add test cases for _usage

Author: Hendrik Muhs

x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/MlJobIT.java

@@ -13,6 +13,7 @@
 import org.elasticsearch.common.util.concurrent.ConcurrentCollections;
 import org.elasticsearch.common.util.concurrent.ConcurrentMapLong;
 import org.elasticsearch.common.util.concurrent.ThreadContext;
+import org.elasticsearch.common.xcontent.support.XContentMapValues;
 import org.elasticsearch.test.SecuritySettingsSourceField;
 import org.elasticsearch.test.rest.ESRestTestCase;
 import org.elasticsearch.xpack.core.ml.integration.MlRestTestStateCleaner;
@@ -22,7 +23,9 @@
 import org.junit.After;
 
 import java.io.IOException;
+import java.util.Collections;
 import java.util.Locale;
+import java.util.Map;
 import java.util.concurrent.atomic.AtomicInteger;
 import java.util.concurrent.atomic.AtomicReference;
 import java.util.regex.Matcher;
@@ -111,6 +114,21 @@ public void testGetJobs_GivenMultipleJobs() throws Exception {
         assertThat(implicitAll, containsString("\"job_id\":\"given-multiple-jobs-job-3\""));
     }
 
+    // tests the _xpack/usage endpoint
+    public void testUsage() throws IOException {
+        createFarequoteJob("job-1");
+        createFarequoteJob("job-2");
+        Map<String, Object> usage = entityAsMap(client().performRequest(new Request("GET", "_xpack/usage")));
+        assertEquals(2, XContentMapValues.extractValue("ml.jobs._all.count", usage));
+        assertEquals(2, XContentMapValues.extractValue("ml.jobs.closed.count", usage));
+        Response openResponse = client().performRequest(new Request("POST", MachineLearning.BASE_PATH + "anomaly_detectors/job-1/_open"));
+        assertEquals(Collections.singletonMap("opened", true), entityAsMap(openResponse));
+        usage = entityAsMap(client().performRequest(new Request("GET", "_xpack/usage")));
+        assertEquals(2, XContentMapValues.extractValue("ml.jobs._all.count", usage));
+        assertEquals(1, XContentMapValues.extractValue("ml.jobs.closed.count", usage));
+        assertEquals(1, XContentMapValues.extractValue("ml.jobs.opened.count", usage));
+    }
+
     private Response createFarequoteJob(String jobId) throws IOException {
         Request request = new Request("PUT", MachineLearning.BASE_PATH + "anomaly_detectors/" + jobId);
         request.setJsonEntity(

x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/MachineLearningFeatureSetTests.java

@@ -240,6 +240,29 @@ public void testUsage() throws Exception {
         }
     }
 
+    public void testUsageDisabledML() throws Exception {
+        when(licenseState.isMachineLearningAllowed()).thenReturn(true);
+        Settings.Builder settings = Settings.builder().put(commonSettings);
+        settings.put("xpack.ml.enabled", false);
+
+        JobManagerHolder emptyJobManagerHolder = new JobManagerHolder();
+        MachineLearningFeatureSet featureSet = new MachineLearningFeatureSet(TestEnvironment.newEnvironment(settings.build()),
+                clusterService, client, licenseState, emptyJobManagerHolder);
+        PlainActionFuture<Usage> future = new PlainActionFuture<>();
+        featureSet.usage(future);
+        XPackFeatureSet.Usage mlUsage = future.get();
+        BytesStreamOutput out = new BytesStreamOutput();
+        mlUsage.writeTo(out);
+        XPackFeatureSet.Usage serializedUsage = new MachineLearningFeatureSetUsage(out.bytes().streamInput());
+
+        for (XPackFeatureSet.Usage usage : Arrays.asList(mlUsage, serializedUsage)) {
+            assertThat(usage, is(notNullValue()));
+            assertThat(usage.name(), is(XPackField.MACHINE_LEARNING));
+            assertThat(usage.enabled(), is(false));
+            assertThat(usage.available(), is(false));
+        }
+    }
+
     public void testNodeCount() throws Exception {
         when(licenseState.isMachineLearningAllowed()).thenReturn(true);
         int nodeCount = randomIntBetween(1, 3);