def detailed(self, selected_hostname=None, **params):
schemagraphs = []
from_date = params.get('from_date', (datetime.datetime.now() - datetime.timedelta(7)).strftime('%Y-%m-%d'))
to_date = params.get('to_date', (datetime.datetime.now() + datetime.timedelta(1)).strftime('%Y-%m-%d'))
filter = params.get('filter', '')
if selected_hostname:
if selected_hostname not in hosts.getAllHostNames():
selected_hostname = hosts.uiShortNameToHostName(selected_hostname)
data = reportdata.get_schema_usage_for_host(selected_hostname, from_date, to_date, filter)
for schema_name, data in data.iteritems():
g_calls = flotgraph.Graph (schema_name + "_calls")
g_calls.addSeries('Sproc calls', 'calls')
g_iud = flotgraph.Graph (schema_name + "_iud")
g_iud.addSeries('IUD', 'iud')
g_scans = flotgraph.Graph (schema_name + "_scans")
g_scans.addSeries('Seq+Ind Scans', 'scans')
for p in data:
g_calls.addPoint('calls', int(time.mktime(p[0].timetuple()) * 1000) , p[1][0])
g_iud.addPoint('iud', int(time.mktime(p[0].timetuple()) * 1000) , p[1][2]+p[1][3]+p[1][4])
g_scans.addPoint('scans', int(time.mktime(p[0].timetuple()) * 1000) , p[1][1])
schemagraphs.append((schema_name, [g_calls.render(), g_iud.render(), g_scans.render()]))
table = tplE.env.get_template('perf_schemas_detailed.html')
return table.render(schemagraphs=schemagraphs, from_date=from_date, to_date=to_date, selected_hostname=selected_hostname, host_names=hosts.getAllHostNames(), filter=filter)
def graph(self, hostuiname, query_id, **params):
hostid, hostuiname = hosts.ensureHostIdAndUIShortname(hostuiname)
from_date = params.get('from_date', (datetime.datetime.now() - datetime.timedelta(1)).strftime('%Y-%m-%d'))
to_date = params.get('to_date', (datetime.datetime.now() + datetime.timedelta(1)).strftime('%Y-%m-%d'))
data = reportdata.getStatStatementsGraph(hostid, query_id, from_date, to_date)
graphcalls = flotgraph.Graph("graphcalls")
graphcalls.addSeries('Number of calls', 'calls')
graphavgruntime = flotgraph.TimeGraph("graphavgruntime")
graphavgruntime.addSeries('Avg. runtime', 'avgruntime')
graphruntime = flotgraph.TimeGraph("graphruntime")
graphruntime.addSeries('Runtime', 'runtime')
graphblocksread = flotgraph.Graph("graphblocksread")
graphblocksread.addSeries('Blocks read', 'blocksread')
graphblocksread.addSeries('Temp blocks read', 'tempblocksread', '#FFFF00')
graphblockswritten = flotgraph.Graph("graphblockswritten")
graphblockswritten.addSeries('Blocks written', 'blockswritten')
graphblockswritten.addSeries('Temp blocks written', 'tempblockswritten', '#FFFF00')
prev_row = None
for d in data:
if prev_row is None:
prev_row = d
continue
calls = d['calls'] - prev_row['calls']
graphcalls.addPoint('calls', int(time.mktime(d['timestamp'].timetuple()) * 1000), calls)
runtime = d['total_time'] - prev_row['total_time']
graphruntime.addPoint('runtime', int(time.mktime(d['timestamp'].timetuple()) * 1000), runtime)
avg_runtime = round(runtime / float(calls), 2) if calls > 0 else 0
graphavgruntime.addPoint('avgruntime', int(time.mktime(d['timestamp'].timetuple()) * 1000), avg_runtime)
graphblocksread.addPoint('blocksread', int(time.mktime(d['timestamp'].timetuple()) * 1000), d['blks_read'] - prev_row['blks_read'])
graphblocksread.addPoint('tempblocksread', int(time.mktime(d['timestamp'].timetuple()) * 1000), d['temp_blks_read'] - prev_row['temp_blks_read'])
graphblockswritten.addPoint('blockswritten', int(time.mktime(d['timestamp'].timetuple()) * 1000), d['blks_written'] - prev_row['blks_written'])
graphblockswritten.addPoint('tempblockswritten', int(time.mktime(d['timestamp'].timetuple()) * 1000), d['temp_blks_written'] - prev_row['temp_blks_written'])
prev_row = d
table = tplE.env.get_template('perf_stat_statements_detailed.html')
return table.render(hostuiname=hostuiname,
query = prev_row['query'],
query_id = prev_row['query_id'],
graphcalls=graphcalls.render(),
graphavgruntime=graphavgruntime.render(),
graphruntime=graphruntime.render(),
graphblocksread=graphblocksread.render(),
graphblockswritten=graphblockswritten.render(),
from_date=from_date, to_date=to_date)
def index(self, hostId=None):
if hostId is not None and not hostId.isdigit():
hostId = hosts.uiShortnameToHostId(hostId)
weeks = 10
data = reportdata.getLoadReportData(hostId, weeks - 1)
graph_load = []
graph_wal = []
if hostId:
graph_data = reportdata.getLoadReportDataDailyAvg(
hostId, weeks - 1)
graph_load = flotgraph.Graph('graph_load', 'left', 30)
graph_load.addSeries('CPU Load daily avg.', 'cpu')
graph_wal = flotgraph.SizeGraph('graph_wal')
graph_wal.addSeries('WAL daily avg.', 'wal')
for p in graph_data:
graph_load.addPoint(
'cpu', int(time.mktime(p['date'].timetuple()) * 1000),
p['cpu_15'])
graph_wal.addPoint(
'wal', int(time.mktime(p['date'].timetuple()) * 1000),
p['wal_b'])
graph_load = graph_load.render()
graph_wal = graph_wal.render()
table = tplE.env.get_template('report_basic.html')
return table.render(hosts=hosts.hosts,
data=data,
graph_load=graph_load,
graph_wal=graph_wal,
weeks=weeks)
def default(self, *p, **params):
if len(p) < 2:
return ""
hostId = int(p[0]) if p[0].isdigit() else hosts.uiShortnameToHostId(p[0])
hostUiName = p[0] if not p[0].isdigit() else hosts.hostIdToUiShortname(p[0])
name = p[1]
interval = {}
if 'interval' in params:
interval['interval'] = str(params['interval'])+' days'
elif 'from' in params and 'to' in params:
interval['from'] = params['from']
interval['to'] = params['to']
else:
days = int(cherrypy.request.cookie['days'].value) if 'days' in cherrypy.request.cookie else 8
interval['from'] = (datetime.datetime.now() - datetime.timedelta(days=days)).strftime('%Y-%m-%d')
interval['to'] = (datetime.datetime.now() + datetime.timedelta(days=1)).strftime('%Y-%m-%d')
data = tabledata.getTableData(hostId, name, interval)
graph_table_size = flotgraph.SizeGraph ("graphtablesize","right")
graph_table_size.addSeries("Table Size","size")
for p in data['table_size']:
graph_table_size.addPoint("size", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_index_size = flotgraph.SizeGraph ("graphindexsize","right")
graph_index_size.addSeries("Index Size", "size")
for p in data['index_size']:
graph_index_size.addPoint("size", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_seq_scans = flotgraph.Graph ("graphseqscans","right")
graph_seq_scans.addSeries("Sequential Scans","count")
for p in data['seq_scans']:
graph_seq_scans.addPoint("count", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_index_scans = flotgraph.Graph ("graphindexscans","right")
graph_index_scans.addSeries("Index Scans","count")
for p in data['index_scans']:
graph_index_scans.addPoint("count", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_t_ins = flotgraph.Graph ("gtupins","right")
graph_t_ins.addSeries("Inserts","count",'#FF0000')
for p in data['ins']:
graph_t_ins.addPoint("count", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_t_upd = flotgraph.Graph ("gtupupd","right")
graph_t_upd.addSeries("Updates","count",'#FF8800')
graph_t_upd.addSeries("Hot Updates","hotcount",'#885500')
for p in data['upd']:
graph_t_upd.addPoint("count", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
for p in data['hot']:
graph_t_upd.addPoint("hotcount", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_t_del = flotgraph.Graph ("gtupdel","right")
graph_t_del.addSeries("Deletes","count")
for p in data['del']:
graph_t_del.addPoint("count", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
data = tabledata.getTableIOData(hostId, name, interval)
graph_index_iob = flotgraph.Graph ("graphindexiob","right")
graph_index_iob.addSeries("Index_hit","ihit")
for p in data['index_hit']:
graph_index_iob.addPoint("ihit", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_index_iod = flotgraph.Graph ("graphindexiod","right")
graph_index_iod.addSeries("Index_read","iread",'#FF0000')
for p in data['index_read']:
graph_index_iod.addPoint("iread", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_heap_iod = flotgraph.Graph ("graphheapiod","right")
graph_heap_iod.addSeries("Heap_read","hread",'#FF0000')
for p in data['heap_read']:
graph_heap_iod.addPoint("hread", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
graph_heap_iob = flotgraph.Graph ("graphheapiob","right")
graph_heap_iob.addSeries("Heap_hit","hhit")
for p in data['heap_hit']:
graph_heap_iob.addPoint("hhit", int(time.mktime(p[0].timetuple()) * 1000) , p[1])
tpl = tplE.env.get_template('table_detail.html')
return tpl.render(name=name,
schema_name=name[:name.find('.')],
host=hostId,
interval=interval,
hostuiname = hostUiName,
hostname = hosts.getHosts()[hostId]['uilongname'],
graphtablesize=graph_table_size.render(),
graphindexsize=graph_index_size.render(),
graphseqscans=graph_seq_scans.render(),
graphindexscans=graph_index_scans.render(),
graphindexiod=graph_index_iod.render(),
graphindexiob=graph_index_iob.render(),
graphheapiod=graph_heap_iod.render(),
graphheapiob=graph_heap_iob.render(),
gtupins=graph_t_ins.render(),
gtupupd=graph_t_upd.render(),
gtupdel=graph_t_del.render(),
target='World')
def default(self, *p, **params):
if len(p) < 2:
return ""
hostId = int(p[0]) if p[0].isdigit() else hosts.uiShortnameToHostId(
p[0])
hostUiName = p[0] if not p[0].isdigit() else hosts.hostIdToUiShortname(
p[0])
table_name = p[1]
if table_name.find('.') == -1:
raise Exception('Full table name needed, e.g. schema_x.table_y')
schema = table_name.split('.')[0]
if 'from' in params and 'to' in params:
interval = {}
interval['from'] = params['from']
interval['to'] = params['to']
else:
interval = {}
interval['from'] = (
datetime.datetime.now() -
datetime.timedelta(days=14)).strftime('%Y-%m-%d')
interval['to'] = (datetime.datetime.now() +
datetime.timedelta(days=1)).strftime('%Y-%m-%d')
data = indexdata.getIndexesDataForTable(hostId, table_name,
interval['from'],
interval['to'])
all_graphs = []
i = 0
for x in data:
one_index_graphs = []
for k, v in x['data'].iteritems():
i += 1
if k == 'size':
graph = flotgraph.SizeGraph("index" + str(i), "right")
else:
graph = flotgraph.Graph("index" + str(i), "right")
graph.addSeries(k, k)
for p in v:
graph.addPoint(k,
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph = graph.render()
one_index_graphs.append({'data': graph, 'i': i, 'type': k})
one_index_graphs.sort(key=lambda x: x['type'])
all_graphs.append({
'name':
x['index_name'],
'graphs':
one_index_graphs,
'last_index_size':
x['last_index_size'],
'total_end_size':
x['total_end_size'],
'pct_of_total_end_size':
x['pct_of_total_end_size']
})
all_graphs = sorted(all_graphs,
key=lambda x: x['last_index_size'],
reverse=True)
tpl = tplE.env.get_template('table_indexes.html')
return tpl.render(table_name=table_name,
host=hostId,
schema=schema,
interval=interval,
hostuiname=hostUiName,
hostname=hosts.getHosts()[hostId]['uilongname'],
all_graphs=all_graphs,
target='World')
def default(self, *p, **params):
if len(p) == 0:
return """Error: Not enough URL parameters. Hostname needed"""
hostId, hostName = hosts.ensureHostIdAndUIShortname(p[0])
sprocName = None
if len(p) > 1:
sprocName = p[1]
if params.get('search'):
sprocName = params.get('sproc_search')
url = '/sprocs/show/' + hostName + '/' + sprocName
raise cherrypy.HTTPRedirect(cherrypy.url(url))
interval = {}
interval['from'] = params.get(
'from', (datetime.datetime.now() -
datetime.timedelta(days=8)).strftime('%Y-%m-%d'))
interval['to'] = params.get(
'to', (datetime.datetime.now() +
datetime.timedelta(days=1)).strftime('%Y-%m-%d'))
graphcalls = flotgraph.Graph("graphcalls")
graphcalls.addSeries('Number of calls', 'calls')
graphtime = flotgraph.TimeGraph("graphruntime")
graphtime.addSeries('Total run time', 'runtime')
graphavg = flotgraph.TimeGraph("graphavg")
graphavg.addSeries('Average run time', 'avg')
graphavgself = flotgraph.TimeGraph("graphselfavg")
graphavgself.addSeries('Average self time', 'avgself')
data = sprocdata.getSingleSprocData(hostId, sprocName, interval)
if data['name']: # None if no data for sproc found
for p in data['total_time']:
graphtime.addPoint('runtime',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
for p in data['calls']:
graphcalls.addPoint('calls',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
for p in data['avg_time']:
graphavg.addPoint('avg',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
for p in data['avg_self_time']:
graphavgself.addPoint(
'avgself', int(time.mktime(p[0].timetuple()) * 1000), p[1])
sproc_name_wo_params = data['name'] if data['name'].find(
'(') == -1 else data['name'][0:data['name'].find('(')]
sproc_params = "" if data['name'].find(
'(') == -1 else data['name'][data['name'].find('(') + 1:-1]
all_sprocs = sprocdata.getAllActiveSprocNames(hostId)
table = tplE.env.get_template('sproc_detail.html')
return table.render(
hostid=hostId,
hostname=hosts.getHostData()[int(hostId)]['uilongname'],
hostuiname=hostName,
name_w_params=data['name'],
params=sproc_params if data['name'] else None,
name_wo_params=sproc_name_wo_params if data['name'] else None,
interval=interval,
sproc_name=sprocName,
all_sprocs=all_sprocs,
all_sprocs_json=json.dumps(all_sprocs),
graphavg=graphavg.render(),
graphselfavg=graphavgself.render(),
graphcalls=graphcalls.render(),
graphruntime=graphtime.render())
def default(self, hostId):
hostId, hostUiName = hosts.ensureHostIdAndUIShortname(
max(hostId, hostId))
days = (cherrypy.request.cookie['days'].value
if 'days' in cherrypy.request.cookie else '8')
sprocs_to_show = (int(cherrypy.request.cookie['sprocs_to_show'].value)
if 'sprocs_to_show' in cherrypy.request.cookie else
10)
graph_load = None
graph_wal = None
graph_size = None
graph_dbstats = None
top_sprocs = None
top_statements = None
graph_checkpoint = None
global_announcement = reportdata.getGetActiveFrontendAnnouncementIfAny(
) # fyi - no escaping is performed deliberately
if tplE._settings.get('show_load', True):
graph_load = flotgraph.Graph('graph_load', 'left', 30)
graph_load.addSeries('CPU Load 15min avg', 'acpu_15min_avg',
'#FF0000')
cpuload = topsprocs.getCpuLoad(hostId, days)
for p in cpuload['load_15min_avg']:
graph_load.addPoint('acpu_15min_avg',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
load = topsprocs.getLoad(hostId, days)
graph_load.addSeries('Sproc Load 15 min', 'load_15min')
for p in load['load_15min']:
graph_load.addPoint('load_15min',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_load = graph_load.render()
if tplE._settings.get('show_wal', True):
graph_wal = flotgraph.Graph('graph_wal', 'left', 30)
graph_wal.addSeries('WAL vol. 15 min (in MB)', 'wal_15min')
walvolumes = topsprocs.getWalVolumes(hostId, days)
for p in walvolumes['wal_15min_growth']:
graph_wal.addPoint('wal_15min',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
if hosts.isHostFeatureEnabled(hostId,
'blockingStatsGatherInterval'):
blocked_processes = topsprocs.getBlockedProcessesCounts(
hostId, days)
graph_wal.addSeries('#Blocked processes (> 5s)',
'blocked_processes', '#FF0000', None, 2)
for p in blocked_processes:
if len(walvolumes['wal_15min_growth']
) > 0 and p[0].timetuple(
) >= walvolumes['wal_15min_growth'][0][0].timetuple(
): # aligning timeline with WAL data
graph_wal.addPoint(
'blocked_processes',
int(time.mktime(p[0].timetuple()) * 1000), p[1])
graph_wal = graph_wal.render()
if tplE._settings.get('show_db_size', True):
graph_size = flotgraph.SizeGraph('graph_size')
sizes = tabledata.getDatabaseSizes(hostId, days)
if hostId in sizes:
tabledata.fillGraph(graph_size, sizes[hostId])
graph_size = graph_size.render()
if tplE._settings.get('show_db_stats', True):
dbstats = reportdata.getDatabaseStatistics(hostId, days)
if len(dbstats) > 0:
graph_dbstats = flotgraph.SizeGraph('graph_dbstats')
graph_dbstats.addSeries('Temp bytes written',
'temp_files_bytes')
graph_dbstats.addSeries('#Backends / 10', 'numbackends',
'#C0C0C0', None, 2)
graph_dbstats.addSeries('#Deadlocks', 'deadlocks', '#FF0000',
None, 2)
graph_dbstats.addSeries('#Rollbacks [incl. exceptions]',
'rollbacks', '#FFFF00', None, 2)
for d in dbstats:
timestamp = int(
time.mktime(d['timestamp'].timetuple()) * 1000)
graph_dbstats.addPoint('temp_files_bytes', timestamp,
d['temp_files_bytes'])
graph_dbstats.addPoint('deadlocks', timestamp,
d['deadlocks'])
graph_dbstats.addPoint('numbackends', timestamp,
d['numbackends'] / 10.0)
graph_dbstats.addPoint('rollbacks', timestamp,
d['rollbacks'])
graph_dbstats = graph_dbstats.render()
if tplE._settings.get('show_top_sprocs', True):
top_sprocs = {}
top_sprocs['hours1avg'] = self.renderTop10LastHours(
topsprocs.avgRuntimeOrder, 1, hostId, sprocs_to_show)
top_sprocs['hours3avg'] = self.renderTop10LastHours(
topsprocs.avgRuntimeOrder, 3, hostId, sprocs_to_show)
top_sprocs['hours1total'] = self.renderTop10LastHours(
topsprocs.totalRuntimeOrder, 1, hostId, sprocs_to_show)
top_sprocs['hours3total'] = self.renderTop10LastHours(
topsprocs.totalRuntimeOrder, 3, hostId, sprocs_to_show)
top_sprocs['hours1calls'] = self.renderTop10LastHours(
topsprocs.totalCallsOrder, 1, hostId, sprocs_to_show)
top_sprocs['hours3calls'] = self.renderTop10LastHours(
topsprocs.totalCallsOrder, 3, hostId, sprocs_to_show)
if tplE._settings.get('show_top_statements', False):
top_statements = {}
tsd = topstatements.getTopStatementsData(hostId,
interval1='3hours',
interval2='1hours',
limit=sprocs_to_show)
if tsd:
top_statements[
'hours1avg'] = self.renderTop10StatementsLastHours(
hostId, tsd.get('avg_int2', []))
top_statements[
'hours3avg'] = self.renderTop10StatementsLastHours(
hostId, tsd.get('avg_int1', []))
top_statements[
'hours1total'] = self.renderTop10StatementsLastHours(
hostId, tsd.get('total_int2', []))
top_statements[
'hours3total'] = self.renderTop10StatementsLastHours(
hostId, tsd.get('total_int1', []))
top_statements[
'hours1calls'] = self.renderTop10StatementsLastHours(
hostId, tsd.get('calls_int2', []))
top_statements[
'hours3calls'] = self.renderTop10StatementsLastHours(
hostId, tsd.get('calls_int1', []))
if tplE._settings.get('show_bgwriter_stats', True):
graph_checkpoint = self.get_rendered_bgwriter_graph(
hostId, int(days))
tmpl = tplE.env.get_template('index.html')
return tmpl.render(
hostid=hostId,
hostname=hosts.getHostnameByHostId(hostId),
hostuiname=hostUiName,
graph_load=graph_load,
graph_wal=graph_wal,
graph_size=graph_size,
graph_dbstats=graph_dbstats,
graph_checkpoint=graph_checkpoint,
top_sprocs=top_sprocs,
top_statements=top_statements,
limit=sprocs_to_show,
features=hosts.getActiveFeatures(hostId),
global_announcement=global_announcement,
target='World',
)
def show(self):
tmpl = env.get_template('logfiles.html')
graphtemp = flotgraph.Graph("tempfilesgraph")
graphtemp.addSeries('Temporary files', 'temp_files', '#FF0000')
tempfile_data = logdata.load_temporary_lines(self.hostId)
for p in tempfile_data:
graphtemp.addPoint('temp_files',
int(time.mktime(p[0].timetuple()) * 1000), p[1])
grapherror = flotgraph.Graph("errorgraph")
grapherror.addSeries('Errors', 'errors', '#FF0000')
grapherror.addSeries('User', 'users', '#FF9900')
error_data = logdata.load_error_lines(self.hostId)
last_x = 0
for p in error_data:
if last_x != 0 and int(time.mktime(
p[0].timetuple())) - last_x > 10 * 60:
grapherror.addPoint('errors', (last_x + 60) * 1000, 0)
grapherror.addPoint(
'errors', (int(time.mktime(p[0].timetuple())) - 60) * 1000,
0)
grapherror.addPoint('errors',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
error_data = logdata.load_user_error_lines(self.hostId)
last_x = 0
for p in error_data:
if last_x != 0 and int(time.mktime(
p[0].timetuple())) - last_x > 10 * 60:
grapherror.addPoint('users', (last_x + 60) * 1000, 0)
grapherror.addPoint(
'users', (int(time.mktime(p[0].timetuple())) - 60) * 1000,
0)
grapherror.addPoint('users',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graphtimeout = flotgraph.Graph("timeoutgraph")
graphtimeout.addSeries('Timeouts', 'timeout', '#FF0000')
graphtimeout.addSeries('User', 'users', '#FF9900')
timeout_data = logdata.load_timeout_lines(self.hostId)
last_x = 0
for p in timeout_data:
if last_x != 0 and int(time.mktime(
p[0].timetuple())) - last_x > 10 * 60:
graphtimeout.addPoint('timeout', (last_x + 60) * 1000, 0)
graphtimeout.addPoint(
'timeout',
(int(time.mktime(p[0].timetuple())) - 60) * 1000, 0)
last_x = int(time.mktime(p[0].timetuple()))
graphtimeout.addPoint('timeout',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
timeout_data = logdata.load_user_timeout_lines(self.hostId)
for p in timeout_data:
graphtimeout.addPoint('users',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graphwait = flotgraph.Graph("waitgraph")
graphwait.addSeries('Waits', 'waits', '#FF0000')
wait_data = logdata.load_wait_lines(self.hostId)
for p in wait_data:
graphwait.addPoint('waits',
int(time.mktime(p[0].timetuple()) * 1000), p[1])
return tmpl.render(hostid=self.hostId,
tempfilesgraph=graphtemp.render(),
errorgraph=grapherror.render(),
timeoutgraph=graphtimeout.render(),
waitgraph=graphwait.render(),
target='World')
def default(self, *p, **params):
graphcalls = flotgraph.Graph("graphcalls")
graphcalls.addSeries('Number of calls', 'calls')
graphtime = flotgraph.TimeGraph("graphruntime")
graphtime.addSeries('Total run time', 'runtime')
graphavg = flotgraph.TimeGraph("graphavg")
graphavg.addSeries('Average run time', 'avg')
graphavgself = flotgraph.TimeGraph("graphselfavg")
graphavgself.addSeries('Average self time', 'avgself')
if (len(p) <= 1):
return """Error: Not enough URL paramter"""
hostId = p[0]
name = p[1]
if len(p) > 2:
sprocNr = p[2]
else:
sprocNr = None
if 'from' in params and 'to' in params:
interval = {}
interval['from'] = params['from']
interval['to'] = params['to']
else:
interval = {}
interval['from'] = (
datetime.datetime.now() -
datetime.timedelta(days=14)).strftime('%Y-%m-%d')
interval['to'] = (datetime.datetime.now() +
datetime.timedelta(days=1)).strftime('%Y-%m-%d')
data = sprocdata.getSingleSprocData(name, hostId, interval, sprocNr)
for p in data['total_time']:
graphtime.addPoint('runtime',
int(time.mktime(p[0].timetuple()) * 1000), p[1])
for p in data['calls']:
graphcalls.addPoint('calls',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
for p in data['avg_time']:
graphavg.addPoint('avg', int(time.mktime(p[0].timetuple()) * 1000),
p[1])
for p in data['avg_self_time']:
graphavgself.addPoint('avgself',
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
table = tplE.env.get_template('sproc_detail.html')
return table.render(hostid=int(hostId),
hostname=hosts.getHostData()[int(hostId)]
['settings']['uiLongName'],
name=data['name'],
interval=interval,
graphavg=graphavg.render(),
graphselfavg=graphavgself.render(),
graphcalls=graphcalls.render(),
graphruntime=graphtime.render())
def default(self, *p, **params):
if len(p) < 2:
return ""
host = p[0]
name = p[1]
if 'interval' in params:
interval = {}
interval['interval'] = str(params['interval']) + ' days'
elif 'from' in params and 'to' in params:
interval = {}
interval['from'] = params['from']
interval['to'] = params['to']
else:
interval = {}
interval['from'] = (
datetime.datetime.now() -
datetime.timedelta(days=14)).strftime('%Y-%m-%d')
interval['to'] = (datetime.datetime.now() +
datetime.timedelta(days=1)).strftime('%Y-%m-%d')
data = tabledata.getTableData(host, name, interval)
graph_table_size = flotgraph.SizeGraph("graphtablesize", "right")
graph_table_size.addSeries("Table Size", "size")
for p in data['table_size']:
graph_table_size.addPoint(
"size", int(time.mktime(p[0].timetuple()) * 1000), p[1])
graph_index_size = flotgraph.SizeGraph("graphindexsize", "right")
graph_index_size.addSeries("Index Size", "size")
for p in data['index_size']:
graph_index_size.addPoint(
"size", int(time.mktime(p[0].timetuple()) * 1000), p[1])
graph_seq_scans = flotgraph.Graph("graphseqscans", "right")
graph_seq_scans.addSeries("Sequential Scans", "count")
for p in data['seq_scans']:
graph_seq_scans.addPoint("count",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_index_scans = flotgraph.Graph("graphindexscans", "right")
graph_index_scans.addSeries("Index Scans", "count")
for p in data['index_scans']:
graph_index_scans.addPoint(
"count", int(time.mktime(p[0].timetuple()) * 1000), p[1])
graph_t_ins = flotgraph.Graph("gtupins", "right")
graph_t_ins.addSeries("Inserts", "count", '#FF0000')
for p in data['ins']:
graph_t_ins.addPoint("count",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_t_upd = flotgraph.Graph("gtupupd", "right")
graph_t_upd.addSeries("Updates", "count", '#FF8800')
graph_t_upd.addSeries("Hot Updates", "hotcount", '#885500')
for p in data['upd']:
graph_t_upd.addPoint("count",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
for p in data['hot']:
graph_t_upd.addPoint("hotcount",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_t_del = flotgraph.Graph("gtupdel", "right")
graph_t_del.addSeries("Deletes", "count")
for p in data['del']:
graph_t_del.addPoint("count",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
data = tabledata.getTableIOData(host, name)
graph_index_iob = flotgraph.Graph("graphindexiob", "right")
graph_index_iob.addSeries("Index_hit", "ihit")
for p in data['index_hit']:
graph_index_iob.addPoint("ihit",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_index_iod = flotgraph.Graph("graphindexiod", "right")
graph_index_iod.addSeries("Index_read", "iread", '#FF0000')
for p in data['index_read']:
graph_index_iod.addPoint("iread",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_heap_iod = flotgraph.Graph("graphheapiod", "right")
graph_heap_iod.addSeries("Heap_read", "hread", '#FF0000')
for p in data['heap_read']:
graph_heap_iod.addPoint("hread",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
graph_heap_iob = flotgraph.Graph("graphheapiob", "right")
graph_heap_iob.addSeries("Heap_hit", "hhit")
for p in data['heap_hit']:
graph_heap_iob.addPoint("hhit",
int(time.mktime(p[0].timetuple()) * 1000),
p[1])
tpl = tplE.env.get_template('table_detail.html')
return tpl.render(
name=name,
host=host,
interval=interval,
hostname=hosts.getHostData()[int(host)]['settings']['uiLongName'],
graphtablesize=graph_table_size.render(),
graphindexsize=graph_index_size.render(),
graphseqscans=graph_seq_scans.render(),
graphindexscans=graph_index_scans.render(),
graphindexiod=graph_index_iod.render(),
graphindexiob=graph_index_iob.render(),
graphheapiod=graph_heap_iod.render(),
graphheapiob=graph_heap_iob.render(),
gtupins=graph_t_ins.render(),
gtupupd=graph_t_upd.render(),
gtupdel=graph_t_del.render(),
target='World')
