Explore: show meta data when available (#25798)

* Return valid metadata even if data is empty

* Make sure fields is not accessed when there is no data

* Meta Info should depend only on meta data

* Refactor condition for better reading

* Change data to empty array for better condition handling

* Remove unecessary checks

* Add test for showing metaData even when data is empty

public/app/core/logs_model.test.ts

@@ -8,7 +8,7 @@ import {
   MutableDataFrame,
   toDataFrame,
 } from '@grafana/data';
-import { dataFrameToLogsModel, dedupLogRows, getSeriesProperties } from './logs_model';
+import { dataFrameToLogsModel, dedupLogRows, getSeriesProperties, logSeriesToLogsModel } from './logs_model';
 
 describe('dedupLogRows()', () => {
   test('should return rows as is when dedup is set to none', () => {
@@ -596,6 +596,37 @@ describe('dataFrameToLogsModel', () => {
   });
 });
 
+describe('logSeriesToLogsModel', () => {
+  it('should return correct metaData even if the data is empty', () => {
+    const logSeries: DataFrame[] = [
+      {
+        fields: [],
+        length: 0,
+        refId: 'A',
+
+        meta: {
+          searchWords: ['test'],
+          limit: 1000,
+          stats: [{ displayName: 'Summary: total bytes processed', value: 97048, unit: 'decbytes' }],
+          custom: { lokiQueryStatKey: 'Summary: total bytes processed' },
+          preferredVisualisationType: 'logs',
+        },
+      },
+    ];
+
+    const metaData = {
+      hasUniqueLabels: false,
+      meta: [
+        { label: 'Limit', value: '1000 (0 returned)', kind: 1 },
+        { label: 'Total bytes processed', value: '97  kB', kind: 1 },
+      ],
+      rows: [],
+    };
+
+    expect(logSeriesToLogsModel(logSeries)).toMatchObject(metaData);
+  });
+});
+
 describe('getSeriesProperties()', () => {
   it('sets a minimum bucket size', () => {
     const result = getSeriesProperties([], 2, undefined, 3, 123);

public/app/core/logs_model.ts

@@ -269,7 +269,7 @@ function separateLogsAndMetrics(dataFrames: DataFrame[]) {
   const logSeries: DataFrame[] = [];
 
   for (const dataFrame of dataFrames) {
-    if (isLogsData(dataFrame)) {
+    if (isLogsData(dataFrame) || !dataFrame.fields.length) {
       logSeries.push(dataFrame);
       continue;
     }
@@ -303,23 +303,29 @@ export function logSeriesToLogsModel(logSeries: DataFrame[]): LogsModel | undefi
   const allLabels: Labels[] = [];
 
   // Find the fields we care about and collect all labels
-  const allSeries: LogFields[] = logSeries.map(series => {
-    const fieldCache = new FieldCache(series);
-    const stringField = fieldCache.getFirstFieldOfType(FieldType.string);
-    if (stringField?.labels) {
-      allLabels.push(stringField.labels);
-    }
-    return {
-      series,
-      timeField: fieldCache.getFirstFieldOfType(FieldType.time),
-      timeNanosecondField: fieldCache.hasFieldWithNameAndType('tsNs', FieldType.time)
-        ? fieldCache.getFieldByName('tsNs')
-        : undefined,
-      stringField,
-      logLevelField: fieldCache.getFieldByName('level'),
-      idField: getIdField(fieldCache),
-    } as LogFields;
-  });
+  let allSeries: LogFields[] = [];
+
+  if (hasFields(logSeries)) {
+    allSeries = logSeries.map(series => {
+      const fieldCache = new FieldCache(series);
+      const stringField = fieldCache.getFirstFieldOfType(FieldType.string);
+
+      if (stringField?.labels) {
+        allLabels.push(stringField.labels);
+      }
+
+      return {
+        series,
+        timeField: fieldCache.getFirstFieldOfType(FieldType.time),
+        timeNanosecondField: fieldCache.hasFieldWithNameAndType('tsNs', FieldType.time)
+          ? fieldCache.getFieldByName('tsNs')
+          : undefined,
+        stringField,
+        logLevelField: fieldCache.getFieldByName('level'),
+        idField: getIdField(fieldCache),
+      } as LogFields;
+    });
+  }
 
   const commonLabels = allLabels.length > 0 ? findCommonLabels(allLabels) : {};
 
@@ -445,6 +451,10 @@ export function logSeriesToLogsModel(logSeries: DataFrame[]): LogsModel | undefi
   };
 }
 
+function hasFields(logSeries: DataFrame[]): boolean {
+  return logSeries.some(series => series.fields.length);
+}
+
 function getIdField(fieldCache: FieldCache): FieldWithIndex | undefined {
   const idFieldNames = ['id'];
   for (const fieldName of idFieldNames) {