datatype='float',
extractor='avg_sql.packets')
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('sql-overall-ts', source='sql_summaries')
# 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('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)
extractor='rtp.media_type_name')
t1.add_column('packets', 'Number of RTP Packets', datatype='integer',
extractor='sum_rtp.packets')
t1.add_column('bytes', 'Number of RTP Bytes',
datatype='integer', extractor='sum_rtp.traffic_bytes')
# 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',
extractor='avg_traffic.total_bytes_ps')
t1.add_column('srv_response_time', 'Average Server Response Time (seconds)',
datatype='float', extractor='avg_tcp.srv_response_time')
t1.add_column('usr_response_time', 'Average User Response Time (seconds)',
datatype='float', extractor='avg_tcp.user_response_time')
# 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',
'DB Instance',
datatype='string',
iskey=True,
extractor='db.instance')
t.add_column('active_sessions',
'Concurrent Active DB Sessions',
datatype='float',
extractor='avg_db.active_sessions')
t.add_column('active_time',
'Total Duration of Active Sessions',
datatype='float',
extractor='sum_db.session_active_time')
t1 = AppResponseTimeSeriesTable.create('db-sessions',
tables={'base': t},
pivot_column_label='DB Instances',
pivot_column_name='db_instance',
value_column_name='active_sessions')
report.add_widget(c3.TimeSeriesWidget,
t1,
'Concurrent Active DB Sessions',
width=12)
t2 = AppResponseTimeSeriesTable.create('db-time',
tables={'base': t},
pivot_column_label='DB Instance',
pivot_column_name='db_instance',
value_column_name='active_time')
report.add_widget(c3.TimeSeriesWidget,
t2,
extractor='web.page.family.id')
t.add_column('page_family_name',
'Web Page Family Name',
datatype='string',
extractor='web.page.family.name')
t.add_column('pages',
'Number of Pages Viewed',
datatype='integer',
extractor='sum_web.pages')
t.add_column('page_bps',
'Average Page Throughput (BPS)',
datatype='float',
extractor='avg_web.traffic_bytes_ps')
t1 = AppResponseTimeSeriesTable.create('web-pages',
tables={'base': t},
pivot_column_label='App Names',
pivot_column_name='page_family_name',
value_column_name='pages')
report.add_widget(yui3.TimeSeriesWidget, t1, 'Number of Pages', width=12)
t2 = AppResponseTimeSeriesTable.create('web-page-bps',
tables={'base': t},
pivot_column_name='page_family_name',
value_column_name='page_bps')
report.add_widget(yui3.TimeSeriesWidget,
t2,
'Average Page Throughput',
width=12)
datatype='string',
iskey=True,
extractor='rtp.media_type')
t.add_column('media_type_name',
'Media Type Name',
datatype='string',
extractor='rtp.media_type_name')
t.add_column('packets',
'Number of RTP Packets',
datatype='integer',
extractor='sum_rtp.packets')
t.add_column('bytes',
'Number of RTP Packets',
datatype='float',
extractor='sum_rtp.traffic_bytes')
t1 = AppResponseTimeSeriesTable.create('uc-packets',
tables={'base': t},
pivot_column_label='Media Types',
pivot_column_name='media_type_name',
value_column_name='packets')
report.add_widget(c3.TimeSeriesWidget, t1, 'Number of Packets', width=12)
t2 = AppResponseTimeSeriesTable.create('uc-bytes',
tables={'base': t},
pivot_column_label='Media Types',
pivot_column_name='media_type_name',
value_column_name='bytes')
report.add_widget(c3.TimeSeriesWidget, t2, 'Number of Bytes', width=12)
'Client Process Name',
datatype='string',
iskey=True,
extractor='db.process_name')
t.add_column('sql_duration',
'Transaction Time',
datatype='float',
extractor='avg_sql.duration')
t.add_column('sql_packets',
'Average Packets',
datatype='float',
extractor='avg_sql.packets')
t1 = AppResponseTimeSeriesTable.create('sql-duration-ts',
tables={'base': t},
pivot_column_label='SQL Process Names',
pivot_column_name='db_process',
value_column_name='sql_duration')
report.add_widget(c3.TimeSeriesWidget,
t1,
'Average Transaction Time (Seconds)',
width=12)
t2 = AppResponseTimeSeriesTable.create('sql-packets',
tables={'base': t},
pivot_column_label='SQL Process Names',
pivot_column_name='db_process',
value_column_name='sql_packets')
report.add_widget(c3.TimeSeriesWidget, t2, 'Average SQL Packets', width=12)
extractor='sum_db.session_active_time')
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('db-session-overall-ts',
source='dbsession_summaries')
# 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('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)
datatype='float',
extractor='avg_web.traffic_bytes_ps')
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('wta-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('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)
t.add_column('srv_response_time',
'Average Server Response Time (seconds)',
datatype='float',
extractor='avg_tcp.srv_response_time')
t.add_column('usr_response_time',
'Average User Response Time (seconds)',
datatype='float',
extractor='avg_tcp.user_response_time')
t.add_column('total_bytes',
'Average Bytes per Second',
datatype='float',
extractor='avg_traffic.total_bytes_ps')
t1 = AppResponseTimeSeriesTable.create('application-srv-response-time',
tables={'base': t},
pivot_column_label='App Names',
pivot_column_name='app_name',
value_column_name='srv_response_time')
report.add_widget(c3.TimeSeriesWidget, t1, 'Server Response Time', width=12)
t2 = AppResponseTimeSeriesTable.create('application-user-resp-time',
tables={'base': t},
pivot_column_name='app_name',
value_column_name='usr_response_time')
report.add_widget(c3.TimeSeriesWidget, t2, 'Server Response Time', width=12)
t3 = AppResponseTimeSeriesTable.create('application-throughput',
tables={'base': t},
pivot_column_name='app_name',
value_column_name='total_bytes')