Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Enhance profile API to add model centric result controlled by view parameter #714

Merged
merged 3 commits into from
Jan 31, 2023
Merged

Enhance profile API to add model centric result controlled by view parameter #714

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
5116a70
Enhance profile API to add model centric result controled by view par…
zane-neo Jan 19, 2023
856498e
Enhance profile API to add model centric result controled by view par…
zane-neo Jan 28, 2023
f3a2888
Enhance profile API to add model centric result controled by view par…
zane-neo Jan 28, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
100 changes: 100 additions & 0 deletions plugin/src/main/java/org/opensearch/ml/action/profile/MLProfileModelResponse.java
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,100 @@
/*
*
* * Copyright OpenSearch Contributors
* * SPDX-License-Identifier: Apache-2.0
*
*/

package org.opensearch.ml.action.profile;

import java.io.IOException;
import java.util.HashMap;
import java.util.Map;

import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;

import org.opensearch.common.io.stream.StreamInput;
import org.opensearch.common.io.stream.StreamOutput;
import org.opensearch.common.io.stream.Writeable;
import org.opensearch.common.xcontent.ToXContentFragment;
import org.opensearch.common.xcontent.XContentBuilder;
import org.opensearch.ml.common.MLTask;
import org.opensearch.ml.profile.MLModelProfile;

@Getter
@NoArgsConstructor
public class MLProfileModelResponse implements ToXContentFragment, Writeable {
@Setter
private String[] targetWorkerNodes;

@Setter
private String[] workerNodes;

private Map<String, MLModelProfile> mlModelProfileMap = new HashMap<>();

private Map<String, MLTask> mlTaskMap = new HashMap<>();

public MLProfileModelResponse(String[] targetWorkerNodes, String[] workerNodes) {
this.targetWorkerNodes = targetWorkerNodes;
this.workerNodes = workerNodes;
}

public MLProfileModelResponse(StreamInput in) throws IOException {
this.workerNodes = in.readOptionalStringArray();
this.targetWorkerNodes = in.readOptionalStringArray();
if (in.readBoolean()) {
this.mlModelProfileMap = in.readMap(StreamInput::readString, MLModelProfile::new);
}
if (in.readBoolean()) {
this.mlTaskMap = in.readMap(StreamInput::readString, MLTask::new);
}
}

@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
if (targetWorkerNodes != null) {
builder.field("target_worker_nodes", targetWorkerNodes);
}
if (workerNodes != null) {
builder.field("worker_nodes", workerNodes);
}
if (mlModelProfileMap.size() > 0) {
builder.startObject("nodes");
for (Map.Entry<String, MLModelProfile> entry : mlModelProfileMap.entrySet()) {
builder.field(entry.getKey(), entry.getValue());
}
builder.endObject();
}
if (mlTaskMap.size() > 0) {
builder.startObject("tasks");
for (Map.Entry<String, MLTask> entry : mlTaskMap.entrySet()) {
builder.field(entry.getKey(), entry.getValue());
}
builder.endObject();
}
builder.endObject();
return builder;
}

@Override
public void writeTo(StreamOutput streamOutput) throws IOException {
streamOutput.writeOptionalStringArray(workerNodes);
streamOutput.writeOptionalStringArray(targetWorkerNodes);
if (mlModelProfileMap.size() > 0) {
streamOutput.writeBoolean(true);
streamOutput.writeMap(mlModelProfileMap, StreamOutput::writeString, (o, r) -> r.writeTo(o));
} else {
streamOutput.writeBoolean(false);
}
if (mlTaskMap.size() > 0) {
streamOutput.writeBoolean(true);
streamOutput.writeMap(mlTaskMap, StreamOutput::writeString, (o, r) -> r.writeTo(o));
} else {
streamOutput.writeBoolean(false);
}

}
}
76 changes: 75 additions & 1 deletion plugin/src/main/java/org/opensearch/ml/rest/RestMLProfileAction.java
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,9 @@

import java.io.IOException;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.stream.Collectors;

Expand All @@ -28,20 +30,29 @@
import org.opensearch.common.xcontent.XContentBuilder;
import org.opensearch.common.xcontent.XContentParser;
import org.opensearch.ml.action.profile.MLProfileAction;
import org.opensearch.ml.action.profile.MLProfileModelResponse;
import org.opensearch.ml.action.profile.MLProfileNodeResponse;
import org.opensearch.ml.action.profile.MLProfileRequest;
import org.opensearch.ml.common.MLTask;
import org.opensearch.ml.profile.MLModelProfile;
import org.opensearch.ml.profile.MLProfileInput;
import org.opensearch.ml.utils.RestActionUtils;
import org.opensearch.rest.BaseRestHandler;
import org.opensearch.rest.BytesRestResponse;
import org.opensearch.rest.RestRequest;
import org.opensearch.rest.RestStatus;

import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableMap;

@Log4j2
public class RestMLProfileAction extends BaseRestHandler {
private static final String PROFILE_ML_ACTION = "profile_ml";

private static final String VIEW = "view";
private static final String MODEL_VIEW = "model";
private static final String NODE_VIEW = "node";

private ClusterService clusterService;

/**
Expand Down Expand Up @@ -80,6 +91,7 @@ protected RestChannelConsumer prepareRequest(RestRequest request, NodeClient cli
} else {
mlProfileInput = createMLProfileInputFromRequestParams(request);
}
String view = RestActionUtils.getStringParam(request, VIEW).orElse(NODE_VIEW);
String[] nodeIds = mlProfileInput.retrieveProfileOnAllNodes()
? getAllNodes(clusterService)
: mlProfileInput.getNodeIds().toArray(new String[0]);
Expand All @@ -93,7 +105,16 @@ protected RestChannelConsumer prepareRequest(RestRequest request, NodeClient cli
List<MLProfileNodeResponse> nodeProfiles = r.getNodes().stream().filter(s -> !s.isEmpty()).collect(Collectors.toList());
log.debug("Build MLProfileNodeResponse for size of {}", nodeProfiles.size());
if (nodeProfiles.size() > 0) {
r.toXContent(builder, ToXContent.EMPTY_PARAMS);
if (NODE_VIEW.equals(view)) {
r.toXContent(builder, ToXContent.EMPTY_PARAMS);
} else if (MODEL_VIEW.equals(view)) {
Map<String, MLProfileModelResponse> modelCentricProfileMap = buildModelCentricResult(nodeProfiles);
builder.startObject("models");
for (Map.Entry<String, MLProfileModelResponse> entry : modelCentricProfileMap.entrySet()) {
builder.field(entry.getKey(), entry.getValue());
}
builder.endObject();
}
}
builder.endObject();
channel.sendResponse(new BytesRestResponse(RestStatus.OK, builder));
Expand All @@ -105,6 +126,59 @@ protected RestChannelConsumer prepareRequest(RestRequest request, NodeClient cli
};
}

/**
* The data structure for node centric is:
* MLProfileNodeResponse:
* taskMap: Map<String, MLTask>
* modelMap: Map<String, MLModelProfile> model_id, MLModelProfile
* And we need to convert to format like this:
* modelMap: Map<String, Map<String, MLModelProfile>>
*/
private Map<String, MLProfileModelResponse> buildModelCentricResult(List<MLProfileNodeResponse> nodeResponses) {
// aggregate model information into one final map.
Map<String, MLProfileModelResponse> modelCentricMap = new HashMap<>();
for (MLProfileNodeResponse mlProfileNodeResponse : nodeResponses) {
String nodeId = mlProfileNodeResponse.getNode().getId();
Map<String, MLModelProfile> modelProfileMap = mlProfileNodeResponse.getMlNodeModels();
Map<String, MLTask> taskProfileMap = mlProfileNodeResponse.getMlNodeTasks();
for (Map.Entry<String, MLModelProfile> entry : modelProfileMap.entrySet()) {
MLProfileModelResponse mlProfileModelResponse = modelCentricMap.get(entry.getKey());
if (mlProfileModelResponse == null) {
mlProfileModelResponse = new MLProfileModelResponse(
entry.getValue().getTargetWorkerNodes(),
entry.getValue().getWorkerNodes()
);
modelCentricMap.put(entry.getKey(), mlProfileModelResponse);
}
if (mlProfileModelResponse.getTargetWorkerNodes() == null || mlProfileModelResponse.getWorkerNodes() == null) {
mlProfileModelResponse.setTargetWorkerNodes(entry.getValue().getTargetWorkerNodes());
mlProfileModelResponse.setWorkerNodes(entry.getValue().getWorkerNodes());
}
// Create a new object and remove targetWorkerNodes and workerNodes.
MLModelProfile modelProfile = new MLModelProfile(
entry.getValue().getModelState(),
entry.getValue().getPredictor(),
null,
null,
entry.getValue().getModelInferenceStats(),
entry.getValue().getPredictRequestStats()
);
mlProfileModelResponse.getMlModelProfileMap().putAll(ImmutableMap.of(nodeId, modelProfile));
}

for (Map.Entry<String, MLTask> entry : taskProfileMap.entrySet()) {
String modelId = entry.getValue().getModelId();
MLProfileModelResponse mlProfileModelResponse = modelCentricMap.get(modelId);
if (mlProfileModelResponse == null) {
mlProfileModelResponse = new MLProfileModelResponse();
modelCentricMap.put(modelId, mlProfileModelResponse);
}
mlProfileModelResponse.getMlTaskMap().putAll(ImmutableMap.of(entry.getKey(), entry.getValue()));
}
}
return modelCentricMap;
}

MLProfileInput createMLProfileInputFromRequestParams(RestRequest request) {
MLProfileInput mlProfileInput = new MLProfileInput();
Optional<String[]> modelIds = splitCommaSeparatedParam(request, PARAMETER_MODEL_ID);
Expand Down
4 changes: 4 additions & 0 deletions plugin/src/main/java/org/opensearch/ml/utils/RestActionUtils.java
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -161,4 +161,8 @@ public static Optional<String[]> splitCommaSeparatedParam(RestRequest request, S
return Optional.ofNullable(request.param(paramName)).map(s -> s.split(","));
}

public static Optional<String> getStringParam(RestRequest request, String paramName) {
return Optional.ofNullable(request.param(paramName));
}

}
112 changes: 112 additions & 0 deletions plugin/src/test/java/org/opensearch/ml/action/profile/MLProfileModelResponseTests.java
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,112 @@
/*
*
* * Copyright OpenSearch Contributors
* * SPDX-License-Identifier: Apache-2.0
*
*/

package org.opensearch.ml.action.profile;

import java.io.IOException;
import java.time.Instant;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;

import org.junit.Before;
import org.opensearch.common.io.stream.BytesStreamOutput;
import org.opensearch.common.xcontent.ToXContent;
import org.opensearch.common.xcontent.XContentBuilder;
import org.opensearch.common.xcontent.XContentType;
import org.opensearch.commons.authuser.User;
import org.opensearch.ml.common.FunctionName;
import org.opensearch.ml.common.MLTask;
import org.opensearch.ml.common.MLTaskState;
import org.opensearch.ml.common.MLTaskType;
import org.opensearch.ml.common.dataset.MLInputDataType;
import org.opensearch.ml.common.model.MLModelState;
import org.opensearch.ml.profile.MLModelProfile;
import org.opensearch.ml.profile.MLPredictRequestStats;
import org.opensearch.ml.utils.TestHelper;
import org.opensearch.test.OpenSearchTestCase;

public class MLProfileModelResponseTests extends OpenSearchTestCase {

MLTask mlTask;
MLModelProfile mlModelProfile;

@Before
public void setup() {
mlTask = MLTask
.builder()
.taskId("test_id")
.modelId("model_id")
.taskType(MLTaskType.TRAINING)
.functionName(FunctionName.AD_LIBSVM)
.state(MLTaskState.CREATED)
.inputType(MLInputDataType.DATA_FRAME)
.progress(0.4f)
.outputIndex("test_index")
.workerNodes(Arrays.asList("test_node"))
.createTime(Instant.ofEpochMilli(123))
.lastUpdateTime(Instant.ofEpochMilli(123))
.error("error")
.user(new User())
.async(false)
.build();
mlModelProfile = MLModelProfile
.builder()
.predictor("test_predictor")
.workerNodes(new String[] { "node1", "node2" })
.modelState(MLModelState.LOADED)
.modelInferenceStats(MLPredictRequestStats.builder().count(10L).average(11.0).max(20.0).min(5.0).build())
.build();
}

public void test_create_MLProfileModelResponse_withArgs() throws IOException {
String[] targetWorkerNodes = new String[] { "node1", "node2" };
String[] workerNodes = new String[] { "node1" };
Map<String, MLModelProfile> profileMap = new HashMap<>();
Map<String, MLTask> taskMap = new HashMap<>();
profileMap.put("node1", mlModelProfile);
taskMap.put("node1", mlTask);
MLProfileModelResponse response = new MLProfileModelResponse(targetWorkerNodes, workerNodes);
response.getMlModelProfileMap().putAll(profileMap);
response.getMlTaskMap().putAll(taskMap);
BytesStreamOutput output = new BytesStreamOutput();
response.writeTo(output);
MLProfileModelResponse newResponse = new MLProfileModelResponse(output.bytes().streamInput());
assertNotNull(newResponse.getTargetWorkerNodes());
assertNotNull(response.getTargetWorkerNodes());
assertEquals(newResponse.getTargetWorkerNodes().length, response.getTargetWorkerNodes().length);
assertEquals(newResponse.getMlModelProfileMap().size(), response.getMlModelProfileMap().size());
assertEquals(newResponse.getMlTaskMap().size(), response.getMlTaskMap().size());
}

public void test_create_MLProfileModelResponse_NoArgs() throws IOException {
MLProfileModelResponse response = new MLProfileModelResponse();
BytesStreamOutput output = new BytesStreamOutput();
response.writeTo(output);
MLProfileModelResponse newResponse = new MLProfileModelResponse(output.bytes().streamInput());
assertNull(response.getWorkerNodes());
assertNull(newResponse.getWorkerNodes());
}

public void test_toXContent() throws IOException {
String[] targetWorkerNodes = new String[] { "node1", "node2" };
String[] workerNodes = new String[] { "node1" };
Map<String, MLModelProfile> profileMap = new HashMap<>();
Map<String, MLTask> taskMap = new HashMap<>();
profileMap.put("node1", mlModelProfile);
taskMap.put("node1", mlTask);
MLProfileModelResponse response = new MLProfileModelResponse(targetWorkerNodes, workerNodes);
response.getMlModelProfileMap().putAll(profileMap);
response.getMlTaskMap().putAll(taskMap);

XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
response.toXContent(builder, ToXContent.EMPTY_PARAMS);
String xContentString = TestHelper.xContentBuilderToString(builder);
System.out.println(xContentString);
}

}
12 changes: 10 additions & 2 deletions plugin/src/test/java/org/opensearch/ml/rest/RestMLProfileActionTests.java
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,7 @@
import static org.mockito.Mockito.times;
import static org.mockito.Mockito.verify;
import static org.mockito.Mockito.when;
import static org.opensearch.ml.utils.TestHelper.getProfileRestRequest;
import static org.opensearch.ml.utils.TestHelper.setupTestClusterState;
import static org.opensearch.ml.utils.TestHelper.*;

import java.io.IOException;
import java.time.Instant;
Expand Down Expand Up @@ -68,6 +67,7 @@
import org.opensearch.threadpool.ThreadPool;

import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableMap;

public class RestMLProfileActionTests extends OpenSearchTestCase {
@Rule
Expand Down Expand Up @@ -286,6 +286,14 @@ public void test_PrepareRequest_Failure() throws Exception {
verify(client, times(1)).execute(eq(MLProfileAction.INSTANCE), argumentCaptor.capture(), any());
}

public void test_WhenViewIsModel_ReturnModelViewResult() throws Exception {
MLProfileInput mlProfileInput = new MLProfileInput();
RestRequest request = getProfileRestRequestWithQueryParams(mlProfileInput, ImmutableMap.of("view", "model"));
profileAction.handleRequest(request, channel, client);
ArgumentCaptor<MLProfileRequest> argumentCaptor = ArgumentCaptor.forClass(MLProfileRequest.class);
verify(client, times(1)).execute(eq(MLProfileAction.INSTANCE), argumentCaptor.capture(), any());
}

private RestRequest getRestRequest() {
Map<String, String> params = new HashMap<>();
params.put("task_id", "test_id");
Expand Down
Loading