Hi all,
I need some help to figure out if this is something possible to do using Kibana.
this is the result table Im trying to get |o:
.................2016-10-05........2016-10-04........2016-10-03
field1.........ratio%..................ratio%..................ratio%
field2.........ratio%..................ratio%..................ratio%
field3.........ratio%..................ratio%..................ratio%
Where the ratio is calculated s follows:
the sum of each field per day, devided by the sum of the total of that field per day.
for example: field1 for date 2016-10-05 should have the ratio of
(100 + 110) / (150 + 150) = 210/300 = 70%
and this a sample of the data:
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb",
"_score": 1,
"_source": {
"field1": 100,
"field_name": "field1",
"env": "env1",
"date": "2016-10-05T14:00:00",
"total_counter": 150,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb",
"_score": 1,
"_source": {
"field1": 110,
"field_name": "field1",
"env": "env1",
"date": "2016-10-05T17:00:00",
"total_counter": 150,
"customer_global_id": "customer1"
}
}
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb",
"_score": 1,
"_source": {
"field1": 50,
"field_name": "field1",
"env": "env1",
"date": "2016-10-04T14:00:00",
"total_counter": 100,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb",
"_score": 1,
"_source": {
"field1": 25,
"field_name": "field1",
"env": "env1",
"date": "2016-10-05T14:00:00",
"total_counter": 50,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb1",
"_score": 1,
"_source": {
"field2": 100,
"field_name": "field2",
"env": "env1",
"date": "2016-10-05T15:00:00",
"total_counter": 150,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb2",
"_score": 1,
"_source": {
"field2": 50,
"field_name": "field2",
"env": "env1",
"date": "2016-10-04T15:00:00",
"total_counter": 100,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb3",
"_score": 1,
"_source": {
"field2": 25,
"field_name": "field2",
"env": "env1",
"date": "2016-10-05T15:00:00",
"total_counter": 50,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb11",
"_score": 1,
"_source": {
"field3": 200,
"field_name": "field3",
"env": "env1",
"date": "2016-10-05T16:00:00",
"total_counter": 200,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb12",
"_score": 1,
"_source": {
"field3": 250,
"field_name": "field3",
"env": "env1",
"date": "2016-10-04T16:00:00",
"total_counter": 300,
"customer_global_id": "customer1"
}
},
{
"_index": "mapping4",
"_type": "field_report",
"_id": "AVeVVavr_DKQUzatrBMb13",
"_score": 1,
"_source": {
"field3": 200,
"field_name": "field3",
"env": "env1",
"date": "2016-10-05T16:00:00",
"total_counter": 250,
"customer_global_id": "customer1"
}
}
Thanks to anyone who got this far