add response_parser test

pkg/tsdb/elasticsearch/response_parser.go

@@ -30,6 +30,7 @@ func (rp *ElasticsearchResponseParser) getTimeSeries() *tsdb.QueryResult {
 }
 
 func (rp *ElasticsearchResponseParser) processBuckets(aggs map[string]interface{}, target *Query, series *[]*tsdb.TimeSeries, props map[string]string, depth int) error {
+
 	var err error
 	maxDepth := len(target.BucketAggs) - 1
 	for aggId, v := range aggs {
@@ -113,7 +114,11 @@ func (rp *ElasticsearchResponseParser) processMetrics(esAgg *simplejson.Json, ta
 			}
 		default:
 			newSeries := tsdb.TimeSeries{}
-			newSeries.Tags = props
+			newSeries.Tags = map[string]string{}
+			for k, v := range props {
+				newSeries.Tags[k] = v
+			}
+
 			newSeries.Tags["metric"] = metric.Type
 			newSeries.Tags["field"] = metric.Field
 			for _, v := range esAgg.Get("buckets").MustArray() {
@@ -121,7 +126,7 @@ func (rp *ElasticsearchResponseParser) processMetrics(esAgg *simplejson.Json, ta
 				key := castToNullFloat(bucket.Get("key"))
 				valueObj, err := bucket.Get(metric.ID).Map()
 				if err != nil {
-					break
+					continue
 				}
 				var value null.Float
 				if _, ok := valueObj["normalized_value"]; ok {

pkg/tsdb/elasticsearch/response_parser_test.go

@@ -0,0 +1,109 @@
+package elasticsearch
+
+import (
+	"encoding/json"
+	"github.com/grafana/grafana/pkg/tsdb"
+	. "github.com/smartystreets/goconvey/convey"
+	"testing"
+)
+
+func testElasticsearchResponse(body string, target Query) *tsdb.QueryResult {
+	var responses Responses
+	err := json.Unmarshal([]byte(body), &responses)
+	So(err, ShouldBeNil)
+
+	responseParser := ElasticsearchResponseParser{responses.Responses, []*Query{&target}}
+	return responseParser.getTimeSeries()
+}
+
+func TestElasticSearchResponseParser(t *testing.T) {
+	Convey("Elasticsearch Response query testing", t, func() {
+		Convey("Build test average metric with moving average", func() {
+			responses := `{
+  "responses": [
+    {
+      "took": 1,
+      "timed_out": false,
+      "_shards": {
+        "total": 5,
+        "successful": 5,
+        "skipped": 0,
+        "failed": 0
+      },
+      "hits": {
+        "total": 4500,
+        "max_score": 0,
+        "hits": []
+      },
+      "aggregations": {
+        "2": {
+          "buckets": [
+            {
+              "1": {
+                "value": null
+              },
+              "key_as_string": "1522205880000",
+              "key": 1522205880000,
+              "doc_count": 0
+            },
+            {
+              "1": {
+                "value": 10
+              },
+              "key_as_string": "1522205940000",
+              "key": 1522205940000,
+              "doc_count": 300
+            },
+            {
+              "1": {
+                "value": 10
+              },
+              "3": {
+                "value": 20
+              },
+              "key_as_string": "1522206000000",
+              "key": 1522206000000,
+              "doc_count": 300
+            },
+            {
+              "1": {
+                "value": 10
+              },
+              "3": {
+                "value": 20
+              },
+              "key_as_string": "1522206060000",
+              "key": 1522206060000,
+              "doc_count": 300
+            }
+          ]
+        }
+      },
+      "status": 200
+    }
+  ]
+}
+`
+			res := testElasticsearchResponse(responses, avgWithMovingAvg)
+			So(len(res.Series), ShouldEqual, 2)
+			So(res.Series[0].Name, ShouldEqual, "Average value")
+			So(len(res.Series[0].Points), ShouldEqual, 4)
+			for i, p := range res.Series[0].Points {
+				if i == 0 {
+					So(p[0].Valid, ShouldBeFalse)
+				} else {
+					So(p[0].Float64, ShouldEqual, 10)
+				}
+				So(p[1].Float64, ShouldEqual, 1522205880000+60000*i)
+			}
+
+			So(res.Series[1].Name, ShouldEqual, "Moving Average Average 1")
+			So(len(res.Series[1].Points), ShouldEqual, 2)
+
+			for _, p := range res.Series[1].Points {
+				So(p[0].Float64, ShouldEqual, 20)
+			}
+
+		})
+	})
+}