use of org.opensearch.cluster.service.ClusterService in project k-NN by opensearch-project.
the class NativeMemoryEntryContextTests method testTrainingDataEntryContext_getIndicesService.
public void testTrainingDataEntryContext_getIndicesService() {
ClusterService clusterService = mock(ClusterService.class);
NativeMemoryEntryContext.TrainingDataEntryContext trainingDataEntryContext = new NativeMemoryEntryContext.TrainingDataEntryContext(0, "test", "test", null, clusterService, 0, 0);
assertEquals(clusterService, trainingDataEntryContext.getClusterService());
}
use of org.opensearch.cluster.service.ClusterService in project k-NN by opensearch-project.
the class ModelCacheTests method testGet_modelDoesNotFitInCache.
public void testGet_modelDoesNotFitInCache() throws ExecutionException, InterruptedException {
String modelId = "test-model-id";
int dimension = 2;
String cacheSize = "1kb";
Model mockModel = new Model(new ModelMetadata(KNNEngine.DEFAULT, SpaceType.DEFAULT, dimension, ModelState.CREATED, ZonedDateTime.now(ZoneOffset.UTC).toString(), "", ""), new byte[BYTES_PER_KILOBYTES + 1], modelId);
ModelDao modelDao = mock(ModelDao.class);
when(modelDao.get(modelId)).thenReturn(mockModel);
Settings settings = Settings.builder().put(MODEL_CACHE_SIZE_LIMIT_SETTING.getKey(), cacheSize).build();
ClusterSettings clusterSettings = new ClusterSettings(settings, ImmutableSet.of(MODEL_CACHE_SIZE_LIMIT_SETTING));
ClusterService clusterService = mock(ClusterService.class);
when(clusterService.getClusterSettings()).thenReturn(clusterSettings);
when(clusterService.getSettings()).thenReturn(settings);
ModelCache.initialize(modelDao, clusterService);
ModelCache modelCache = new ModelCache();
assertEquals(mockModel, modelCache.get(modelId));
assertFalse(modelCache.contains(modelId));
}
use of org.opensearch.cluster.service.ClusterService in project k-NN by opensearch-project.
the class ModelCacheTests method testRebuild_afterSettingUpdate.
public void testRebuild_afterSettingUpdate() throws ExecutionException, InterruptedException {
String modelId = "test-model-id";
int dimension = 2;
int modelSize = 2 * BYTES_PER_KILOBYTES;
Model mockModel = new Model(new ModelMetadata(KNNEngine.DEFAULT, SpaceType.DEFAULT, dimension, ModelState.CREATED, ZonedDateTime.now(ZoneOffset.UTC).toString(), "", ""), new byte[modelSize], modelId);
String cacheSize1 = "1kb";
String cacheSize2 = "4kb";
ModelDao modelDao = mock(ModelDao.class);
when(modelDao.get(modelId)).thenReturn(mockModel);
Settings settings = Settings.builder().put(MODEL_CACHE_SIZE_LIMIT_SETTING.getKey(), cacheSize1).build();
ClusterSettings clusterSettings = new ClusterSettings(settings, ImmutableSet.of(MODEL_CACHE_SIZE_LIMIT_SETTING));
ClusterService clusterService = mock(ClusterService.class);
when(clusterService.getClusterSettings()).thenReturn(clusterSettings);
when(clusterService.getSettings()).thenReturn(settings);
ModelCache.initialize(modelDao, clusterService);
ModelCache modelCache = new ModelCache();
// Add element to cache - element should not remain in cache
modelCache.get(modelId);
assertEquals(0, modelCache.getTotalWeightInKB());
// Rebuild and make sure cache is empty
Settings newSettings = Settings.builder().put(MODEL_CACHE_SIZE_LIMIT_SETTING.getKey(), cacheSize2).build();
clusterService.getClusterSettings().applySettings(newSettings);
assertEquals(0, modelCache.getTotalWeightInKB());
// Add element again - element should remain in cache
modelCache.get(modelId);
assertEquals((modelSize / BYTES_PER_KILOBYTES) + 1, modelCache.getTotalWeightInKB());
}
use of org.opensearch.cluster.service.ClusterService in project k-NN by opensearch-project.
the class ModelCacheTests method testContains.
public void testContains() throws ExecutionException, InterruptedException {
String modelId1 = "test-model-id-1";
int dimension = 2;
int modelSize1 = 100;
Model mockModel1 = new Model(new ModelMetadata(KNNEngine.DEFAULT, SpaceType.DEFAULT, dimension, ModelState.CREATED, ZonedDateTime.now(ZoneOffset.UTC).toString(), "", ""), new byte[modelSize1], modelId1);
String modelId2 = "test-model-id-2";
String cacheSize = "10%";
ModelDao modelDao = mock(ModelDao.class);
when(modelDao.get(modelId1)).thenReturn(mockModel1);
Settings settings = Settings.builder().put(MODEL_CACHE_SIZE_LIMIT_SETTING.getKey(), cacheSize).build();
ClusterSettings clusterSettings = new ClusterSettings(settings, ImmutableSet.of(MODEL_CACHE_SIZE_LIMIT_SETTING));
ClusterService clusterService = mock(ClusterService.class);
when(clusterService.getClusterSettings()).thenReturn(clusterSettings);
when(clusterService.getSettings()).thenReturn(settings);
ModelCache.initialize(modelDao, clusterService);
ModelCache modelCache = new ModelCache();
assertFalse(modelCache.contains(modelId1));
modelCache.get(modelId1);
assertTrue(modelCache.contains(modelId1));
assertFalse(modelCache.contains(modelId2));
}
use of org.opensearch.cluster.service.ClusterService in project k-NN by opensearch-project.
the class ModelCacheTests method testGetTotalWeight.
public void testGetTotalWeight() throws ExecutionException, InterruptedException {
String modelId1 = "test-model-id-1";
String modelId2 = "test-model-id-2";
int dimension = 2;
String cacheSize = "10%";
int size1 = BYTES_PER_KILOBYTES;
Model mockModel1 = new Model(new ModelMetadata(KNNEngine.DEFAULT, SpaceType.DEFAULT, dimension, ModelState.CREATED, ZonedDateTime.now(ZoneOffset.UTC).toString(), "", ""), new byte[size1], modelId1);
int size2 = BYTES_PER_KILOBYTES * 3;
Model mockModel2 = new Model(new ModelMetadata(KNNEngine.DEFAULT, SpaceType.DEFAULT, dimension, ModelState.CREATED, ZonedDateTime.now(ZoneOffset.UTC).toString(), "", ""), new byte[size2], modelId2);
ModelDao modelDao = mock(ModelDao.class);
when(modelDao.get(modelId1)).thenReturn(mockModel1);
when(modelDao.get(modelId2)).thenReturn(mockModel2);
Settings settings = Settings.builder().put(MODEL_CACHE_SIZE_LIMIT_SETTING.getKey(), cacheSize).build();
ClusterSettings clusterSettings = new ClusterSettings(settings, ImmutableSet.of(MODEL_CACHE_SIZE_LIMIT_SETTING));
ClusterService clusterService = mock(ClusterService.class);
when(clusterService.getClusterSettings()).thenReturn(clusterSettings);
when(clusterService.getSettings()).thenReturn(settings);
ModelCache.initialize(modelDao, clusterService);
ModelCache modelCache = new ModelCache();
modelCache.get(modelId1);
modelCache.get(modelId2);
modelCache.get(modelId1);
modelCache.get(modelId2);
assertEquals((size1 + size2) / BYTES_PER_KILOBYTES + 2, modelCache.getTotalWeightInKB());
}
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