5,main]
java.lang.RuntimeException: Cannot open /home/hpcass/data/node00/system/Versions-hc-3 because partitioner does not match org.apache.cassandra.dht.RandomPartitioner
In fact I’m greeted with a lot of them. This is then followed by what looks like possibly.. normal startup messaging?
INFO 13:03:36,166 Creating new commitlog segment /home/hpcass/commitlog/node00/CommitLog-1331586216166.log INFO 13:03:36,175 Couldn't detect any schema definitions in local storage. INFO 13:03:36,175 Found table data in data directories. Consider using the CLI to define your schema. INFO 13:03:36,197 Replaying /home/hpcass/commitlog/node00/CommitLog-1331328557751.log INFO 13:03:36,222 Finished reading /home/hpcass/commitlog/node00/CommitLog-1331328557751.log INFO 13:03:36,227 Enqueuing flush of Memtable-LocationInfo@1762056890(213/266 serialized/live bytes, 7 ops) INFO 13:03:36,228 Writing Memtable-LocationInfo@1762056890(213/266 serialized/live bytes, 7 ops) INFO 13:03:36,228 Enqueuing flush of Memtable-Versions@202783062(83/103 serialized/live bytes, 3 ops) INFO 13:03:36,277 Completed flushing /home/hpcass/data/node00/system/LocationInfo-hc-16-Data.db (377 bytes) INFO 13:03:36,285 Writing Memtable-Versions@202783062(83/103 serialized/live bytes, 3 ops) INFO 13:03:36,357 Completed flushing /home/hpcass/data/node00/system/Versions-hc-4-Data.db (247 bytes) INFO 13:03:36,358 Log replay complete, 9 replayed mutations INFO 13:03:36,366 Cassandra version: 1.0.8 INFO 13:03:36,366 Thrift API version: 19.20.0 INFO 13:03:36,367 Loading persisted ring state INFO 13:03:36,384 Starting up server gossip INFO 13:03:36,386 Enqueuing flush of Memtable-LocationInfo@846275759(88/110 serialized/live bytes, 2 ops) INFO 13:03:36,386 Writing Memtable-LocationInfo@846275759(88/110 serialized/live bytes, 2 ops) INFO 13:03:36,440 Completed flushing /home/hpcass/data/node00/system/LocationInfo-hc-17-Data.db (196 bytes) INFO 13:03:36,446 Starting Messaging Service on port 7000 INFO 13:03:36,452 Using saved token 0 INFO 13:03:36,453 Enqueuing flush of Memtable-LocationInfo@59584763(38/47 serialized/live bytes, 2 ops) INFO 13:03:36,454 Writing Memtable-LocationInfo@59584763(38/47 serialized/live bytes, 2 ops) INFO 13:03:36,556 Completed flushing /home/hpcass/data/node00/system/LocationInfo-hc-18-Data.db (148 bytes) INFO 13:03:36,558 Node /10.1.0.23 state jump to normal INFO 13:03:36,558 Bootstrap/Replace/Move completed! Now serving reads. INFO 13:03:36,559 Will not load MX4J, mx4j-tools.jar is not in the classpath INFO 13:03:36,587 Binding thrift service to /10.1.0.23:9160 INFO 13:03:36,590 Using TFastFramedTransport with a max frame size of 15728640 bytes. INFO 13:03:36,593 Using synchronous/threadpool thrift server on /10.1.0.23 : 9160 INFO 13:03:36,593 Listening for thrift clients...
Despite the fatal errors, it does seem to have restarted the cluster with the new Partition engine:
Address DC Rack Status State Load Owns Token
7169015515630842424558524306038950250903273734
10.1.0.27 datacenter1 rack1 Down Normal ? 93.84% -2742379978670691477635174047251157095949195165
10.1.0.23 datacenter1 rack1 Up Normal 15.79 KB 86.37% 0
10.1.0.26 datacenter1 rack1 Down Normal ? 77.79% 896682280808232140910919391534960240163386913
10.1.0.24 datacenter1 rack1 Up Normal 15.79 KB 53.08% 1927726543429020693034590137790785169819652674
10.1.0.25 datacenter1 rack1 Up Normal 15.79 KB 35.85% 6138493926725652010223830601932265434881918085
10.1.0.28 datacenter1 rack1 Down Normal ? 53.08% 716901551563084242455852430603895025090327373
Starting up the other three nodes (example:)
INFO 14:10:06,663 Node /10.1.0.25 has restarted, now UP INFO 14:10:06,663 InetAddress /10.1.0.25 is now UP INFO 14:10:06,664 Node /10.1.0.25 state jump to normal INFO 14:10:06,664 Node /10.1.0.24 has restarted, now UP INFO 14:10:06,665 InetAddress /10.1.0.24 is now UP INFO 14:10:06,665 Node /10.1.0.24 state jump to normal INFO 14:10:06,666 Node /10.1.0.23 has restarted, now UP INFO 14:10:06,667 InetAddress /10.1.0.23 is now UP INFO 14:10:06,668 Node /10.1.0.23 state jump to normal INFO 14:10:06,760 Completed flushing /home/hpcass/data/node01/system/LocationInfo-hc-18-Data.db (166 bytes) INFO 14:10:06,762 Node /10.1.0.26 state jump to normal INFO 14:10:06,763 Bootstrap/Replace/Move completed! Now serving reads. INFO 14:10:06,764 Will not load MX4J, mx4j-tools.jar is not in the classpath INFO 14:10:06,862 Binding thrift service to /10.1.0.26:9160
Re-checking the ring displays:
Address DC Rack Status State Load Owns Token
7169015515630842424558524306038950250903273734
10.1.0.27 datacenter1 rack1 Up Normal 11.37 KB 93.84% -2742379978670691477635174047251157095949195165
10.1.0.23 datacenter1 rack1 Up Normal 15.79 KB 86.37% 0
10.1.0.26 datacenter1 rack1 Up Normal 18.38 KB 77.79% 896682280808232140910919391534960240163386913
10.1.0.24 datacenter1 rack1 Up Normal 15.79 KB 53.08% 1927726543429020693034590137790785169819652674
10.1.0.25 datacenter1 rack1 Up Normal 15.79 KB 35.85% 6138493926725652010223830601932265434881918085
10.1.0.28 datacenter1 rack1 Up Normal 15.79 KB 53.08% 7169015515630842424558524306038950250903273734
Switching partition engine appears to be easy enough. What I suspect however (and I’ve not confirmed this, is that the data would have been compromised or likely destroyed in this process. The documentation I’ve read so far indicated that you could not do this. Once setup with a specific partitioning engine that cluster was bound to it.
My conclusion is that if you have not yet started to saturate your cluster with data, and you wish to change the partitioning engine, it would appear that the right time to do it is now.. before you start to load data.
I plan to test this theory later after the first trial data load to see if in fact it mangles the information. More to follow!
Despite the information that I thought nodetool was telling me, my cluster was unusable because of the partitioner change. What is the last step required to change partition? NUKE THE DATA. Unfun.. but that is what I need to do.
Having 6 nodes means 6 times the fun. Here is the kicker though, I’ll just move the data aside and re-construct, and that will let me swap it back in if I decided to go back and forth testing the impacts of Random vs. Ordered for my needs. Will I get away with this? I don’t know. That won’t stop me from trying!
The data was stored in ~/data/node00 (node## etc.). This is all I did:
mv data/node00 data/node00-bop # bop = btye order partition.
Restarted node00:
hpcass:~/nodes$ node00/bin/cassandra -f INFO 16:38:46,525 Logging initialized INFO 16:38:46,529 JVM vendor/version: OpenJDK 64-Bit Server VM/1.6.0_0 INFO 16:38:46,529 Heap size: 6291456000/6291456000 INFO 16:38:46,529 Classpath: node00/bin/../conf:node00/bin/../build/classes/main:node00/bin/../build/classes/thrift:node00/bin/../lib/antlr-3.2.jar:node00/bin/../lib/apache-cassandra-1.0.8.jar:node00/bin/../lib/apache-cassandra-clientutil-1.0.8.jar:node00/bin/../lib/apache-cassandra-thrift-1.0.8.jar:node00/bin/../lib/avro-1.4.0-fixes.jar:node00/bin/../lib/avro-1.4.0-sources-fixes.jar:node00/bin/../lib/commons-cli-1.1.jar:node00/bin/../lib/commons-codec-1.2.jar:node00/bin/../lib/commons-lang-2.4.jar:node00/bin/../lib/compress-lzf-0.8.4.jar:node00/bin/../lib/concurrentlinkedhashmap-lru-1.2.jar:node00/bin/../lib/guava-r08.jar:node00/bin/../lib/high-scale-lib-1.1.2.jar:node00/bin/../lib/jackson-core-asl-1.4.0.jar:node00/bin/../lib/jackson-mapper-asl-1.4.0.jar:node00/bin/../lib/jamm-0.2.5.jar:node00/bin/../lib/jline-0.9.94.jar:node00/bin/../lib/json-simple-1.1.jar:node00/bin/../lib/libthrift-0.6.jar:node00/bin/../lib/log4j-1.2.16.jar:node00/bin/../lib/servlet-api-2.5-20081211.jar:node00/bin/../lib/slf4j-api-1.6.1.jar:node00/bin/../lib/slf4j-log4j12-1.6.1.jar:node00/bin/../lib/snakeyaml-1.6.jar:node00/bin/../lib/snappy-java-1.0.4.1.jar INFO 16:38:46,531 JNA not found. Native methods will be disabled. INFO 16:38:46,538 Loading settings from file:/home/hpcass/nodes/node00/conf/cassandra.yaml INFO 16:38:46,635 DiskAccessMode 'auto' determined to be mmap, indexAccessMode is mmap INFO 16:38:46,645 Global memtable threshold is enabled at 2000MB INFO 16:38:46,839 Creating new commitlog segment /home/hpcass/commitlog/node00/CommitLog-1331599126839.log INFO 16:38:46,848 Couldn't detect any schema definitions in local storage. INFO 16:38:46,849 Found table data in data directories. Consider using the CLI to define your schema. INFO 16:38:46,863 Replaying /home/hpcass/commitlog/node00/CommitLog-1331597615041.log INFO 16:38:46,887 Finished reading /home/hpcass/commitlog/node00/CommitLog-1331597615041.log INFO 16:38:46,892 Enqueuing flush of Memtable-LocationInfo@1834491520(98/122 serialized/live bytes, 4 ops) INFO 16:38:46,893 Enqueuing flush of Memtable-Versions@875509103(83/103 serialized/live bytes, 3 ops) INFO 16:38:46,894 Writing Memtable-LocationInfo@1834491520(98/122 serialized/live bytes, 4 ops) INFO 16:38:47,001 Completed flushing /home/hpcass/data/node00/system/LocationInfo-hc-1-Data.db (208 bytes) INFO 16:38:47,009 Writing Memtable-Versions@875509103(83/103 serialized/live bytes, 3 ops) INFO 16:38:47,057 Completed flushing /home/hpcass/data/node00/system/Versions-hc-1-Data.db (247 bytes) INFO 16:38:47,057 Log replay complete, 6 replayed mutations INFO 16:38:47,066 Cassandra version: 1.0.8 INFO 16:38:47,066 Thrift API version: 19.20.0 INFO 16:38:47,067 Loading persisted ring state INFO 16:38:47,070 Starting up server gossip INFO 16:38:47,091 Enqueuing flush of Memtable-LocationInfo@952443392(88/110 serialized/live bytes, 2 ops) INFO 16:38:47,092 Writing Memtable-LocationInfo@952443392(88/110 serialized/live bytes, 2 ops) INFO 16:38:47,141 Completed flushing /home/hpcass/data/node00/system/LocationInfo-hc-2-Data.db (196 bytes) INFO 16:38:47,149 Starting Messaging Service on port 7000 INFO 16:38:47,155 Using saved token 0 INFO 16:38:47,157 Enqueuing flush of Memtable-LocationInfo@1623810826(38/47 serialized/live bytes, 2 ops) INFO 16:38:47,157 Writing Memtable-LocationInfo@1623810826(38/47 serialized/live bytes, 2 ops) INFO 16:38:47,237 Completed flushing /home/hpcass/data/node00/system/LocationInfo-hc-3-Data.db (148 bytes) INFO 16:38:47,239 Node /10.1.0.23 state jump to normal INFO 16:38:47,240 Bootstrap/Replace/Move completed! Now serving reads. INFO 16:38:47,241 Will not load MX4J, mx4j-tools.jar is not in the classpath INFO 16:38:47,269 Binding thrift service to /10.1.0.23:9160 INFO 16:38:47,272 Using TFastFramedTransport with a max frame size of 15728640 bytes. INFO 16:38:47,274 Using synchronous/threadpool thrift server on /10.1.0.23 : 9160 INFO 16:38:47,275 Listening for thrift clients... ^Z [1]+ Stopped node00/bin/cassandra -f hpcass:~/nodes$ bg [1]+ node00/bin/cassandra -f &
With the process backgrounded, checked the files in the new data directory for my node:
hpcass:~/data/node00$ ls -1 system LocationInfo-hc-1-Data.db LocationInfo-hc-1-Digest.sha1 LocationInfo-hc-1-Filter.db LocationInfo-hc-1-Index.db LocationInfo-hc-1-Statistics.db LocationInfo-hc-2-Data.db LocationInfo-hc-2-Digest.sha1 LocationInfo-hc-2-Filter.db LocationInfo-hc-2-Index.db LocationInfo-hc-2-Statistics.db LocationInfo-hc-3-Data.db LocationInfo-hc-3-Digest.sha1 LocationInfo-hc-3-Filter.db LocationInfo-hc-3-Index.db LocationInfo-hc-3-Statistics.db Versions-hc-1-Data.db Versions-hc-1-Digest.sha1 Versions-hc-1-Filter.db Versions-hc-1-Index.db Versions-hc-1-Statistics.db
Following that clearing and rebuild, I see the node tool results look a lot better:
hpcass@feed0:~/nodes$ cass00/bin/nodetool -h localhost ring
Address DC Rack Status State Load Owns Token
6138493926725652010223830601932265434881918085
10.1.0.23 datacenter1 rack1 Up Normal 15.68 KB 33.29% 0
10.1.0.24 datacenter1 rack1 Up Normal 18.34 KB 30.87% 1927726543429020693034590137790785169819652674
10.1.0.25 datacenter1 rack1 Up Normal 18.34 KB 35.85% 6138493926725652010223830601932265434881918085
After resetting the old numerated nodes, I had a complete disaster! Negative node tokens? How did that happen? Restarts did nothing to fix this either.
Address DC Rack Status State Load Owns Token
7169015515630842424558524306038950250903273734
10.1.0.27 datacenter1 rack1 Up Normal 15.79 KB 93.84% -2742379978670691477635174047251157095949195165
10.1.0.23 datacenter1 rack1 Up Normal 15.79 KB 86.37% 0
10.1.0.26 datacenter1 rack1 Up Normal 15.79 KB 77.79% 896682280808232140910919391534960240163386913
10.1.0.24 datacenter1 rack1 Up Normal 15.79 KB 53.08% 1927726543429020693034590137790785169819652674
10.1.0.25 datacenter1 rack1 Up Normal 15.79 KB 35.85% 6138493926725652010223830601932265434881918085
10.1.0.28 datacenter1 rack1 Up Normal 15.79 KB 53.08% 7169015515630842424558524306038950250903273734
To resolve this, I simply re-ran my token generator to get a new set of tokens:
node00 10.1.0.23 token: 0 node01 10.1.0.26 token: 28356863910078205288614550619314017621 node02 10.1.0.24 token: 56713727820156410577229101238628035242 node03 10.1.0.27 token: 85070591730234615865843651857942052863 node04 10.1.0.25 token: 113427455640312821154458202477256070485 node05 10.1.0.28 token: 141784319550391026443072753096570088106
Followed by manually setting the tokens in the ring:
bin/nodetool -h 10.1.0.24 move 56713727820156410577229101238628035242 bin/nodetool -h 10.1.0.25 move 113427455640312821154458202477256070485 bin/nodetool -h 10.1.0.26 move 28356863910078205288614550619314017621 bin/nodetool -h 10.1.0.27 move 85070591730234615865843651857942052863 bin/nodetool -h 10.1.0.28 move 141784319550391026443072753096570088106
This.. gave me the results I was expecting!
Address DC Rack Status State Load Owns Token
141784319550391026443072753096570088106
10.1.0.23 datacenter1 rack1 Up Normal 24.95 KB 16.67% 0
10.1.0.26 datacenter1 rack1 Up Normal 20.72 KB 16.67% 28356863910078205288614550619314017621
10.1.0.24 datacenter1 rack1 Up Normal 25.1 KB 16.67% 56713727820156410577229101238628035242
10.1.0.27 datacenter1 rack1 Up Normal 13.38 KB 16.67% 85070591730234615865843651857942052863
10.1.0.25 datacenter1 rack1 Up Normal 25.1 KB 16.67% 113427455640312821154458202477256070485
10.1.0.28 datacenter1 rack1 Up Normal 25.14 KB 16.67% 141784319550391026443072753096570088106
Now, the question of actually connecting to the cluster can be answered. Pick one of the nodes and ports to connect too. I picked node00 on .23 (cli defaulted to port 9160 so I didn’t have to specify that):
node00/bin/cassandra-cli -h 10.1.0.23 Connected to: "test-ip" on 10.1.0.23/9160 Welcome to Cassandra CLI version 1.0.8 Type 'help;' or '?' for help. Type 'quit;' or 'exit;' to quit.
The big problem I had, was that the cli never did seem to respond. The trick is to end your command with a semi-colon. That might seem obvious to you, and generally obvious to me.. but I’d not seen the docs actually call out that little FACT.
[default@unknown] show cluster name; test-ip
Created a test column family from the helpful Cassandra Wiki.
create keyspace Twissandra;
Keyspace names must be case-insensitively unique ("Twissandra" conflicts with "Twissandra")
[default@unknown]
[default@unknown]
[default@unknown] create column family User with comparator = UTF8Type;
Not authenticated to a working keyspace.
[default@unknown] use Twissandra;
Authenticated to keyspace: Twissandra
[default@Twissandra] create column family User with comparator = UTF8Type;
adf453a0-6cb0-11e1-0000-13393ec611bd
Waiting for schema agreement...
... schemas agree across the cluster
[default@Twissandra]
AND WE’RE OFF!! Next article will cover actually finishing up this last test and then adding real data. MORE TO COME!!
NEXT: Cassandra – A Use case examined (IP data)
Getting it all ready…
PREV: Cassandra and Big Data – building a single-node “cluster”
First, I wanted to see how much of a system footprint 3 instances of Cassandra had on this little system. Here you can see the 3 instances patiently waiting for something todo. Sitting idle for about 24 hours (note, TIME+ is system time, not wall clock), total memory utilization has crept up from 11% to 14% per process.
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
4554 bigdata 20 0 891m 134m 4388 S 7.6 14.4 7:47.96 java
4632 bigdata 20 0 917m 133m 4340 S 0.7 14.3 7:45.64 java
4593 bigdata 20 0 896m 133m 4168 S 0.3 14.3 7:40.37 java
Keep in mind this test box has a single core CPU with a whopping 1GB of memory. If I can get it to work on this box without pushing it over, you should be able to run a single instance on any box with a reasonable expectation of function.
The data model I wanted to use is pretty basic: IP traffic, consisting of the following elements:
* IPv4 address
* destination port
* timestamp
* TTL (this is a Cassandra construct to allow auto-tombstoning of data when it’s usefulness has expired)
To get this data, I’m thinking of simply running TCPdump on a box, or possibly my laptop, to generate some traffic, then stream that into a program to insert into Cassandra as fast as the packets go by.
With the limited disk space on the box (see below) I can’t run it indefinitely, but I should be able to run it for an afternoon to load a keyspace, then start to figure out how to get the data back out!
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/sda1 75956320 4344788 67753152 7% /
none 470324 640 469684 1% /dev
none 478024 420 477604 1% /dev/shm
none 478024 108 477916 1% /var/run
none 478024 0 478024 0% /var/lock
One thing I could do is load the data into the database, then run a 2nd pass processor on it and mutate the data with reverse lookups. Sort of a poor-man’s Wireshark type of tool. Now, if I wire this into my eventually to be setup RPZ enabled DNS resolver, I could track all data on my network, including all the requests from my Apple TV device. It might be interesting to see what it’s *really* doing on the network.
Before staring to code though, it looks like I need to ensure my JDK / Java libs are all up to date… and also to facilitate working with the documentation I’m reviewing.. Apache ANT will be installed too.
Java JDK – Java Software Development Kit
The JDK is a development environment for building applications, applets, and components using the Java programming language.
The JDK includes tools useful for developing and testing programs written in the Java programming language and running on the Java&™; platform.
Package URL: http://download.oracle.com/otn-pub/java/jdk/7u3-b04/jdk-7u3-linux-x64.tar.gz
mkdir jdk
cd jdk
wget http://download.oracle.com/otn-pub/java/jdk/7u3-b04/jdk-7u3-linux-x64.tar.gz
Extract the package:
tar xvzf jdk-7u3-linux-x64.tar.gz
Although I could simply run the JDK from the local user location, I decided to go for the ‘System Install’ option, and created a jdk location in user/lib, then copied the parts there according to the info in the docs. In this case I just downloaded the JRE again… you could skip that step and copy the .gz file already downloaded above. Your call.
sudo mkdir /usr/lib/jdk
cd /usr/lib/jdk
sudo wget http://download.oracle.com/otn-pub/java/jdk/7u3-b04/jdk-7u3-linux-x64.tar.gz
sudo tar xvzf jdk-7u3-linux-x64.tar.gz
sudo rm jdk-7u3-linux-x64.tar.gz
Oracle’s page says that it’s now ‘installed’ but I suspect there are a more than a few more steps required here! This is almost as good as Oracle technical support… I’ll try to be a little more helpful.
Setting the path in my ~/.bash_profile will resolve the path issue for Ant and JUnit. This is what I set in my file:
export JAVA_HOME=/usr/lib/jdk/jdk1.7.0_03
ANT – Apache Ant
Apache Ant is a Java library and command-line tool whose mission is to drive processes described in build files as targets and extension points dependent upon each other. The main known usage of Ant is the build of Java applications. Ant supplies a number of built-in tasks allowing to compile, assemble, test and run Java applications. Ant can also be used effectively to build non Java applications, for instance C or C++ applications. More generally, Ant can be used to pilot any type of process which can be described in terms of targets and tasks.
Package URL: http://www.carfab.com/apachesoftware//ant/binaries/apache-ant-1.8.3-bin.tar.gz
mkdir ant
cd ant
wget http://www.carfab.com/apachesoftware//ant/binaries/apache-ant-1.8.3-bin.tar.gz
Extract the package:
tar xvzf apache-ant-1.8.3-bin.tar.gz
Docs inside Ant say to go back to the web and read the installation instructions, located here: http://ant.apache.org/manual/install.html#installing I happen to like where my ant stuff was installed so I’m going to set ANT_HOME in my ~/.bash_profile to the location where I extracted the stuff. Ideal? Probably not but I’m doing this research on a perfectly good Saturday.. you get what you’re paying for.
export ANT_HOME=/home/bigdata/ant/apache-ant-1.8.3
export PATH=$PATH:$ANT_HOME/bin
Testing to see if the paths and parts are there worked. This error is actually expected (we’ll write the build.xml later).
$ ant
Buildfile: build.xml does not exist!
Build failed
JUnit – Test framework for test based development
JUnit is a simple framework to write repeatable tests. It is an instance of the xUnit architecture for unit testing frameworks.
mkdir junit
cd junit
wget https://github.com/downloads/KentBeck/junit/junit-4.10.jar
wget https://github.com/downloads/KentBeck/junit/junit4.10.zip
Extract the source package, in case I need it:
unzip junit4.10.zip
I can’t say this is the best way to do this, it’s cookie-cutter implementation from documentation. If you see something that does not make sense or is flat out stupid, post comment and let me know!
Create primary development folder and expected sub-folders. You’re naming conventions may vary:
mkdir cBuild
mkdir cBuild/src
mkdir cBuild/src/{java,test}
mkdir cBuild/lib
Populate the lib with libraries from the Cassandra distribution and Junit.
cp cassA-1.0.8/lib/*.jar cBuild/lib/.
cp junit/*.jar cBuild/lib/.
To employ JUnit testing harness via Ant Java builder, a build.xml file is required in the cBuild base directory. Here are sample contents. You’re paths may differ if you went your own way on the directories.
vi cBuild/build.xml
<project name="jCas" default="dist" basedir=".">
<property name="src" location="src/java"/>
<property name="test.src" location="src/test"/>
<property name="build" location="build"/>
<property name="build.classes" location="build/classes"/>
<property name="test.build" location="build/test"/>
<property name="dist" location="dist"/>
<property name="lib" location="lib"/>
<!-- Tags used by Ant to help build paths, most useful when multiple .jar files are required -->
<path id="jCas.classpath">
<pathelement location="${build.classes}"/>
<fileset dir="${lib}" includes="*.jar"/>
</path>
<!-- exclude test cases from the final .jar file, this defines that policy -->
<path id="jCas.test.classpath">
<pathelement location="${test.build}"/>
<path refid="jCas.classpath"/>
</path>
<!-- Define the 'init' target, used by other build phases -->
<target name="init">
<mkdir dir="${build}"/>
<mkdir dir="${build.classes}"/>
<mkdir dir="${test.build}"/>
</target>
<!-- 'compile' target -->
<target name="compile" depends="init">
<javac srcdir="${src}" destdir="${build.classes}">
<classpath refid="jCas.classpath"/>
</javac>
</target>
<!-- 'test compile' target -->
<target name="compile-test" depends="init">
<javac srcdir="${test.src}" destdir="${test.build}">
<classpath refid="jCas.test.classpath"/>
</javac>
</target>
<!-- setup policies that tell JUnit to execute tests on files in test that end with .class -->
<target name="test" depends="compile-test,compile">
<junit printsummary="yes" showoutput="true">
<classpath refid="jCas.test.classpath"/>
<batchtest>
<fileset dir="${test.build}" includes="**/Test.class"/>
</batchtest>
</junit>
</target>
<!-- on a good build, dist target creates final JAR jCas.tar -->
<target name="dist" depends="compile">
<mkdir dir="${dist}/lib"/>
<jar jarfile="${dist}/lib/jCas.jar" basedir="${build.classes}"/>
</target>
<!-- run target allows execution of the built classes -->
<target name="run" depends="dist">
<java classname="${classToRun}">
<classpath refid="jCas.classpath"/>
</java>
</target>
<!-- clean target gets rid of all the left over files from builds -->
<target name="clean">
<delete dir="${build}"/>
<delete dir="${dist}"/>
</target>
</project>
NOTE!. There is a bug in Ant 1.8 that requires the addition of this element, or you will be plagued with nasty warnings:
...
This is the proper way to modify that above two javac blocks to include these element:
<javac srcdir="${src}" destdir="${build.classes} includeantruntime="false"">
<javac srcdir="${test.src}" destdir="${test.build}" includeantruntime="false">
Testing this build environment
Having created the build.xml file, it needs to be tested to make sure it even works.
Create a test case and build case
cd cBuild/src
vi Test.java
import junit.framework.*;
public class Test extends TestCase {
public void test() {
assertEquals( "Equality Test", 0, 0);
}
}
Create a really simple program..
vi X1.java
public class X1 {
public static void main (String [] args) {
System.out.println("This is Java.... drink up!");
}
}
Now the rubber meets the road if everything is setup properly and we can build a file!
Run ant with target set to 'test'
~/cBuild$ ant test Buildfile: /home/bigdata/cBuild/build.xml init: compile-test: compile: [javac] Compiling 1 source file to /home/bigdata/cBuild/build/classes test: BUILD SUCCESSFUL Total time: 7 seconds
Run ant with target set to 'diet'
~/cBuild$ ~/cBuild$ ant dist Buildfile: /home/bigdata/cBuild/build.xml init: compile: dist: [jar] Building jar: /home/bigdata/cBuild/dist/lib/jCas.jar BUILD SUCCESSFUL Total time: 1 second
It's a good idea to check your .jar to make sure your class is actually in it. Ant, for some reason beyond understanding or logic, WON'T let you know if your lib was skipped (had it happen in my first build.. exceptionally ungood).
~/cBuild$ jar -tf dist/lib/jCas.jar
META-INF/
META-INF/MANIFEST.MF
X1.class
As you can see, there is no Whiskey, but X1 is in the jar.
RUN!!!
~/cBuild$ ant -DclassToRun=X1 run Buildfile: /home/bigdata/cBuild/build.xml init: compile: dist: run: [java] This is Java.... drink up! BUILD SUCCESSFUL Total time: 1 second
SUCCESS!!!
All told it took me about 3 1/2 hours to get this setup, parts installed, these notes written up and a SIMPLE Java program executed. So.. let your own expectations accordingly. Hopefully you'll save a lot of time with the build.xml file.. I typed that in char for char. You could just do a cut-paste, fix up anything you don't like in my path names and let it rip.
Good luck.. more to follow on Cassandra!!! (even though this post was more about getting ready to write code to access it).
Cassandra – Getting off the ground.
Continuation of post: Apache Cassandra Project – processing “Big Data”
While researching a project on Big Data services, I knew that I’d need a multi-node cluster to experiment with, but a pile of hardware was not immediately available.
Using the VERY helpful book Cassandra High Performance Cookbook I was able to build a 3 node cluster on a single machine. This is how I did it:
For this cluster test example, I am using Ubunto 10, with following JVM
JVM vendor/version: OpenJDK 64-Bit Server VM/1.6.0_22
Downloaded Cassandra 1.0.8 package from here:
http://apache.mirrors.tds.net//cassandra/1.0.8/apache-cassandra-1.0.8-bin.tar.gz
Created new user on system: bigdata
Create the required base data directories
$ mkdir commitlog,log,data,saved_caches
Moved that package there and started the build
$ cp /tmp/apache-cassandra-1.0.8-bin.tar.gz .
Unzipped and extracted the contents
$ gunzip apache-cassandra-1.0.8-bin.tar.gz $ tar xvf apache-cassandra-1.0.8-bin.tar
Moved the long directory name to first instance cassA-1.0.8
$ mv apache-cassandra-1.0.8 cassA-1.0.8
Extracted again and renamed this to the other two planned instances:
$ tar xfv apache-cassandra-1.0.8-bin.tar $ mv apache-cassandra-1.0.8 cassB-1.0.8 $ tar xfv apache-cassandra-1.0.8-bin.tar $ mv apache-cassandra-1.0.8 cassC-1.0.8
This gave me three packages to build, and each with a unique IP
cassA-1.0.8 10.1.1.101 cassB-1.0.8 10.1.1.102 cassC-1.0.8 10.1.1.103
Edit configuration files in each instance (casaA-1.0.8 used as example:)
$ vi cassA-1.0.8/conf/cassandra.yaml
[...]
# directories where Cassandra should store data on disk.
data_file_directories:
- /home/bigdata/data/cassA
# commit log
commitlog_directory: /home/bigdata/commitlog/cassA
# saved caches
saved_caches_directory: /home/bigdata/saved_caches/cassA
[...]
# If blank, Cassandra will request a token bisecting the range of
# the heaviest-loaded existing node. If there is no load information
# available, such as is the case with a new cluster, it will pick
# a random token, which will lead to hot spots.
initial_token: 0
[...]
# Setting this to 0.0.0.0 is always wrong.
listen_address: 10.1.1.101
[...]
rpc_address: 10.1.1.101
[...]
# seeds is actually a comma-delimited list of addresses.
# Ex: ",,"
- seeds: "10.1.100.101,10.1.100.102,10.1.100.103"
[...]
Setting a separate logfile is recommended. Edit config to set separate log
vi cassA-1.0.8/conf/log4j-server.properties [...] log4j.appender.R.File=/home/bigdata/log/cassA.log [...]
Repeat for instances cassB and cassC, setting the token value for B and C to appropriate values (see Extra Credit below if you need to know how to do *that* part):
#cassB initial_token: 56713727820156410577229101238628035242 #cassC initial_token: 113427455640312821154458202477256070485
To enable the JMX management console, each instance will require it’s own port. Edit the env file to set that up.
vi cassA-1.0.8/conf/cassandra-env.sh [...] # Specifies the default port over which Cassandra will be available for # JMX connections. JMX_PORT="8001" [...]
Repeated for the other two instances, defining 8002 and 8003 respectively.
Now, for the final trick, start up the instances:
cassA-1.0.8/bin/cassandra cassB-1.0.8/bin/cassandra cassC-1.0.8/bin/cassandra
Cluster elements started up, and they can be seen active in the process table here:
$ ps -lf F S UID PID PPID C PRI NI ADDR SZ WCHAN STIME TTY TIME CMD 0 S bigdata 4554 1 2 80 0 - 226846 futex_ 12:13 pts/0 00:00:05 java -ea -XX:+UseThreadPriorities -XX:ThreadPriorityPolicy= 0 S bigdata 4593 1 2 80 0 - 210824 futex_ 12:13 pts/0 00:00:05 java -ea -XX:+UseThreadPriorities -XX:ThreadPriorityPolicy= 0 S bigdata 4632 1 2 80 0 - 226830 futex_ 12:13 pts/0 00:00:05 java -ea -XX:+UseThreadPriorities -XX:ThreadPriorityPolicy= 0 R bigdata 5047 3054 0 80 0 - 5483 - 12:16 pts/0 00:00:00 ps -lf
Finally, to check the status, connect to of the JMX node ports and check the ring. You only need to connect to one of the cluster’s nodes to check the complete cluster’s status:
$ bin/nodetool -h 10.1.100.101 -port 8001 ring
Address DC Rack Status State Load Owns Token
113427455640312821154458202477256070485
10.1.100.101 datacenter1 rack1 Up Normal 21.86 KB 33.33% 0
10.1.100.102 datacenter1 rack1 Up Normal 20.28 KB 33.33% 56713727820156410577229101238628035242
10.1.100.103 datacenter1 rack1 Up Normal 29.1 KB 33.33% 113427455640312821154458202477256070485
Now, that’s a functional 3 instance cluster running on a single node. These are not in separate VMs, and if you wanted to experiment with this on a larger cluster, running multiple instances on multiple VM’s on a single hypervisor.. I don’t really see why you cannot!
In the next article, I’m going to start feeding data into the cluster. Stay tuned for that!
To create the token value I needed for this three ring cluster, I used the following PERL script. BTW, bignum is required unless you want PERL printing these big numbers in scientific notation:
#!/usr/bin/perl
use bignum;
my $nodes = shift;
print "Calculate tokens for $nodes nodes\n";
print "node 0\ttoken: 0\n" unless $nodes;
exit unless $nodes;
my $factor = 2**127;
print "factor = $factor\n";
for (my $i=0;$i<$nodes;$i++) {
my $token = $i * ( $factor / $nodes);
print "node $i\ttoken: $token\n";
}
Running the script for three nodes gave me the following results:
$ ./maketokens.pl 3 Calculate tokens for 3 nodes factor = 170141183460469231731687303715884105728 node 0 token: 0 node 1 token: 56713727820156410577229101238628035242.67 node 2 token: 113427455640312821154458202477256070485.34
If you are setting up a standard mutli-box cluster, make sure you have the following ports opened up on any firewalls. If not, the cluster members wont' find each other:
# TCP port, for commands and data storage_port: 7000 # SSL port, for encrypted communication. Unused unless enabled in # encryption_options ssl_storage_port: 7001
NEXT: Setting up a Java build env to prepare for Cassandra development