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)