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logs: more tests related to timestamp handling (#70819)

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Gábor Farkas 2023-06-28 13:50:29 +02:00 committed by GitHub
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commit 3f44412bfd
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370
public/app/core/logsModel_parse.test.ts
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@ -1498,4 +1498,374 @@ describe('logSeriesToLogsModel should parse different logs-dataframe formats', (
}
`);
});
it('should parse timestamps when no nanosecond data and no nanosecond field', () => {
const frames: DataFrame[] = [
{
refId: 'A',
fields: [
{
name: 'timestamp',
type: FieldType.time,
config: {},
values: [1686142519756, 1686142520411, 1686142519997],
},
{
name: 'body',
type: FieldType.string,
config: {},
values: ['line1', 'line2', 'line3'],
},
],
length: 3,
},
];
expect(logSeriesToLogsModel(frames)).toMatchInlineSnapshot(`
{
"hasUniqueLabels": false,
"meta": [],
"rows": [
{
"dataFrame": {
"fields": [
{
"config": {},
"name": "timestamp",
"type": "time",
"values": [
1686142519756,
1686142520411,
1686142519997,
],
},
{
"config": {},
"name": "body",
"type": "string",
"values": [
"line1",
"line2",
"line3",
],
},
],
"length": 3,
"refId": "A",
},
"datasourceType": undefined,
"entry": "line1",
"entryFieldIndex": 1,
"hasAnsi": false,
"hasUnescapedContent": false,
"labels": {},
"logLevel": "unknown",
"raw": "line1",
"rowIndex": 0,
"searchWords": [],
"timeEpochMs": 1686142519756,
"timeEpochNs": "1686142519756000000",
"timeFromNow": "mock:dateTimeFormatTimeAgo:2023-06-07T06:55:19-06:00",
"timeLocal": "2023-06-07 06:55:19",
"timeUtc": "2023-06-07 12:55:19",
"uid": "A_0",
"uniqueLabels": {},
},
{
"dataFrame": {
"fields": [
{
"config": {},
"name": "timestamp",
"type": "time",
"values": [
1686142519756,
1686142520411,
1686142519997,
],
},
{
"config": {},
"name": "body",
"type": "string",
"values": [
"line1",
"line2",
"line3",
],
},
],
"length": 3,
"refId": "A",
},
"datasourceType": undefined,
"entry": "line2",
"entryFieldIndex": 1,
"hasAnsi": false,
"hasUnescapedContent": false,
"labels": {},
"logLevel": "unknown",
"raw": "line2",
"rowIndex": 1,
"searchWords": [],
"timeEpochMs": 1686142520411,
"timeEpochNs": "1686142520411000000",
"timeFromNow": "mock:dateTimeFormatTimeAgo:2023-06-07T06:55:20-06:00",
"timeLocal": "2023-06-07 06:55:20",
"timeUtc": "2023-06-07 12:55:20",
"uid": "A_1",
"uniqueLabels": {},
},
{
"dataFrame": {
"fields": [
{
"config": {},
"name": "timestamp",
"type": "time",
"values": [
1686142519756,
1686142520411,
1686142519997,
],
},
{
"config": {},
"name": "body",
"type": "string",
"values": [
"line1",
"line2",
"line3",
],
},
],
"length": 3,
"refId": "A",
},
"datasourceType": undefined,
"entry": "line3",
"entryFieldIndex": 1,
"hasAnsi": false,
"hasUnescapedContent": false,
"labels": {},
"logLevel": "unknown",
"raw": "line3",
"rowIndex": 2,
"searchWords": [],
"timeEpochMs": 1686142519997,
"timeEpochNs": "1686142519997000000",
"timeFromNow": "mock:dateTimeFormatTimeAgo:2023-06-07T06:55:19-06:00",
"timeLocal": "2023-06-07 06:55:19",
"timeUtc": "2023-06-07 12:55:19",
"uid": "A_2",
"uniqueLabels": {},
},
],
}
`);
});
it('should parse timestamps when no nanosecond data and nanosecond field', () => {
const frames: DataFrame[] = [
{
refId: 'A',
fields: [
{
name: 'timestamp',
type: FieldType.time,
config: {},
values: [1686142519756, 1686142520411, 1686142519997],
},
{
name: 'body',
type: FieldType.string,
config: {},
values: ['line1', 'line2', 'line3'],
},
{
name: 'tsNs',
type: FieldType.string,
config: {},
values: ['1686142519756641000', '1686142520411000000', '1686142519997123456'],
},
],
length: 3,
},
];
expect(logSeriesToLogsModel(frames)).toMatchInlineSnapshot(`
{
"hasUniqueLabels": false,
"meta": [],
"rows": [
{
"dataFrame": {
"fields": [
{
"config": {},
"name": "timestamp",
"type": "time",
"values": [
1686142519756,
1686142520411,
1686142519997,
],
},
{
"config": {},
"name": "body",
"type": "string",
"values": [
"line1",
"line2",
"line3",
],
},
{
"config": {},
"name": "tsNs",
"type": "string",
"values": [
"1686142519756641000",
"1686142520411000000",
"1686142519997123456",
],
},
],
"length": 3,
"refId": "A",
},
"datasourceType": undefined,
"entry": "line1",
"entryFieldIndex": 1,
"hasAnsi": false,
"hasUnescapedContent": false,
"labels": {},
"logLevel": "unknown",
"raw": "line1",
"rowIndex": 0,
"searchWords": [],
"timeEpochMs": 1686142519756,
"timeEpochNs": "1686142519756641000",
"timeFromNow": "mock:dateTimeFormatTimeAgo:2023-06-07T06:55:19-06:00",
"timeLocal": "2023-06-07 06:55:19",
"timeUtc": "2023-06-07 12:55:19",
"uid": "A_0",
"uniqueLabels": {},
},
{
"dataFrame": {
"fields": [
{
"config": {},
"name": "timestamp",
"type": "time",
"values": [
1686142519756,
1686142520411,
1686142519997,
],
},
{
"config": {},
"name": "body",
"type": "string",
"values": [
"line1",
"line2",
"line3",
],
},
{
"config": {},
"name": "tsNs",
"type": "string",
"values": [
"1686142519756641000",
"1686142520411000000",
"1686142519997123456",
],
},
],
"length": 3,
"refId": "A",
},
"datasourceType": undefined,
"entry": "line2",
"entryFieldIndex": 1,
"hasAnsi": false,
"hasUnescapedContent": false,
"labels": {},
"logLevel": "unknown",
"raw": "line2",
"rowIndex": 1,
"searchWords": [],
"timeEpochMs": 1686142520411,
"timeEpochNs": "1686142520411000000",
"timeFromNow": "mock:dateTimeFormatTimeAgo:2023-06-07T06:55:20-06:00",
"timeLocal": "2023-06-07 06:55:20",
"timeUtc": "2023-06-07 12:55:20",
"uid": "A_1",
"uniqueLabels": {},
},
{
"dataFrame": {
"fields": [
{
"config": {},
"name": "timestamp",
"type": "time",
"values": [
1686142519756,
1686142520411,
1686142519997,
],
},
{
"config": {},
"name": "body",
"type": "string",
"values": [
"line1",
"line2",
"line3",
],
},
{
"config": {},
"name": "tsNs",
"type": "string",
"values": [
"1686142519756641000",
"1686142520411000000",
"1686142519997123456",
],
},
],
"length": 3,
"refId": "A",
},
"datasourceType": undefined,
"entry": "line3",
"entryFieldIndex": 1,
"hasAnsi": false,
"hasUnescapedContent": false,
"labels": {},
"logLevel": "unknown",
"raw": "line3",
"rowIndex": 2,
"searchWords": [],
"timeEpochMs": 1686142519997,
"timeEpochNs": "1686142519997123456",
"timeFromNow": "mock:dateTimeFormatTimeAgo:2023-06-07T06:55:19-06:00",
"timeLocal": "2023-06-07 06:55:19",
"timeUtc": "2023-06-07 12:55:19",
"uid": "A_2",
"uniqueLabels": {},
},
],
}
`);
});
});