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[ML] [Inference] fix number inference models returned in x-pack info call (#53540) (#53560) 

the ML portion of the x-pack info API was erroneously counting configuration documents and definition documents. The underlying implementation of our storage separates the two out.

This PR filters the query so that only trained model config documents are counted.
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Benjamin Trent 2020-03-13 16:53:34 -04:00 committed by GitHub
parent 4e43ede735
commit 1262ab2762
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4
x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MachineLearningFeatureSet.java
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@ -24,6 +24,7 @@ import org.elasticsearch.cluster.service.ClusterService;
import org.elasticsearch.common.Nullable;
import org.elasticsearch.common.inject.Inject;
import org.elasticsearch.env.Environment;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.ingest.IngestStats;
import org.elasticsearch.license.XPackLicenseState;
import org.elasticsearch.plugins.Platforms;
@ -39,6 +40,7 @@ import org.elasticsearch.xpack.core.ml.action.GetDatafeedsStatsAction;
import org.elasticsearch.xpack.core.ml.action.GetJobsStatsAction;
import org.elasticsearch.xpack.core.ml.datafeed.DatafeedState;
import org.elasticsearch.xpack.core.ml.dataframe.DataFrameAnalyticsState;
import org.elasticsearch.xpack.core.ml.inference.TrainedModelConfig;
import org.elasticsearch.xpack.core.ml.inference.persistence.InferenceIndexConstants;
import org.elasticsearch.xpack.core.ml.job.config.Job;
import org.elasticsearch.xpack.core.ml.job.config.JobState;
@ -351,6 +353,8 @@ public class MachineLearningFeatureSet implements XPackFeatureSet {
addInferenceIngestUsage(response, inferenceUsage);
SearchRequestBuilder requestBuilder = client.prepareSearch(InferenceIndexConstants.INDEX_PATTERN)
.setSize(0)
.setQuery(QueryBuilders.boolQuery()
.filter(QueryBuilders.termQuery(InferenceIndexConstants.DOC_TYPE.getPreferredName(), TrainedModelConfig.NAME)))
.setTrackTotalHits(true);
ClientHelper.executeAsyncWithOrigin(client.threadPool().getThreadContext(),
ClientHelper.ML_ORIGIN,