ExtractFields: properly detect value types from extracted fields (#41995)

packages/grafana-data/src/dataframe/processDataFrame.test.ts

@@ -11,6 +11,7 @@ import { DataFrameDTO, FieldType, TableData, TimeSeries } from '../types/index';
 import { dateTime } from '../datetime/moment_wrapper';
 import { MutableDataFrame } from './MutableDataFrame';
 import { ArrayDataFrame } from './ArrayDataFrame';
+import { getFieldTypeFromValue } from '.';
 
 describe('toDataFrame', () => {
   it('converts timeseries to series', () => {
@@ -118,15 +119,13 @@ describe('toDataFrame', () => {
     expect(guessFieldTypeFromValue('xxxx')).toBe(FieldType.string);
   });
 
-  it('Guess Column Types from strings', () => {
-    expect(guessFieldTypeFromValue('1')).toBe(FieldType.number);
-    expect(guessFieldTypeFromValue('1.234')).toBe(FieldType.number);
-    expect(guessFieldTypeFromValue('NaN')).toBe(FieldType.number);
-    expect(guessFieldTypeFromValue('3.125e7')).toBe(FieldType.number);
-    expect(guessFieldTypeFromValue('True')).toBe(FieldType.boolean);
-    expect(guessFieldTypeFromValue('FALSE')).toBe(FieldType.boolean);
-    expect(guessFieldTypeFromValue('true')).toBe(FieldType.boolean);
-    expect(guessFieldTypeFromValue('xxxx')).toBe(FieldType.string);
+  it('Get column types from values', () => {
+    expect(getFieldTypeFromValue(1)).toBe(FieldType.number);
+    expect(getFieldTypeFromValue(1.234)).toBe(FieldType.number);
+    expect(getFieldTypeFromValue(NaN)).toBe(FieldType.number);
+    expect(getFieldTypeFromValue(3.125e7)).toBe(FieldType.number);
+    expect(getFieldTypeFromValue(true)).toBe(FieldType.boolean);
+    expect(getFieldTypeFromValue('xxxx')).toBe(FieldType.string);
   });
 
   it('Guess Column Types from series', () => {

packages/grafana-data/src/dataframe/processDataFrame.ts

@@ -189,10 +189,33 @@ export function guessFieldTypeFromNameAndValue(name: string, v: any): FieldType
   return guessFieldTypeFromValue(v);
 }
 
+/**
+ * Check the field type to see what the contents are
+ */
+export function getFieldTypeFromValue(v: any): FieldType {
+  if (v instanceof Date || isDateTime(v)) {
+    return FieldType.time;
+  }
+
+  if (isNumber(v)) {
+    return FieldType.number;
+  }
+
+  if (isString(v)) {
+    return FieldType.string;
+  }
+
+  if (isBoolean(v)) {
+    return FieldType.boolean;
+  }
+
+  return FieldType.other;
+}
+
 /**
  * Given a value this will guess the best column type
  *
- * TODO: better Date/Time support!  Look for standard date strings?
+ * NOTE: this is will try to see if string values can be mapped to other types (like number)
  */
 export function guessFieldTypeFromValue(v: any): FieldType {
   if (v instanceof Date || isDateTime(v)) {
@@ -237,7 +260,7 @@ export function guessFieldTypeForField(field: Field): FieldType | undefined {
   // 2. Check the first non-null value
   for (let i = 0; i < field.values.length; i++) {
     const v = field.values.get(i);
-    if (v !== null) {
+    if (v != null) {
       return guessFieldTypeFromValue(v);
     }
   }

public/app/core/components/TransformersUI/extractFields/extractFields.test.ts

@@ -14,23 +14,28 @@ describe('Fields from JSON', () => {
 
     const frames = extractFieldsTransformer.transformer(cfg)([data]);
     expect(frames.length).toEqual(1);
-    expect(frames[0].fields.map((v) => v.name)).toMatchInlineSnapshot(`
-      Array [
-        "a",
-        "av",
-        "c",
-        "e",
-        "ev",
-        "h",
-        "l",
-        "o",
-        "op",
-        "s",
-        "sym",
-        "v",
-        "vw",
-        "z",
-      ]
+    expect(
+      frames[0].fields.reduce((acc, v) => {
+        acc[v.name] = v.type;
+        return acc;
+      }, {} as any)
+    ).toMatchInlineSnapshot(`
+      Object {
+        "a": "string",
+        "av": "number",
+        "c": "string",
+        "e": "number",
+        "ev": "string",
+        "h": "string",
+        "l": "string",
+        "o": "string",
+        "op": "string",
+        "s": "number",
+        "sym": "string",
+        "v": "number",
+        "vw": "string",
+        "z": "number",
+      }
     `);
   });
 });

public/app/core/components/TransformersUI/extractFields/extractFields.ts

@@ -4,7 +4,7 @@ import {
   DataTransformerID,
   Field,
   FieldType,
-  guessFieldTypeForField,
+  getFieldTypeFromValue,
   SynchronousDataTransformerInfo,
 } from '@grafana/data';
 import { findField } from 'app/features/dimensions';
@@ -72,14 +72,13 @@ function addExtractedFields(frame: DataFrame, options: ExtractFieldsOptions): Da
   }
 
   const fields = names.map((name) => {
-    const f: Field = {
+    const buffer = values.get(name);
+    return {
       name,
-      values: new ArrayVector(values.get(name)),
-      type: FieldType.boolean,
+      values: new ArrayVector(buffer),
+      type: buffer ? getFieldTypeFromValue(buffer.find((v) => v != null)) : FieldType.other,
       config: {},
-    };
-    f.type = guessFieldTypeForField(f) ?? FieldType.other;
-    return f;
+    } as Field;
   });
 
   if (!options.replace) {