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Implement testStopAndRestart for ClassificationIT (#50585) (#50698)

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Przemysław Witek 2020-01-07 13:41:37 +01:00 committed by GitHub
parent 35453e2b0e
commit 4116452d90
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x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/ClassificationIT.java
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@ -19,12 +19,14 @@ import org.elasticsearch.action.index.IndexAction;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.support.WriteRequest;
import org.elasticsearch.common.unit.TimeValue;
import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.rest.RestStatus;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.xpack.core.ml.action.EvaluateDataFrameAction;
import org.elasticsearch.xpack.core.ml.dataframe.DataFrameAnalyticsConfig;
import org.elasticsearch.xpack.core.ml.dataframe.DataFrameAnalyticsState;
import org.elasticsearch.xpack.core.ml.dataframe.analyses.BoostedTreeParams;
import org.elasticsearch.xpack.core.ml.dataframe.analyses.BoostedTreeParamsTests;
import org.elasticsearch.xpack.core.ml.dataframe.analyses.Classification;
@ -44,6 +46,7 @@ import java.util.Set;
import static java.util.stream.Collectors.toList;
import static org.elasticsearch.common.xcontent.support.XContentMapValues.extractValue;
import static org.hamcrest.Matchers.allOf;
import static org.hamcrest.Matchers.anyOf;
import static org.hamcrest.Matchers.equalTo;
import static org.hamcrest.Matchers.greaterThan;
import static org.hamcrest.Matchers.greaterThanOrEqualTo;
@ -243,6 +246,64 @@ public class ClassificationIT extends MlNativeDataFrameAnalyticsIntegTestCase {
"classification_training_percent_is_50_boolean", BOOLEAN_FIELD, BOOLEAN_FIELD_VALUES, "boolean");
}
public void testStopAndRestart() throws Exception {
initialize("classification_stop_and_restart");
String predictedClassField = KEYWORD_FIELD + "_prediction";
indexData(sourceIndex, 350, 0, KEYWORD_FIELD);
DataFrameAnalyticsConfig config = buildAnalytics(jobId, sourceIndex, destIndex, null, new Classification(KEYWORD_FIELD));
registerAnalytics(config);
putAnalytics(config);
assertIsStopped(jobId);
assertProgress(jobId, 0, 0, 0, 0);
startAnalytics(jobId);
// Wait until state is one of REINDEXING or ANALYZING, or until it is STOPPED.
assertBusy(() -> {
DataFrameAnalyticsState state = getAnalyticsStats(jobId).getState();
assertThat(
state,
is(anyOf(
equalTo(DataFrameAnalyticsState.REINDEXING),
equalTo(DataFrameAnalyticsState.ANALYZING),
equalTo(DataFrameAnalyticsState.STOPPED))));
});
stopAnalytics(jobId);
waitUntilAnalyticsIsStopped(jobId);
// Now let's start it again
try {
startAnalytics(jobId);
} catch (Exception e) {
if (e.getMessage().equals("Cannot start because the job has already finished")) {
// That means the job had managed to complete
} else {
throw e;
}
}
waitUntilAnalyticsIsStopped(jobId, TimeValue.timeValueMinutes(1));
SearchResponse sourceData = client().prepareSearch(sourceIndex).setTrackTotalHits(true).setSize(1000).get();
for (SearchHit hit : sourceData.getHits()) {
Map<String, Object> destDoc = getDestDoc(config, hit);
Map<String, Object> resultsObject = getFieldValue(destDoc, "ml");
assertThat(getFieldValue(resultsObject, predictedClassField), is(in(KEYWORD_FIELD_VALUES)));
assertThat(getFieldValue(resultsObject, "is_training"), is(true));
assertTopClasses(resultsObject, 2, KEYWORD_FIELD, KEYWORD_FIELD_VALUES);
}
assertProgress(jobId, 100, 100, 100, 100);
assertThat(searchStoredProgress(jobId).getHits().getTotalHits().value, equalTo(1L));
assertModelStatePersisted(stateDocId());
assertInferenceModelPersisted(jobId);
assertMlResultsFieldMappings(predictedClassField, "keyword");
assertEvaluation(KEYWORD_FIELD, KEYWORD_FIELD_VALUES, "ml." + predictedClassField);
}
public void testDependentVariableCardinalityTooHighError() throws Exception {
initialize("cardinality_too_high");
indexData(sourceIndex, 6, 5, KEYWORD_FIELD);