How to use our index name in data section in vega?

Elastic Stack Kibana
1

I want to create tree layout graph in vega from my index which its name is 123. the index has many fields but I want only two fields of the index to be showed in the graph which is A and B. The question is how to use my index name in data section of the query. an example of tree layout query is presented below. so please help me how to add my index name in the data section in below query.

{
  "$schema": "https://vega.github.io/schema/vega/v5.json",
  "description": "An example of Cartesian layouts for a node-link diagram of hierarchical data.",
  "width": 600,
  "height": 1600,
  "padding": 5,

  "signals": [
    {
      "name": "labels", "value": true,
      "bind": {"input": "checkbox"}
    },
    {
      "name": "layout", "value": "tidy",
      "bind": {"input": "radio", "options": ["tidy", "cluster"]}
    },
    {
      "name": "links", "value": "diagonal",
      "bind": {
        "input": "select",
        "options": ["line", "curve", "diagonal", "orthogonal"]
      }
    },
    {
      "name": "separation", "value": false,
      "bind": {"input": "checkbox"}
    }
  ],

  "data": [
    {
      "name": "tree",
      "url": "data/flare.json",
      "transform": [
        {
          "type": "stratify",
          "key": "id",
          "parentKey": "parent"
        },
        {
          "type": "tree",
          "method": {"signal": "layout"},
          "size": [{"signal": "height"}, {"signal": "width - 100"}],
          "separation": {"signal": "separation"},
          "as": ["y", "x", "depth", "children"]
        }
      ]
    },
    {
      "name": "links",
      "source": "tree",
      "transform": [
        { "type": "treelinks" },
        {
          "type": "linkpath",
          "orient": "horizontal",
          "shape": {"signal": "links"}
        }
      ]
    }
  ],

  "scales": [
    {
      "name": "color",
      "type": "linear",
      "range": {"scheme": "magma"},
      "domain": {"data": "tree", "field": "depth"},
      "zero": true
    }
  ],

  "marks": [
    {
      "type": "path",
      "from": {"data": "links"},
      "encode": {
        "update": {
          "path": {"field": "path"},
          "stroke": {"value": "#ccc"}
        }
      }
    },
    {
      "type": "symbol",
      "from": {"data": "tree"},
      "encode": {
        "enter": {
          "size": {"value": 100},
          "stroke": {"value": "#fff"}
        },
        "update": {
          "x": {"field": "x"},
          "y": {"field": "y"},
          "fill": {"scale": "color", "field": "depth"}
        }
      }
    },
    {
      "type": "text",
      "from": {"data": "tree"},
      "encode": {
        "enter": {
          "text": {"field": "name"},
          "fontSize": {"value": 9},
          "baseline": {"value": "middle"}
        },
        "update": {
          "x": {"field": "x"},
          "y": {"field": "y"},
          "dx": {"signal": "datum.children ? -7 : 7"},
          "align": {"signal": "datum.children ? 'right' : 'left'"},
          "opacity": {"signal": "labels ? 1 : 0"}
        }
      }
    }
  ]
}
2

If you follow the Vega tutorial you'll see that the data key is in fact an object that encodes a url parameter with the query that you want to do against Elasticsearch and an index parameter.

This is a screenshot from one of the vega visualization included with the sample data

image
image1291×976 77.5 KB

1 Like
3

thanks from help

4

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