t2.copy_columns(t1)
t2.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t3 = AppResponseTimeSeriesTable.create('sql-duration-ts',
tables={'base': t2},
pivot_column_name='db_process',
value_column_name='sql_duration',
hide_pivot_field=True)
t4 = AppResponseTopNTimeSeriesTable.create('sql-duration',
tables={'overall': t1},
related_tables={'ts': t3},
pivot_column_name='db_process',
value_column_name='sql_duration',
n=topn)
report.add_widget(c3.TimeSeriesWidget,
t4,
"Top {} SQL Durations".format(topn),
width=12)
t5 = AppResponseTimeSeriesTable.create('sql-packets-ts',
tables={'base': t2},
pivot_column_name='db_process',
value_column_name='sql_packets',
hide_pivot_field=True)
t6 = AppResponseTopNTimeSeriesTable.create('sql-packets',
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('applications-overall-ts', source='aggregates')
# Add this time key column is the main differentiator between t2 and t1
t2.copy_columns(t1)
t2.add_column('start_time', 'Time', datatype='time', iskey=True,
extractor='start_time')
t3 = AppResponseTimeSeriesTable.create('app-throughput-ts',
tables={'base': t2},
pivot_column_name='app_name',
value_column_name='total_bytes',
hide_pivot_field=True)
t4 = AppResponseTopNTimeSeriesTable.create('app-throughput',
tables={'overall': t1},
related_tables={'ts': t3},
pivot_column_name='app_name',
value_column_name='total_bytes',
n=topn)
report.add_widget(c3.TimeSeriesWidget, t4,
"Apps/Top {} Throughput".format(topn),
width=12)
t5 = AppResponseTimeSeriesTable.create('app-srv-resp-ts',
tables={'base': t2},
pivot_column_name='app_name',
value_column_name='srv_response_time',
hide_pivot_field=True)
t6 = AppResponseTopNTimeSeriesTable.create(
'app-srv-resp',
t2.copy_columns(t1)
t2.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t3 = AppResponseTimeSeriesTable.create('db-active-session-ts',
tables={'base': t2},
pivot_column_name='db_instance',
value_column_name='active_sessions',
hide_pivot_field=True)
t4 = AppResponseTopNTimeSeriesTable.create('db-active-session',
tables={'overall': t1},
related_tables={'ts': t3},
pivot_column_name='db_instance',
value_column_name='active_sessions',
n=topn)
report.add_widget(c3.TimeSeriesWidget,
t4,
"DB Sessions/Top {} Active Sessions".format(topn),
width=12)
t5 = AppResponseTimeSeriesTable.create('db-active-time-ts',
tables={'base': t2},
pivot_column_name='db_instance',
value_column_name='active_time',
hide_pivot_field=True)
t6 = AppResponseTopNTimeSeriesTable.create('db-active-time',
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('uc-overall-ts', source='aggregates')
# Add this time key column is the main differentiator between t2 and t1
t2.copy_columns(t1)
t2.add_column('start_time', 'Time', datatype='time', iskey=True,
extractor='start_time')
t3 = AppResponseTimeSeriesTable.create('uc-packets-ts',
tables={'base': t2},
pivot_column_name='media_type_name',
value_column_name='packets',
hide_pivot_field=True)
t4 = AppResponseTopNTimeSeriesTable.create('uc-packets',
tables={'overall': t1},
related_tables={'ts': t3},
pivot_column_name='media_type_name',
value_column_name='packets',
n=topn)
report.add_widget(c3.TimeSeriesWidget, t4,
"RTP Packets/Top {} Media Type".format(topn),
width=12)
t5 = AppResponseTimeSeriesTable.create('uc-bytes-ts',
tables={'base': t2},
pivot_column_name='media_type_name',
value_column_name='bytes',
hide_pivot_field=True)
t6 = AppResponseTopNTimeSeriesTable.create('uc-bytes',
tables={'overall': t1},
t2.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t3 = AppResponseTimeSeriesTable.create('wta-pages-ts',
tables={'base': t2},
pivot_column_name='page_family_name',
value_column_name='pages',
hide_pivot_field=True)
t4 = AppResponseTopNTimeSeriesTable.create(
'wta-pages',
tables={'overall': t1},
related_tables={'ts': t3},
pivot_column_name='page_family_name',
value_column_name='pages',
n=topn)
report.add_widget(c3.TimeSeriesWidget,
t4,
"Page Families/Top {} Pages Viewed".format(topn),
width=12)
t5 = AppResponseTimeSeriesTable.create('wta-page-bps-ts',
tables={'base': t2},
pivot_column_name='page_family_name',
value_column_name='page_bps',
hide_pivot_field=True)