Don't read lazily to catch QuestDb errors early

3 files changed, 26 insertions, 15 deletions

diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java
index 0fb537d8462..19cc9f5714f 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java
@@ -38,12 +38,12 @@ public class ClusterModel {
     private final MetricsDb metricsDb;
     private final Clock clock;
     private final Duration scalingDuration;
+    private final ClusterTimeseries clusterTimeseries;
+    private final ClusterNodesTimeseries nodeTimeseries;
 
     // Lazily initialized members
     private Double queryFractionOfMax = null;
     private Double maxQueryGrowthRate = null;
-    private ClusterNodesTimeseries nodeTimeseries = null;
-    private ClusterTimeseries clusterTimeseries = null;
 
     public ClusterModel(Application application,
                         Cluster cluster,
@@ -57,6 +57,8 @@ public class ClusterModel {
         this.metricsDb = metricsDb;
         this.clock = clock;
         this.scalingDuration = computeScalingDuration(cluster, clusterSpec);
+        this.clusterTimeseries = metricsDb.getClusterTimeseries(application.id(), cluster.id());
+        this.nodeTimeseries = new ClusterNodesTimeseries(scalingDuration(), cluster, nodes, metricsDb);
     }
 
     /** For testing */
@@ -64,7 +66,8 @@ public class ClusterModel {
                  Cluster cluster,
                  Clock clock,
                  Duration scalingDuration,
-                 ClusterTimeseries clusterTimeseries) {
+                 ClusterTimeseries clusterTimeseries,
+                 ClusterNodesTimeseries nodeTimeseries) {
         this.application = application;
         this.cluster = cluster;
         this.nodes = null;
@@ -73,20 +76,15 @@ public class ClusterModel {
 
         this.scalingDuration = scalingDuration;
         this.clusterTimeseries = clusterTimeseries;
+        this.nodeTimeseries = nodeTimeseries;
     }
 
     /** Returns the predicted duration of a rescaling of this cluster */
     public Duration scalingDuration() { return scalingDuration; }
 
-    public ClusterNodesTimeseries nodeTimeseries() {
-        if (nodeTimeseries != null) return nodeTimeseries;
-        return nodeTimeseries = new ClusterNodesTimeseries(scalingDuration(), cluster, nodes, metricsDb);
-    }
+    public ClusterNodesTimeseries nodeTimeseries() { return nodeTimeseries; }
 
-    public ClusterTimeseries clusterTimeseries() {
-        if (clusterTimeseries != null) return clusterTimeseries;
-        return clusterTimeseries = metricsDb.getClusterTimeseries(application.id(), cluster.id());
-    }
+    public ClusterTimeseries clusterTimeseries() { return clusterTimeseries; }
 
     /**
      * Returns the predicted max query growth rate per minute as a fraction of the average traffic
diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterNodesTimeseries.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterNodesTimeseries.java
index 5f974abd84f..9b77d8b48c8 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterNodesTimeseries.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterNodesTimeseries.java
@@ -34,6 +34,11 @@ public class ClusterNodesTimeseries {
         this.timeseries = timeseries;
     }
 
+    private ClusterNodesTimeseries(NodeList clusterNodes, List<NodeTimeseries> timeseries) {
+        this.clusterNodes = clusterNodes;
+        this.timeseries = timeseries;
+    }
+
     /** Returns the average number of measurements per node */
     public int measurementsPerNode() {
         int measurementCount = timeseries.stream().mapToInt(m -> m.size()).sum();
@@ -61,4 +66,8 @@ public class ClusterNodesTimeseries {
         return timeseries.stream().map(nodeTimeseries -> nodeTimeseries.filter(filter)).collect(Collectors.toList());
     }
 
+    public static ClusterNodesTimeseries empty() {
+        return new ClusterNodesTimeseries(NodeList.of(), List.of());
+    }
+
 }
diff --git a/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModelTest.java b/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModelTest.java
index 550ecceee23..c6575931c6d 100644
--- a/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModelTest.java
+++ b/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModelTest.java
@@ -36,13 +36,15 @@ public class ClusterModelTest {
         // No current traffic share: Ideal load is low but capped
         var model1 = new ClusterModel(application.with(new Status(0.0, 1.0)),
                                       cluster, clock, Duration.ofMinutes(10),
-                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock));
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock),
+                                      ClusterNodesTimeseries.empty());
         assertEquals(0.131, model1.idealLoad().cpu(), delta);
 
         // Almost no current traffic share: Ideal load is low but capped
         var model2 = new ClusterModel(application.with(new Status(0.0001, 1.0)),
                                       cluster, clock, Duration.ofMinutes(10),
-                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock));
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock),
+                                      ClusterNodesTimeseries.empty());
         assertEquals(0.131, model2.idealLoad().cpu(), delta);
     }
 
@@ -57,13 +59,15 @@ public class ClusterModelTest {
         // No current traffic: Ideal load is low but capped
         var model1 = new ClusterModel(application,
                                       cluster, clock, Duration.ofMinutes(10),
-                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock));
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock),
+                                      ClusterNodesTimeseries.empty());
         assertEquals(0.275, model1.idealLoad().cpu(), delta);
 
         // Almost no current traffic: Ideal load is low but capped
         var model2 = new ClusterModel(application.with(new Status(0.0001, 1.0)),
                                       cluster, clock, Duration.ofMinutes(10),
-                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0001, t -> 0.0, clock));
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0001, t -> 0.0, clock),
+                                      ClusterNodesTimeseries.empty());
         assertEquals(0.040, model2.idealLoad().cpu(), delta);
     }