fix(timeseries): groupby format was wrong (#87593)

- This updates the groupby format to match the spec
- groupby should be a list of dicts instead of just a dict so that the
fields are ordered

Author: wmak

src/sentry/snuba/discover.py

@@ -398,7 +398,10 @@ def create_result_key(
 ) -> str:
     """Create the string key to be used in the top events result dictionary"""
     groupby = create_groupby_dict(result_row, fields, issues)
-    result = ",".join(groupby.values())
+    groupby_values: list[str] = []
+    for value in groupby:
+        groupby_values.extend(value.values())
+    result = ",".join(groupby_values)
     # If the result would be identical to the other key, include the field name
     # only need the first field since this would only happen with a single field
     if result == OTHER_KEY:
@@ -408,24 +411,24 @@ def create_result_key(
 
 def create_groupby_dict(
     result_row: SnubaRow, fields: list[str], issues: Mapping[int, str | None]
-) -> dict[str, str]:
-    values = {}
+) -> list[dict[str, str]]:
+    values = []
     for field in fields:
         if field == "issue.id":
             issue_id = issues.get(result_row["issue.id"], "unknown")
             if issue_id is None:
                 issue_id = "unknown"
-            values[field] = issue_id
+            values.append({field: issue_id})
         elif field == "transaction.status":
-            values[field] = SPAN_STATUS_CODE_TO_NAME.get(result_row[field], "unknown")
+            values.append({field: SPAN_STATUS_CODE_TO_NAME.get(result_row[field], "unknown")})
         else:
             value = result_row.get(field)
             if isinstance(value, list):
                 if len(value) > 0:
                     value = value[-1]
                 else:
                     value = ""
-            values[field] = str(value)
+            values.append({field: str(value)})
     return values
 
 

tests/snuba/api/endpoints/test_organization_events_timeseries.py

@@ -212,7 +212,7 @@ def test_simple_top_events(self):
         timeseries = response.data["timeseries"][0]
         assert len(timeseries["values"]) == 3
         assert timeseries["axis"] == "count()"
-        assert timeseries["groupBy"] == {"message": "very bad"}
+        assert timeseries["groupBy"] == [{"message": "very bad"}]
         assert timeseries["meta"] == {
             "order": 0,
             "isOther": False,
@@ -238,7 +238,7 @@ def test_simple_top_events(self):
         timeseries = response.data["timeseries"][1]
         assert len(timeseries["values"]) == 3
         assert timeseries["axis"] == "p95()"
-        assert timeseries["groupBy"] == {"message": "very bad"}
+        assert timeseries["groupBy"] == [{"message": "very bad"}]
         assert timeseries["meta"] == {
             "order": 0,
             "isOther": False,
@@ -264,7 +264,7 @@ def test_simple_top_events(self):
         timeseries = response.data["timeseries"][2]
         assert len(timeseries["values"]) == 3
         assert timeseries["axis"] == "count()"
-        assert timeseries["groupBy"] == {"message": "oh my"}
+        assert timeseries["groupBy"] == [{"message": "oh my"}]
         assert timeseries["meta"] == {
             "order": 1,
             "isOther": False,
@@ -290,7 +290,7 @@ def test_simple_top_events(self):
         timeseries = response.data["timeseries"][3]
         assert len(timeseries["values"]) == 3
         assert timeseries["axis"] == "p95()"
-        assert timeseries["groupBy"] == {"message": "oh my"}
+        assert timeseries["groupBy"] == [{"message": "oh my"}]
         assert timeseries["meta"] == {
             "order": 1,
             "isOther": False,