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Tech Tip
If you run a lot of terminal tabs or scripts that all need to make OpenSSH connections to the same server, you can speed them all up with multiplexing: making the first one act as the master and letting the others share its TCP connection to the server.
If you don't already have a config file in the .ssh directory in your home directory, create it with permissions 600: readable and writeable only by you.
Then, add these lines:
Host * ControlMaster auto ControlPath ~/.ssh/master-%r@%h:%p
ControlMaster auto tells ssh to try to start a master if none is running, or to use an existing master otherwise. ControlPath is the location of a socket for the ssh processes to communicate among themselves. The %r, %h and %p are replaced with your user name, the host to which you're connecting and the port number—only ssh sessions from the same user to the same host on the same port can or should share a TCP connection, so each group of multiplexed ssh processes needs a separate socket.
To make sure it worked, start one ssh session and keep it running. Then, in another window, open another connection with the -v option:
~$ ssh -v example.com echo "hi"
And, instead of the long verbose messages of a normal ssh session, you'll see a few lines, ending with:
debug1: auto-mux: Trying existing master hi
Pretty fast.
If you have to connect to an old ssh implementation that doesn't support multiplexed connections, you can make a separate Host section:
Host antique.example.com ControlMaster no
For more info, see man ssh and man ssh_config.
Tech Tip
You can use the convert command that comes with ImageMagick to extract parts of an image.
You can cut out a 100-pixel-wide chunk from somewhere in the middle of an image:
$ convert -crop 100x+0+0 orig/wrapperbg775.gif slice0.gif $ convert -crop +200+0 orig/wrapperbg775.gif slice1.gif $ convert +append slice0.gif slice1.gif wrapperbg675.gif
You can duplicate a 100-pixel-wide chunk from somewhere in the middle of an image:
$ convert -crop 100x+100+0 orig/wrapperbg775.gif slice100.gif $ convert +append slice0.gif slice100.gif slice 100.gif ↪slice1.gif wrapperbg875.gif
Note that there was no need to specify the height of the image in any of the above commands. If you need to adjust the height instead of the width, the steps are similar, but use -append instead of +append to paste the slices vertically.
Tech Tip
Occasionally, you need to process a number of files—some of which have been compressed and some which have not (think log files). Rather than running two variations, one compressed and one not, wrap it in a bash function:
function data_source ()
{
local F=$1
# strip the gz if it's there
F=$(echo $F | perl -pe 's/.gz$//')
if [[ -f $F ]] ; then
cat $F
elif [[ -f $F.gz ]] ; then
nice gunzip -c $F
fi
}
which nicely allows:
for file in * ; do data_source $file | ... done
Whether you're dealing with gzip'd files or uncompressed, you no longer have to treat them differently mentally. With a little more effort, bzip files also could be detected and handled.
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.
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It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Pi Cobbler Breakout Kit for Raspberry Pi.
Congratulations to our winners so far:
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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?
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