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Added validation that vector is not NaN #100

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Apr 28, 2020
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Added validation that vector is not NaN #100

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d7b528b
Added validation that vector is not NaN
jmazanec15 Apr 27, 2020
2576966
added infinity check
jmazanec15 Apr 27, 2020
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6 changes: 6 additions & 0 deletions src/main/java/com/amazon/opendistroforelasticsearch/knn/index/KNNVectorFieldMapper.java
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Expand Up @@ -250,10 +250,16 @@ public void parse(ParseContext context) throws IOException {
if (token == XContentParser.Token.START_ARRAY) {
token = context.parser().nextToken();
while (token != XContentParser.Token.END_ARRAY) {
if (Float.isNaN(context.parser().floatValue())) {
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Should we also add check for Float.isInfinite?

https://docs.oracle.com/javase/7/docs/api/java/lang/Float.html#isInfinite(float)

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Yes I think that makes sense.

throw new IllegalArgumentException("KNN vector values cannot be NaN");
}
vector.add(context.parser().floatValue());
token = context.parser().nextToken();
}
} else if (token == XContentParser.Token.VALUE_NUMBER) {
if (Float.isNaN(context.parser().floatValue())) {
throw new IllegalArgumentException("KNN vector values cannot be NaN");
}
vector.add(context.parser().floatValue());
context.parser().nextToken();
}
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12 changes: 12 additions & 0 deletions src/test/java/com/amazon/opendistroforelasticsearch/knn/index/KNNESIT.java
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Expand Up @@ -155,6 +155,18 @@ public void testVectorMappingValidationInvalidDimension() {
KNNVectorFieldMapper.MAX_DIMENSION + " for vector: " + FIELD_NAME));
}

public void testVectorMappingValidationInvalidVectorNaN() throws IOException {
Settings settings = Settings.builder()
.put(getKNNDefaultIndexSettings())
.build();

createKnnIndex(INDEX_NAME, settings, createKnnIndexMapping(FIELD_NAME, 2));

Float[] vector = {Float.NaN, Float.NaN};
Exception ex = expectThrows(ResponseException.class, () -> addKnnDoc(INDEX_NAME, "3", FIELD_NAME, vector));
assertThat(ex.getMessage(), containsString("KNN vector values cannot be NaN"));
}

public void testVectorMappingValidationUpdateDimension() throws Exception {
Settings settings = Settings.builder()
.put(getKNNDefaultIndexSettings())
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