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This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -23,7 +23,10 @@ osd_data[osd['osd']]={'osdSize': []} # Create osdSize bucket for Size statistics for field in ['kb','kb_used','kb_avail']: # Loop through the fields we care about osd_data[osd['osd']]['osdSize'].append(osd[field]) # Append fields to osdSize bucket if osd['kb'] > 0: osd_data[osd['osd']]['osdSize'].append("{0:0.2f}".format(float(osd['kb_used'])/osd['kb']*100)) # Append Use Percentage formatted to 2 decimal points else: osd_data[osd['osd']]['osdSize'].append("0.00") for field in fields: # Loop through All Fields osd_data[osd['osd']][field]={'PrimPG#': 0, 'SecPG#': 0} # Create PG Count Buckets -
Nov 5, 2014 . 1 changed file with 61 additions and 24 deletions.There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -6,35 +6,72 @@ obj=json.load(sys.stdin) # osd_data_object osd.id = [ 'osdSize': [size,used,avail,used%], 'TotalPGs': [primary, secondary], 'PoolName1': [primary, secondary] , 'PoolName2': [primary, secondary], ... ]; osd_data={} # pool_data_object Pool.id = [ pool object from json ]; pool_data={} dfFields=['Size','Used','Avail','Use%'] # Headers for OSD Size data fields=['TotalPGs'] # Begin headers for PG Count data for pool in obj['osdmap']['pools']: # Loop through pools to populate Pool data and Field Headers (with pool_name) pool_data[str(pool['pool'])]=pool # Populate pool_data fields.append(pool['pool_name']) # Populate Field Headers with pool_name for osd in obj['pgmap']['osd_stats']: # Loop through OSD Size statistics osd_data[osd['osd']]={'osdSize': []} # Create osdSize bucket for Size statistics for field in ['kb','kb_used','kb_avail']: # Loop through the fields we care about osd_data[osd['osd']]['osdSize'].append(osd[field]) # Append fields to osdSize bucket osd_data[osd['osd']]['osdSize'].append("{0:0.2f}".format(float(osd['kb_used'])/float(osd['kb'])*100)) # Append Use Percentage formatted to 2 decimal points for field in fields: # Loop through All Fields osd_data[osd['osd']][field]={'PrimPG#': 0, 'SecPG#': 0} # Create PG Count Buckets for pg in obj['pgmap']['pg_stats']: # Loop through ALL PGs poolID,_=pg['pgid'].split('.',1) # Split the Pool ID from the PG.id primSec='PrimPG#' # Default to Primary PG for osdIndex in range(0,len(pg['acting'])): # Loop through all OSDs in the 'acting' state if osdIndex > 0: # If we're not on the first one, it's a secondary copy primSec='SecPG#' osd_data[pg['acting'][osdIndex]]['TotalPGs'][primSec]+=1 # Increment TotalPG counter for either Pri or Sec copy osd_data[pg['acting'][osdIndex]][pool_data[poolID]['pool_name']][primSec]+=1 # Increment PerPool counter for either Pri or Sec copy ## Begin output of per OSD data print ',,'+','.join('' for x in dfFields)+',,,'.join(str(x) for x in fields) # Print top row of header print 'osd,'+','.join(x for x in dfFields)+',pri,sec,sum'.join('' for x in fields)+',pri,sec,sum' # Print 2nd row of header for osdid in osd_data: # Loop through all OSDs osdSum=0 # Reset per-OSD Sum outline=str(osdid) # Start output line with OSD.id for field in range(0,len(dfFields)): # Loop through osdSize fields outline+=','+str(osd_data[osdid]['osdSize'][field]) # Append osdSize statistics to the output line for field in fields: # Loop through PG Count Fields both=osd_data[osdid][field]['PrimPG#']+osd_data[osdid][field]['SecPG#'] # Calculate sum of both Pri and Sec PGs outline+=','+str(osd_data[osdid][field]['PrimPG#'])+','+str(osd_data[osdid][field]['SecPG#'])+','+str(both); # Append Pri, Sec and Sum PG counts print outline # Print output line ## Start Summary lines sumLine='Sum' avgLine='Avg' minLine='Min' maxLine='Max' for field in range(0,len(dfFields)): # Loop through osdSize fields if field < 3: # If we're on osd Sizes / use KB, adjust it to Gb to not exceed max int size sumLine+=','+str(sum(osd_data[x]['osdSize'][field]/1024/1024 for x in osd_data))+'g' # Append sum of the osdSize field else: # We're on the Use%, so sum doesn't make sense here, leave it empty sumLine+=',' minLine+=','+str(min(osd_data[x]['osdSize'][field] for x in osd_data)) # Append min value to Summary line maxLine+=','+str(max(osd_data[x]['osdSize'][field] for x in osd_data)) # Append max value to Summary line avgLine+=','+str("{0:0.2f}".format(sum(float(osd_data[x]['osdSize'][field]) for x in osd_data)/len(osd_data))) # Append Average value to Summary line for field in fields: # Loop through all PG Count Fields, appending sum, min, max and avg sumLine+=','+str(sum(osd_data[x][field]['PrimPG#'] for x in osd_data))+','+str(sum(osd_data[x][field]['SecPG#'] for x in osd_data))+','+str(sum(osd_data[x][field]['PrimPG#']+osd_data[x][field]['SecPG#'] for x in osd_data)) minLine+=','+str(min(osd_data[x][field]['PrimPG#'] for x in osd_data))+','+str(min(osd_data[x][field]['SecPG#'] for x in osd_data))+','+str(min(osd_data[x][field]['PrimPG#']+osd_data[x][field]['SecPG#'] for x in osd_data)) maxLine+=','+str(max(osd_data[x][field]['PrimPG#'] for x in osd_data))+','+str(max(osd_data[x][field]['SecPG#'] for x in osd_data))+','+str(max(osd_data[x][field]['PrimPG#']+osd_data[x][field]['SecPG#'] for x in osd_data)) avgLine+=','+str("{0:0.2f}".format(sum(float(osd_data[x][field]['PrimPG#']) for x in osd_data)/len(osd_data)))+','+str("{0:0.2f}".format(sum(float(osd_data[x][field]['SecPG#']) for x in osd_data)/len(osd_data)))+','+str("{0:0.2f}".format(sum(float(osd_data[x][field]['PrimPG#']+osd_data[x][field]['SecPG#']) for x in osd_data)/len(osd_data))) ## Print Summary lines print sumLine print avgLine print minLine print maxLine -
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This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,40 @@ #!/usr/bin/env python import sys import simplejson as json obj=json.load(sys.stdin) # osd_data_object osd.id = [ 'TotalPGs': [primary, secondary], 'PoolName1': [primary, secondary] , 'PoolName2': [primary, secondary], ... ]; osd_data={} # pool_data_object Pool.id = [ pool object from json ]; pool_data={} fields=['TotalPGs']; for pool in obj['osdmap']['pools']: pool_data[str(pool['pool'])]=pool fields.append(pool['pool_name']); for osd in obj['osdmap']['osds']: osd_data[osd['osd']]={}; for field in fields: osd_data[osd['osd']][field]={'PrimPG#': 0, 'SecPG#': 0} for pg in obj['pgmap']['pg_stats']: poolID,_=pg['pgid'].split('.',1) primSec='PrimPG#' for osdIndex in range(0,len(pg['acting'])): if osdIndex > 0: primSec='SecPG#' osd_data[pg['acting'][osdIndex]]['TotalPGs'][primSec]+=1 osd_data[pg['acting'][osdIndex]][pool_data[poolID]['pool_name']][primSec]+=1 print "osd\t"+"(pri,sec)\t".join(str(x) for x in fields) for osdid in osd_data: outline=str(osdid)+'\t' for field in fields: outline+='\t('+str(osd_data[osdid][field]['PrimPG#'])+','+str(osd_data[osdid][field]['SecPG#'])+')'; print outline