IBM's Universal Database
You must have the prerequisite Java Runtime Environment (JRE) level to use the DB2 Administration Tools. For more information, refer to the Control Center README, which can be found in the INSTHOME/sqllib/cc/prime directory, where INSTHOME is the home directory of the user created for the instance during the installation (for example, /home/db2inst1/sqllib/cc/prime). Let me save you some time and take you through the quickest way I found to get the graphical tools running on your workstation. Perform the following steps:
Log on to your workstation as a user with root authority
In order to run the graphical tools, you need to be running at least Java 1.1.7 v3 or later. A JRE is available from the Blackdown web site at www.blackdown.org/java-linux/mirrors.html. For this example, I visited the mirror site at: ftp://metalab.unc.edu/pub/linux/devel/lang/java/blackdown.org/JDK-1.1.7/i386/glibc/v3/, downloaded the jre_1.1.7-v3-glibc-x86-native.tar.gz file and placed it in the /tmp directory. For all the latest information on supported JREs and browsers, go to http://www.software.ibm.com/data/db2/.
Note that you must download the native threads version of the JRE that you want to use. The DB2 Control Center does not support green threads.
Once you have downloaded an appropriate JRE, unpack the file by entering the following command:
tar xvfz jre_1.1.7-v3-glibc-x86-native.tar.gz
Log on to your workstation as the db2inst1 user.
Update your PATH so that your workstation knows the location of the JRE's binary files just installed. Assuming you are following along the example, for Bash or Bourne shells enter this command: export PATH=/tmp/jre117_v3/bin:$PATH; for C shell enter: setenv PATH /tmp/jre117_v7/bin:${PATH}, where /tmp/jre117_v7/bin is the path to the downloaded JRE binary files.
Start the JDBC Applet Server by entering the following command: db2jstrt 6790.
Start a graphical administration tool. For this example, let's start the Control Center using the command db2cc 6790.
The Control Center Sign On window opens. Enter a valid DB2 user that has SYSADM authority on the instance with which you intend to work. For our example, enter the db2inst user ID and the corresponding password. For more information, refer to the “Administration Guide”.
Now, you have completed all the steps necessary to configure your workstation for the DB2 graphical tools.
If you followed the steps and considerations that I have outlined in this article, you should have a running copy of DB2 on your Linux workstation, a sample database, a running Control Center and a smile on your face!

- « first
- ‹ previous
- 1
- 2
- 3
- 4
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Sponsored by AMD
If you already use virtualized infrastructure, you are well on your way to leveraging the power of the cloud. Virtualization offers the promise of limitless resources, but how do you manage that scalability when your DevOps team doesn’t scale? In today’s hypercompetitive markets, fast results can make a difference between leading the pack vs. obsolescence. Organizations need more benefits from cloud computing than just raw resources. They need agility, flexibility, convenience, ROI, and control.
Stackato private Platform-as-a-Service technology from ActiveState extends your private cloud infrastructure by creating a private PaaS to provide on-demand availability, flexibility, control, and ultimately, faster time-to-market for your enterprise.
Sponsored by ActiveState
| Non-Linux FOSS: libnotify, OS X Style | Jun 18, 2013 |
| Containers—Not Virtual Machines—Are the Future Cloud | Jun 17, 2013 |
| Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer | Jun 12, 2013 |
| Weechat, Irssi's Little Brother | Jun 11, 2013 |
| One Tail Just Isn't Enough | Jun 07, 2013 |
| Introduction to MapReduce with Hadoop on Linux | Jun 05, 2013 |
- Containers—Not Virtual Machines—Are the Future Cloud
- Non-Linux FOSS: libnotify, OS X Style
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Linux Systems Administrator
- Introduction to MapReduce with Hadoop on Linux
- RSS Feeds
- Tech Tip: Really Simple HTTP Server with Python
- Weechat, Irssi's Little Brother
- Senior Perl Developer
- Validate an E-Mail Address with PHP, the Right Way
Featured Jobs
| Linux Systems Administrator | Houston and Austin, Texas | Host Gator |
| Senior Perl Developer | Austin, Texas | Host Gator |
| Technical Support Rep | Houston and Austin, Texas | Host Gator |
| UX Designer | Austin, Texas | Host Gator |
| Web & UI Developer (JavaScript & j Query) | Austin, Texas | Host Gator |
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?




24 min 33 sec ago
1 hour 13 min ago
1 hour 36 min ago
3 hours 13 min ago
3 hours 15 min ago
5 hours 8 min ago
7 hours 57 min ago
13 hours 10 min ago
13 hours 12 min ago
13 hours 14 min ago