Hello Team,
Records are loaded in mongodb as per details below:
- _id
- :
- 5f76dea38c3771266ee0317c
- time
- :
- "2020-10-01 00:00"
- rnc
- :
- "MBSC_ROD"
- v10_cssr_speech_(no_ident_encrypt)(%)
- :
- "100"
- v10_cdr_speech(%)
- :
- "0"
- v10_no__of_voice_calls(number)
- :
- "58"
- v10_no__of_cs_call_drops(number)
- :
- "0"
- v10_speech_rrc_setup_success_ratio(%)
- :
- "100"
- v10_speech_rab_setup_success_ratio(%)
- :
- "100"
- v10_cs_traffic_(erl)
- :
- "1.6801"
- efd_ps_rab_setup_success_rate(%)
- :
- "99.8202"
- efd_ps_call_drop_rate(%)(%)
- :
- "0.4754"
- v10_dl_traffic_(gbytes)
- :
- "8.9251"
- v10_ul_traffic_(gbytes)
- :
- "0.8561"
- total_ps_throughput
- :
- "87217.2814"
- id
- :
- "2020-10-01 00:00MBSC_ROD"
- _id
- :
- 5f76dea38c3771266ee0317d
- time
- :
- "2020-10-01 00:00"
- rnc
- :
- "RNC_FL"
- v10_cssr_speech_(no_ident_encrypt)(%)
- :
- "99.9751"
- v10_cdr_speech(%)
- :
- "0.0234"
- v10_no__of_voice_calls(number)
- :
- "4190"
- v10_no__of_cs_call_drops(number)
- :
- "1"
- v10_speech_rrc_setup_success_ratio(%)
- :
- "99.9751"
- v10_speech_rab_setup_success_ratio(%)
- :
- "100"
- v10_cs_traffic_(erl)
- :
- "173.5029"
- efd_ps_rab_setup_success_rate(%)
- :
- "99.8672"
- efd_ps_call_drop_rate(%)(%)
- :
- "0.0589"
- v10_dl_traffic_(gbytes)
- :
- "74.2592"
- v10_ul_traffic_(gbytes)
- :
- "6.8139"
- total_ps_throughput
- :
- "363001.5898"
- id
- :
- "2020-10-01 00:00RNC_FL"
- _id
- :
- 5f76dea38c3771266ee0317e
- time
- :
- "2020-10-01 00:00"
- rnc
- :
- "RNC_PL"
- v10_cssr_speech_(no_ident_encrypt)(%)
- :
- "99.9216"
- v10_cdr_speech(%)
- :
- "0.1479"
- v10_no__of_voice_calls(number)
- :
- "3945"
- v10_no__of_cs_call_drops(number)
- :
- "6"
- v10_speech_rrc_setup_success_ratio(%)
- :
- "99.9723"
- v10_speech_rab_setup_success_ratio(%)
- :
- "99.9493"
- v10_cs_traffic_(erl)
- :
- "179.7597"
- efd_ps_rab_setup_success_rate(%)
- :
- "99.9242"
- efd_ps_call_drop_rate(%)(%)
- :
- "0.0495"
- v10_dl_traffic_(gbytes)
- :
- "87.3757"
- v10_ul_traffic_(gbytes)
- :
- "8.6842"
- total_ps_throughput
- :
- "430241.8535"
- id
- :
- "2020-10-01 00:00RNC_PL"
- _id
- :
- 5f76dea38c3771266ee0317f
- time
- :
- "2020-10-01 00:15"
- rnc
- :
- "MBSC_ROD"
- v10_cssr_speech_(no_ident_encrypt)(%)
- :
- "100"
- v10_cdr_speech(%)
- :
- "0"
- v10_no__of_voice_calls(number)
- :
- "77"
- v10_no__of_cs_call_drops(number)
- :
- "0"
- v10_speech_rrc_setup_success_ratio(%)
- :
- "100"
- v10_speech_rab_setup_success_ratio(%)
- :
- "100"
- v10_cs_traffic_(erl)
- :
- "0.9053"
- efd_ps_rab_setup_success_rate(%)
- :
- "99.725
.....
We will require to do a summation of v10_no__of_voice_calls(number) for each time based on RNCs. For example, 00:00, there are 3 RNCs. So, on Tableau, we will require the sum of 'v10_no__of_voice_calls(number)' for each RNCs at 00:00. For each time calculation will be like this.
Kindly advise.
Regards,
Roshan
7 answers