Vega-lite 数据转换为 un-nest objects

Question

数据来自 elasticsearch url 并具有以下形式：

{
    "took": 44,
    "timed_out": false,
    "hits": {
        "total": 11,
        "max_score": 0,
        "hits": [
            {
                "_index": "dataindex",
                "_type": "span",
                "_id": "tKVUs3kBhoeKMUMeIwCv",
                "_score": 0,
                "_source": {
                    "fieldA": 272.2,
                    "fieldB": 73,
                    "fieldX": "event 1"
                }
            },
            {
                "_index": "dataindex",
                "_type": "span",
                "_id": "iuVetHkBhoeKMUMe4O92",
                "_score": 0,
                "_source": {
                    "fieldA": 305.2,
                    "fieldB": 80,
                    "fieldX": "event 2"
                }
            },
            {
                "_index": "dataindex",
                "_type": "span",
                "_id": "Yt-QwXkBhoeKMUMex3tp",
                "_score": 0,
                "_source": {
                    "fieldA": 281.8,
                    "fieldB": 73,
                    "fieldX": "event 3"
                }
            }
        ]
    }
}

我想制作一个散点图矩阵。 hits.hits下的数据数组可以通过format.property配置访问。

{
  "$schema": "https://vega.github.io/schema/vega-lite/v4.json",
  "repeat": {
    "row": [
      "_source.fieldA",
      "_source.fieldB"
    ],
    "column": [
      "_source.fieldB",
      "_source.fieldA"
    ]
  },
  "spec": {
    "data": {
      "url": "url/to/elastic/query",
      "format": {"property": "hits.hits", "type": "json"}
    },
    "mark": "point",
    "encoding": {
      "x": {
        "field": {"repeat": "column"},
        "type": "quantitative"
      },
      "y": {
        "field": {"repeat": "row"},
        "type": "quantitative"
      },
      "color": {
        "field": "_source.fieldX",
        "type": "nominal"
      },
      "shape": {
        "field": "_source.fieldX",
        "type": "nominal"
      }
    }
  }
}

但是还有一个额外的 _source 级别需要在任何地方指出（重复、颜色、形状），而且它在轴和图例标题中也是这样显示的：

是否有可以消除此 _source 级别的转换类型？因此，进入 encoding 阶段的数据可能就像源只是

[
{
    "fieldA": 272.2,
    "fieldB": 73,
    "fieldX": "event 1"
},{
    "fieldA": 305.2,
    "fieldB": 80,
    "fieldX": "event 2"
}
]

或者在重复矩阵中动态重命名轴的方法？

Answer 1

有一种方法，您必须提供一次字段，它会出现在单个级别而不是嵌套。按照下面或 editor:

中的方法执行 calculate 转换

{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
    "transform": [
    {"calculate": "datum._source.fieldA", "as": "fieldA"},
    {"calculate": "datum._source.fieldB", "as": "fieldB"},
    {"calculate": "datum._source.fieldX", "as": "fieldX"}
  ],
  "repeat": {
    "row": ["fieldA", "fieldB"],
    "column": ["fieldB", "fieldA"]
  },
  "spec": {
    "data": {
      "values": {
        "took": 44,
        "timed_out": false,
        "hits": {
          "total": 11,
          "max_score": 0,
          "hits": [
            {
              "_index": "dataindex",
              "_type": "span",
              "_id": "tKVUs3kBhoeKMUMeIwCv",
              "_score": 0,
              "_source": {"fieldA": 272.2, "fieldB": 73, "fieldX": "event 1"}
            },
            {
              "_index": "dataindex",
              "_type": "span",
              "_id": "iuVetHkBhoeKMUMe4O92",
              "_score": 0,
              "_source": {"fieldA": 305.2, "fieldB": 80, "fieldX": "event 2"}
            },
            {
              "_index": "dataindex",
              "_type": "span",
              "_id": "Yt-QwXkBhoeKMUMex3tp",
              "_score": 0,
              "_source": {"fieldA": 281.8, "fieldB": 73, "fieldX": "event 3"}
            }
          ]
        }
      },
      "format": {"property": "hits.hits", "type": "json"}
    },
    "mark": "point",
    "encoding": {
      "x": {"field": {"repeat": "column"}, "type": "quantitative"},
      "y": {"field": {"repeat": "row"}, "type": "quantitative"},
      "color": {"field": "fieldX", "type": "nominal"},
      "shape": {"field": "fieldX", "type": "nominal"}
    }
  }
}

Vega-lite 数据转换为 un-nest objects

Vega-lite data transformation to un-nest objects

elasticsearch

vega-lite