python wrapper around ssh to distribute tasks across multiple machines
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README.md
kssh

README.md

kssh

python wrapper around ssh to distribute tasks across multiple machines by splitting the input into blocks and assigning blocks to machine. the script polls for completion of the task on a machine, and then assigns a new block.

reads in machine details from a JSON file with argument --machines:

[{
	"hostname": "default", 		# default settings, can be overridden per machine
	"username": "user",
	"connect_cmd": "ssh -o UserKnownHostsFile=/dev/null -o StrictHostKeyChecking=no -o ConnectTimeout=10 -o ConnectionAttempts=2",
	"poll_interval": 10,			# interval for polling for block complete
	"poll_timeout": 2,				# initial timeout for polling ssh session
	"upload_timeout": 2,			# initial timeout for the block upload ssh session
	"download_timeout": 2,		# initial timeout for the output download ssh session
	"init_timeout": 2					# timeout for the initialization steps
},
{
	"hostname": "worker1.example.com", # per machine settings
	"wd": "~/working_dir",
	"init_timeout": 10
},
	...
]

timeout values are adjusted as the script runs using a weighted moving average. however, the closer the initial settings are to optimal, the quicker we will converge.

depending upon whether you specify multiple files or a single file as --input, the script will either distribute blocks as lines in the single input file or as whole files. the number of lines per block can be specified with --blocksize.

you can specify an initialization file to be copied to the remote machines and an initialization script using --init-file and --init-script, respectively. The file will be copied first then the script will be run.

for each assigned block, the parameter --task will be executed with the block as stdin. stdout and stderr will be returned from the remote machine. The script expects the task to return 0 on success. That can be changed with --task-success-code.

as a simple example:

./kssh --input list_of_urls --blocksize 100 --task "xargs -P 5 curl"

will size 100 urls per block to each machine and run 5 curls in parallel per machine. the output of curl will be written to stdout.