/usr/bin/pegasus-statistics is in pegasus-wms 4.0.1+dfsg-8.
This file is owned by root:root, with mode 0o755.
The actual contents of the file can be viewed below.
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import os
import re
import sys
import logging
import optparse
import subprocess
import traceback
# Initialize logging object
logger = logging.getLogger()
# Use pegasus-config to find our lib path
bin_dir = os.path.normpath(os.path.join(os.path.dirname(sys.argv[0])))
pegasus_config = os.path.join(bin_dir, "pegasus-config") + " --noeoln --python"
lib_dir = subprocess.Popen(pegasus_config, stdout=subprocess.PIPE, shell=True).communicate()[0]
pegasus_config = os.path.join(bin_dir, "pegasus-config") + " --noeoln --python-externals"
lib_ext_dir = subprocess.Popen(pegasus_config, stdout=subprocess.PIPE, shell=True).communicate()[0]
# Insert this directory in our search path
os.sys.path.insert(0, lib_ext_dir)
os.sys.path.insert(0, lib_dir)
import Pegasus.common
from Pegasus.tools import utils
from Pegasus.tools import db_utils
from Pegasus.plots_stats import utils as stats_utils
from netlogger.analysis.workflow.stampede_statistics import StampedeStatistics
from netlogger.analysis.schema.schema_check import SchemaVersionError
# Regular expressions
re_parse_property = re.compile(r'([^:= \t]+)\s*[:=]?\s*(.*)')
# Global variables
prog_base = os.path.split(sys.argv[0])[1] # Name of this program
workflow_summary_file_name = "summary"
workflow_summary_time_file_name = "summary-time"
workflow_statistics_file_name = "workflow"
job_statistics_file_name = "jobs"
logical_transformation_statistics_file_name = "breakdown"
time_statistics_file_name = "time"
time_statistics_per_host_file_name = "time-per-host"
text_file_extension = ".txt"
csv_file_extension = ".csv"
calc_wf_stats = False
calc_wf_summary = False
calc_jb_stats = False
calc_tf_stats = False
calc_ti_stats = False
time_filter = None
NEW_LINE_STR ="\n"
DEFAULT_OUTPUT_DIR = "statistics"
# Transformations file column names
transformation_stats_col_name_text = ["Transformation", "Count", "Succeeded", "Failed", "Min", "Max", "Mean", "Total"]
transformation_stats_col_name_csv = ["Workflow_Id", "Dax_Label", "Transformation", "Count", "Succeeded", "Failed", "Min", "Max", "Mean", "Total"]
transformation_stats_col_size = [60, 12, 12, 12, 20, 20, 20, 12]
# Jobs file column names
job_stats_col_name_text = ['#Job', 'Try', 'Site', 'Kickstart', 'Mult', 'Kickstart-Mult', 'CPU-Time', 'Post', 'CondorQTime', 'Resource', 'Runtime', 'Seqexec', 'Seqexec-Delay', 'Exitcode', 'Hostname']
job_stats_col_name_csv = ['Workflow_Id', 'Dax_Label', 'Job', 'Try', 'Site', 'Kickstart', 'Mult', 'Kickstart-Mult', 'CPU-Time', 'Post', 'CondorQTime', 'Resource', 'Runtime', 'Seqexec', 'Seqexec-Delay', 'Exitcode', 'Hostname']
job_stats_col_size = [60, 4, 15, 12, 6, 16, 12, 12, 12, 12, 12, 12, 15, 10, 30]
# Summary file column names
workflow_summary_col_name_csv = ["Type", "Succeeded", "Failed", "Incomplete", "Total", "Retries", "Total_Run)"]
workflow_summary_col_name_text = ["Type", "Succeeded", "Failed", "Incomplete", "Total", " ", "Retries", "Total Run (Retries Included)"]
workflow_summary_col_size = [20, 20, 20, 20, 20, 5, 20, 20]
workflow_time_summary_col_name_csv = ["Stat_Type", "time_seconds"]
# Workflow file column names
workflow_status_col_name_text = ["#", "Type", "Succeeded", "Failed", "Incomplete", "Total", " ",
"Retries", "Total Run (Retries Included)", "Workflow Retries"]
workflow_status_col_name_csv = ["Workflow_Id", "Dax_Label", "Type", "Succeeded", "Failed", "Incomplete",
"Total", "Retries", "Total_Run", "Workflow_Retries"]
workflow_status_col_size = [40, 15, 12, 12, 12, 12, 5, 12, 30, 18]
# Time file column names
time_stats_col_name_csv = ["Stat_Type", "Date", "Count", "Runtime"]
time_stats_col_name_text = ["Date", "Count", "Runtime"]
time_stats_col_size = [30, 20, 20]
time_host_stats_col_name_csv = ["Stat_Type", "Date", "Host", "Count", "Runtime(sec)"]
time_host_stats_col_name_text = ["Date", "Host", "Count", "Runtime (sec)"]
time_host_stats_col_size = [30, 80, 20, 20]
class JobStatistics:
def __init__(self):
self.name = None
self.site = None
self.kickstart = None
self.multiplier_factor = None
self.kickstart_mult = None
self.remote_cpu_time = None
self.post = None
self.condor_delay = None
self.resource = None
self.runtime = None
self.condorQlen =None
self.seqexec = None
self.seqexec_delay = None
self.retry_count = 0
self.exitcode = None
self.hostname = None
def getFormattedJobStatistics(self, output_format):
"""
Returns the formatted job statistics information
@return: formatted job statistics information
"""
formatted_job_stats = [self.name]
if output_format == "text":
formatted_job_stats.append(" " + str(self.retry_count))
else:
formatted_job_stats.append(str(self.retry_count))
if self.site is None:
formatted_job_stats.append('-')
else:
formatted_job_stats.append(self.site)
formatted_job_stats.append(round_to_str(self.kickstart))
formatted_job_stats.append(str(self.multiplier_factor))
formatted_job_stats.append(round_to_str(self.kickstart_mult))
if self.remote_cpu_time is None:
formatted_job_stats.append('-')
else:
formatted_job_stats.append(round_to_str(self.remote_cpu_time))
formatted_job_stats.append(round_to_str(self.post))
formatted_job_stats.append(round_to_str(self.condor_delay))
formatted_job_stats.append(round_to_str(self.resource))
formatted_job_stats.append(round_to_str(self.runtime))
formatted_job_stats.append(round_to_str(self.seqexec))
formatted_job_stats.append(round_to_str(self.seqexec_delay))
formatted_job_stats.append(str(self.exitcode))
formatted_job_stats.append(self.hostname)
return formatted_job_stats
def setup_logger(level_str):
"""
Sets the logging level
@param level_str: logging level
"""
level_str = level_str.lower()
if level_str == "debug":
logger.setLevel(logging.DEBUG)
if level_str == "warning":
logger.setLevel(logging.WARNING)
if level_str == "error":
logger.setLevel(logging.ERROR)
if level_str == "info":
logger.setLevel(logging.INFO)
return
def formatted_wf_summary_legends_part1():
"""
Returns the first part of the workflow summary legend
@return : workflow summary legend
"""
formatted_wf_statistics_legend = ""
formatted_wf_statistics_legend += """
# Workflow summary:
# Summary of the workflow execution. It shows total
# tasks/jobs/sub workflows run, how many succeeded/failed etc.
# In case of hierarchical workflow the calculation shows the
# statistics across all the sub workflows.It shows the following
# statistics about tasks, jobs and sub workflows.
# * Succeeded - total count of succeeded tasks/jobs/sub workflows.
# * Failed - total count of failed tasks/jobs/sub workflows.
# * Incomplete - total count of tasks/jobs/sub workflows that are
# not in succeeded or failed state. This includes all the jobs
# that are not submitted, submitted but not completed etc. This
# is calculated as difference between 'total' count and sum of
# 'succeeded' and 'failed' count.
# * Total - total count of tasks/jobs/sub workflows.
# * Retries - total retry count of tasks/jobs/sub workflows.
# * Total Run - total count of tasks/jobs/sub workflows executed
# during workflow run. This is the cumulative of retries,
# succeeded and failed count.
"""
return formatted_wf_statistics_legend
def formatted_wf_summary_legends_part2():
"""
Returns the second part of the workflow summary legend
@return : workflow summary legend
"""
formatted_wf_statistics_legend = ""
formatted_wf_statistics_legend += """
# Workflow wall time:
# The walltime from the start of the workflow execution
# to the end as reported by the DAGMAN.In case of rescue dag the value
# is the cumulative of all retries.
"""
formatted_wf_statistics_legend += """
# Workflow cumulative job wall time:
# The sum of the walltime of all jobs as reported by kickstart.
# In case of job retries the value is the cumulative of all retries.
# For workflows having sub workflow jobs (i.e SUBDAG and SUBDAX jobs),
# the walltime value includes jobs from the sub workflows as well.
"""
formatted_wf_statistics_legend += """
# Cumulative job walltime as seen from submit side:
# The sum of the walltime of all jobs as reported by DAGMan.
# This is similar to the regular cumulative job walltime, but includes
# job management overhead and delays. In case of job retries the value is
# the cumulative of all retries. For workflows having sub workflow jobs
# (i.e SUBDAG and SUBDAX jobs), the walltime value includes jobs
# from the sub workflows as well.
"""
return formatted_wf_statistics_legend
def formatted_wf_summary_legends_txt():
"""
Returns the complete workflow summary legend
@return : workflow summary legend
"""
formatted_wf_statistics_legend ="# legends\n"
formatted_wf_statistics_legend += formatted_wf_summary_legends_part1()
formatted_wf_statistics_legend += formatted_wf_summary_legends_part2()
return formatted_wf_statistics_legend
def formatted_wf_summary_legends_csv1():
"""
Returns the workflow summary legend for the first summary csv file
@return : workflow summary legend
"""
formatted_wf_statistics_legend ="# legends\n"
formatted_wf_statistics_legend += formatted_wf_summary_legends_part1()
return formatted_wf_statistics_legend
def formatted_wf_summary_legends_csv2():
"""
Returns the workflow summary legend for the second summary csv file
@return : workflow summary legend
"""
formatted_wf_statistics_legend ="# legends\n"
formatted_wf_statistics_legend += formatted_wf_summary_legends_part2()
return formatted_wf_statistics_legend
def formatted_wf_status_legends():
"""
Returns the workflow table legend
@return : workflow table legend
"""
formatted_wf_statistics_legend ="# legends\n"
formatted_wf_statistics_legend +="""
#Workflow summary - Summary of the workflow execution. It shows total
# tasks/jobs/sub workflows run, how many succeeded/failed etc.
# In case of hierarchical workflow the calculation shows the
# statistics of each individual sub workflow.The file also
# contains a 'Total' table at the bottom which is the cummulative
# of all the individual statistics details.t shows the following
# statistics about tasks, jobs and sub workflows.
#
# * Workflow Retries - number of times a workflow was retried.
# * Succeeded - total count of succeeded tasks/jobs/sub workflows.
# * Failed - total count of failed tasks/jobs/sub workflows.
# * Incomplete - total count of tasks/jobs/sub workflows that are
# not in succeeded or failed state. This includes all the jobs
# that are not submitted, submitted but not completed etc. This
# is calculated as difference between 'total' count and sum of
# 'succeeded' and 'failed' count.
# * Total - total count of tasks/jobs/sub workflows.
# * Retries - total retry count of tasks/jobs/sub workflows.
# * Total Run - total count of tasks/jobs/sub workflows executed
# during workflow run. This is the cumulative of retries,
# succeeded and failed count.
#
"""
return formatted_wf_statistics_legend
def formatted_job_stats_legends():
"""
Returns the job table legend
@return : job table legend
"""
formatted_job_stats_legend = "# legends\n"
formatted_job_stats_legend += "# Job - name of the job\n"
formatted_job_stats_legend += "# Try - number representing the job instance run count\n"
formatted_job_stats_legend += "# Site - site where the job ran\n"
formatted_job_stats_legend += "# Kickstart - actual duration of the job instance in seconds on the remote compute node\n"
formatted_job_stats_legend += "# Mult - multiplier factor specified by the user\n"
formatted_job_stats_legend += "# Kickstart-Mult - Kickstart time multiplied by the multiplier factor\n"
formatted_job_stats_legend += "# CPU-Time - remote cpu time computed as the stime + utime\n"
formatted_job_stats_legend += "# Post - postscript time as reported by DAGMan\n"
formatted_job_stats_legend += "# CondorQTime - time between submission by DAGMan and the remote Grid submission. It is an estimate of the time spent in the condor q on the submit node\n"
formatted_job_stats_legend += "# Resource - time between the remote Grid submission and start of remote execution. It is an estimate of the time job spent in the remote queue\n"
formatted_job_stats_legend += "# Runtime - time spent on the resource as seen by Condor DAGMan. Is always >=kickstart\n"
formatted_job_stats_legend += "# Seqexec - time taken for the completion of a clustered job\n"
formatted_job_stats_legend += "# Seqexec-Delay - time difference between the time for the completion of a clustered job and sum of all the individual tasks kickstart time\n"
formatted_job_stats_legend += "# Exitcode - exitcode for this job\n"
formatted_job_stats_legend += "# Hostname - name of the host where the job ran, as reported by kickstart\n"
return formatted_job_stats_legend
def formatted_transformation_stats_legends():
"""
Returns the transformation table legend
@return : transformation table legend
"""
formatted_transformation_stats_legend="# legends\n"
formatted_transformation_stats_legend +="# Transformation - name of the transformation.\n"
formatted_transformation_stats_legend +="# Count - the number of times the invocations corresponding to the transformation was executed.\n"
formatted_transformation_stats_legend +="# Succeeded - the count of the succeeded invocations corresponding to the transformation.\n"
formatted_transformation_stats_legend +="# Failed - the count of the failed invocations corresponding to the transformation.\n"
formatted_transformation_stats_legend +="# Min(sec) - the minimum invocation runtime value corresponding to the transformation.\n"
formatted_transformation_stats_legend +="# Max(sec) - the maximum invocation runtime value corresponding to the transformation.\n"
formatted_transformation_stats_legend +="# Mean(sec) - the mean of the invocation runtime corresponding to the transformation.\n"
formatted_transformation_stats_legend +="# Total(sec) - the cumulative of invocation runtime corresponding to the transformation.\n"
return formatted_transformation_stats_legend
def formatted_time_stats_legends_text():
"""
Returns the time table legend
@return : time table legend
"""
filter = str(time_filter)
formatted_time_stats_legend = "# legends" + NEW_LINE_STR
formatted_time_stats_legend += "# Job instance statistics per " + filter + " : the number of job instances run, total runtime sorted by " + filter+ NEW_LINE_STR
formatted_time_stats_legend += "# Invocation statistics per " + filter + " : the number of invocations , total runtime sorted by " + filter+ NEW_LINE_STR
formatted_time_stats_legend += "# Job instance statistics by host per " + filter + " : the number of job instance run, total runtime on each host sorted by " + filter+ NEW_LINE_STR
formatted_time_stats_legend += "# Invocation by host per " + filter + " : the number of invocations, total runtime on each host sorted by " + filter + NEW_LINE_STR
return formatted_time_stats_legend
def formatted_time_stats_legends_csv():
"""
Returns the time table legend
@return : time table legend
"""
filter = str(time_filter)
formatted_time_stats_legend = "# legends" + NEW_LINE_STR
formatted_time_stats_legend += "# Job instance statistics per " + filter + " : the number of job instances run, total runtime sorted by " + filter+ NEW_LINE_STR
formatted_time_stats_legend += "# Invocation statistics per " + filter + " : the number of invocations , total runtime sorted by " + filter+ NEW_LINE_STR
return formatted_time_stats_legend
def formatted_time_host_stats_legends_csv():
"""
Returns the time table legend
@return : time table legend
"""
filter = str(time_filter)
formatted_time_stats_legend = "# legends" + NEW_LINE_STR
formatted_time_stats_legend += "# Job instance statistics by host per " + filter + " : the number of job instance run, total runtime on each host sorted by " + filter + NEW_LINE_STR
formatted_time_stats_legend += "# Invocation by host per " + filter + " : the number of invocations, total runtime on each host sorted by " + filter + NEW_LINE_STR
return formatted_time_stats_legend
def write_to_file(file_path, mode, content):
"""
Utility method for writing content to a given file
@param file_path : file path
@param mode : file writing mode 'a' append , 'w' write
@param content : content to write to file
"""
try:
fh = open(file_path, mode)
fh.write(content)
except IOError:
logger.error("Unable to write to file " + file_path)
sys.exit(1)
else:
fh.close()
def format_seconds(duration):
"""
Utility for converting time to a readable format
@param duration : time in seconds and miliseconds
@return time in format day,hour, min,sec
"""
return stats_utils.format_seconds(duration)
def convert_to_str(value):
"""
Utility for returning a str representation of the given value.
Return '-' if value is None
@parem value : the given value that need to be converted to string
"""
if value is None:
return '-'
return str(value)
def print_row(content, column_format, output_format):
"""
Utility method for generating formatted row based on the column format given
@param content : list of column values
@param column_format : column_size of each columns
"""
row_str = ""
if output_format == "text":
for index in range(len(content)):
row_str += (content[index].ljust(column_format[index]))
elif output_format == "csv":
for word in content:
if row_str != "":
row_str += ","
row_str += word
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
return row_str
def print_workflow_details(output_db_url, wf_uuid, output_dir):
"""
Prints the workflow statistics information of all workflows
@param output_db_url : time in seconds and miliseconds
@param wf_uuid : uuid of the top level workflow
"""
try:
expanded_workflow_stats = StampedeStatistics(output_db_url)
expanded_workflow_stats.initialize(wf_uuid)
except SchemaVersionError:
logger.error("------------------------------------------------------")
logger.error("Database schema mismatch! Please run the upgrade tool")
logger.error("to upgrade the database to the latest schema version.")
sys.exit(1)
except:
logger.error("Failed to load the database." + output_db_url )
logger.warning(traceback.format_exc())
sys.exit(1)
# print workflow statistics
wf_uuid_list = [wf_uuid]
desc_wf_uuid_list = expanded_workflow_stats.get_descendant_workflow_ids()
for wf_det in desc_wf_uuid_list:
wf_uuid_list.append(wf_det.wf_uuid)
if calc_wf_stats:
# Do it for the text file
wf_stats_file_txt = os.path.join(output_dir,
workflow_statistics_file_name + text_file_extension)
write_to_file(wf_stats_file_txt, "w", formatted_wf_status_legends())
workflow_status_table_header_str = print_row(workflow_status_col_name_text,
workflow_status_col_size,
"text")
workflow_status_table_header_str += NEW_LINE_STR
write_to_file(wf_stats_file_txt, "a", workflow_status_table_header_str)
# Now output the csv file too
wf_stats_file_csv = os.path.join(output_dir,
workflow_statistics_file_name + csv_file_extension)
write_to_file(wf_stats_file_csv, "w", formatted_wf_status_legends())
workflow_status_table_header_str = print_row(workflow_status_col_name_csv,
workflow_status_col_size,
"csv")
workflow_status_table_header_str += NEW_LINE_STR
write_to_file(wf_stats_file_csv, "a", workflow_status_table_header_str)
if calc_jb_stats:
# Write the text file
jobs_stats_file_txt = os.path.join(output_dir, job_statistics_file_name + text_file_extension)
write_to_file(jobs_stats_file_txt, "w", formatted_job_stats_legends())
# Now write the csv file
jobs_stats_file_csv = os.path.join(output_dir, job_statistics_file_name + csv_file_extension)
write_to_file(jobs_stats_file_csv, "w", formatted_job_stats_legends())
if calc_tf_stats:
# Write the text file
transformation_stats_file_txt = os.path.join(output_dir,
logical_transformation_statistics_file_name +
text_file_extension)
write_to_file(transformation_stats_file_txt, "w", formatted_transformation_stats_legends())
# Now write the csv file
transformation_stats_file_csv = os.path.join(output_dir,
logical_transformation_statistics_file_name +
csv_file_extension)
write_to_file(transformation_stats_file_csv, "w", formatted_transformation_stats_legends())
if calc_ti_stats:
# Create the text file
time_stats_file_txt = os.path.join(output_dir, time_statistics_file_name + text_file_extension)
write_to_file(time_stats_file_txt, "w", formatted_time_stats_legends_text())
content = print_statistics_by_time_and_host(expanded_workflow_stats, "text",
combined=True, per_host=True)
write_to_file(time_stats_file_txt, "a", content)
# Now create the csv file
time_stats_file_csv = os.path.join(output_dir, time_statistics_file_name + csv_file_extension)
write_to_file(time_stats_file_csv, "w", formatted_time_stats_legends_csv())
content = print_statistics_by_time_and_host(expanded_workflow_stats, "csv",
combined=True, per_host=False)
write_to_file(time_stats_file_csv, "a", content)
# Now create the second, per-host csv file
time_stats_file2_csv = os.path.join(output_dir, time_statistics_per_host_file_name +
csv_file_extension)
write_to_file(time_stats_file2_csv, "w", formatted_time_host_stats_legends_csv())
content = print_statistics_by_time_and_host(expanded_workflow_stats, "csv",
combined=False, per_host=True)
write_to_file(time_stats_file2_csv, "a", content)
if calc_jb_stats or calc_tf_stats or calc_wf_stats:
for sub_wf_uuid in wf_uuid_list:
try:
individual_workflow_stats = StampedeStatistics(output_db_url, False)
individual_workflow_stats.initialize(sub_wf_uuid)
except SchemaVersionError:
logger.error("------------------------------------------------------")
logger.error("Database schema mismatch! Please run the upgrade tool")
logger.error("to upgrade the database to the latest schema version.")
sys.exit(1)
except:
logger.error("Failed to load the database." + output_db_url )
logger.warning(traceback.format_exc())
sys.exit(1)
wf_det = individual_workflow_stats.get_workflow_details()[0]
workflow_id = str(sub_wf_uuid)
dax_label = str(wf_det.dax_label)
logger.info("Generating statistics information about the workflow " +
workflow_id + " ... ")
if calc_jb_stats:
logger.debug("Generating job instance statistics information for workflow " +
workflow_id + " ... ")
individual_workflow_stats.set_job_filter('all')
# Write the text file
content = print_individual_wf_job_stats(individual_workflow_stats,
workflow_id, dax_label, "text")
write_to_file(jobs_stats_file_txt, "a", content)
# Now write the csv file
content = print_individual_wf_job_stats(individual_workflow_stats,
workflow_id, dax_label, "csv")
write_to_file(jobs_stats_file_csv, "a", content)
if calc_tf_stats:
logger.debug("Generating invocation statistics information for workflow " +
workflow_id + " ... ")
individual_workflow_stats.set_job_filter('all')
# Write the text file
content = print_wf_transformation_stats(individual_workflow_stats,
workflow_id, dax_label, "text")
write_to_file(transformation_stats_file_txt, "a", content)
# Now write the csv file
content = print_wf_transformation_stats(individual_workflow_stats,
workflow_id, dax_label, "csv")
write_to_file(transformation_stats_file_csv, "a", content)
if calc_wf_stats:
logger.debug("Generating workflow statistics information for workflow " +
workflow_id + " ... ")
individual_workflow_stats.set_job_filter('all')
# Write text file
content = print_individual_workflow_stats(individual_workflow_stats,
workflow_id, dax_label, "text")
write_to_file(wf_stats_file_txt, "a", content)
# Write csv file
content = print_individual_workflow_stats(individual_workflow_stats,
workflow_id, dax_label, "csv")
write_to_file(wf_stats_file_csv, "a", content)
individual_workflow_stats.close()
stats_output = NEW_LINE_STR + "SUMMARY".center(100, '*')
stats_output += NEW_LINE_STR
if calc_wf_summary:
# First we generate the txt file
summary_output = formatted_wf_summary_legends_txt()
summary_output += NEW_LINE_STR
logger.info("Generating workflow summary ... ")
summary_output += print_workflow_summary(expanded_workflow_stats, "text",
wf_summary=True, time_summary=True)
wf_summary_file_txt = os.path.join(output_dir,
workflow_summary_file_name + text_file_extension)
write_to_file(wf_summary_file_txt, "w", summary_output)
stats_output += summary_output
stats_output += NEW_LINE_STR
stats_output += "Summary : "
stats_output += wf_summary_file_txt + "\n"
# Now we generate the first csv summary file
summary_output = formatted_wf_summary_legends_csv1()
summary_output += NEW_LINE_STR
summary_output += print_workflow_summary(expanded_workflow_stats, "csv",
wf_summary=True, time_summary=False)
wf_summary_file_csv = os.path.join(output_dir,
workflow_summary_file_name + csv_file_extension)
write_to_file(wf_summary_file_csv, "w", summary_output)
# Now we generate the second csv summary file
summary_output = formatted_wf_summary_legends_csv2()
summary_output += NEW_LINE_STR
summary_output += print_workflow_summary(expanded_workflow_stats, "csv",
wf_summary=False, time_summary=True)
wf_summary_file2_csv = os.path.join(output_dir,
workflow_summary_time_file_name + csv_file_extension)
write_to_file(wf_summary_file2_csv, "w", summary_output)
if calc_wf_stats:
stats_output += NEW_LINE_STR
# Write text file
content = print_individual_workflow_stats(expanded_workflow_stats , "Total", "", "text")
write_to_file(wf_stats_file_txt, "a" , content)
stats_output += "Workflow execution statistics : "
stats_output += wf_stats_file_txt +"\n"
# Now write the csv file
content = print_individual_workflow_stats(expanded_workflow_stats , "TOTAL", "", "csv")
write_to_file(wf_stats_file_csv, "a" , content)
if calc_jb_stats:
stats_output += NEW_LINE_STR
stats_output += "Job instance statistics : "
stats_output += jobs_stats_file_txt +"\n"
if calc_tf_stats:
stats_output += NEW_LINE_STR
expanded_workflow_stats.set_job_filter('all')
# Write the text file
content = print_wf_transformation_stats(expanded_workflow_stats , "All", "", "text")
write_to_file(transformation_stats_file_txt, "a" , content)
stats_output += "Transformation statistics : "
stats_output += transformation_stats_file_txt +"\n"
# Now write the csv file
content = print_wf_transformation_stats(expanded_workflow_stats , "ALL", "", "csv")
write_to_file(transformation_stats_file_csv, "a" , content)
if calc_ti_stats:
stats_output += NEW_LINE_STR
stats_output += "Time statistics : "
stats_output += time_stats_file_txt +"\n"
expanded_workflow_stats.close()
stats_output += NEW_LINE_STR
stats_output += "".center(100, '*')
print stats_output
return
def print_workflow_summary(workflow_stats, output_format, wf_summary=True, time_summary=True):
"""
Prints the workflow statistics summary of an top level workflow
@param workflow_stats : workflow statistics object reference
"""
summary_str = ""
if wf_summary == True:
# status
workflow_stats.set_job_filter('nonsub')
# Tasks
total_tasks = workflow_stats.get_total_tasks_status()
total_succeeded_tasks = workflow_stats.get_total_succeeded_tasks_status()
total_failed_tasks = workflow_stats.get_total_failed_tasks_status()
total_unsubmitted_tasks = total_tasks - (total_succeeded_tasks + total_failed_tasks)
total_task_retries = workflow_stats.get_total_tasks_retries()
total_invocations = total_succeeded_tasks + total_failed_tasks + total_task_retries
# Jobs
total_jobs = workflow_stats.get_total_jobs_status()
total_succeeded_jobs = workflow_stats.get_total_succeeded_jobs_status()
total_failed_jobs = workflow_stats.get_total_failed_jobs_status()
total_unsubmitted_jobs = total_jobs - (total_succeeded_jobs + total_failed_jobs)
total_job_retries = workflow_stats.get_total_jobs_retries()
total_job_instance_retries = total_succeeded_jobs + total_failed_jobs + total_job_retries
# Sub workflows
workflow_stats.set_job_filter('subwf')
total_sub_wfs = workflow_stats.get_total_jobs_status()
total_succeeded_sub_wfs = workflow_stats.get_total_succeeded_jobs_status()
total_failed_sub_wfs = workflow_stats.get_total_failed_jobs_status()
total_unsubmitted_sub_wfs = total_sub_wfs - (total_succeeded_sub_wfs + total_failed_sub_wfs)
total_sub_wfs_retries = workflow_stats.get_total_jobs_retries()
total_sub_wfs_tries = total_succeeded_sub_wfs + total_failed_sub_wfs + total_sub_wfs_retries
# Format the output
if output_format == "text":
summary_str += "".center(sum(workflow_summary_col_size), '-')
summary_str += NEW_LINE_STR
if output_format == "text":
summary_str += print_row(workflow_summary_col_name_text, workflow_summary_col_size,
output_format)
content = ["Tasks", convert_to_str(total_succeeded_tasks),
convert_to_str(total_failed_tasks),
convert_to_str(total_unsubmitted_tasks), convert_to_str(total_tasks),
"||", convert_to_str(total_task_retries), convert_to_str(total_invocations)]
elif output_format == "csv":
summary_str += print_row(workflow_summary_col_name_csv, workflow_summary_col_size,
output_format)
content = ["Tasks", convert_to_str(total_succeeded_tasks),
convert_to_str(total_failed_tasks),
convert_to_str(total_unsubmitted_tasks), convert_to_str(total_tasks),
convert_to_str(total_task_retries), convert_to_str(total_invocations)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
summary_str += NEW_LINE_STR
summary_str += print_row(content, workflow_summary_col_size, output_format)
if output_format == "text":
content = ["Jobs", convert_to_str(total_succeeded_jobs),
convert_to_str(total_failed_jobs),
convert_to_str(total_unsubmitted_jobs), convert_to_str(total_jobs),
"||", str(total_job_retries), convert_to_str(total_job_instance_retries)]
elif output_format == "csv":
content = ["Jobs", convert_to_str(total_succeeded_jobs),
convert_to_str(total_failed_jobs),
convert_to_str(total_unsubmitted_jobs), convert_to_str(total_jobs),
str(total_job_retries), convert_to_str(total_job_instance_retries)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
summary_str += NEW_LINE_STR
summary_str += print_row(content, workflow_summary_col_size, output_format)
if output_format == "text":
content = ["Sub Workflows", convert_to_str(total_succeeded_sub_wfs),
convert_to_str(total_failed_sub_wfs),
convert_to_str(total_unsubmitted_sub_wfs),
convert_to_str(total_sub_wfs), "||", str(total_sub_wfs_retries),
convert_to_str(total_sub_wfs_tries)]
elif output_format == "csv":
content = ["Sub_Workflows", convert_to_str(total_succeeded_sub_wfs),
convert_to_str(total_failed_sub_wfs),
convert_to_str(total_unsubmitted_sub_wfs),
convert_to_str(total_sub_wfs), str(total_sub_wfs_retries),
convert_to_str(total_sub_wfs_tries)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
summary_str += NEW_LINE_STR
summary_str += print_row(content, workflow_summary_col_size, output_format)
summary_str += NEW_LINE_STR
if output_format == "text":
summary_str += "".center(sum(workflow_summary_col_size), '-')
summary_str += NEW_LINE_STR
if time_summary == True:
workflow_states_list = workflow_stats.get_workflow_states()
workflow_wall_time = stats_utils.get_workflow_wall_time(workflow_states_list)
workflow_cum_job_wall_time = workflow_stats.get_workflow_cum_job_wall_time()
submit_side_job_wall_time = workflow_stats.get_submit_side_job_wall_time()
summary_str += NEW_LINE_STR
if output_format == "text":
if workflow_wall_time is None:
summary_str += "Workflow wall time : -\n"
else:
summary_str += "Workflow wall time : %-20s (total %d seconds)\n" % \
(format_seconds(workflow_wall_time), (workflow_wall_time))
summary_str += NEW_LINE_STR
if workflow_cum_job_wall_time is None:
summary_str += "Workflow cumulative job wall time : -\n"
else:
summary_str += "Workflow cumulative job wall time : %-20s (total %d seconds)\n" % \
(format_seconds(workflow_cum_job_wall_time), workflow_cum_job_wall_time)
summary_str += NEW_LINE_STR
if submit_side_job_wall_time is None:
summary_str += "Cumulative job walltime as seen from submit side : -\n"
else:
summary_str += "Cumulative job walltime as seen from submit side : %-20s (total %d seconds)\n" % \
(format_seconds(submit_side_job_wall_time), submit_side_job_wall_time)
elif output_format == "csv":
# Print header line
summary_str += print_row(workflow_time_summary_col_name_csv, None, output_format)
summary_str += NEW_LINE_STR
if workflow_wall_time is None:
summary_str += "Workflow_wall_time,"
else:
summary_str += ('Workflow_wall_time,%s' % workflow_wall_time)
summary_str += NEW_LINE_STR
if workflow_cum_job_wall_time is None:
summary_str += "Workflow_cumulative_job_wall_time,"
else:
summary_str += ('Workflow_cumulative_job_wall_time,%s' %
workflow_cum_job_wall_time)
summary_str += NEW_LINE_STR
if submit_side_job_wall_time is None:
summary_str += "Cumulative_job_walltime_from_submit_side,"
else:
summary_str += ('Cumulative_job_walltime_from_submit_side,%s' %
submit_side_job_wall_time)
summary_str += NEW_LINE_STR
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
return summary_str
def print_individual_workflow_stats(workflow_stats, workflow_id, dax_label, output_format):
"""
Prints the workflow statistics of workflow
@param workflow_stats : workflow statistics object reference
@param workflow_id : workflow_id (title of the workflow table)
"""
content_str = "\n"
# individual workflow status
# Add dax_label to workflow_id if writing text file
if output_format == "text" and dax_label != "":
workflow_id = workflow_id + " (" + dax_label +")"
# workflow status
workflow_stats.set_job_filter('all')
total_wf_retries = workflow_stats.get_workflow_retries()
# only used for the text output...
content = [workflow_id, convert_to_str(total_wf_retries)]
retry_col_size = workflow_status_col_size[len(workflow_status_col_size) - 1]
wf_status_str = print_row(content,
[sum(workflow_status_col_size) - retry_col_size, retry_col_size],
output_format)
# tasks
workflow_stats.set_job_filter('nonsub')
total_tasks = workflow_stats.get_total_tasks_status()
total_succeeded_tasks = workflow_stats.get_total_succeeded_tasks_status()
total_failed_tasks = workflow_stats.get_total_failed_tasks_status()
total_unsubmitted_tasks = total_tasks - (total_succeeded_tasks + total_failed_tasks)
total_task_retries = workflow_stats.get_total_tasks_retries()
total_task_invocations = total_succeeded_tasks + total_failed_tasks + total_task_retries
if output_format == "text":
content = ["", "Tasks", convert_to_str(total_succeeded_tasks),
convert_to_str(total_failed_tasks),
convert_to_str(total_unsubmitted_tasks), convert_to_str(total_tasks), "||",
convert_to_str(total_task_retries), convert_to_str(total_task_invocations), ""]
elif output_format == "csv":
content = [workflow_id, dax_label, "Tasks", convert_to_str(total_succeeded_tasks),
convert_to_str(total_failed_tasks),
convert_to_str(total_unsubmitted_tasks), convert_to_str(total_tasks),
convert_to_str(total_task_retries), convert_to_str(total_task_invocations),
convert_to_str(total_wf_retries)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
tasks_status_str = print_row(content, workflow_status_col_size, output_format)
# job status
workflow_stats.set_job_filter('nonsub')
total_jobs = workflow_stats.get_total_jobs_status()
total_succeeded_jobs = workflow_stats.get_total_succeeded_jobs_status()
total_failed_jobs = workflow_stats.get_total_failed_jobs_status()
total_unsubmitted_jobs = total_jobs - (total_succeeded_jobs + total_failed_jobs)
total_job_retries = workflow_stats.get_total_jobs_retries()
total_job_invocations = total_succeeded_jobs + total_failed_jobs + total_job_retries
if output_format == "text":
content = ["", "Jobs", convert_to_str(total_succeeded_jobs), convert_to_str(total_failed_jobs),
convert_to_str(total_unsubmitted_jobs), convert_to_str(total_jobs),
"||", convert_to_str(total_job_retries), convert_to_str(total_job_invocations), ""]
elif output_format == "csv":
content = [workflow_id, dax_label, "Jobs", convert_to_str(total_succeeded_jobs),
convert_to_str(total_failed_jobs),
convert_to_str(total_unsubmitted_jobs), convert_to_str(total_jobs),
convert_to_str(total_job_retries), convert_to_str(total_job_invocations),
convert_to_str(total_wf_retries)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
jobs_status_str = print_row(content, workflow_status_col_size, output_format)
# sub workflow
workflow_stats.set_job_filter('subwf')
total_sub_wfs = workflow_stats.get_total_jobs_status()
total_succeeded_sub_wfs = workflow_stats.get_total_succeeded_jobs_status()
total_failed_sub_wfs = workflow_stats.get_total_failed_jobs_status()
total_unsubmitted_sub_wfs = total_sub_wfs - (total_succeeded_sub_wfs + total_failed_sub_wfs)
total_sub_wfs_retries = workflow_stats.get_total_jobs_retries()
total_sub_wfs_invocations = total_succeeded_sub_wfs + total_failed_sub_wfs + total_sub_wfs_retries
if output_format == "text":
content = ["", "Sub Workflows", convert_to_str(total_succeeded_sub_wfs),
convert_to_str(total_failed_sub_wfs), convert_to_str(total_unsubmitted_sub_wfs),
convert_to_str(total_sub_wfs), "||", convert_to_str(total_sub_wfs_retries),
convert_to_str(total_sub_wfs_invocations), ""]
elif output_format == "csv":
content = [workflow_id, dax_label, "Sub_Workflows", convert_to_str(total_succeeded_sub_wfs),
convert_to_str(total_failed_sub_wfs), convert_to_str(total_unsubmitted_sub_wfs),
convert_to_str(total_sub_wfs), convert_to_str(total_sub_wfs_retries),
convert_to_str(total_sub_wfs_invocations), convert_to_str(total_wf_retries)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sub_wf_status_str = print_row(content, workflow_status_col_size, output_format)
if output_format == "text":
# Only print these in the text format output
content_str += "".center(sum(workflow_status_col_size), '-') + "\n"
content_str += wf_status_str + "\n"
content_str += tasks_status_str + "\n"
content_str += jobs_status_str + "\n"
content_str += sub_wf_status_str + "\n"
return content_str
def print_individual_wf_job_stats(workflow_stats, workflow_id, dax_label, output_format):
"""
Prints the job statistics of workflow
@param workflow_stats : workflow statistics object reference
@param workflow_id : workflow_id (title for the table)
"""
job_stats_dict = {}
job_stats_list = []
job_retry_count_dict = {}
# Add dax_label to workflow_id if writing text file
if output_format == "text":
workflow_id = workflow_id + " (" + dax_label +")"
if output_format == "text":
job_status_str = "\n# " + workflow_id + "\n"
else:
job_status_str = "\n"
# Print header
if output_format == "text":
job_status_str += print_row(job_stats_col_name_text, job_stats_col_size, output_format)
elif output_format == "csv":
job_status_str += print_row(job_stats_col_name_csv, job_stats_col_size, output_format)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
job_status_str += "\n"
wf_job_stats_list = workflow_stats.get_job_statistics()
# Go through each job in the workflow
for job in wf_job_stats_list:
job_stats = JobStatistics()
job_stats.name = job.job_name
job_stats.site = job.site
job_stats.kickstart = job.kickstart
job_stats.multiplier_factor = job.multiplier_factor
job_stats.kickstart_mult = job.kickstart_multi
job_stats.remote_cpu_time = job.remote_cpu_time
job_stats.post = job.post_time
job_stats.runtime = job.runtime
job_stats.condor_delay = job.condor_q_time
job_stats.resource = job.resource_delay
job_stats.seqexec = job.seqexec
job_stats.exitcode = utils.raw_to_regular(job.exit_code)
job_stats.hostname = job.host_name
if job_stats.seqexec is not None and job_stats.kickstart is not None:
job_stats.seqexec_delay = (float(job_stats.seqexec) - float(job_stats.kickstart))
if job_retry_count_dict.has_key(job.job_name):
job_retry_count_dict[job.job_name] += 1
else:
job_retry_count_dict[job.job_name] = 1
job_stats.retry_count = job_retry_count_dict[job.job_name]
job_stats_list.append(job_stats)
# printing
content_list = []
# find the pretty print length
for job_stat in job_stats_list:
job_det = job_stat.getFormattedJobStatistics(output_format)
if output_format == "text":
index = 0
for content in job_det:
job_status_str += str(content).ljust(job_stats_col_size[index])
index = index + 1
elif output_format == "csv":
job_status_str += workflow_id
job_status_str += ","
job_status_str += dax_label
for content in job_det:
job_status_str += "," + str(content)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
job_status_str += NEW_LINE_STR
return job_status_str
def round_to_str(value , to=3):
"""
Utility method for rounding the float value to rounded string
@param value : value to round
@param to : how many decimal points to round to
"""
return stats_utils.round_decimal_to_str(value,to)
def print_wf_transformation_stats(workflow_stats, workflow_id, dax_label, output_format):
"""
Prints the transformation statistics of workflow
@param workflow_stats : workflow statistics object reference
@param workflow_id : workflow_id (title of the transformation statistics)
"""
transformation_status_str = "\n"
# Add dax_label to workflow_id if writing text file
if output_format == "text" and dax_label != "":
workflow_id = workflow_id + " (" + dax_label +")"
# In text file, we need a line with the workflow id first
if output_format == "text":
transformation_status_str = "\n# " + workflow_id + "\n"
if output_format == "text":
transformation_status_str += print_row(transformation_stats_col_name_text,
transformation_stats_col_size,
output_format)
elif output_format == "csv":
transformation_status_str += print_row(transformation_stats_col_name_csv,
transformation_stats_col_size,
output_format)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
transformation_status_str += NEW_LINE_STR
for transformation in workflow_stats.get_transformation_statistics():
if output_format == "text":
content = [transformation.transformation, str(transformation.count),
str(transformation.success), str(transformation.failure),
round_to_str(transformation.min), round_to_str(transformation.max),
round_to_str(transformation.avg), round_to_str(transformation.sum)]
elif output_format == "csv":
content = [workflow_id, dax_label, transformation.transformation,
str(transformation.count),
str(transformation.success), str(transformation.failure),
round_to_str(transformation.min), round_to_str(transformation.max),
round_to_str(transformation.avg), round_to_str(transformation.sum)]
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
transformation_status_str += print_row(content, transformation_stats_col_size, output_format)
transformation_status_str += NEW_LINE_STR
return transformation_status_str
def print_statistics_by_time_and_host(workflow_stats, output_format, combined=True, per_host=True):
"""
Prints the job instance and invocation statistics sorted by time
@param workflow_stats : workflow statistics object reference
@param output_format : indicates how to format the output, currently supported "text" and "csv"
@param combined : print combined output (all hosts consolidated)
@param per_host : print per-host totals
"""
statistics_by_time_str = NEW_LINE_STR
workflow_stats.set_job_filter('nonsub')
workflow_stats.set_time_filter('hour')
workflow_stats.set_transformation_filter(exclude=['condor::dagman'])
if combined == True:
statistics_by_time_str +="# Job instances statistics per " + time_filter
statistics_by_time_str += NEW_LINE_STR
if output_format == "text":
statistics_by_time_str += print_row(time_stats_col_name_text,
time_stats_col_size, output_format)
elif output_format == "csv":
statistics_by_time_str += print_row(time_stats_col_name_csv,
time_stats_col_size, output_format)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
statistics_by_time_str += NEW_LINE_STR
stats_by_time = workflow_stats.get_jobs_run_by_time()
formatted_stats_list = stats_utils.convert_stats_to_base_time(stats_by_time, time_filter)
for stats in formatted_stats_list:
if output_format == "text":
content = [stats['date_format'], str(stats['count']),
round_to_str(stats['runtime'])]
elif output_format == "csv":
content = ["Job instances/" + time_filter, stats['date_format'],
str(stats['count']), round_to_str(stats['runtime'])]
else:
print "%s: error: output format %s not recognized!" % (prog_base,
output_format)
sys.exit(1)
statistics_by_time_str += print_row(content,
time_stats_col_size, output_format)
statistics_by_time_str += NEW_LINE_STR
if combined == True:
statistics_by_time_str += NEW_LINE_STR
statistics_by_time_str += "# Invocation statistics run per " + time_filter
statistics_by_time_str += NEW_LINE_STR
if output_format == "text":
statistics_by_time_str += print_row(time_stats_col_name_text,
time_stats_col_size, output_format)
elif output_format == "csv":
statistics_by_time_str += print_row(time_stats_col_name_csv,
time_stats_col_size, output_format)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
statistics_by_time_str += NEW_LINE_STR
stats_by_time = workflow_stats.get_invocation_by_time()
formatted_stats_list = stats_utils.convert_stats_to_base_time(stats_by_time, time_filter)
for stats in formatted_stats_list:
if output_format == "text":
content = [stats['date_format'], str(stats['count']),
round_to_str(stats['runtime'])]
elif output_format == "csv":
content = ["Invocations/" + time_filter, stats['date_format'],
str(stats['count']), round_to_str(stats['runtime'])]
else:
print "%s: error: output format %s not recognized!" % (prog_base,
output_format)
sys.exit(1)
statistics_by_time_str += print_row(content, time_stats_col_size, output_format)
statistics_by_time_str += NEW_LINE_STR
if per_host == True:
statistics_by_time_str += NEW_LINE_STR
statistics_by_time_str += "# Job instances statistics on host per " + time_filter
statistics_by_time_str += NEW_LINE_STR
if output_format == "text":
statistics_by_time_str += print_row(time_host_stats_col_name_text,
time_host_stats_col_size, output_format)
elif output_format == "csv":
statistics_by_time_str += print_row(time_host_stats_col_name_csv,
time_host_stats_col_size, output_format)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
statistics_by_time_str += NEW_LINE_STR
stats_by_time = workflow_stats.get_jobs_run_by_time_per_host()
formatted_stats_list = stats_utils.convert_stats_to_base_time(stats_by_time, time_filter, True)
for stats in formatted_stats_list:
if output_format == "text":
content = [stats['date_format'], str(stats['host']), str(stats['count']),
round_to_str(stats['runtime'])]
elif output_format == "csv":
content = ["Job_instances/host/" + time_filter, stats['date_format'],
str(stats['host']), str(stats['count']),
round_to_str(stats['runtime'])]
else:
print "%s: error: output format %s not recognized!" % (prog_base,
output_format)
sys.exit(1)
statistics_by_time_str += print_row(content, time_host_stats_col_size, output_format)
statistics_by_time_str += NEW_LINE_STR
if per_host == True:
statistics_by_time_str += NEW_LINE_STR
statistics_by_time_str += "# Invocation statistics on host per " + time_filter
statistics_by_time_str += NEW_LINE_STR
if output_format == "text":
statistics_by_time_str += print_row(time_host_stats_col_name_text,
time_host_stats_col_size, output_format)
elif output_format == "csv":
statistics_by_time_str += print_row(time_host_stats_col_name_csv,
time_host_stats_col_size, output_format)
else:
print "%s: error: output format %s not recognized!" % (prog_base, output_format)
sys.exit(1)
statistics_by_time_str += NEW_LINE_STR
stats_by_time = workflow_stats.get_invocation_by_time_per_host()
formatted_stats_list = stats_utils.convert_stats_to_base_time(stats_by_time, time_filter, True)
for stats in formatted_stats_list:
if output_format == "text":
content = [stats['date_format'], str(stats['host']), str(stats['count']),
round_to_str(stats['runtime'])]
elif output_format == "csv":
content = ["Invocations/host/" + time_filter, stats['date_format'],
str(stats['host']), str(stats['count']),
round_to_str(stats['runtime'])]
else:
print "%s: error: output format %s not recognized!" % (prog_base,
output_format)
sys.exit(1)
statistics_by_time_str += print_row(content, time_host_stats_col_size, output_format)
statistics_by_time_str += NEW_LINE_STR
return statistics_by_time_str
def set_statistics_level(stats_level):
"""
Sets the statistics level
@param stats_level
"""
global calc_wf_stats
global calc_wf_summary
global calc_jb_stats
global calc_tf_stats
global calc_ti_stats
if stats_level =='all':
calc_wf_stats = True
calc_wf_summary = True
calc_jb_stats = True
calc_tf_stats = True
calc_ti_stats = True
elif stats_level =='summary':
calc_wf_summary = True
elif stats_level =='wf_stats':
calc_wf_stats = True
elif stats_level == 'jb_stats':
calc_jb_stats = True
elif stats_level == 'tf_stats':
calc_tf_stats = True
else:
calc_ti_stats = True
# ---------main----------------------------------------------------------------------------
def main():
# Configure command line option parser
prog_usage = prog_base +" [options] [SUBMIT_DIRECTORY]"
parser = optparse.OptionParser(usage=prog_usage)
parser.add_option("-o", "--output", action = "store", dest = "output_dir",
help = "Writes the output to given directory.")
parser.add_option("-c","--conf", action = "store", type = "string", dest = "config_properties",
help = "Specifies the properties file to use. This option overrides all other property files.")
parser.add_option("-s", "--statistics-level", action = "store", dest = "statistics_level",
choices=['all', 'summary', 'wf_stats', 'jb_stats', 'tf_stats', 'ti_stats'],
help = "Valid levels are: all,summary,wf_stats,jb_stats,tf_stats,ti_stats; Default is summary.")
parser.add_option("-t", "--time-filter", action = "store", dest = "time_filter",
choices=['day', 'hour'],
help = "Valid levels are: day,hour; Default is day.")
parser.add_option("-i", "--ignore-db-inconsistency", action = "store_const", const = 0,
dest = "ignore_db_inconsistency",
help = "turn off the check for db consistency")
parser.add_option("-v", "--verbose", action="count", default=0, dest="verbose",
help="Increase verbosity, repeatable")
parser.add_option("-q", "--quiet", action="count", default=0, dest="quiet",
help="Decrease verbosity, repeatable")
# Parse command line options
(options, args) = parser.parse_args()
if len(args) > 1:
parser.error("Invalid argument")
sys.exit(1)
if len(args) < 1:
submit_dir = os.getcwd()
else:
submit_dir = os.path.abspath(args[0])
# Copy options from the command line parser
# default is info
log_level = 1
log_level_str = "info"
log_level += (options.verbose - options.quiet)
if log_level <= 0:
log_level_str = "error"
elif log_level == 1:
log_level_str = "warning"
elif log_level == 2:
log_level_str = "info"
elif log_level >= 3:
log_level_str = "debug"
setup_logger(log_level_str)
logger.info(prog_base +" : initializing...")
if options.ignore_db_inconsistency is None:
if not utils.loading_completed(submit_dir):
if utils.monitoring_running(submit_dir):
logger.warning("pegasus-monitord still running. Please wait for it to complete. ")
else:
logger.warning("Please run pegasus monitord in replay mode. ")
sys.exit(1)
else:
logger.warning("The tool is meant to be run after the completion of workflow run.")
# Figure out what statistics we need to calculate
if options.statistics_level is not None:
statistics_level = options.statistics_level
else:
statistics_level = 'summary'
set_statistics_level(statistics_level)
global time_filter
if options.time_filter is not None:
time_filter = options.time_filter
else:
time_filter = 'day'
# Change the legend to show the time filter format
time_stats_col_name_text[0] += str(stats_utils.get_date_print_format(time_filter))
time_stats_col_name_csv[1] += str(stats_utils.get_date_print_format(time_filter))
time_host_stats_col_name_text[0] += str(stats_utils.get_date_print_format(time_filter))
time_host_stats_col_name_csv[1] += str(stats_utils.get_date_print_format(time_filter))
if options.output_dir is not None:
output_dir = options.output_dir
if not os.path.isdir(output_dir):
logger.warning("Output directory doesn't exists. Creating directory... ")
try:
os.mkdir(output_dir)
except:
logger.error("Unable to create output directory." + output_dir)
sys.exit(1)
else:
output_dir = os.path.join(submit_dir, DEFAULT_OUTPUT_DIR)
utils.create_directory(output_dir, True)
output_db_url, wf_uuid = db_utils.get_db_url_wf_uuid(submit_dir, options.config_properties)
if output_db_url is not None:
print_workflow_details(output_db_url, wf_uuid, output_dir)
sys.exit(0)
if __name__ == '__main__':
main()
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