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[ML] add _cat/ml/trained_models API #51529
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/* | ||
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||
* or more contributor license agreements. Licensed under the Elastic License; | ||
* you may not use this file except in compliance with the Elastic License. | ||
*/ | ||
package org.elasticsearch.xpack.ml.rest.cat; | ||
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import org.elasticsearch.action.ActionListener; | ||
import org.elasticsearch.action.ActionResponse; | ||
import org.elasticsearch.action.support.GroupedActionListener; | ||
import org.elasticsearch.client.node.NodeClient; | ||
import org.elasticsearch.cluster.metadata.MetaData; | ||
import org.elasticsearch.common.Strings; | ||
import org.elasticsearch.common.Table; | ||
import org.elasticsearch.common.unit.ByteSizeValue; | ||
import org.elasticsearch.common.unit.TimeValue; | ||
import org.elasticsearch.rest.RestController; | ||
import org.elasticsearch.rest.RestRequest; | ||
import org.elasticsearch.rest.RestResponse; | ||
import org.elasticsearch.rest.action.RestResponseListener; | ||
import org.elasticsearch.rest.action.cat.AbstractCatAction; | ||
import org.elasticsearch.rest.action.cat.RestTable; | ||
import org.elasticsearch.xpack.core.action.util.PageParams; | ||
import org.elasticsearch.xpack.core.ml.action.GetDataFrameAnalyticsAction; | ||
import org.elasticsearch.xpack.core.ml.action.GetTrainedModelsAction; | ||
import org.elasticsearch.xpack.core.ml.action.GetTrainedModelsStatsAction; | ||
import org.elasticsearch.xpack.core.ml.dataframe.DataFrameAnalyticsConfig; | ||
import org.elasticsearch.xpack.core.ml.dataframe.analyses.DataFrameAnalysis; | ||
import org.elasticsearch.xpack.core.ml.inference.TrainedModelConfig; | ||
import org.elasticsearch.xpack.core.security.user.XPackUser; | ||
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import java.util.Collection; | ||
import java.util.Collections; | ||
import java.util.HashSet; | ||
import java.util.List; | ||
import java.util.Map; | ||
import java.util.Set; | ||
import java.util.function.Function; | ||
import java.util.stream.Collectors; | ||
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import static org.elasticsearch.rest.RestRequest.Method.GET; | ||
import static org.elasticsearch.xpack.core.ml.action.GetTrainedModelsAction.Request.ALLOW_NO_MATCH; | ||
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public class RestCatTrainedModelsAction extends AbstractCatAction { | ||
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public RestCatTrainedModelsAction(RestController controller) { | ||
controller.registerHandler(GET, "_cat/ml/trained_models/{" + TrainedModelConfig.MODEL_ID.getPreferredName() + "}", this); | ||
controller.registerHandler(GET, "_cat/ml/trained_models", this); | ||
} | ||
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@Override | ||
public String getName() { | ||
return "cat_ml_get_trained_models_action"; | ||
} | ||
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@Override | ||
protected RestChannelConsumer doCatRequest(RestRequest restRequest, NodeClient client) { | ||
String modelId = restRequest.param(TrainedModelConfig.MODEL_ID.getPreferredName()); | ||
if (Strings.isNullOrEmpty(modelId)) { | ||
modelId = MetaData.ALL; | ||
} | ||
GetTrainedModelsStatsAction.Request statsRequest = new GetTrainedModelsStatsAction.Request(modelId); | ||
GetTrainedModelsAction.Request modelsAction = new GetTrainedModelsAction.Request(modelId, false, null); | ||
if (restRequest.hasParam(PageParams.FROM.getPreferredName()) || restRequest.hasParam(PageParams.SIZE.getPreferredName())) { | ||
statsRequest.setPageParams(new PageParams(restRequest.paramAsInt(PageParams.FROM.getPreferredName(), PageParams.DEFAULT_FROM), | ||
restRequest.paramAsInt(PageParams.SIZE.getPreferredName(), PageParams.DEFAULT_SIZE))); | ||
modelsAction.setPageParams(new PageParams(restRequest.paramAsInt(PageParams.FROM.getPreferredName(), PageParams.DEFAULT_FROM), | ||
restRequest.paramAsInt(PageParams.SIZE.getPreferredName(), PageParams.DEFAULT_SIZE))); | ||
} | ||
statsRequest.setAllowNoResources(true); | ||
modelsAction.setAllowNoResources(restRequest.paramAsBoolean(ALLOW_NO_MATCH.getPreferredName(), | ||
statsRequest.isAllowNoResources())); | ||
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return channel -> { | ||
final ActionListener<Table> listener = ActionListener.notifyOnce(new RestResponseListener<>(channel) { | ||
@Override | ||
public RestResponse buildResponse(final Table table) throws Exception { | ||
return RestTable.buildResponse(table, channel); | ||
} | ||
}); | ||
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client.execute(GetTrainedModelsAction.INSTANCE, modelsAction, ActionListener.wrap( | ||
trainedModels -> { | ||
final List<TrainedModelConfig> trainedModelConfigs = trainedModels.getResources().results(); | ||
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Set<String> potentialAnalyticsIds = new HashSet<>(); | ||
// Analytics Configs are created by the XPackUser | ||
trainedModelConfigs.stream() | ||
.filter(c -> XPackUser.NAME.equals(c.getCreatedBy())) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I think we want a better way of differentiating user models and DFA models in the future. Maybe a reserved tag for DFA models There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @davidkyle possibly. Users cannot set the But I see your point for models we provide as a resource. Those weren't created by a DFA. |
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.forEach(c -> potentialAnalyticsIds.addAll(c.getTags())); | ||
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// Find the related DataFrameAnalyticsConfigs | ||
String requestIdPattern = Strings.collectionToDelimitedString(potentialAnalyticsIds, "*,") + "*"; | ||
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final GroupedActionListener<ActionResponse> groupedListener = createGroupedListener(restRequest, | ||
2, | ||
trainedModels.getResources().results(), | ||
listener); | ||
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client.execute(GetTrainedModelsStatsAction.INSTANCE, | ||
statsRequest, | ||
ActionListener.wrap(groupedListener::onResponse, groupedListener::onFailure)); | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Do you need the wrap? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yes, generic types get upset if there is no wrapper. |
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GetDataFrameAnalyticsAction.Request dataFrameAnalyticsRequest = | ||
new GetDataFrameAnalyticsAction.Request(requestIdPattern); | ||
dataFrameAnalyticsRequest.setAllowNoResources(true); | ||
dataFrameAnalyticsRequest.setPageParams(new PageParams(0, potentialAnalyticsIds.size())); | ||
client.execute(GetDataFrameAnalyticsAction.INSTANCE, | ||
dataFrameAnalyticsRequest, | ||
ActionListener.wrap(groupedListener::onResponse, groupedListener::onFailure)); | ||
}, | ||
listener::onFailure | ||
)); | ||
}; | ||
} | ||
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@Override | ||
protected void documentation(StringBuilder sb) { | ||
sb.append("/_cat/ml/trained_models\n"); | ||
sb.append("/_cat/ml/trained_models/{model_id}\n"); | ||
} | ||
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@Override | ||
protected Table getTableWithHeader(RestRequest request) { | ||
Table table = new Table(); | ||
table.startHeaders(); | ||
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// Trained Model Info | ||
table.addCell("id", TableColumnAttributeBuilder.builder().setDescription("the trained model id").build()); | ||
table.addCell("created_by", TableColumnAttributeBuilder.builder("who created the model", false) | ||
.setAliases("c", "createdBy") | ||
.setTextAlignment(TableColumnAttributeBuilder.TextAlign.RIGHT) | ||
.build()); | ||
table.addCell("heap_size", TableColumnAttributeBuilder.builder() | ||
.setDescription("the estimated heap size to keep the model in memory") | ||
.setAliases("hs","modelHeapSize") | ||
.build()); | ||
table.addCell("operations", TableColumnAttributeBuilder.builder() | ||
.setDescription("the estimated number of operations to use the model") | ||
.setAliases("o", "modelOperations") | ||
.build()); | ||
table.addCell("license", TableColumnAttributeBuilder.builder("The license level of the model", false) | ||
.setAliases("l") | ||
.build()); | ||
table.addCell("create_time", TableColumnAttributeBuilder.builder("The time the model was created", false) | ||
.setAliases("ct") | ||
.build()); | ||
table.addCell("version", TableColumnAttributeBuilder.builder("The version of Elasticsearch when the model was created", false) | ||
.setAliases("v") | ||
.build()); | ||
table.addCell("description", TableColumnAttributeBuilder.builder("The model description", false) | ||
.setAliases("d") | ||
.build()); | ||
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// Trained Model Stats | ||
table.addCell("ingest.pipelines", TableColumnAttributeBuilder.builder("The number of pipelines referencing the model") | ||
.setAliases("ip", "ingestPipelines") | ||
.build()); | ||
table.addCell("ingest.count", TableColumnAttributeBuilder.builder("The total number of docs processed by the model", false) | ||
.setAliases("ic", "ingestCount") | ||
.build()); | ||
table.addCell("ingest.time", TableColumnAttributeBuilder.builder( | ||
"The total time spent processing docs with this model", | ||
false) | ||
.setAliases("it", "ingestTime") | ||
.build()); | ||
table.addCell("ingest.current", TableColumnAttributeBuilder.builder( | ||
"The total documents currently being handled by the model", | ||
false) | ||
.setAliases("icurr", "ingestCurrent") | ||
.build()); | ||
table.addCell("ingest.failed", TableColumnAttributeBuilder.builder( | ||
"The total count of failed ingest attempts with this model", | ||
false) | ||
.setAliases("if", "ingestFailed") | ||
.build()); | ||
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table.addCell("data_frame.id", TableColumnAttributeBuilder.builder( | ||
"The data frame analytics config id that created the model (if still available)", | ||
false) | ||
.setAliases("dfid", "dataFrameAnalytics") | ||
.build()); | ||
table.addCell("data_frame.create_time", TableColumnAttributeBuilder.builder( | ||
"The time the data frame analytics config was created", | ||
false) | ||
.setAliases("dft", "dataFrameAnalyticsTime") | ||
.build()); | ||
table.addCell("data_frame.source_index", TableColumnAttributeBuilder.builder( | ||
"The source index used to train in the data frame analysis", | ||
false) | ||
.setAliases("dfsi", "dataFrameAnalyticsSrcIndex") | ||
.build()); | ||
table.addCell("data_frame.analysis", TableColumnAttributeBuilder.builder( | ||
"The analysis used by the data frame to build the model", | ||
false) | ||
.setAliases("dfa", "dataFrameAnalyticsAnalysis") | ||
.build()); | ||
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table.endHeaders(); | ||
return table; | ||
} | ||
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private GroupedActionListener<ActionResponse> createGroupedListener(final RestRequest request, | ||
final int size, | ||
final List<TrainedModelConfig> configs, | ||
final ActionListener<Table> listener) { | ||
return new GroupedActionListener<>(new ActionListener<>() { | ||
@Override | ||
public void onResponse(final Collection<ActionResponse> responses) { | ||
GetTrainedModelsStatsAction.Response statsResponse = extractResponse(responses, GetTrainedModelsStatsAction.Response.class); | ||
GetDataFrameAnalyticsAction.Response analytics = extractResponse(responses, GetDataFrameAnalyticsAction.Response.class); | ||
listener.onResponse(buildTable(request, | ||
statsResponse.getResources().results(), | ||
configs, | ||
analytics == null ? Collections.emptyList() : analytics.getResources().results())); | ||
} | ||
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@Override | ||
public void onFailure(final Exception e) { | ||
listener.onFailure(e); | ||
} | ||
}, size); | ||
} | ||
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private Table buildTable(RestRequest request, | ||
List<GetTrainedModelsStatsAction.Response.TrainedModelStats> stats, | ||
List<TrainedModelConfig> configs, | ||
List<DataFrameAnalyticsConfig> analyticsConfigs) { | ||
Table table = getTableWithHeader(request); | ||
assert configs.size() == stats.size(); | ||
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Map<String, DataFrameAnalyticsConfig> analyticsMap = analyticsConfigs.stream() | ||
.collect(Collectors.toMap(DataFrameAnalyticsConfig::getId, Function.identity())); | ||
Map<String, GetTrainedModelsStatsAction.Response.TrainedModelStats> statsMap = stats.stream() | ||
.collect(Collectors.toMap(GetTrainedModelsStatsAction.Response.TrainedModelStats::getModelId, Function.identity())); | ||
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configs.forEach(config -> { | ||
table.startRow(); | ||
// Trained Model Info | ||
table.addCell(config.getModelId()); | ||
table.addCell(config.getCreatedBy()); | ||
table.addCell(new ByteSizeValue(config.getEstimatedHeapMemory())); | ||
table.addCell(config.getEstimatedOperations()); | ||
table.addCell(config.getLicenseLevel()); | ||
table.addCell(config.getCreateTime()); | ||
table.addCell(config.getVersion().toString()); | ||
table.addCell(config.getDescription()); | ||
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GetTrainedModelsStatsAction.Response.TrainedModelStats modelStats = statsMap.get(config.getModelId()); | ||
table.addCell(modelStats.getPipelineCount()); | ||
boolean hasIngestStats = modelStats != null && modelStats.getIngestStats() != null; | ||
table.addCell(hasIngestStats ? modelStats.getIngestStats().getTotalStats().getIngestCount() : 0); | ||
table.addCell(hasIngestStats ? | ||
TimeValue.timeValueMillis(modelStats.getIngestStats().getTotalStats().getIngestTimeInMillis()) : | ||
TimeValue.timeValueMillis(0)); | ||
table.addCell(hasIngestStats ? modelStats.getIngestStats().getTotalStats().getIngestCurrent() : 0); | ||
table.addCell(hasIngestStats ? modelStats.getIngestStats().getTotalStats().getIngestFailedCount() : 0); | ||
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DataFrameAnalyticsConfig dataFrameAnalyticsConfig = config.getTags() | ||
.stream() | ||
.filter(analyticsMap::containsKey) | ||
.map(analyticsMap::get) | ||
.findFirst() | ||
.orElse(null); | ||
table.addCell(dataFrameAnalyticsConfig == null ? "__none__" : dataFrameAnalyticsConfig.getId()); | ||
table.addCell(dataFrameAnalyticsConfig == null ? null : dataFrameAnalyticsConfig.getCreateTime()); | ||
table.addCell(dataFrameAnalyticsConfig == null ? | ||
null : | ||
Strings.arrayToCommaDelimitedString(dataFrameAnalyticsConfig.getSource().getIndex())); | ||
DataFrameAnalysis analysis = dataFrameAnalyticsConfig == null ? null : dataFrameAnalyticsConfig.getAnalysis(); | ||
table.addCell(analysis == null ? null : analysis.getWriteableName()); | ||
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table.endRow(); | ||
}); | ||
return table; | ||
} | ||
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@SuppressWarnings("unchecked") | ||
private static <A extends ActionResponse> A extractResponse(final Collection<? extends ActionResponse> responses, Class<A> c) { | ||
return (A) responses.stream().filter(c::isInstance).findFirst().get(); | ||
} | ||
} |
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This is the only cat action that supports paging
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Correct, and it probably should as there is a limit of 10K when reading configs from an index.
Our
_cat
APIs are the only ones that return data that are stored in indices (i think)