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WIP: Create v2 version

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This commit is contained in:
Ivana
2020-07-10 13:22:24 +02:00
parent 1088740dc4
commit 712c061ebb
3 changed files with 79 additions and 116 deletions
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public/app/plugins/datasource/elasticsearch/elastic_response.ts
+71 -93
View File
@@ -390,93 +390,22 @@ export class ElasticResponse {
return result;
}
getTimeSeries(isV2 = false) {
if (isV2) {
const dataFrame: DataFrame[] = [];
for (let n = 0; n < this.response.responses.length; n++) {
const response = this.response.responses[n];
if (response.error) {
throw this.getErrorFromElasticResponse(this.response, response.error);
}
if (response.hits && response.hits.hits.length > 0) {
const { propNames, docs } = flattenHits(response.hits.hits);
if (docs.length > 0) {
const series = createEmptyDataFrame(propNames, this.targets[0].timeField);
// Add a row for each document
for (const doc of docs) {
series.add(doc);
}
dataFrame.push(series);
}
}
if (response.aggregations) {
const aggregations = response.aggregations;
const target = this.targets[n];
const tmpSeriesList: any[] = [];
const table = new TableModel();
this.processBuckets(aggregations, target, tmpSeriesList, table, {}, 0);
this.trimDatapoints(tmpSeriesList, target);
this.nameSeries(tmpSeriesList, target);
if (table.rows.length > 0) {
dataFrame.push(toDataFrame(table));
}
for (let y = 0; y < tmpSeriesList.length; y++) {
let series = toDataFrame(tmpSeriesList[y]);
// When log results, show aggregations only in graph. Log fields are then going to be shown in table.
dataFrame.push(series);
}
}
}
return { data: dataFrame };
} else {
const seriesList = [];
for (let i = 0; i < this.response.responses.length; i++) {
const response = this.response.responses[i];
if (response.error) {
throw this.getErrorFromElasticResponse(this.response, response.error);
}
if (response.hits && response.hits.hits.length > 0) {
this.processHits(response.hits, seriesList);
}
if (response.aggregations) {
const aggregations = response.aggregations;
const target = this.targets[i];
const tmpSeriesList: any[] = [];
const table = new TableModel();
this.processBuckets(aggregations, target, tmpSeriesList, table, {}, 0);
this.trimDatapoints(tmpSeriesList, target);
this.nameSeries(tmpSeriesList, target);
for (let y = 0; y < tmpSeriesList.length; y++) {
seriesList.push(tmpSeriesList[y]);
}
if (table.rows.length > 0) {
seriesList.push(table);
}
}
}
return { data: seriesList };
getTimeSeries(processToDataFrames = false): DataQueryResponse {
if (processToDataFrames) {
return this.processResponseToDataFrames(false);
}
return this.processResponseToSeries();
}
getLogs(logMessageField?: string, logLevelField?: string): DataQueryResponse {
return this.processResponseToDataFrames(true, logMessageField, logLevelField);
}
processResponseToDataFrames(
isLogsRequest: boolean,
logMessageField?: string,
logLevelField?: string
): DataQueryResponse {
const dataFrame: DataFrame[] = [];
for (let n = 0; n < this.response.responses.length; n++) {
@@ -485,17 +414,24 @@ export class ElasticResponse {
throw this.getErrorFromElasticResponse(this.response, response.error);
}
const { propNames, docs } = flattenHits(response.hits.hits);
if (docs.length > 0) {
let series = createEmptyDataFrame(propNames, this.targets[0].timeField, logMessageField, logLevelField);
if (response.hits && response.hits.hits.length > 0) {
const { propNames, docs } = flattenHits(response.hits.hits);
if (docs.length > 0) {
const series = createEmptyDataFrame(propNames, this.targets[0].timeField, logMessageField, logLevelField);
// Add a row for each document
for (const doc of docs) {
series.add(doc);
// Add a row for each document
for (const doc of docs) {
if (logLevelField) {
// Remap level field based on the datasource config. This field is then used in explore to figure out the
// log level. We may rewrite some actual data in the level field if they are different.
doc['level'] = doc[logLevelField];
}
series.add(doc);
}
dataFrame.push(series);
}
series = addPreferredVisualisationType(series, 'logs');
dataFrame.push(series);
}
if (response.aggregations) {
@@ -508,11 +444,17 @@ export class ElasticResponse {
this.trimDatapoints(tmpSeriesList, target);
this.nameSeries(tmpSeriesList, target);
if (table.rows.length > 0) {
dataFrame.push(toDataFrame(table));
}
for (let y = 0; y < tmpSeriesList.length; y++) {
let series = toDataFrame(tmpSeriesList[y]);
// When log results, show aggregations only in graph. Log fields are then going to be shown in table.
series = addPreferredVisualisationType(series, 'graph');
if (isLogsRequest) {
series = addPreferredVisualisationType(series, 'graph');
}
dataFrame.push(series);
}
@@ -521,6 +463,42 @@ export class ElasticResponse {
return { data: dataFrame };
}
processResponseToSeries = () => {
const seriesList = [];
for (let i = 0; i < this.response.responses.length; i++) {
const response = this.response.responses[i];
if (response.error) {
throw this.getErrorFromElasticResponse(this.response, response.error);
}
if (response.hits && response.hits.hits.length > 0) {
this.processHits(response.hits, seriesList);
}
if (response.aggregations) {
const aggregations = response.aggregations;
const target = this.targets[i];
const tmpSeriesList: any[] = [];
const table = new TableModel();
this.processBuckets(aggregations, target, tmpSeriesList, table, {}, 0);
this.trimDatapoints(tmpSeriesList, target);
this.nameSeries(tmpSeriesList, target);
for (let y = 0; y < tmpSeriesList.length; y++) {
seriesList.push(tmpSeriesList[y]);
}
if (table.rows.length > 0) {
seriesList.push(table);
}
}
}
return { data: seriesList };
};
}
type Doc = {
public/app/plugins/datasource/elasticsearch/metric_agg.ts
+3 -10
View File
@@ -101,14 +101,7 @@ export class ElasticMetricAggCtrl {
$scope.updateMovingAvgModelSettings();
break;
}
case 'raw_document': {
$scope.agg.settings.size = $scope.agg.settings.size || 500;
$scope.settingsLinkText = 'Size: ' + $scope.agg.settings.size;
$scope.target.metrics.splice(0, $scope.target.metrics.length, $scope.agg);
$scope.target.bucketAggs = [];
break;
}
case 'raw_document':
case 'raw_document_v2': {
$scope.agg.settings.size = $scope.agg.settings.size || 500;
$scope.settingsLinkText = 'Size: ' + $scope.agg.settings.size;
@@ -173,8 +166,8 @@ export class ElasticMetricAggCtrl {
// reset back to metric/group by query
if (
($scope.target.bucketAggs.length === 0 && $scope.agg.type !== 'raw_document') ||
$scope.agg.type !== 'raw_document_v2'
$scope.target.bucketAggs.length === 0 &&
($scope.agg.type !== 'raw_document' || $scope.agg.type !== 'raw_document_v2')
) {
$scope.target.bucketAggs = [queryDef.defaultBucketAgg()];
}
public/app/plugins/datasource/elasticsearch/query_builder.ts
+5 -13
View File
@@ -212,25 +212,17 @@ export class ElasticQueryBuilder {
// If target doesn't have bucketAggs and type is not raw_document, it is invalid query.
if (target.bucketAggs.length === 0) {
metric = target.metrics[0];
//tu treba pridat
// if (!metric || metric.type !== 'raw_document') {
// throw { message: 'Invalid query' };
// }
if (!metric || !(metric.type === 'raw_document' || metric.type === 'raw_document_v2')) {
throw { message: 'Invalid query' };
}
}
/* Handle document query:
* Check if metric type is raw_document. If metric doesn't have size (or size is 0), update size to 500.
* Otherwise it will not be a valid query and error will be thrown.
*/
if (target.metrics?.[0]?.type === 'raw_document') {
metric = target.metrics[0];
const size = (metric.settings && metric.settings.size !== 0 && metric.settings.size) || 500;
return this.documentQuery(query, size);
}
/* Handle document query v2:
*/
if (target.metrics?.[0]?.type === 'raw_document_v2') {
if (target.metrics?.[0]?.type === 'raw_document' || target.metrics?.[0]?.type === 'raw_document_v2') {
metric = target.metrics[0];
const size = (metric.settings && metric.settings.size !== 0 && metric.settings.size) || 500;
return this.documentQuery(query, size);