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exhaust object to allow subsequent objects to be parsed correctly

This commit is contained in:
Simon Willnauer 2013-03-06 15:34:59 +01:00
parent 1f217f6a7b
commit 12a2808168
1 changed files with 82 additions and 80 deletions
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164
src/main/java/org/elasticsearch/search/suggest/phrase/PhraseSuggestParser.java
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@ -159,93 +159,95 @@ public final class PhraseSuggestParser implements SuggestContextParser {
while ((token = parser.nextToken()) != XContentParser.Token.END_OBJECT) { while ((token = parser.nextToken()) != XContentParser.Token.END_OBJECT) {
if (token == XContentParser.Token.FIELD_NAME) { if (token == XContentParser.Token.FIELD_NAME) {
fieldName = parser.currentName(); fieldName = parser.currentName();
break; if ("linear".equals(fieldName)) {
} ensureNoSmoothing(suggestion);
} final double[] lambdas = new double[3];
if ("linear".equals(fieldName)) { while ((token = parser.nextToken()) != Token.END_OBJECT) {
ensureNoSmoothing(suggestion); if (token == XContentParser.Token.FIELD_NAME) {
final double[] lambdas = new double[3]; fieldName = parser.currentName();
while ((token = parser.nextToken()) != Token.END_OBJECT) {
if (token == XContentParser.Token.FIELD_NAME) {
fieldName = parser.currentName();
}
if (token.isValue()) {
if ("trigram_lambda".equals(fieldName)) {
lambdas[0] = parser.doubleValue();
if (lambdas[0] < 0) {
throw new ElasticSearchIllegalArgumentException("trigram_lambda must be positive");
} }
} else if ("bigram_lambda".equals(fieldName)) { if (token.isValue()) {
lambdas[1] = parser.doubleValue(); if ("trigram_lambda".equals(fieldName)) {
if (lambdas[1] < 0) { lambdas[0] = parser.doubleValue();
throw new ElasticSearchIllegalArgumentException("bigram_lambda must be positive"); if (lambdas[0] < 0) {
throw new ElasticSearchIllegalArgumentException("trigram_lambda must be positive");
}
} else if ("bigram_lambda".equals(fieldName)) {
lambdas[1] = parser.doubleValue();
if (lambdas[1] < 0) {
throw new ElasticSearchIllegalArgumentException("bigram_lambda must be positive");
}
} else if ("unigram_lambda".equals(fieldName)) {
lambdas[2] = parser.doubleValue();
if (lambdas[2] < 0) {
throw new ElasticSearchIllegalArgumentException("unigram_lambda must be positive");
}
} else {
throw new ElasticSearchIllegalArgumentException(
"suggester[phrase][smoothing][linear] doesn't support field [" + fieldName + "]");
}
} }
} else if ("unigram_lambda".equals(fieldName)) {
lambdas[2] = parser.doubleValue();
if (lambdas[2] < 0) {
throw new ElasticSearchIllegalArgumentException("unigram_lambda must be positive");
}
} else {
throw new ElasticSearchIllegalArgumentException("suggester[phrase][smoothing][linear] doesn't support field [" + fieldName + "]");
} }
} double sum = 0.0d;
} for (int i = 0; i < lambdas.length; i++) {
double sum = 0.0d; sum += lambdas[i];
for (int i = 0; i < lambdas.length; i++) { }
sum += lambdas[i]; if (Math.abs(sum - 1.0) > 0.001) {
} throw new ElasticSearchIllegalArgumentException("linear smoothing lambdas must sum to 1");
if (Math.abs(sum - 1.0) > 0.001) { }
throw new ElasticSearchIllegalArgumentException("linear smoothing lambdas must sum to 1"); suggestion.setModel(new WordScorer.WordScorerFactory() {
} @Override
suggestion.setModel(new WordScorer.WordScorerFactory() { public WordScorer newScorer(IndexReader reader, String field, double realWordLikelyhood, BytesRef separator)
@Override throws IOException {
public WordScorer newScorer(IndexReader reader, String field, double realWordLikelyhood, BytesRef separator) return new LinearInterpoatingScorer(reader, field, realWordLikelyhood, separator, lambdas[0], lambdas[1],
throws IOException { lambdas[2]);
return new LinearInterpoatingScorer(reader, field, realWordLikelyhood, separator, lambdas[0], lambdas[1], }
lambdas[2]); });
} } else if ("laplace".equals(fieldName)) {
}); ensureNoSmoothing(suggestion);
} else if ("laplace".equals(fieldName)) { double theAlpha = 0.5;
ensureNoSmoothing(suggestion);
double theAlpha = 0.5;
while ((token = parser.nextToken()) != Token.END_OBJECT) { while ((token = parser.nextToken()) != Token.END_OBJECT) {
if (token == XContentParser.Token.FIELD_NAME) { if (token == XContentParser.Token.FIELD_NAME) {
fieldName = parser.currentName(); fieldName = parser.currentName();
} }
if (token.isValue() && "alpha".equals(fieldName)) { if (token.isValue() && "alpha".equals(fieldName)) {
theAlpha = parser.doubleValue(); theAlpha = parser.doubleValue();
}
}
final double alpha = theAlpha;
suggestion.setModel(new WordScorer.WordScorerFactory() {
@Override
public WordScorer newScorer(IndexReader reader, String field, double realWordLikelyhood, BytesRef separator)
throws IOException {
return new LaplaceScorer(reader, field, realWordLikelyhood, separator, alpha);
}
});
} else if ("stupid_backoff".equals(fieldName)) {
ensureNoSmoothing(suggestion);
double theDiscount = 0.4;
while ((token = parser.nextToken()) != Token.END_OBJECT) {
if (token == XContentParser.Token.FIELD_NAME) {
fieldName = parser.currentName();
}
if (token.isValue() && "discount".equals(fieldName)) {
theDiscount = parser.doubleValue();
}
}
final double discount = theDiscount;
suggestion.setModel(new WordScorer.WordScorerFactory() {
@Override
public WordScorer newScorer(IndexReader reader, String field, double realWordLikelyhood, BytesRef separator)
throws IOException {
return new StupidBackoffScorer(reader, field, realWordLikelyhood, separator, discount);
}
});
} else {
throw new ElasticSearchIllegalArgumentException("suggester[phrase] doesn't support object field [" + fieldName + "]");
} }
} }
final double alpha = theAlpha;
suggestion.setModel( new WordScorer.WordScorerFactory() {
@Override
public WordScorer newScorer(IndexReader reader, String field, double realWordLikelyhood, BytesRef separator) throws IOException {
return new LaplaceScorer(reader, field, realWordLikelyhood, separator, alpha);
}
});
} else if ("stupid_backoff".equals(fieldName)) {
ensureNoSmoothing(suggestion);
double theDiscount = 0.4;
while ((token = parser.nextToken()) != Token.END_OBJECT) {
if (token == XContentParser.Token.FIELD_NAME) {
fieldName = parser.currentName();
}
if (token.isValue() && "discount".equals(fieldName)) {
theDiscount = parser.doubleValue();
}
}
final double discount = theDiscount;
suggestion.setModel( new WordScorer.WordScorerFactory() {
@Override
public WordScorer newScorer(IndexReader reader, String field, double realWordLikelyhood, BytesRef separator) throws IOException {
return new StupidBackoffScorer(reader, field, realWordLikelyhood, separator, discount);
}
});
} else {
throw new ElasticSearchIllegalArgumentException("suggester[phrase] doesn't support object field [" + fieldName + "]");
} }
} }