Better HoltWinters parameter validation (#38747)

We validate HW parameters (namely, window > 2 * period) when parsing
the XContent... but that means transport clients can configure bad
params.

This change allows model to validate the window and throw an 
exception if they wish.

It also makes some test changes:

- removes testBadModelParams(), which was a junk test (didn't do
anything), and bad param checking is done elsewhere in units tests
- Fixes one of the windows in testHoltWintersNotEnoughData()
- Ensures the period in testHoltWintersNotEnoughData() is >> window
- Removes `setTypes()` since that's deprecated

server/src/main/java/org/elasticsearch/search/aggregations/pipeline/HoltWintersModel.java

@@ -304,12 +304,6 @@ public class HoltWintersModel extends MovAvgModel {
             double gamma = parseDoubleParam(settings, "gamma", DEFAULT_GAMMA);
             int period = parseIntegerParam(settings, "period", DEFAULT_PERIOD);
 
-            if (windowSize < 2 * period) {
-                throw new ParseException("Field [window] must be at least twice as large as the period when " +
-                        "using Holt-Winters.  Value provided was [" + windowSize + "], which is less than (2*period) == "
-                        + (2 * period), 0);
-            }
-
             SeasonalityType seasonalityType = DEFAULT_SEASONALITY_TYPE;
 
             if (settings != null) {
@@ -332,6 +326,21 @@ public class HoltWintersModel extends MovAvgModel {
         }
     };
 
+    /**
+     * If the model is a HoltWinters, we need to ensure the window and period are compatible.
+     * This is verified in the XContent parsing, but transport clients need these checks since they
+     * skirt XContent parsing
+     */
+    @Override
+    protected void validate(long window, String aggregationName) {
+        super.validate(window, aggregationName);
+        if (window < 2 * period) {
+            throw new IllegalArgumentException("Field [window] must be at least twice as large as the period when " +
+                "using Holt-Winters.  Value provided was [" + window + "], which is less than (2*period) == "
+                + (2 * period));
+        }
+    }
+
     @Override
     public int hashCode() {
         return Objects.hash(alpha, beta, gamma, period, seasonalityType, pad);

server/src/main/java/org/elasticsearch/search/aggregations/pipeline/MovAvgModel.java

@@ -99,6 +99,15 @@ public abstract class MovAvgModel implements NamedWriteable, ToXContentFragment
      */
     protected abstract double[] doPredict(Collection<Double> values, int numPredictions);
 
+    /**
+     * This method allows models to validate the window size if required
+     */
+    protected void validate(long window, String aggregationName) {
+        if (window <= 0) {
+            throw new IllegalArgumentException("[window] must be a positive integer in aggregation [" + aggregationName + "]");
+        }
+    }
+
     /**
      * Returns an empty set of predictions, filled with NaNs
      * @param numPredictions Number of empty predictions to generate

server/src/main/java/org/elasticsearch/search/aggregations/pipeline/MovAvgPipelineAggregationBuilder.java

@@ -147,6 +147,10 @@ public class MovAvgPipelineAggregationBuilder extends AbstractPipelineAggregatio
         if (window <= 0) {
             throw new IllegalArgumentException("[window] must be a positive integer: [" + name + "]");
         }
+        // If we have a model we can validate the window now
+        if (model != null) {
+            model.validate(window, name);
+        }
         this.window = window;
         return this;
     }
@@ -265,7 +269,8 @@ public class MovAvgPipelineAggregationBuilder extends AbstractPipelineAggregatio
             throw new IllegalStateException(PipelineAggregator.Parser.BUCKETS_PATH.getPreferredName()
                     + " must contain a single entry for aggregation [" + name + "]");
         }
-        
+        // Validate any model-specific window requirements
+        model.validate(window, name);
         validateSequentiallyOrderedParentAggs(parent, NAME, name);
     }
 

server/src/test/java/org/elasticsearch/search/aggregations/pipeline/MovAvgIT.java

@@ -401,7 +401,7 @@ public class MovAvgIT extends ESIntegTestCase {
      */
     public void testSimpleSingleValuedField() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -449,7 +449,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
     public void testLinearSingleValuedField() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -497,7 +497,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
     public void testEwmaSingleValuedField() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -545,7 +545,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
     public void testHoltSingleValuedField() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -594,7 +594,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
     public void testHoltWintersValuedField() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -648,7 +648,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
         SearchResponse response = client()
                 .prepareSearch("neg_idx")
-                .setTypes("type")
+                
                 .addAggregation(
                         histogram("histo")
                                 .field(INTERVAL_FIELD)
@@ -701,7 +701,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testSizeZeroWindow() {
         try {
             client()
-                    .prepareSearch("idx").setTypes("type")
+                    .prepareSearch("idx")
                     .addAggregation(
                             histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                     .extendedBounds(0L, interval * (numBuckets - 1))
@@ -720,7 +720,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testBadParent() {
         try {
             client()
-                    .prepareSearch("idx").setTypes("type")
+                    .prepareSearch("idx")
                     .addAggregation(
                             range("histo").field(INTERVAL_FIELD).addRange(0, 10)
                                     .subAggregation(randomMetric("the_metric", VALUE_FIELD))
@@ -739,7 +739,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testNegativeWindow() {
         try {
             client()
-                    .prepareSearch("idx").setTypes("type")
+                    .prepareSearch("idx")
                     .addAggregation(
                             histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                     .extendedBounds(0L, interval * (numBuckets - 1))
@@ -758,7 +758,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testNoBucketsInHistogram() {
 
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field("test").interval(interval)
                                 .subAggregation(randomMetric("the_metric", VALUE_FIELD))
@@ -780,7 +780,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testNoBucketsInHistogramWithPredict() {
         int numPredictions = randomIntBetween(1,10);
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field("test").interval(interval)
                                 .subAggregation(randomMetric("the_metric", VALUE_FIELD))
@@ -803,7 +803,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testZeroPrediction() {
         try {
             client()
-                    .prepareSearch("idx").setTypes("type")
+                    .prepareSearch("idx")
                     .addAggregation(
                             histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                     .extendedBounds(0L, interval * (numBuckets - 1))
@@ -824,7 +824,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testNegativePrediction() {
         try {
             client()
-                    .prepareSearch("idx").setTypes("type")
+                    .prepareSearch("idx")
                     .addAggregation(
                             histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                     .extendedBounds(0L, interval * (numBuckets - 1))
@@ -842,31 +842,35 @@ public class MovAvgIT extends ESIntegTestCase {
         }
     }
 
-    @AwaitsFix(bugUrl = "https://github.com/elastic/elasticsearch/issues/34046")
     public void testHoltWintersNotEnoughData() {
         Client client = client();
-        expectThrows(SearchPhaseExecutionException.class, () -> client.prepareSearch("idx").setTypes("type")
+        expectThrows(SearchPhaseExecutionException.class, () -> client.prepareSearch("idx")
-                    .addAggregation(
+            .addAggregation(
-                            histogram("histo").field(INTERVAL_FIELD).interval(interval)
+                histogram("histo").field(INTERVAL_FIELD).interval(interval)
-                                    .extendedBounds(0L, interval * (numBuckets - 1))
+                    .extendedBounds(0L, interval * (numBuckets - 1))
-                                    .subAggregation(metric)
+                    .subAggregation(metric)
-                                    .subAggregation(movingAvg("movavg_counts", "_count")
+                    .subAggregation(movingAvg("movavg_counts", "_count")
-                                            .window(10)
+                        .window(10)
-                                            .modelBuilder(new HoltWintersModel.HoltWintersModelBuilder()
+                        .modelBuilder(new HoltWintersModel.HoltWintersModelBuilder()
-                                                    .alpha(alpha).beta(beta).gamma(gamma).period(20).seasonalityType(seasonalityType))
+                            .alpha(alpha).beta(beta).gamma(gamma)
-                                            .gapPolicy(gapPolicy))
+                            .period(interval * 10)
-                                    .subAggregation(movingAvg("movavg_values", "the_metric")
+                            .seasonalityType(seasonalityType))
-                                            .window(windowSize)
+                        .gapPolicy(gapPolicy))
-                                            .modelBuilder(new HoltWintersModel.HoltWintersModelBuilder()
+                    .subAggregation(movingAvg("movavg_values", "the_metric")
-                                                    .alpha(alpha).beta(beta).gamma(gamma).period(20).seasonalityType(seasonalityType))
+                        .window(10)
-                                            .gapPolicy(gapPolicy))
+                        .modelBuilder(new HoltWintersModel.HoltWintersModelBuilder()
-                    ).get());
+                            .alpha(alpha).beta(beta).gamma(gamma)
+                            .period(interval * 10)
+                            .seasonalityType(seasonalityType))
+                        .gapPolicy(gapPolicy))
+            ).get());
+
     }
 
     public void testTwoMovAvgsWithPredictions() {
         SearchResponse response = client()
                 .prepareSearch("double_predict")
-                .setTypes("type")
+                
                 .addAggregation(
                         histogram("histo")
                                 .field(INTERVAL_FIELD)
@@ -980,24 +984,9 @@ public class MovAvgIT extends ESIntegTestCase {
         }
     }
 
-    @AwaitsFix(bugUrl="https://github.com/elastic/elasticsearch/issues/34046")
-    public void testBadModelParams() {
-        expectThrows(SearchPhaseExecutionException.class, () -> client()
-                    .prepareSearch("idx").setTypes("type")
-                    .addAggregation(
-                            histogram("histo").field(INTERVAL_FIELD).interval(interval)
-                                    .extendedBounds(0L, interval * (numBuckets - 1))
-                                    .subAggregation(metric)
-                                    .subAggregation(movingAvg("movavg_counts", "_count")
-                                            .window(10)
-                                            .modelBuilder(randomModelBuilder(100))
-                                            .gapPolicy(gapPolicy))
-                    ).get());
-    }
-
     public void testHoltWintersMinimization() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -1083,7 +1072,7 @@ public class MovAvgIT extends ESIntegTestCase {
      */
     public void testMinimizeNotEnoughData() {
         SearchResponse response = client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -1137,7 +1126,7 @@ public class MovAvgIT extends ESIntegTestCase {
     public void testCheckIfNonTunableCanBeMinimized() {
         try {
             client()
-                .prepareSearch("idx").setTypes("type")
+                .prepareSearch("idx")
                 .addAggregation(
                         histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                 .extendedBounds(0L, interval * (numBuckets - 1))
@@ -1155,7 +1144,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
         try {
             client()
-                    .prepareSearch("idx").setTypes("type")
+                    .prepareSearch("idx")
                     .addAggregation(
                             histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                     .extendedBounds(0L, interval * (numBuckets - 1))
@@ -1185,7 +1174,7 @@ public class MovAvgIT extends ESIntegTestCase {
         for (MovAvgModelBuilder builder : builders) {
             try {
                 client()
-                        .prepareSearch("idx").setTypes("type")
+                        .prepareSearch("idx")
                         .addAggregation(
                                 histogram("histo").field(INTERVAL_FIELD).interval(interval)
                                         .extendedBounds(0L, interval * (numBuckets - 1))
@@ -1225,7 +1214,7 @@ public class MovAvgIT extends ESIntegTestCase {
 
         SearchResponse response = client()
             .prepareSearch("predict_non_empty")
-            .setTypes("type")
+            
             .addAggregation(
                 histogram("histo")
                     .field(INTERVAL_FIELD)