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From Apache Wiki <wikidi...@apache.org>
Subject [Tajo Wiki] Update of "GettingStarted" by HyunsikChoi
Date Fri, 05 Apr 2013 02:45:14 GMT
Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Tajo Wiki" for change notification.

The "GettingStarted" page has been changed by HyunsikChoi:

Moved from the site.

New page:
== Prerequisites ==
 * Hadoop 2.0.3-alpha
 * Java 1.6

== Build Tajo from Source Code ==
Download the source code and build Tajo as follows:

$ git clone http://git-wip-us.apache.org/repos/asf/incubator-tajo.git tajo
$ cd tajo
$ mvn package -DskipTests -Pdist -Dtar
$ ls tajo-dist/target/tajo-x.y.z.tar.gz

If you meet some errors or you want to know the build instruction in more detail, please read
Build Instruction.

== Unpack tarball ==

You should unpack the tarball (refer to build instruction).

$ tar xzvf tajo-0.2.0-SNAPSHOT.tar.gz

This will result in the creation of subdirectory named tajo-x.y.z-SNAPSHOT. You MUST copy
this directory into the same directory on all yarn cluster nodes.

== Configuration ==
First of all, you need to set the environment variables for your Hadoop cluster and Tajo.

export JAVA_HOME=/usr/lib/jvm/openjdk-1.6.x
export HADOOP_HOME=/usr/local/hadoop-2.0.x
export YARN_HOME=/usr/local/hadoop-2.0.x
export TAJO_HOME=<tajo-install-dir>

Tajo requires an auxiliary service called PullServer for data repartitioning. For this, you
must add or modify the following configuration parameters in $HADOOP_HOME/etc/hadoop/yarn-site.xml.





For the auxiliary, you should copy some jar files to the Hadoop Yarn library dir.

$ cp $TAJO_HOME/tajo-common-x.y.z.jar $HADOOP_HOME/share/hadoop/yarn/lib
$ cp $TAJO_HOME/tajo-catalog-common-x.y.z.jar $HADOOP_HOME/hadoop/share/yarn/lib
$ cp $TAJO_HOME/tajo-core-pullserver-x.y.z.jar $HADOOP_HOME/hadoop/share/yarn/lib
$ cp $TAJO_HOME/tajo-core-storage-x.y.z.jar $HADOOP_HOME/hadoop/share/yarn/lib

Please copy $TAJO_HOME/conf/tajo-site.xml.template to tajo-site.xml. You must add the following
configs to your tajo-site.xml and then change hostname and port to your namenode address.


If you want know configuration in more detail, read Configuration Guide.

== Running Tajo ==
Before launching the tajo, you should create the tajo root dir and set the permission as follows:
$ $HADOOP_HOME/bin/hadoop fs -mkdir       /tajo
$ $HADOOP_HOME/bin/hadoop fs -chmod g+w   /tajo

To launch the tajo master, execute start-tajo.sh.
$ $TAJO_HOME/bin/start-tajo.sh

After then, you can use tajo-cli to access the command line interface of Tajo.
$ $TAJO_HOME/bin/tajo cli

== Query Execution ==
First of all, we need to prepare some data for query execution.

$ mkdir /home/x/table1
$ cd /home/x/table1
$ cat > table1
<CTRL + D>

This schema of this table is (int, string, float, string).

$ $TAJO_HOME/bin/tajo cli

tajo> create external table table1 (id int, name string, score float, type string) using
csv with ('csvfile.delimiter'='|') location 'file:/home/x/table1'

In order to load an external table, we need to use 'create external table' statement. In the
location clause, you should use the absolute path with an appropriate scheme. If the table
resides in HDFS, we should use 'hdfs' instead of 'file'.

If you want to know DDL statements in more detail, please see Query Language.
tajo> /t

'/t' command shows the list of tables.

tajo> /d table1

table name: table1
table path: file:/home/x/table1
store type: CSV
number of rows: 0
volume (bytes): 78 B
id      INT
name    STRING
score   FLOAT
type    STRING

'/d [table name]' command shows the description of a given table.

Now, you can execute SQL queries as follows:

tajo> select * from table1 where id > 2
final state: QUERY_SUCCEEDED, init time: 4.118 sec, execution time: 4.334 sec, total response
time: 8.452 sec
result: hdfs://x.x.x.x:8020/user/x/tajo/q_1363768615503_0001_000001

id,  name,  score,  type
- - - - - - - - - -  - - -
3,  ghi,  3.4,  c
4,  jkl,  4.5,  d
5,  mno,  5.6,  e

(In the current implementation, for each query, Tajo has some initial overhead to launch containers
on node managers. However, we will reduce this overhead soon.)

Enjoy Apache Tajo!

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