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Enhance profile API to add model centric result controlled by view pa…
…rameter (opensearch-project#714) * Enhance profile API to add model centric result controled by view paramter Signed-off-by: Zan Niu <zaniu@amazon.com> * Enhance profile API to add model centric result controled by view parameter Signed-off-by: Zan Niu <zaniu@amazon.com> * Enhance profile API to add model centric result controled by view parameter Signed-off-by: Zan Niu <zaniu@amazon.com> --------- Signed-off-by: Zan Niu <zaniu@amazon.com>
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plugin/src/main/java/org/opensearch/ml/action/profile/MLProfileModelResponse.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,100 @@ | ||
| /* | ||
| * | ||
| * * Copyright OpenSearch Contributors | ||
| * * SPDX-License-Identifier: Apache-2.0 | ||
| * | ||
| */ | ||
|
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| package org.opensearch.ml.action.profile; | ||
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| import java.io.IOException; | ||
| import java.util.HashMap; | ||
| import java.util.Map; | ||
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| import lombok.Getter; | ||
| import lombok.NoArgsConstructor; | ||
| import lombok.Setter; | ||
|
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| 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; | ||
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| @Getter | ||
| @NoArgsConstructor | ||
| public class MLProfileModelResponse implements ToXContentFragment, Writeable { | ||
| @Setter | ||
| private String[] targetWorkerNodes; | ||
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| @Setter | ||
| private String[] workerNodes; | ||
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| private Map<String, MLModelProfile> mlModelProfileMap = new HashMap<>(); | ||
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| private Map<String, MLTask> mlTaskMap = new HashMap<>(); | ||
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| public MLProfileModelResponse(String[] targetWorkerNodes, String[] workerNodes) { | ||
| this.targetWorkerNodes = targetWorkerNodes; | ||
| this.workerNodes = workerNodes; | ||
| } | ||
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| 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); | ||
| } | ||
| } | ||
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| @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; | ||
| } | ||
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| @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); | ||
| } | ||
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|
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| } | ||
| } |
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112 changes: 112 additions & 0 deletions
112
plugin/src/test/java/org/opensearch/ml/action/profile/MLProfileModelResponseTests.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,112 @@ | ||
| /* | ||
| * | ||
| * * Copyright OpenSearch Contributors | ||
| * * SPDX-License-Identifier: Apache-2.0 | ||
| * | ||
| */ | ||
|
|
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| package org.opensearch.ml.action.profile; | ||
|
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| import java.io.IOException; | ||
| import java.time.Instant; | ||
| import java.util.Arrays; | ||
| import java.util.HashMap; | ||
| import java.util.Map; | ||
|
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| 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; | ||
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| public class MLProfileModelResponseTests extends OpenSearchTestCase { | ||
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| MLTask mlTask; | ||
| MLModelProfile mlModelProfile; | ||
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| @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(); | ||
| } | ||
|
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| 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()); | ||
| } | ||
|
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| 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()); | ||
| } | ||
|
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| 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); | ||
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| XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent()); | ||
| response.toXContent(builder, ToXContent.EMPTY_PARAMS); | ||
| String xContentString = TestHelper.xContentBuilderToString(builder); | ||
| System.out.println(xContentString); | ||
| } | ||
|
|
||
| } |
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