[ML] Modernize ML node detection (#79623)

droberts195 · web-flow · commit 9b92926ed961 · 2021-10-21T15:47:49.000+01:00
Where possible we should now detect ML nodes by looking for the ML node role rather than an attribute. Sadly this is not possible in the YAML tests, as the syntax doesn't support asserting that a list contains a particular item without asserting on the entire list contents. So in the YAML case we need to look for the ml.machine_memory node attribute, as this is reliably set on ML nodes but not other types of nodes. After #79622 is merged this closes #79518
diff --git a/x-pack/plugin/build.gradle b/x-pack/plugin/build.gradle
@@ -98,7 +98,6 @@ tasks.named("yamlRestTestV7CompatTransform").configure{ task ->
   task.skipTest("vectors/50_vector_stats/Usage stats on vector fields", "not supported for compatibility")
   task.skipTest("roles/30_prohibited_role_query/Test use prohibited query inside role query", "put role request with a term lookup (deprecated) and type. Requires validation in REST layer")
   task.skipTest("ml/jobs_crud/Test create job with delimited format", "removing undocumented functionality")
-  task.skipTest("ml/jobs_get_stats/Test get job stats after uploading data prompting the creation of some stats", "https://github.com/elastic/elasticsearch/issues/79518")
   task.skipTest("ml/datafeeds_crud/Test update datafeed to point to missing job", "behaviour change #44752 - not allowing to update datafeed job_id")
   task.skipTest("ml/datafeeds_crud/Test update datafeed to point to different job", "behaviour change #44752 - not allowing to update datafeed job_id")
   task.skipTest("ml/datafeeds_crud/Test update datafeed to point to job already attached to another datafeed", "behaviour change #44752 - not allowing to update datafeed job_id")
diff --git a/x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java b/x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java
@@ -618,12 +618,8 @@ public MachineLearning(Settings settings) {
     protected XPackLicenseState getLicenseState() { return XPackPlugin.getSharedLicenseState(); }
 
     public static boolean isMlNode(DiscoveryNode node) {
-        Map<String, String> nodeAttributes = node.getAttributes();
-        try {
-            return Long.parseLong(nodeAttributes.get(MACHINE_MEMORY_NODE_ATTR)) > 0;
-        } catch (NumberFormatException e) {
-            return false;
-        }
+        logger.info("DMR node roles are " + node.getRoles());
+        return node.getRoles().contains(DiscoveryNodeRole.ML_ROLE);
     }
 
     public List<Setting<?>> getSettings() {
diff --git a/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/MachineLearningInfoTransportActionTests.java b/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/MachineLearningInfoTransportActionTests.java
@@ -543,10 +543,8 @@ private ClusterState givenNodeCount(int nodeCount) {
         DiscoveryNodes.Builder nodesBuilder = DiscoveryNodes.builder();
         for (int i = 0; i < nodeCount; i++) {
             Map<String, String> attrs = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
-            Set<DiscoveryNodeRole> roles = new HashSet<>();
-            roles.add(DiscoveryNodeRole.DATA_ROLE);
-            roles.add(DiscoveryNodeRole.MASTER_ROLE);
-            roles.add(DiscoveryNodeRole.INGEST_ROLE);
+            Set<DiscoveryNodeRole> roles = Set.of(DiscoveryNodeRole.DATA_ROLE, DiscoveryNodeRole.MASTER_ROLE,
+                DiscoveryNodeRole.INGEST_ROLE, DiscoveryNodeRole.ML_ROLE);
             nodesBuilder.add(new DiscoveryNode("ml-feature-set-given-ml-node-" + i,
                 new TransportAddress(TransportAddress.META_ADDRESS, 9100 + i),
                 attrs,
diff --git a/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/action/TransportStartDataFrameAnalyticsActionTests.java b/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/action/TransportStartDataFrameAnalyticsActionTests.java
@@ -12,6 +12,7 @@
 import org.elasticsearch.cluster.ClusterState;
 import org.elasticsearch.cluster.metadata.Metadata;
 import org.elasticsearch.cluster.node.DiscoveryNode;
+import org.elasticsearch.cluster.node.DiscoveryNodeRole;
 import org.elasticsearch.cluster.node.DiscoveryNodes;
 import org.elasticsearch.cluster.service.ClusterService;
 import org.elasticsearch.common.settings.ClusterSettings;
@@ -32,8 +33,8 @@
 import org.elasticsearch.xpack.ml.process.MlMemoryTracker;
 
 import java.net.InetAddress;
-import java.util.Collections;
 import java.util.Map;
+import java.util.Set;
 
 import static org.hamcrest.Matchers.allOf;
 import static org.hamcrest.Matchers.containsString;
@@ -177,7 +178,8 @@ private static DiscoveryNode createNode(int i, boolean isMlNode, Version nodeVer
             "_node_id" + i,
             new TransportAddress(InetAddress.getLoopbackAddress(), 9300 + i),
             isMlNode ? Map.of("ml.machine_memory", String.valueOf(ByteSizeValue.ofGb(1).getBytes())) : Map.of(),
-            Collections.emptySet(),
+            isMlNode ? Set.of(DiscoveryNodeRole.MASTER_ROLE, DiscoveryNodeRole.DATA_ROLE, DiscoveryNodeRole.ML_ROLE)
+                : Set.of(DiscoveryNodeRole.MASTER_ROLE, DiscoveryNodeRole.DATA_ROLE),
             nodeVersion);
     }
 }
diff --git a/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/autoscaling/MlAutoscalingDeciderServiceTests.java b/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/autoscaling/MlAutoscalingDeciderServiceTests.java
@@ -46,7 +46,6 @@
 import java.util.Arrays;
 import java.util.Collections;
 import java.util.Date;
-import java.util.HashSet;
 import java.util.List;
 import java.util.Optional;
 import java.util.Set;
@@ -705,7 +704,7 @@ private static List<DiscoveryNode> withMlNodes(String... nodeName) {
                     .put(MachineLearning.MACHINE_MEMORY_NODE_ATTR, String.valueOf(DEFAULT_NODE_SIZE))
                     .put(MachineLearning.MAX_JVM_SIZE_NODE_ATTR, String.valueOf(DEFAULT_JVM_SIZE))
                     .map(),
-                new HashSet<>(List.of(DiscoveryNodeRole.MASTER_ROLE)),
+                Set.of(DiscoveryNodeRole.ML_ROLE),
                 Version.CURRENT))
             .collect(Collectors.toList());
     }
diff --git a/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/job/JobNodeSelectorTests.java b/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/job/JobNodeSelectorTests.java
@@ -11,6 +11,7 @@
 import org.elasticsearch.cluster.ClusterState;
 import org.elasticsearch.cluster.metadata.Metadata;
 import org.elasticsearch.cluster.node.DiscoveryNode;
+import org.elasticsearch.cluster.node.DiscoveryNodeRole;
 import org.elasticsearch.cluster.node.DiscoveryNodes;
 import org.elasticsearch.common.Randomness;
 import org.elasticsearch.common.collect.MapBuilder;
@@ -42,6 +43,7 @@
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
+import java.util.Set;
 import java.util.SortedMap;
 import java.util.TreeMap;
 
@@ -59,6 +61,10 @@ public class JobNodeSelectorTests extends ESTestCase {
     // To simplify the logic in this class all jobs have the same memory requirement
     private static final long MAX_JOB_BYTES = ByteSizeValue.ofGb(1).getBytes();
     private static final ByteSizeValue JOB_MEMORY_REQUIREMENT = ByteSizeValue.ofMb(10);
+    private static final Set<DiscoveryNodeRole> ROLES_WITH_ML =
+        Set.of(DiscoveryNodeRole.MASTER_ROLE, DiscoveryNodeRole.ML_ROLE, DiscoveryNodeRole.DATA_ROLE);
+    private static final Set<DiscoveryNodeRole> ROLES_WITHOUT_ML =
+        Set.of(DiscoveryNodeRole.MASTER_ROLE, DiscoveryNodeRole.DATA_ROLE);
 
     private MlMemoryTracker memoryTracker;
     private boolean isMemoryTrackerRecentlyRefreshed;
@@ -77,22 +83,22 @@ public void testNodeNameAndVersion() {
         TransportAddress ta = new TransportAddress(InetAddress.getLoopbackAddress(), 9300);
         Map<String, String> attributes = new HashMap<>();
         attributes.put("unrelated", "attribute");
-        DiscoveryNode node = new DiscoveryNode("_node_name1", "_node_id1", ta, attributes, Collections.emptySet(), Version.CURRENT);
+        DiscoveryNode node = new DiscoveryNode("_node_name1", "_node_id1", ta, attributes, ROLES_WITHOUT_ML, Version.CURRENT);
         assertEquals("{_node_name1}{version=" + node.getVersion() + "}", JobNodeSelector.nodeNameAndVersion(node));
     }
 
     public void testNodeNameAndMlAttributes() {
         TransportAddress ta = new TransportAddress(InetAddress.getLoopbackAddress(), 9300);
         SortedMap<String, String> attributes = new TreeMap<>();
         attributes.put("unrelated", "attribute");
-        DiscoveryNode node = new DiscoveryNode("_node_name1", "_node_id1", ta, attributes, Collections.emptySet(), Version.CURRENT);
+        DiscoveryNode node = new DiscoveryNode("_node_name1", "_node_id1", ta, attributes, ROLES_WITHOUT_ML, Version.CURRENT);
         assertEquals("{_node_name1}", JobNodeSelector.nodeNameAndMlAttributes(node));
 
         attributes.put("ml.machine_memory", "5");
-        node = new DiscoveryNode("_node_name1", "_node_id1", ta, attributes, Collections.emptySet(), Version.CURRENT);
+        node = new DiscoveryNode("_node_name1", "_node_id1", ta, attributes, ROLES_WITH_ML, Version.CURRENT);
         assertEquals("{_node_name1}{ml.machine_memory=5}", JobNodeSelector.nodeNameAndMlAttributes(node));
 
-        node = new DiscoveryNode(null, "_node_id1", ta, attributes, Collections.emptySet(), Version.CURRENT);
+        node = new DiscoveryNode(null, "_node_id1", ta, attributes, ROLES_WITH_ML, Version.CURRENT);
         assertEquals("{_node_id1}{ml.machine_memory=5}", JobNodeSelector.nodeNameAndMlAttributes(node));
     }
 
@@ -321,9 +327,9 @@ public void testSelectLeastLoadedMlNodeForDataFrameAnalyticsJob_firstJobTooBigMe
     public void testSelectLeastLoadedMlNode_noMlNodes() {
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -358,11 +364,11 @@ public void testSelectLeastLoadedMlNode_maxConcurrentOpeningJobs() {
         Map<String, String> nodeAttr = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name3", "_node_id3", new TransportAddress(InetAddress.getLoopbackAddress(), 9302),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -465,11 +471,11 @@ public void testSelectLeastLoadedMlNode_concurrentOpeningJobsAndStaleFailedJob()
         Map<String, String> nodeAttr = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name3", "_node_id3", new TransportAddress(InetAddress.getLoopbackAddress(), 9302),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -532,9 +538,9 @@ public void testSelectLeastLoadedMlNode_noCompatibleJobTypeNodes() {
         Map<String, String> nodeAttr = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -577,7 +583,7 @@ public void testSelectLeastLoadedMlNode_reasonsAreInDeterministicOrder() {
                     "_node_id1",
                     new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
                     nodeAttr,
-                    Collections.emptySet(),
+                    ROLES_WITH_ML,
                     Version.CURRENT
                 )
             )
@@ -587,7 +593,7 @@ public void testSelectLeastLoadedMlNode_reasonsAreInDeterministicOrder() {
                     "_node_id2",
                     new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
                     nodeAttr,
-                    Collections.emptySet(),
+                    ROLES_WITH_ML,
                     Version.CURRENT
                 )
             )
@@ -639,9 +645,9 @@ public void testSelectLeastLoadedMlNode_noNodesMatchingModelSnapshotMinVersion()
         Map<String, String> nodeAttr = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                nodeAttr, Collections.emptySet(), Version.fromString("6.2.0")))
+                nodeAttr, ROLES_WITH_ML, Version.fromString("6.2.0")))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                nodeAttr, Collections.emptySet(), Version.fromString("6.1.0")))
+                nodeAttr, ROLES_WITH_ML, Version.fromString("6.1.0")))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -677,9 +683,9 @@ public void testSelectLeastLoadedMlNode_jobWithRules() {
         Map<String, String> nodeAttr = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                nodeAttr, Collections.emptySet(), Version.fromString("6.2.0")))
+                nodeAttr, ROLES_WITH_ML, Version.fromString("6.2.0")))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                nodeAttr, Collections.emptySet(), Version.fromString("6.4.0")))
+                nodeAttr, ROLES_WITH_ML, Version.fromString("6.4.0")))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -711,9 +717,9 @@ public void testSelectMlNodeOnlyOutOfCandidates() {
         Map<String, String> nodeAttr = Map.of(MachineLearning.MACHINE_MEMORY_NODE_ATTR, "1000000000");
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                nodeAttr, Collections.emptySet(), Version.CURRENT))
+                nodeAttr, ROLES_WITH_ML, Version.CURRENT))
             .build();
 
         PersistentTasksCustomMetadata.Builder tasksBuilder = PersistentTasksCustomMetadata.builder();
@@ -745,9 +751,9 @@ public void testSelectMlNodeOnlyOutOfCandidates() {
     public void testConsiderLazyAssignmentWithNoLazyNodes() {
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .build();
 
         ClusterState.Builder cs = ClusterState.builder(new ClusterName("_name"));
@@ -769,9 +775,9 @@ public void testConsiderLazyAssignmentWithNoLazyNodes() {
     public void testConsiderLazyAssignmentWithLazyNodes() {
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("_node_name1", "_node_id1", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .add(new DiscoveryNode("_node_name2", "_node_id2", new TransportAddress(InetAddress.getLoopbackAddress(), 9301),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .build();
 
         ClusterState.Builder cs = ClusterState.builder(new ClusterName("_name"));
@@ -823,7 +829,7 @@ public void testMaximumPossibleNodeMemoryTooSmall() {
     public void testPerceivedCapacityAndMaxFreeMemory() {
         DiscoveryNodes nodes = DiscoveryNodes.builder()
             .add(new DiscoveryNode("not_ml_node_name", "_node_id", new TransportAddress(InetAddress.getLoopbackAddress(), 9300),
-                Collections.emptyMap(), Collections.emptySet(), Version.CURRENT))
+                Collections.emptyMap(), ROLES_WITHOUT_ML, Version.CURRENT))
             .add(new DiscoveryNode(
                 "filled_ml_node_name",
                 "filled_ml_node_id",
@@ -832,7 +838,7 @@ public void testPerceivedCapacityAndMaxFreeMemory() {
                     .put(MachineLearning.MAX_JVM_SIZE_NODE_ATTR, "10")
                     .put(MachineLearning.MACHINE_MEMORY_NODE_ATTR, Long.toString(ByteSizeValue.ofGb(30).getBytes()))
                     .map(),
-                Collections.emptySet(),
+                ROLES_WITH_ML,
                 Version.CURRENT))
             .add(new DiscoveryNode("not_filled_ml_node",
                 "not_filled_ml_node_id",
@@ -841,7 +847,7 @@ public void testPerceivedCapacityAndMaxFreeMemory() {
                     .put(MachineLearning.MAX_JVM_SIZE_NODE_ATTR, "10")
                     .put(MachineLearning.MACHINE_MEMORY_NODE_ATTR, Long.toString(ByteSizeValue.ofGb(30).getBytes()))
                     .map(),
-                Collections.emptySet(),
+                ROLES_WITH_ML,
                 Version.CURRENT))
             .add(new DiscoveryNode("not_filled_smaller_ml_node",
                 "not_filled_smaller_ml_node_id",
@@ -850,7 +856,7 @@ public void testPerceivedCapacityAndMaxFreeMemory() {
                     .put(MachineLearning.MAX_JVM_SIZE_NODE_ATTR, "10")
                     .put(MachineLearning.MACHINE_MEMORY_NODE_ATTR, Long.toString(ByteSizeValue.ofGb(10).getBytes()))
                     .map(),
-                Collections.emptySet(),
+                ROLES_WITH_ML,
                 Version.CURRENT))
             .build();
 
@@ -894,7 +900,7 @@ private ClusterState.Builder fillNodesWithRunningJobs(Map<String, String> nodeAt
         for (int i = 0; i < numNodes; i++) {
             String nodeId = "_node_id" + i;
             TransportAddress address = new TransportAddress(InetAddress.getLoopbackAddress(), 9300 + i);
-            nodes.add(new DiscoveryNode("_node_name" + i, nodeId, address, nodeAttr, Collections.emptySet(), Version.CURRENT));
+            nodes.add(new DiscoveryNode("_node_name" + i, nodeId, address, nodeAttr, ROLES_WITH_ML, Version.CURRENT));
             for (int j = 0; j < numRunningJobsPerNode; j++) {
                 int id = j + (numRunningJobsPerNode * i);
                 // Both anomaly detector jobs and data frame analytics jobs should count towards the limit
diff --git a/x-pack/plugin/src/yamlRestTest/resources/rest-api-spec/test/ml/jobs_get_stats.yml b/x-pack/plugin/src/yamlRestTest/resources/rest-api-spec/test/ml/jobs_get_stats.yml
