Hi,
Can you please tell me how to do the mapping in Elastic Search ? I am facing issue in doing visualization in Kibana .
I am having the following mapping in my application:
PUT /error_radius_stats
{
"mappings": {
"doc": {
"properties": {
"report_date":{
"type": "date",
"format": "yyyy-MM-dd"
},
"Error Radius Distribution": {
"properties": {
"Range": {
"properties": {
"0-50": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"100-200": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"1000-2000": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"200-300": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"300-400": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"400-500": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"50-100": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"500-1000": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
">2000": {
"properties": {
"Count": {
"type": "float"
},
"Percentage": {
"type": "long"
}
}
},
"Predicted error_radius": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
},
"Total wbns": {
"properties": {
"Count": {
"type": "long"
}
}
},
"error_radius-1": {
"properties": {
"Count": {
"type": "long"
},
"Percentage": {
"type": "float"
}
}
}
}
}
}
}
}
}
}
}
I want to visualize this apping in kibana using 'data_table'. The table format which I want to have is below:
range | count | Percentage
0-50 | "long" | "float value"
50-100 | "long" | "float value"
100-200 | "long" | "float value"
200-300 | "long" | "float value"
.
.
.
.
But the table I am getting now is like:
0-50 (count) | 0-50% | 50-100(count) | 50-100% ........
"long" |"float value"|"long" | "float value" ........
Basically I am getting the value row-wise. And I want the values column-wise.
Please help me out.
Thanks.