Between the elephant ( the
tradional image of the Hadoop framework) and the Oracle Iron Man
(Big Data..) an english setter could be seen as the link to the
right data
Data, Data, Data, we are living in a world where data
technology based on popular applications , search engines,
Webservers, rich sms messages, email clients, weather forecasts
and so on, have a predominant role in our life.
More and more technologies are used to analyze/track our
behavior, try to detect patterns, to propose us "the best/right
user experience" from the Google Ad services, to Telco companies
or large consumer sites (like Amazon:) ). The more we use all
these technologies, the more we generate data, and thus there is
a need of huge data marts and specific hardware/software servers
(as the Exadata servers) in order to treat/analyze/understand
the trends and offer new services to the users.
Some of these "data feeds" are raw, unstructured data, and
cannot be processed effectively by normal SQL queries. Large
scale distributed processing was an emerging infrastructure need
and the solution seemed to be the "collocation of compute nodes
with the data", which in turn leaded to MapReduce parallel
patterns and the development of the Hadoop framework, which is
based on MapReduce and a distributed file system (HDFS) that
runs on larger clusters of rather inexpensive servers.
Several Oracle products are using the distributed / aggregation
pattern for data calculation ( Coherence, NoSql, times ten ) so
once that you are familiar with one of these technologies, lets
says with coherence aggregators, you will find the whole Hadoop,
MapReduce concept very similar.
Oracle Big Data Appliance is based on the Cloudera Distribution
(CDH), and the Oracle Big Data Connectors can be plugged on a
Hadoop cluster running the CDH distribution or equivalent Hadoop
clusters.
In this paper, a "lab like" implementation of this concept is
done on a single Linux X64 server, running an Oracle Database
11g Enterprise Edition Release 11.2.0.4.0, and a single node
Apache hadoop-1.2.1 HDFS cluster, using the SQL connector for HDFS.
The whole setup is fairly simple:
Install on a Linux x64 server ( or virtual box appliance)
an Oracle Database 11g Enterprise Edition Release 11.2.0.4.0
server
Get the Apache Hadoop distribution from:
http://mir2.ovh.net/ftp.apache.org/dist/hadoop/common/hadoop-1.2.1.
Get the Oracle Big Data Connectors from:
http://www.oracle.com/technetwork/bdc/big-data-connectors/downloads/index.html?ssSourceSiteId=ocomen.
Check the java version of your Linux server with the command:
java -version
java version "1.7.0_40"
Java(TM) SE Runtime Environment (build 1.7.0_40-b43)
Java HotSpot(TM) 64-Bit Server VM (build 24.0-b56, mixed mode)
Decompress the hadoop hadoop-1.2.1.tar.gz file to
/u01/hadoop-1.2.1
Modify your .bash_profile
export HADOOP_HOME=/u01/hadoop-1.2.1
export PATH=$PATH:$HADOOP_HOME/bin
export HIVE_HOME=/u01/hive-0.11.0
export PATH=$PATH:$HADOOP_HOME/bin:$HIVE_HOME/bin
(also see my
sample .bash_profile)
Set up ssh trust for Hadoop
process, this is a mandatory step, in our case we have to
establish a "local trust" as will are using a single node
configuration
copy the new public keys to the
list of authorized keys
connect and test the ssh setup
to your localhost:
We will run a "pseudo-Hadoop
cluster", in what is called "local standalone mode", all
the Hadoop java components are running in one Java
process, this is enough for our demo purposes. We need to
"fine tune" some Hadoop configuration files, we have to go
at our $HADOOP_HOME/conf, and modify the files:
core-site.xml
hdfs-site.xml
mapred-site.xml
check that the hadoop binaries
are referenced correctly from the command line by
executing:
hadoop -version
As Hadoop is managing our
"clustered HDFS" file system we have to create "the
mount point" and format it , the mount point will be
declared to core-site.xml as:
The layout under the
/u01/hadoop-1.2.1/data will be created and used by
other hadoop components (MapReduce = /mapred/...)
HDFS is using the /dfs/... layout structure
format the HDFS hadoop file system:
Start the java components
for the HDFS system
As an additional check,
you can use the GUI Hadoop browsers to check the
content of your HDFS configurations:
Once our HDFS
Hadoop setup is done you can use the HDFS
file system to store data ( big data : )), and
plug them back and forth to Oracle Databases by
the means of the Big Data Connectors ( which is
the next configuration step).
You can create / use a Hive db, but in our case we
will make a simple integration of "raw data" ,
through the creation of an External Table to a local
Oracle instance ( on the same Linux box, we run the
Hadoop HDFS one node cluster and one Oracle DB).
Download some public "big
data", I use the site:
http://france.meteofrance.com/france/observations,
from where I can get *.csv files for my big data
simulations :).
Here is the data layout of my
example file:
Download the Big Data
Connector from the OTN (oraosch-2.2.0.zip), unzip it
to your local file system (see picture below)
Modify your environment in order
to access the connector libraries , and make the following
test:
[oracle@dg1 bin]$./hdfs_stream
Usage: hdfs_stream locationFile
[oracle@dg1 bin]$
Load the data to the Hadoop hdfs
file system:
hadoop fs -mkdir bgtest_data
hadoop fs -put obsFrance.txt bgtest_data/obsFrance.txt
hadoop fs -ls /user/oracle/bgtest_data/obsFrance.txt
[oracle@dg1 bg-data-raw]$ hadoop fs -ls /user/oracle/bgtest_data/obsFrance.txt
Found 1 items
-rw-r--r-- 1 oracle supergroup 54103 2013-10-22 06:10 /user/oracle/bgtest_data/obsFrance.txt
[oracle@dg1 bg-data-raw]$hadoop fs -ls hdfs:///user/oracle/bgtest_data/obsFrance.txt
Found 1 items
-rw-r--r-- 1 oracle supergroup 54103 2013-10-22 06:10 /user/oracle/bgtest_data/obsFrance.txt
Check the content of the HDFS with
the browser UI:
Start the Oracle database, and run
the following script in order to create the Oracle database
user, the Oracle directories for the Oracle Big Data
Connector (dg1 it’s my own db id replace accordingly yours):
#!/bin/bash
export ORAENV_ASK=NO
export ORACLE_SID=dg1
. oraenv
sqlplus /nolog <<EOF
CONNECT / AS sysdba;
CREATE OR REPLACE DIRECTORY osch_bin_path AS '/u01/orahdfs-2.2.0/bin';
CREATE USER BGUSER IDENTIFIED BY oracle;
GRANT CREATE SESSION, CREATE TABLE TO BGUSER;
GRANT EXECUTE ON sys.utl_file TO BGUSER;
GRANT READ, EXECUTE ON DIRECTORY osch_bin_path TO BGUSER;
CREATE OR REPLACE DIRECTORY BGT_LOG_DIR as '/u01/BG_TEST/logs';
GRANT READ, WRITE ON DIRECTORY BGT_LOG_DIR to BGUSER;
CREATE OR REPLACE DIRECTORY BGT_DATA_DIR as '/u01/BG_TEST/data';
GRANT READ, WRITE ON DIRECTORY BGT_DATA_DIR to BGUSER;
EOF
Put the following in a file named t3.sh and make it executable,
hadoop jar $OSCH_HOME/jlib/orahdfs.jar \
oracle.hadoop.exttab.ExternalTable \
-D oracle.hadoop.exttab.tableName=BGTEST_DP_XTAB \
-D oracle.hadoop.exttab.defaultDirectory=BGT_DATA_DIR \
-D oracle.hadoop.exttab.dataPaths="hdfs:///user/oracle/bgtest_data/obsFrance.txt" \
-D oracle.hadoop.exttab.columnCount=7 \
-D oracle.hadoop.connection.url=jdbc:oracle:thin:@//localhost:1521/dg1 \
-D oracle.hadoop.connection.user=BGUSER \
-D oracle.hadoop.exttab.printStackTrace=true \
-createTable --noexecute
then test the creation fo the external table with it:
[oracle@dg1 samples]$ ./t3.sh
./t3.sh: line 2: /u01/orahdfs-2.2.0: Is a directory
Oracle SQL Connector for HDFS Release 2.2.0 - Production
Copyright (c) 2011, 2013, Oracle and/or its affiliates. All rights reserved.
Enter Database Password:]
The create table command was not executed.
The following table would be created.
CREATE TABLE "BGUSER"."BGTEST_DP_XTAB"
(
"C1" VARCHAR2(4000),
"C2" VARCHAR2(4000),
"C3" VARCHAR2(4000),
"C4" VARCHAR2(4000),
"C5" VARCHAR2(4000),
"C6" VARCHAR2(4000),
"C7" VARCHAR2(4000)
)
ORGANIZATION EXTERNAL
(
TYPE ORACLE_LOADER
DEFAULT DIRECTORY "BGT_DATA_DIR"
ACCESS PARAMETERS
(
RECORDS DELIMITED BY 0X'0A'
CHARACTERSET AL32UTF8
STRING SIZES ARE IN CHARACTERS
PREPROCESSOR "OSCH_BIN_PATH":'hdfs_stream'
FIELDS TERMINATED BY 0X'2C'
MISSING FIELD VALUES ARE NULL
(
"C1" CHAR(4000),
"C2" CHAR(4000),
"C3" CHAR(4000),
"C4" CHAR(4000),
"C5" CHAR(4000),
"C6" CHAR(4000),
"C7" CHAR(4000)
)
)
LOCATION
(
'osch-20131022081035-74-1'
)
) PARALLEL REJECT LIMIT UNLIMITED;
The following location files would be created.
osch-20131022081035-74-1 contains 1 URI, 54103 bytes
54103 hdfs://localhost:19000/user/oracle/bgtest_data/obsFrance.txt
Then remove
the --noexecute flag and create the
external Oracle table for the Hadoop data.
Check the results:
The create table command succeeded.
CREATE TABLE "BGUSER"."BGTEST_DP_XTAB"
(
"C1" VARCHAR2(4000),
"C2" VARCHAR2(4000),
"C3" VARCHAR2(4000),
"C4" VARCHAR2(4000),
"C5" VARCHAR2(4000),
"C6" VARCHAR2(4000),
"C7" VARCHAR2(4000)
)
ORGANIZATION EXTERNAL
(
TYPE ORACLE_LOADER
DEFAULT DIRECTORY "BGT_DATA_DIR"
ACCESS PARAMETERS
(
RECORDS DELIMITED BY 0X'0A'
CHARACTERSET AL32UTF8
STRING SIZES ARE IN CHARACTERS
PREPROCESSOR "OSCH_BIN_PATH":'hdfs_stream'
FIELDS TERMINATED BY 0X'2C'
MISSING FIELD VALUES ARE NULL
(
"C1" CHAR(4000),
"C2" CHAR(4000),
"C3" CHAR(4000),
"C4" CHAR(4000),
"C5" CHAR(4000),
"C6" CHAR(4000),
"C7" CHAR(4000)
)
)
LOCATION
(
'osch-20131022081719-3239-1'
)
) PARALLEL REJECT LIMIT UNLIMITED;
The following location files were created.
osch-20131022081719-3239-1 contains 1 URI, 54103 bytes
54103 hdfs://localhost:19000/user/oracle/bgtest_data/obsFrance.txt
This is the view from the SQL Developer:
and finally the number of lines in the oracle table, imported from our Hadoop HDFS cluster
SQL select count(*) from "BGUSER"."BGTEST_DP_XTAB";
COUNT(*)
----------
1151
In a next post we will integrate data from a Hive database, and try
some ODI integrations with the ODI Big Data connector. Our simplistic
approach is just a step to show you how these unstructured data world
can be integrated to Oracle infrastructure.
Hadoop, BigData, NoSql are great technologies, they are widely used
and Oracle is offering a large integration infrastructure based on
these services.
Oracle University
presents a complete curriculum on all the Oracle related technologies:
NoSQL:
Introduction to Oracle NoSQL Database
Using Oracle NoSQL Database
Big Data:
Introduction to Big Data
Oracle Big Data Essentials
Oracle Big Data Overview
Oracle Data Integrator:
Oracle Data Integrator 12c: New Features
Oracle Data Integrator 11g: Integration and Administration
Oracle Data Integrator: Administration and Development
Oracle Data Integrator 11g: Advanced Integration and Development
Oracle Coherence 12c:
Oracle Coherence 12c: New Features
Oracle Coherence 12c: Share and Manage Data in Clusters
Oracle Coherence 12c:
Oracle GoldenGate 11g: Fundamentals for Oracle
Oracle GoldenGate 11g: Fundamentals for SQL Server
Oracle GoldenGate 11g Fundamentals for Oracle
Oracle GoldenGate 11g Fundamentals for DB2
Oracle GoldenGate 11g Fundamentals for Teradata
Oracle GoldenGate 11g Fundamentals for HP NonStop
Oracle GoldenGate 11g Management Pack: Overview
Oracle GoldenGate 11g Troubleshooting and Tuning
Oracle GoldenGate 11g: Advanced Configuration for Oracle
Other Resources:
Apache Hadoop :
http://hadoop.apache.org/ is the homepage
for these technologies.
"Hadoop Definitive Guide 3rdEdition" by Tom White
is a classical lecture for people who want to know more about
Hadoop , and some active "googling " will also give you some more
references.
About the author:
Eugene Simos is based in France and joined Oracle
through the BEA-Weblogic Acquisition, where he worked for the
Professional Service, Support, end Education for major accounts
across the EMEA Region. He worked in the banking sector, ATT, Telco
companies giving him extensive experience on production
environments. Eugen currently specializes in Oracle Fusion
Middleware teaching an array of courses on Weblogic/Webcenter,
Content,BPM /SOA/Identity-Security/GoldenGate/Virtualisation/Unified
Comm Suite) throughout the EMEA region.
