Loki: Fix error when some queries return zero results (#28645)

* Fix logSeriesToLogsModel when some data frames have empty fields

* Update test

* Update public/app/core/logs_model.ts

Co-authored-by: Zoltán Bedi <zoltan.bedi@gmail.com>

Co-authored-by: Zoltán Bedi <zoltan.bedi@gmail.com>

public/app/core/logs_model.test.ts

@@ -700,6 +700,78 @@ describe('logSeriesToLogsModel', () => {
 
 
     expect(logSeriesToLogsModel(logSeries)).toMatchObject(metaData);
     expect(logSeriesToLogsModel(logSeries)).toMatchObject(metaData);
   });
   });
+  it('should return correct metaData when some data frames have empty fields', () => {
+    const logSeries: DataFrame[] = [
+      toDataFrame({
+        fields: [
+          {
+            name: 'ts',
+            type: FieldType.time,
+            values: ['1970-01-01T00:00:01Z', '1970-02-01T00:00:01Z', '1970-03-01T00:00:01Z'],
+          },
+          {
+            name: 'line',
+            type: FieldType.string,
+            values: ['WARN boooo 0', 'WARN boooo 1', 'WARN boooo 2'],
+            labels: {
+              foo: 'bar',
+              level: 'dbug',
+            },
+          },
+          {
+            name: 'id',
+            type: FieldType.string,
+            values: ['0', '1', '2'],
+          },
+        ],
+        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',
+        },
+      }),
+      toDataFrame({
+        fields: [],
+        length: 0,
+        refId: 'B',
+        meta: {
+          searchWords: ['test'],
+          limit: 1000,
+          stats: [{ displayName: 'Summary: total bytes processed', value: 97048, unit: 'decbytes' }],
+          custom: { lokiQueryStatKey: 'Summary: total bytes processed' },
+          preferredVisualisationType: 'logs',
+        },
+      }),
+    ];
+
+    const logsModel = dataFrameToLogsModel(logSeries, 0, 'utc');
+    expect(logsModel.meta).toMatchObject([
+      { kind: 2, label: 'Common labels', value: { foo: 'bar', level: 'dbug' } },
+      { kind: 1, label: 'Limit', value: '2000 (3 returned)' },
+      { kind: 1, label: 'Total bytes processed', value: '194  kB' },
+    ]);
+    expect(logsModel.rows).toHaveLength(3);
+    expect(logsModel.rows).toMatchObject([
+      {
+        entry: 'WARN boooo 0',
+        labels: { foo: 'bar' },
+        logLevel: LogLevel.debug,
+      },
+      {
+        entry: 'WARN boooo 1',
+        labels: { foo: 'bar' },
+        logLevel: LogLevel.debug,
+      },
+      {
+        entry: 'WARN boooo 2',
+        labels: { foo: 'bar' },
+        logLevel: LogLevel.debug,
+      },
+    ]);
+  });
 });
 });
 
 
 describe('getSeriesProperties()', () => {
 describe('getSeriesProperties()', () => {

public/app/core/logs_model.ts

@@ -270,6 +270,7 @@ function separateLogsAndMetrics(dataFrames: DataFrame[]) {
   const logSeries: DataFrame[] = [];
   const logSeries: DataFrame[] = [];
 
 
   for (const dataFrame of dataFrames) {
   for (const dataFrame of dataFrames) {
+    // We want to show meta stats even if no result was returned. That's why we are pushing also data frames with no fields.
     if (isLogsData(dataFrame) || !dataFrame.fields.length) {
     if (isLogsData(dataFrame) || !dataFrame.fields.length) {
       logSeries.push(dataFrame);
       logSeries.push(dataFrame);
       continue;
       continue;
@@ -306,8 +307,12 @@ export function logSeriesToLogsModel(logSeries: DataFrame[]): LogsModel | undefi
   // Find the fields we care about and collect all labels
   // Find the fields we care about and collect all labels
   let allSeries: LogFields[] = [];
   let allSeries: LogFields[] = [];
 
 
-  if (hasFields(logSeries)) {
-    allSeries = logSeries.map(series => {
+  // We are sometimes passing data frames with no fields because we want to calculate correct meta stats.
+  // Therefore we need to filter out series with no fields. These series are used only for meta stats calculation.
+  const seriesWithFields = logSeries.filter(series => series.fields.length);
+
+  if (seriesWithFields.length) {
+    allSeries = seriesWithFields.map(series => {
       const fieldCache = new FieldCache(series);
       const fieldCache = new FieldCache(series);
       const stringField = fieldCache.getFirstFieldOfType(FieldType.string);
       const stringField = fieldCache.getFirstFieldOfType(FieldType.string);
 
 
@@ -463,10 +468,6 @@ 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 {
 function getIdField(fieldCache: FieldCache): FieldWithIndex | undefined {
   const idFieldNames = ['id'];
   const idFieldNames = ['id'];
   for (const fieldName of idFieldNames) {
   for (const fieldName of idFieldNames) {